THE CATHOLIC UNIVERSITY OF AMERICA
KRAS 4B Silent Mutations in NIH/3T3 Cells Lead to a Tumorigenic Phenotype
A DISSERTATION
Submitted to the Faculty of the
Department of Biology
School of Arts and Sciences
Of The Catholic University of America
In Partial Fulfillment of the Requirements For the
Degree
Doctor of Philosophy
©
Copyright
All Rights Reserved
By
Andrew Michael Waters
Washington D.C.
2016
KRAS 4B Silent Mutations in NIH/3T3 Cells Lead to a Tumorigenic Phenotype
Andrew M. Waters, Ph.D.
Director: Franklin Portugal, Ph.D.
It has long been assumed that silent mutations do not affect the fate of a particular protein
because the amino acid sequence remains unchanged. However, we are learning that
redundancies in the genetic code can lead to changes in protein expression and subsequent
phenotypic changes. Surprisingly, silent mutations have recently been associated with more than
fifty human diseases. KRAS, the most frequently mutated proto-oncogene in human cancers, is
often constitutively activated in cancers that are associated with a poor prognosis. While the
majority of research on KRAS mutant cancers has focused on missense mutations at G12
(glycine, residue 12), G13 (glycine, residue 13), and Q61 (glutamine, residue 61), there exists a
subset of cancer patients with non-random clustering of silent mutations at G12, G13, and G60.
The goal of this study was to examine these silent mutations in the human KRAS 4B gene and
begin to clarify the role synonymous codons play in conferring tumorigenic phenotypes on
mouse NIH/3T3 cells. We present data showing silent mutations in the human KRAS 4B gene at
G12, G13, and G60 altered KRAS protein expression levels when expressed in NIH/3T3 cells
and affected activation status of RAS-associated signaling pathways. Moreover, NIH/3T3 cells
that expressed the human wild-type (WT) KRAS 4B sequence were contact inhibited, whereas
some of the cells transfected with silent KRAS mutations resulted in loss of contact inhibition.
The KRAS silent mutations also affected proliferation rates, saturation densities, migration, and
invasion. This study links silent mutations in the KRAS gene to tumorigenic phenotypes in
mammalian cells and uncovers a previously underappreciated aspect of cancer research.
This dissertation by Andrew Michael Waters fulfills the dissertation requirement for the
doctoral degree in Cell and Microbial Biology approved by Franklin H. Portugal, Ph.D., as
Director, by Pamela L. Tuma, Ph.D. and Ann K. Corsi, Ph.D., as Readers, and by James L.
Hartley, PhD., as Advisor.
Franklin H. Portugal, Ph.D., Director
Pamela L. Tuma, Ph.D., Reader
Ann K. Corsi, Ph.D., Reader
ii
Table of Contents
Page
List of Figures
iv
List of Tables
vii
List of Abbreviations
ix
Definition of Terms
xii
Acknowledgments
xiii
Dedication
xv
Introduction
1
Methods and Materials
26
Results
53
Chapter I: Transient Transfections
54
Chapter II: Stably-Selected Cell Lines
73
Discussion
96
References
115
iii
List of Figures
Page
1.
DNA Codon Chart
2
2.
mRNA Secondary Structure Can Affect Translation Rates
5
3.
Silent Mutations Can Affect miRNA Binding Sites
7
4.
RAS Proteins Cycle Between an Active and Inactive State in the Cell
13
5.
The Three RAS Signaling Pathways Implicated in Oncogenesis
17
6.
HRAS vs. KRAS Protein Translation Rates
20
7.
Missense vs. Silent Mutations in KRAS 4B Tumor Samples
21
8.
Entry Clone Plasmid Constructs
26
9.
Alignment of Sanger Sequencing Results for Confirmed Constructs
31
10.
Agarose Gel Electrophoresis of KRAS 4B WT, G12V, G12G, G13G,
and G60G Silent-Mutant Entry Clone Plasmids
32
11.
Site-Specific Recombination
32
12.
Agarose Gel Electrophoresis of eGFP, KRAS 4B WT, G12V, G12G,
G13G and G60G Silent-Mutant Expression Clone Plasmids
33
13.
STR Profile of NIH/3T3 Cells from Mouse Cell Line Authentication
Assay
36
14.
Agarose Gel Electrophoresis of Total RNA from NIH/3T3 Cells
Transiently Transfected with eGFP, KRAS 4B WT, G12V, G12G,
G13G, and G60G Silent-Mutant Entry Clone Plasmids
44
15.
KRAS 4B Silent Mutations Alter Protein Expression Levels in
Transiently Transfected NIH/3T3 Cells
55
16.
Quantification of KRAS mRNA Level Changes in Transiently
Transfected NIH/3T3 Cells
58
iv
17.
Cells Transiently Transfected with KRAS Silent Mutations Containing
Predicted miRNA Binding Sites Have Lowered KRAS Protein
Expression As Compared to Cells Transfected with WT KRAS
59
18.
Predicted Global mRNA Secondary Structure and Free Energy for Each
of the KRAS Constructs
60
19.
Predicted Local mRNA Secondary Structure and Free Energy for Each
of the KRAS Constructs
61
20.
KRAS Protein Expression vs. Cell Titer-Glo® RLU (relative luminescent 63
units) in Transiently Transfected NIH/3T3 Cells
21.
KRAS Silent Mutations Lead to Focus Formation in Transiently
Transfected NIH/3T3 Cells
22.
KRAS Silent Mutations in G48G, G77G, and G151G Constructs Do Not 67
Lead to Substantial Protein Expression Differences in Transiently
Transfected NIH/3T3 Cells
23.
KRAS Silent Mutations at G48, G77, and G151 Do Not Lead to
Substantial Focus Formation in Transiently Transfected NIH/3T3 Cells
68
24.
KRAS Silent Mutations Lead to Variable Activation of the MAPK
Pathway as Determined by Phosphorylation of Erk1/2 in Transiently
Transfected NIH/3T3 Cells
70
25.
KRAS Silent Mutations Lead to Variable Activation of the PI3K
Pathway as Determined by Phosphorylation of Akt in Transiently
Transfected NIH/3T3 Cells
71
26.
Increasing WT KRAS Concentrations Result in Bell-shaped KRAS
Protein Expression in Transiently Transfected NIH/3T3 Cells
72
27.
KRAS Protein Expression Levels and Proliferation Rate Changes of
Silent-Mutant Containing Stably-Selected NIH/3T3 Cells
75
28.
Silent-Mutant NIH/3T3 Cell Lines Reach Higher Cell Densities than
NIH/3T3-WT Cells in 25 cm2 Tissue Culture (TC) Flasks
79
29.
Silent-Mutant NIH/3T3 Cell Lines Result in Amorphous Colony
Formation
80
v
65
30.
Silent-Mutant NIH/3T3 Cell Lines Show Changes in Wound Healing
Ability
83
31.
Silent-Mutant Cell Lines Show Changes in Migration Patterns Towards
Chemo-attractant
84
32.
Silent-Mutant Cell Lines Show Enhanced Invasion Towards a
Chemo-attractant
86
33.
Silent-Mutant Cell Lines Show More Aggressive Self-Organization As
Compared to NIH/3T3-WT Cells in an Extracellular Matrix After 12
Days
88
34.
Silent-Mutant Cell Lines Show Enhanced Invasive Potential in 3D
Spheroid Assays as Compared to NIH/3T3-WT Cells After 10 Days
89
35.
Silent-Mutant Cell Lines Show Altered Levels of MAPK Activation
91
36.
Silent-Mutant Cell Lines Show Substantial Phospho-Erk1/2 Differences
92
37.
Silent-Mutant Cell Lines Show Altered Levels of PI3K Activation
93
38.
Silent-Mutant Cell Lines Show Altered Ral-GEF Activation as
Measured by Expression and Activation of RalA
94
39.
Alignment of KRAS and HRAS Genes From Different Species
98
40.
Silent-Mutant Cell Lines Exhibit Altered Tumorigenic Potential
107
41.
Working Model for Silent-Mutant Induced Alterations to Tumorigenic
Potential in the KRAS gene in NIH/3T3 Cells
108
vi
List of Tables
Page
1.
The Twenty Protein-Coding Amino Acids Have Different Levels of
Degeneracy
3
2.
Arginine Codon Usage in Humans and E. coli
3
3.
Synonymous Codons are Associated with Many Diseases
5
4.
Frequency of RAS Isoform Mutations in Selected Human Cancers
19
5.
Inverse Correlation of Codon Usage Frequency and Mutation Incidence
in Human Cancers Among the RAS Proteins
20
6.
Primers Used for Generating Silent Mutations
28
7.
Sanger Sequencing Primers for Entry Clone Constructs
30
8.
Human KRAS 4B Digital Droplet PCR Primers
46
9.
mCherry Percentages for Each Construct 72 Hours Post-Transfection
56
10.
Glycine Codon Usage in Mouse Cells
57
11.
Doubling Time of Transiently Transfected NIH/3T3 Cells
64
12.
KRAS Protein Expression Levels in Stably Transfected Cells Trend
with Glycine Codon Usage at G12 and G60
76
13.
Doubling Times for Silent-Mutant NIH/3T3 Cell Lines and Controls
77
14.
Peak Cells Per Flask for Silent-Mutant Cell Lines and Controls
78
15.
Summary of Results
97
16.
G12, G13, and G60 Codon Usage Comparisons for KRAS and HRAS
Across Species
100
17.
Comparison of Mouse, Human, Rat, and Pig Glycine Codon Usage
102
vii
18.
Ratio of Active RalA to Phospho-Erk to Phospho-Akt as it Relates to
Colony Forming and Migration
viii
106
List of Abbreviations
Nucleotides
A
C
G
T
U
Adenine
Cytosine
Guanine
Thymine
Uracil
Amino Acids
A
C
D
E
F
G
H
I
K
L
M
N
P
Q
R
S
T
V
W
Y
ABC
AML
BCL2L12
BCA
BCP
bp
BSA
CAMs
CAT
cDNA
CF
Alanine
Cysteine
Aspartic Acid
Glutamic Acid
Phenylalanine
Glycine
Histidine
Isoleucine
Lysine
Leucine
Methionine
Asparagine
Proline
Glutamine
Arginine
Serine
Threonine
Valine
Tryptophan
Tyrosine
ATP Binding Cassette
Acute Myeloid Leukemia
B-cell lymphoma-like 12
Bicinchoninic Acid
1–bromo–3–chloropropane
Base Pairs
Bovine Serum Albumin
Cellular Adhesion Molecules
chloramphenicol acetyltransferase
complementary DNA
Cystic Fibrosis
ix
CFTR
COMT
COSMIC
CFU
CMV
ddPCR
DMEM
DNA
E. coli
EDTA
eGFP
EGFR
FBS
GAP
GAPDH
GDP
GEFs
GFP
Grb2
GTP
HRAS
IRGM
kb
kDa
KRAS
LB
MAPK
MAPKK
MAPKKK
MDR1
miRNA
mRNA
NRAS
NSCLC
ori
ORF
P02
P10
PBS
PCR
PDK1
P-gp
PI3K
cystic fibrosis transmembrane conductance regulator
catechol-O-methyltransferase
Catalog of Somatic Mutations in Cancer
Colony Forming Units
Cytomegalovirus
digital droplet Polymerase Chain Reaction
Dulbecco’s Modified Eagle Medium
Deoxyribonucleic acid
Escherichia coli
Ethylenediaminetetraacetate
enhanced Green Fluorescent Protein
Epidermal Growth Factor Receptor
Fetal Bovine Serum
GTPase-Activating Protein
Glyceraldehyde-3-Phosphate-Dehydrogenase
Guanosine-5'-diphosphate
Guanine nucleotide-exchange factors
Green Fluorescent Protein
Growth Factor Receptor-Bound Protein 2
Guanosine-5'-triphosphate
Harvey RAS
immunity-related GTPase family M
Kilobases
KiloDalton
Kirsten RAS
Luria-Bertani
Mitogen-Activated Protein Kinase
MAP Kinase Kinase
MAP Kinase Kinase Kinase
Multidrug Resistance 1
micro RNA
Messenger RNA
Neuroblastoma RAS
Non-Small Cell Lung Cancer
Origin of Replication
Open Reading Frame
Passage 2
Passage 10
Phosphate Buffered Saline
Polymerase Chain Reaction
Phosphoinositide-Dependent Kinase-1
Permeability-glycoprotein
Phosphoinositide 3-kinase
x
PI(4,5)P2
PI(3,4,5)P3
PH
RBD
RLU
RNA
RO
rRNA
RTK
SB
SKCM
SNP
SpnR
Sos
STR
TBS-T
TC
TCGA
TE
tRNA
WT
°C
Phosphotidylinositol-4,5-bisphosphate
Phosphotidylinositol-3,4,5 triphosphate
Pleckstrin Homology
RAS binding domain
Relative Luminescent Units
Ribonucleic acid
Reverse osmosis
Ribosomal RNA
Receptor Tyrosine Kinase
Superior Broth
Skin Cutaneous Melanoma
Single Nucleotide Polymorphism
Spectinomycin resistance gene
Son of sevenless
Short Tandem Repeat
Tris-Buffered Saline Tween-20
Tissue Culture
The Cancer Genome Atlas
Tris-Ethylenediaminetetraacetate
Transfer RNA
Wild-Type
Degrees Celsius
xi
Definitions of Terms
Contact Inhibition – The cessation of growth, division, and movement in cells that touch each
other.
Proto-oncogene – A normal gene that becomes an oncogene with specific mutations.
Saturation Density – The number of cells that can live and survive in a given surface area.
Silent mutation – A substitution of one base for another that alters the nucleotide sequence
within the coding region of the gene, but preserves the amino acid sequence, due to redundancy
in the genetic code.
Single Nucleotide Polymorphism – A DNA sequence variation occurring at a frequency of 1%
or greater in the genome among members of a common biological species.
Synonymous codons – Triplets of nucleotides that code for the same amino acid, even though
the three base code is different, due to redundancy in the genetic code.
Synthetic – Manufactured by a chemical reaction; can be biological, as in the case of DNA,
RNA, and protein synthesis, or manufactured de novo, as in chemical synthesis of
oligonucleotides.
Transformation – The conversion of normal cells to malignant cells.
Transgene – A gene that has been transferred from one organism to another organism from a
different species.
Tumorigenic Phenotype – An observable characteristic of a cell or group of cells that is
consistent with known traits of cancerous cells. Examples include: altered morphology, loss of
contact inhibition, enhanced proliferative capacity, high saturation density, increased migration,
increased invasion, etc.
xii
Acknowledgments
First and foremost, I thank my mentor Dr. James Hartley, who provided both the initial
encouragement to pursue a Ph.D. degree and unwavering support throughout this project. With
greatest sincerity, I also thank my faculty advisor and advocate, Dr. Franklin Portugal. Together,
Drs. Hartley and Portugal taught me how to think critically and to push boundaries. I also thank
my committee members Dr. Pamela Tuma and Dr. Ann Corsi, who offered a critical eye and
useful insight along the way. In addition to those already mentioned, I thank Dr. James Greene,
Dr. Venigalla Rao, Dr. Karen Ross, Dr. J. Michael Mullins, and Dr. Ekaterina Nestorovich for
the expansion of my knowledge on this endeavor. I express deep gratitude to my colleagues at
the Frederick National Laboratory for Cancer Research, most notably Drs. Rachel Bagni,
Dominic Esposito, and Matthew Holderfield, for sound technical advice and help with
experimental design. Thanks especially to my classmates for moral support and thank you to
Troy Taylor, John-Paul Denson, and Nicole Fer for moral and technical support.
I would like to sincerely thank Yonggan Wu, of the Bioinformatics Group in State Key
Laboratory of Virology at Wuhan Institute of Virology in China, for help with the microRNA
prediction software, MiRPara, which he developed. I would like to thank Jamie Almeida at the
National Institute of Standards and Technology and Allison Meade of the Frederick National
Laboratory for Cancer Research for technical assistance in cell line authentication. I express
gratitude to Dr. Roland Nardone, Professor Emeritus, for useful conversation and expert
technical advice regarding cell line authentication. Additionally, I would like to thank David
Sun and Xiaolin Wu of the Frederick National Laboratory of Cancer Research for technical
support and expert advice with interpretation of the digital droplet PCR experiments.
This pursuit would not have been achievable without the continued support of my family
members, who have helped to shape me into the person I am today. From my father, Neil
Waters, I learned to work hard and to always remain humble. From my mother, Michelle
Waters-Smith, I learned the importance of education and to follow my instincts. From my older
brother, Matt Waters, who was better than me at almost everything growing up, I have learned to
be driven to succeed against what sometimes seems like insurmountable odds. From my little
xiii
brother, John Waters, I have learned to roll with the punches, and not crack under pressure.
Additionally, thank you to Randy Smith, Diane Sharlow Waters, and Josh Sharlow, who have
always been there for much needed support.
Most of all, I want to thank my wife Bridget, whom I met at CUA orientation, on the first
day of this journey. I am a better person because of you, and with you by my side, I am stronger
than I would ever be alone.
Today, I truly stand on the shoulders of giants.
xiv
Dedication
This dissertation is dedicated to all those who have battled or are currently battling cancer,
including my father Neil, my grandmother Florence, my uncle Chris, and Harley. Seeing your
strength in this fight is my greatest inspiration. May this body of work inspire others to think
about unanswered problems in a different way.
-Andrew
Research is to see what everybody else has seen, and to think what nobody else has thought.
Albert Szent-Gyorgyi
xv
INTRODUCTION
The genetic code relies on triplets of nucleotides, or codons, to code for amino acids [1, 2].
With sixty-four potential nucleotide combinations (three of which encode stop codons) of
adenine (A), cytosine (C), guanine (G), and uracil (U)/thymine (T), and twenty protein-coding
amino acids, the genetic code is redundant (Figure 1) [3]. Methionine (M), the start codon, and
tryptophan (W) are the only amino acids with one codon. The remaining amino acids have two,
three, four, or six synonymous codons. Degeneracy lies in the third nucleotide position of the
codon for all amino acids except arginine (R) and leucine (L), which have first and third base
degeneracy, and serine (S), which has first, second, and third base degeneracy (Table 1) [3].
The Anfinsen principle, cited 5,908 times since 1973, states the amino acid sequence of a
protein is solely responsible for its structure [49]. Redundancy in the genetic code has
historically been regarded as evolutionarily neutral [4]. However, intra-species codon variability
exists, whereby within an organism, the synonymous codons for an amino acid are not equally
represented in the genome [5]. This intra-species variability can be partially explained because
tRNAs (transfer RNAs) are differentially represented [149-151]. Additionally, different
organisms maintain vastly different tRNA pools [16]. By extension, there is substantial interspecies codon variability among organisms. The most frequently used codon for one amino acid
in an organism can be the least frequently used codon for that amino acid in another organism
(Table 2) [5].
Inter-species codon variability is one of the challenges of expressing a recombinant protein in a heterologous host. Since 1977, researchers and pharmaceutical companies have been
taking advantage of synonymous codons by optimizing their gene sequence [6], a process which
1
2
Figure 1. DNA Codon Chart. The twenty amino acids are represented by sixty-one codons,
with each amino acid having between one and six encoding synonymous codons.
involves using the host system's most frequently used codons while maintaining the native amino
acid sequence, to speed up the rates of translation and produce more recombinant protein.
Codon optimization has become a common practice in the biotechnology industry, with genes for
some therapeutic proteins being altered by as much as 80% from their wild-type (WT) nucleotide
sequence [7].
However, we are in the midst of a paradigm shift regarding codon usage. Synonymous
codons have recently been implicated in multiple phenotypic changes [12]. For example, a
synthetic, semi-random gene library of green fluorescent protein (GFP) enriched with
synonymous codons resulted in a 250-fold difference in GFP protein expression in Escherichia
coli (E. coli), even though the amino acid sequence remained unchanged [8]. Additionally,
3
Table 1. The Twenty Protein-Coding Amino Acids Have Different Levels of Degeneracy
One Codon
Two Codons
Three Codons
Four Codons
Six Codons
Methionine (M)
Tryptophan (W)
Phenylalanine (F)
Histidine (H)
Glutamine (Q)
Asparagine (N)
Lysine (K)
Aspartic Acid (D)
Glutamic Acid (E)
Cysteine (C)
Tyrosine (Y)
Isoleucine (I)
Glycine (G)
Threonine (T)
Alanine (A)
Valine (V)
Proline (P)
Arginine (R)
Leucine (L)
Serine (S)
codon “de-optimization” has been used successfully to attenuate viruses [9, 133]. The gene for
the poliovirus capsid protein was codon de-optimized by selecting for underrepresented codon
pairs [9]. This modified virus resulted in 1000-fold viral attenuation, and the modified virus was
sufficient to provide protective immunity to mice from an otherwise lethal dose, even though the
capsid protein amino acid sequence remained unchanged [9]. More recently, a similar codon deoptimization strategy to attenuate the H1N1 influenza virus has been shown to induce cellular,
humoral, and innate immune responses in mice and provide protection against subsequent
challenges [133].
Table 2. Arginine Codon Usage in Humans and E. coli
Synonymous Codon Changes are Implicated in Human Disease
Permeability-glycoprotein (P-gp), an ATP-binding cassette (ABC) transmembrane
transporter, is a broad specificity ATP-driven efflux pump that interacts with a variety of
4
chemotherapeutic agents (actinomycin-D, doxorubicin, vinblastine, paclitaxel) [20]. Some
individuals have a C3435T single nucleotide polymorphism (SNP) in the Multidrug Resistance 1
(MDR1) gene, which codes for P-gp [10, 11]. This particular SNP codes for a silent mutation, in
that it does not change the encoded isoleucine amino acid. However, the silent mutations alter
the substrate and inhibitor specificity of P-gp, affecting the protein's efflux ability for certain
compounds [10, 11].
In the last eight years, synonymous codons have been associated with fifty human
diseases (Table 3) [12]. A study from Stanford University asserts silent mutations are as likely
to be mechanistically associated with diseases as non-silent mutations [104]. The mechanisms
by which silent mutations can affect proteins are still being elucidated, but changes in
translational efficiency can be conferred in several ways. A single nucleotide change that does
not affect the amino acid sequence can affect the messenger RNA (mRNA) secondary structure
and its predicted free energy [7, 8, 12, 15], mRNA decay rates, mRNA stability, and alter the
pace of ribosomal translocation [97]. While the ribosome does possess a helicase activity,
translation is temporarily delayed as the secondary structure is unwound (Figure 2) [13, 14].
Secondary structure changes alter the folding energy of mRNA, with the most favorable or stable
conformation generally resulting in the least amount of protein synthesized, as the free energy
must be overcome to translate the protein [15]. GFP protein from the library mentioned above
was greatly influenced by mRNA stability and folding near the ribosomal binding site, which
explained more than half of the protein expression level variations [8]. Similarly, there are three
haplotypes of the catechol-O-methyltransferase (COMT) gene in humans that vary in two
synonymous positions and one non-synonymous position. The COMT protein is a key regulator
of pain perception [15]. It is the haplotypes that vary in the synonymous positions that have the
5
Table 3.
Synonymous Codons are Associated with Many Diseases
List of selected diseases/syndromes associated with synonymous codons. [12]
greatest difference in enzymatic activity and perception of pain [15]. The synonymous changes
stabilize the stem-loop structures of the mRNA. The mRNA with the most stable secondary
structure results in the lowest levels of synthesized protein and consequently the lowest
enzymatic activity [15].
Figure 2. mRNA Secondary Structure Can Affect Translation Rates. mRNA secondary structure
can affect translation rates and protein expression levels. Stable mRNA structures are associated
with stem-loop structures that require longer times to translate, while loose mRNA structures are
associated with faster translation. Adapted and used with permission. [16]
Another way in which synonymous codon changes can affect protein expression is by
altering ribosomal RNA (rRNA)-mRNA interactions. rRNA has been shown to interact with
mRNA through complementary interactions at “clinger” sites, which delays translation [16].
There are several "clinger" sites in mRNA that are complementary to rRNA. The mRNA’s of
6
hundreds of genes contain “clinger” sites complementary to specific rRNAs and these sites
appear to be evolutionarily conserved [16].
Silent mutations can also affect protein expression levels by eliminating or introducing
microRNA (miRNA) binding sites within mRNA, with implications for human health. For
example, in normal individuals, inflammation of the epithelial lining in the gut mucosa leads to
up-regulation of miR-196, which binds to and destabilizes the mRNA coding for the IRGM
(immunity-related GTPase family M) protein [17, 18]. Because IRGM inhibits bacterial lysis
inside intestinal cells, up-regulation of miR-196 normally leads to lower levels of IRGM and
lysis of intracellular bacteria. However, some individuals have a silent mutation in IRGM that
inhibits miR-196 binding, ultimately allowing the bacteria to persist in the gut and leading to
phenotypes associated with Crohn's disease (Figure 3) [17, 18].
Mutations in miRNA binding sites are also thought to be important in cancers. Melanoma
samples have recently been shown through sequencing to contain an overabundance of silent
(F17F) mutations in the B-cell lymphoma-like 12 (BCL2L12) gene as compared to normal
individuals [22]. This silent mutation causes loss of a miRNA binding site and subsequent
increased mRNA stability, resulting in over-expression of the encoded protein [22]. The added
stability of the mRNA and increased protein expression leads to a hyperactivity of anti-apoptotic
signaling and promotes cell survival [22]. There is also a clustering of the F17F silent mutations
in The Cancer Genome Atlas (TCGA) [22]. Additionally, an analysis of human skin cutaneous
melanoma (SKCM) data contained in TCGA identified three genes (transmembrane protein 216,
crumbs family member 1, and p16 or cyclin-dependent kinase inhibitor 2A) that are significantly
enriched for synonymous codon usage compared to the healthy population [99].
7
Figure 3. Silent mutations can affect miRNA binding sites. Individuals with a silent mutation in
the IRGM gene are susceptible to bacteria associated with Crohn's disease because miR-196
binding is inhibited. Adapted image used with permission [18].
The majority of eukaryotic proteins are folded co-translationally as they begin to emerge
from the ribosome (most apparent in α/β proteins [50] containing alternating α-helices and βsheets [51]). It has been suggested that the presence of rare codons at particular positions along
the mRNA have been evolutionarily conserved to slow down translation and allow the emerging
peptide domains to fold properly before continuing with translation. A pause in translation
allows distinct domains to fold independently, whereby a more frequently used codon increases
the translation rate and allows the domains to fold in a cooperative manner [12]. Therefore, rare
codons can affect the final conformation of the peptide. Indeed, a rare, synonymous codon that
slows down translation is hypothesized to be the reason for the protein folding differences and
altered efflux ability in P-gp for the individuals containing the silent mutation [10]. Likewise, a
three-base deletion in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that
spans amino acids 507 and 508 is the most common cause of cystic fibrosis (CF). The deletion
8
leads to a silent mutation at amino acid position 507 (isoleucine codon ATC becomes isoleucine
codon ATT) and loss of phenylalanine at position 508, which leads to misfolded CFTR protein
and ultimately CF. For twenty years, researchers have focused on the loss of phenylalanine due
to the Δ508 mutation [12]. Recently, it has been observed that the synonymous isoleucine
change at amino acid 507 is responsible for altered mRNA folding, decreased translation rate,
and aberrant protein folding [21]. By reverting to the wild-type isoleucine codon, in the presence
of Δ508, the wild-type mRNA structure is restored, resulting in increased protein expression
levels [21].
In E. coli, substituting rare codons for more frequently used codons in proteins that are cotranslationally folded has been shown to affect the final folding conformation in a predictable
way, even though the protein expression levels are similar [98], suggesting small changes to
translation rate can have substantial effects on protein folding. In a cell-free system, replacing
sixteen consecutive rare E. coli codons with frequently used codons in the chloramphenicol
acetyltransferase (CAT) gene led to increased translation rates and protein synthesis, but a 20%
decrease in specific activity of the encoded protein, presumably due to the accumulation of
misfolded protein [107]. In E. coli, alpha helices tend to be encoded by frequently used codons
while beta sheets and coiled segments tend to be encoded by underrepresented codons [108],
implying frequency of codon usage can be used to specify structural motifs [107].
Finally, silent mutations can affect the splice junctions of pre-mRNA (the transcribed
strand prior to splicing) [12, 16, 19]. There is conservation of splice sites within an organism, so
any changes to the 5' splice site, 3' splice site, or branch site can cause aberrant splicing. Silent
mutations can cause splicing out of regions that are normally contained in exons. Conversely,
silent mutations could interfere with splicing out of intronic regions, leading to altered
9
transcripts. Some individuals possess silent mutations at particular nucleotides adjacent to splice
junctions in TP53, the gene that codes for p53 protein, resulting in inactivation of the splice sites
[19]. This inactivation is potentially dangerous because p53 is a critical protein in preventing
cancer progression because of its central role in the cell cycle, DNA damage and repair, and
apoptosis [31].
Characteristics of Cancer
The second leading cause of death in the United States is cancer, accounting for nearly
one in four deaths [70]. Cancer is a group of more than one hundred diseases that are
characterized by uncontrolled cell growth and invasion of malignant cells from the primary site
to other sites in the body [31, 32, 74-77]. On a molecular level, our current understanding is that
cancers result from the accumulation of detrimental mutations, epigenetic changes, or a
combination of such mutations and epigenetic changes [31-32, 74]. When a cell from a solid
tissue acquires a mutation that allows it to proliferate and grow out of control, a neoplasm is
formed [31, 74]. These neoplastic growths can be further characterized as benign or malignant.
Benign tumors are neoplasms that have not invaded the surrounding tissue, while malignant
tumors are neoplasms in which the cells have acquired an invasive phenotype [31]. These
malignant tumors are generally characterized by the site of derivation in the body. Carcinomas
(including adenocarcinomas, the cancers of glandular tissues) are cancers that arise in epithelial
cells and account for roughly 85% to 90% of all cancers [31, 32]. Malignant tumors derived
from the mesoderm cells (mesenchymal cells and fibroblasts) of the bone or muscle are
characterized as sarcomas, and make up only about 1% of tumors. Cancers of hematopoeitic
origin (lymphomas, leukemias, and myelomas) make up 7% of cancers, while neuroectodermal
10
tumors (gliomas, glioblastomas, neuroblastomas, schwannomas, and medulloblastomas) account
for around 1% of tumors [31].
Two classes of genes are associated with tumorigenesis and cancer. Oncogenes are genes
in which a mutation leads to a "gain-of-function," while mutated tumor suppressor genes
contribute to cancer because of "loss-of-function" [31, 32, 74]. A mutated oncogene, to use an
analogy, is like a car careening down a hill with the accelerator stuck to the floor, while a
mutated tumor suppressor gene is like a car going down a hill without functioning brakes. In
both scenarios, the car rushes forward, unable to control its speed or slow down. To distinguish
between oncogenes and tumor suppressors experimentally, transfection experiments can be
performed. Transfecting cells with an oncogene will promote tumor progression, while
transfecting cells with a tumor suppressor will suppress tumor progression [31]. Some cell lines
that have been transfected with an oncogene exhibit a "transformed" phenotype, characterized by
altered morphology, loss of contact inhibition, anchorage independence, ability to proliferate
indefinitely, reduced requirement for mitogenic growth factors, high saturation density, increased
migration, and increased invasion [32].
Although cancers are derived from many different cell and tissue types, the cells that
make up the cancers maintain certain characteristic features, or hallmarks, that distinguish solid
tumors from healthy tissue. The first of these hallmarks is self-sufficiency in growth signaling
[75, 76]. Non-cancerous cells rely on growth stimulatory proteins and hormones, or mitogens, to
grow and divide. In contrast, tumor cells provide their own growth signals, reducing or
eliminating their dependence on the extracellular environment [75]. A second hallmark is
insensitivity to signals that inhibit growth. Normal cells respond to anti-growth signals by either
entering a quiescent state or becoming terminally differentiated. Cancer cells avoid these
11
cytostatic signals and continue to proliferate [75]. Thirdly, cancer cells avoid apoptosis by a
variety of mechanisms [75]. A combination of the first three hallmarks, in addition to increased
telomere maintenance as a result of up-regulation of telomerase, allows cancer cells to have
limitless replicative potential in vitro, the fourth hallmark of cancer [88, 89]. In contrast, normal
human cells maintain a capacity for only sixty to seventy doublings in vitro [75, 78] before
entering senescence. Sustained angiogenesis is the fifth hallmark of cancer. Normal tissue, by
modulating the balance between angiogenesis-initiating signals and angiogenesis-inhibitory
signals, tightly regulates growth of new blood vessels. In contrast, tumor tissue swings the
balance in the direction of new blood vessel growth [75]. Invasion and metastasis is the sixth
cancer hallmark. In order for tumor cells to move away from the primary site, they must invade
the extracellular matrix. Through rearrangement of transmembrane proteins like cadherins,
cellular adhesion molecules (CAMs) and integrins, and up-regulation of extracellular proteases,
tumor cells acquire an invasive phenotype that permits degradation of the extracellular matrix
[75]. At the point of extravasation, tumor cells can migrate into the bloodstream or lymph
system to a different site, setting up secondary tumors, or metastases [31]. These metastases
affect critical organs and are what lead to cancer deaths in the majority of cancer patients [79].
Invasion and metastasis is the only cancer hallmark that distinguishes metastatic from benign
tumors [77].
Genomic instability is an emerging hallmark, in which cancer cells acquire many more
mutations than normal cells [76]. It is often difficult to distinguish the driver mutations from the
passenger mutations. Current knowledge suggests the latter fail to confer any known growth
advantage to the cancer cell. On average, the genomes of the colon, breast, brain, and pancreatic
cancers have between thirty-three and sixty-six missense or nonsense mutations, while those of
12
melanomas and lung cancers frequently have more than 200 such mutations [80]. Of these
mutations, two to eight may be driver mutations, in that they confer a selective growth advantage
upon the mutated cells [80]. The remaining mutations are thought to be passenger mutations that
are “along for the ride.” Driver gene mutations can be identified by the frequency with which a
particular mutated gene is observed in cancers, and can occur in either oncogenes or tumor
suppressors [80]. In contrast to driver mutations, passenger mutations are rarely found twice in
the same gene [32]. Driver mutations can be, with appropriate controls, determined
experimentally by introducing the mutated gene into a functional model and showing enhanced
tumorigenic potential that results [81].
RAS Proteins
The most frequently mutated proto-oncogenes in human cancer are the RAS genes [23,
36]. Research points to the mutant RAS genes as prominent drivers of cancers [52-57, 80].
Additional lines of evidence also support the RAS proteins as drivers of human cancers. They
include; frequency with which mutations in RAS proteins show up in human cancers (30%) [25];
the results of the unbiased retroviral screens of the 1970's linking human gene mutations to
causative agents for human cancers, of which more than 50% of the genes identified were in
RAS proteins or components of RAS signaling [137]; and the causal association of RAS
mutations to acquired therapeutic resistance in cancers [138]. Although the RAS proteins have
been intensely studied for over three decades, they are commonly referred to as "undruggable"
because no therapy targeting RAS proteins has been successful in the clinic [23].
The RAS proteins are small, 21 kilodalton (kDa) G proteins that are intimately involved in
regulating critical cellular processes, including growth, proliferation, survival, migration,
invasion, and angiogenesis [24, 25]. The RAS proteins are structurally α/β proteins [86] that
13
cycle between inactive and active states, being bound to guanosine-5'-diphosphate (GDP) in the
inactive state and guanosine-5'-triphosphate (GTP) in the active state. The catalytic hydrolysis
of the γ-phosphate of GTP switches the RAS proteins into the inactive state [26, 41]. The
intrinsic hydrolysis rate of the RAS proteins is low with an in vitro half-life of up to twenty-five
minutes at 37 degrees Celsius (°C) [139]. GTPase-activating proteins (GAPs) interact with RAS
proteins to increase the hydrolysis rate by several orders of magnitude [27-29, 41]. RASGAP,
the protein responsible for the majority of the arginine-finger assisted hydrolysis, provides a
necessary positively charged arginine residue at amino acid position 789 (termed an "arginine
finger") that helps stabilize the transition state of GTP hydrolysis in the RAS proteins [32, 41].
Activation of RAS from the GDP state to the GTP state is dependent on guanine nucleotideexchange factors (GEFs) to facilitate exchange of GDP for GTP in the nucleotide binding site
(Figure 4) [30]. The GEF most commonly associated with the RAS proteins is son of sevenless
(Sos) [42].
Figure 4.
RAS Proteins Cycle Between an Active and Inactive State in the Cell. Inactive
RAS proteins are bound to GDP while active RAS proteins are bound to GTP. GEFs stimulate
exchange of GDP for GTP and GAPs hydrolyze GTP to GDP [31].
14
In response to extracellular growth factors binding to transmembrane receptors, RAS
proteins are localized to the cell membrane via farnesylation or geranylgeranylation, and
palmitoylation or electrostatic interactions [43]. Once localized in the membrane, the RAS
proteins transmit their signals through at least nine distinct effectors [24]. Because of integral
role in a large number of pathways, the RAS proteins have been referred to as "the beating heart
of signal transduction" [48]. Tight control of signaling pathways is maintained through
regulation of wild-type RAS activity.
PI3K Pathway
One way RAS proteins control cell growth is through the phosphoinositide 3-kinase
(PI3K) pathway. Activated RAS proteins in the membrane bind directly to PI3K through a RAS
binding domain (RBD), increasing the activity of the PI3K catalytic domain by up to 20-fold and
bringing PI3K into close association with phosphotidylinositol-4,5-bisphosphate [PI(4,5)P2] in
the plasma membrane [90, 105]. Upon stimulation, PI3K phosphorylates the third carbon of the
inositol ring of PI(4,5)P2, converting the lipid to phosphotidylinositol-3,4,5 triphosphate
[PI(3,4,5)P3], which sets in motion a cascade of molecular events [33]. Akt kinase is recruited to
PI(3,4,5)P3 by its pleckstrin homology (PH) domain, where it is phosphorylated by phosphoinositide-dependent kinase-1 (PDK1). Phosphorylation of Akt results in its activation, and Akt
phosphorylates other proteins that then lead to cell growth, such as mTOR; cell proliferation,
such as GSK-3β; cell survival, such as Bad [32,33]; and migration, such as Girdin [73].
MAPK Pathway
The mitogen-activated protein kinase pathway (MAPK) is another important and heavily
studied effector cascade directly downstream of RAS and is responsible for cell division [34].
15
The MAPK pathway involves a series of phosphorylation events resulting in activation of the
subsequent effectors. To start the cascade, a growth factor binds to the extracellular domain of a
transmembrane receptor tyrosine kinase (RTK), which leads to recruitment and dimerization
with another RTK [31, 32]. The dimeric RTKs undergo a conformational change and
phosphorylate each other on the cytoplasmic side of the membrane in trans on multiple tyrosine
residues, which are then bound by various proteins with SH2 domains (domains of proteins that
recognize specific phospho-tyrosine residues) [31,32]. In the case of RAS signaling, growth
factor receptor-bound protein 2 (Grb2), the adaptor protein, binds to a phospho-tyrosine via its
SH2 domain. Grb2 also contains two SH3 domains (which bind proline-rich motifs on other
proteins) that bind Sos, a GEF for RAS proteins [31]. Sos binds to membrane-tethered RAS and
causes a conformational change, orienting the nucleotide binding domain of RAS towards the
cytoplasm (where GTP concentration is ~10 times higher than GDP), which facilitates the
release of GDP and the binding of GTP in the active site of RAS proteins [31]. Activated RAS
then binds the serine-threonine kinase Raf (MAP Kinase Kinase Kinase, or MAPKKK) through a
RBD, leading to Raf activation. Raf kinase activates Mek1 and Mek2 kinases (MAP Kinase
Kinase, or MAPKK) by phosphorylation, which activates Erk1 and Erk2 kinases (MAPK) by
phosphorylation. Activated Erk1/2 proteins can both phosphorylate cytoplasmic proteins (Mnk1
and Nrf2) and translocate to the nuclear space, where transcription factors involved in cell
proliferation (Ets, Elk-1, and SAP-1) can be phosphorylated [32].
Ral-GEF Pathway
A third important RAS signaling pathway is the Ral-GEF pathway. Similar to the RAS
proteins, the Ral proteins are activated by exchanging GDP in their active site for GTP [25].
16
Ral-GEF proteins are recruited to the plasma membrane because of their affinity to bind to
membrane-bound active RAS proteins, which causes a conformational change in the Ral-GEFs,
further enhancing their ability to remove GDP and exchange it for GTP on the Ral proteins [32].
Active RalA and RalB proteins activate Sec5 and Exo84, proteins involved in anchorageindependent growth. RalA can also activate RalBP1, which activates Cdc42 and Rac, proteins
involved in motility and invasion [25, 32, 122]. RalA is critical for tumor initiation and growth
in RAS-mutant cancers, and overexpression of RalA protein has been observed in several human
tumors [122, 123]. Moreover, RalA inhibition has been shown to reduce RAS-induced
transformation in multiple cancer cell lines, and it has been posited that enhanced activation of
RalA promotes tumor growth [122].
Given the role of RAS proteins in growth, proliferation, survival, migration, and
invasion, dysregulation of these pathways can lead to uncontrolled cell growth and division, and
ultimately cancer. The PI3K, MAPK, and Ral-GEF signaling pathways all share overlapping
RAS peptide sequence binding sites (amino acids 32-40) [109, 110], and are all implicated in
oncogenesis (Figure 5) [24, 32]. The majority of oncogenic mutations in the RAS proteins are
found at amino acid positions 12, 13, or 61 [25]. Missense mutations at these residues impair
RASGAP from stimulating the hydrolysis of GTP, leaving RAS in a state of constitutive
activation. This leads to hyperactivity of the pathways involved in growth, proliferation,
survival, migration, and invasion [25]. The constitutive signaling leads to tumorigenesis by the
combined effort of several RAS signaling pathways as opposed to one individual pathway [32,
109]. This conclusion is supported by the observation that mutations that activate Raf kinase
(MAPKKK) lead to a more pronounced increase in phosphorylated Erk1/2 levels do than
oncogenic RAS proteins, yet the transforming potential of mutant RAS is fifty times greater than
17
that of mutant Raf [44]. Providing additional supporting evidence is the observation that mutant
RAS proteins that can only activate the MAPK pathway cannot sufficiently induce transformation of mouse embryonic fibroblasts [109, 110]. Moreover, while activation of at least two
pathways is required for transformation in RAS mutant murine fibroblasts, it is not necessary that
one of those activated pathways be MAPK [111].
Figure 5. The Three RAS Signaling Pathways Implicated in Oncogenesis. The PI3K pathway
(left, aquamarine), MAPK pathway (center, black), and Ral-GEF pathway (red, right) have
overlapping roles in tumorigenesis. Purple indicates effector function [32].
Harvey RAS (HRAS), neuroblastoma RAS (NRAS), Kirsten RAS 4A (KRAS 4A), and
Kirsten RAS 4B (KRAS 4B) are four distinct, yet homologous RAS proteins, encoded by three
different genes [36] (KRAS 4A and KRAS 4B are results of alternative splicing events of the
KRAS mRNA). The RAS genes were identified in the 1960's in Harvey and Kirsten strains of
tumor-causing retroviruses [37, 38]. Although the RAS proteins are similar in amino acid
18
sequence (~85% amino acid homology [36]) and have partially redundant functions with shared
receptors, mutated RAS proteins are found with different frequencies in human tumors,
suggesting they may have unique, non-redundant roles [23].
While farnesylation of all RAS proteins provides an affinity for membrane localization,
HRAS, NRAS, and KRAS 4A are subsequently palmitoylated at the Golgi, and KRAS 4B is not
[43, 91]. In contrast to other RAS isoforms, KRAS 4B maintains a positively charged, lysinerich C-terminus, which allows it to localize to the plasma membrane without Golgi assistance.
This “Golgi-less” membrane trafficking allows KRAS 4B to be enriched in membrane
microdomains distinct from those of HRAS, NRAS, and KRAS 4A [59, 60, 91, 156]. Unlike the
other RAS isoforms, the polybasic lysine stretch at the C-terminus KRAS 4B is capable of
forming protein-protein interactions with calmodulin [47, 91]. An additional isoform-specific
difference is that KRAS mutant cells have been shown to express proteins commonly associated
with stem cells while HRAS and NRAS mutant cells have not [39]. Furthermore, KRAS-null
mice are embryonic lethal, while NRAS- or HRAS-null mice survive [23, 40]. Interestingly, and
perhaps paradoxically, there is evidence that the wild-type KRAS protein possesses tumor
suppressive potential [43, 45-46].
KRAS is the most frequently mutated of the RAS proteins found in human tumors
(21.7%, compared to 7.8% for NRAS and 3.2% for HRAS) [25]. Because the exons that encode
KRAS are identical at all G12, G13, and Q61, missense mutations affect both the KRAS 4A and
KRAS 4B proteins. There is also a differential representation of the isoforms in different human
cancers, with KRAS being mutated in a high percentage of pancreatic, colorectal, and lung
cancers, while NRAS is frequently mutated in melanomas (Table 4) [23]. Furthermore, there are
KRAS mutant-specific preferences within human cancers that are not understood. For example,
19
23% of KRAS mutant colorectal cancers contain a G13D mutation, whereas less than 1% of
KRAS mutant pancreatic cancers contain a G13D mutation [23].
It is not understood why different RAS isoforms appear with different frequencies in
specific tumors [23], but a role for rare codons regulating KRAS oncogenesis has been described
[57-59]. KRAS is enriched for rare codons, which slows down the translation rate, and mutant
KRAS protein expression levels are lower than that of HRAS and NRAS [57]. In contrast to
Table 4. Frequency of RAS Isoform Mutations in Selected Human Cancers
Used with permission [23].
mutant KRAS, mutant HRAS is enriched for frequently used codons, has a more rapid translation
rate, and expresses 20-fold more protein (Figure 6). Mutant NRAS contains a mixture of
common and rare codons and the protein expression level of mutant NRAS falls between that of
mutant HRAS and mutant KRAS [57]. Increasing the translation rate of mutant KRAS to levels
similar to mutant HRAS by substituting for the rare codons more frequently used codons results
in a less tumorigenic phenotype both in vitro and in vivo [57-59]. It is hypothesized that the
lower protein expression levels of mutant KRAS are high enough to initiate tumorigenesis, but
20
low enough to avoid senescence and apoptosis [57, 59]. Providing supporting evidence for the
hypothesis is the observation that there is an inverse correlation between frequency of codon
usage and protein expression, and tumorigenesis (Table 5).
Figure 6. HRAS vs. KRAS Protein Translation Rates. HRAS is translated more quickly than
KRAS, leading to increased protein expression. KRAS is enriched for rare codons, which leads
to slower translation rates and decreased protein expression. Used with permission [57].
Table 5. Inverse Correlation of Codon Usage Frequency and Mutation Incidence in Human
Cancers Among the RAS Proteins
HRAS
KRAS
15
40
% Rarest Codons
67
25
% Commonest Codons
3
22
Mutation Incidence in Human Cancers
Used with permission [57].
NRAS
34
37
8
KRAS and Silent Mutations
The Catalog of Somatic Mutations in Cancer (COSMIC) retrieves and displays
mutational information from tumor samples collected and curated in the published literature and
from whole genome re-sequencing studies undertaken by the Cancer Genome Project [61].
There is a clustering of silent mutations in the KRAS protein at amino acid positions 12, 13, and
60, which closely mimics the oncogenic missense mutations found at amino acid positions 12,
13, and 61 (Figure 7) [62]. Notably, there is a large scale difference in Figure 7, with the top
21
panel being over three orders of magnitude higher than the bottom panel. This indicates that for
a particular amino acid, missense mutations are observed in the COSMIC database ~1000 times
more often than silent mutations. However, the clustering of silent mutations being observed at
or near the common missense mutations is a trend found in other oncogenes [62]. Moreover, it
has recently been reported that oncogenes contain an overabundance of somatic silent mutations
in tumors, and those silent mutations can act as drivers of human cancers [19].
There are no known KRAS SNPs in any of the codon positions of amino acids 12, 13, 60,
or 61 in the healthy population [63, 64]. None of the commercially available clinical kits we
investigated (cobas® KRAS Mutation Test marketed by Roche, therascreen® KRAS RGQ PCR
Kit marketed by Qiagen, or the KRAS XL StripAssay® marketed by Oasis Diagnostics), detect
silent KRAS mutations [65-68, 93]. Yet, Sanger sequencing of the KRAS gene in a small study of
acute myeloid leukemia (AML) patients revealed silent mutations at G12 and G13 in 20% of
individuals. In contrast, 0% of the patients had missense G12 or G13 mutations [102].
22
Figure 7. Missense vs. Silent Mutations in KRAS 4B Tumor Samples. The x-axis represents the
amino acids of the KRAS protein from amino acid 1 (left) to amino acid 188 (right). The y-axis
represents the frequency of mutation at a particular amino acid along the KRAS protein as
catalogued by the COSMIC database. The y-axis scale is over three orders of magnitude larger
in the top panel than in the bottom panel [61, 62].
Treatment with epidermal growth factor receptor (EGFR) monoclonal antibody
inhibitors cetuximab and panitumumab are contraindicated in colorectal cancer patients with
functional KRAS missense mutations that lead to RASGAP insensitivity [66]. More than fifty
percent of colorectal cancer patients diagnosed as "wild-type" for KRAS fail to respond to EGFR
therapy [95, 96]. A small percentage (<1%) of colorectal cancer patients overexpress wild-type
KRAS protein due to KRAS gene amplification. These patients are resistant to EGFR
monoclonal antibody therapy [116]. Furthermore, a subset of colorectal cancer patients possess
non-canonical missense mutations at residues other than G12, G13, or Q61 in their KRAS gene,
resulting in enhanced protein expression levels and a transformed phenotype in vitro [117].
Overexpression of WT KRAS protein has also been observed in head, neck, endometrial,
ovarian, lung, gastric, and bladder cancers [127-132]. It is, therefore, possible that a portion of
the patients unresponsive to EGFR monoclonal antibody therapy possess KRAS silent mutations
that enhance KRAS protein expression levels. Remarkably, sequencing of the KRAS gene for
sixty-one colorectal cancer patients previously screened through the FDA approved therascreen®
KRAS RGQ PCR Kit revealed ten of the individuals (16%) had a silent G13G mutation (C→T)
that was unassociated with a KRAS missense mutation [69], making it the most frequently
observed mutation in the study. These particular silent mutations are not catalogued in the
COSMIC database.
23
Statement of the Problem
Significant progress has been made in the treatment and prevention of many types of
cancers. However, many cancers, including 40% of non-small cell lung cancers (NSCLC), have
no known driver mutations [71]. It is plausible that previously overlooked (and often ignored)
silent mutations could contribute to tumorigenesis by affecting protein expression levels of
cancer-associated genes. The resulting protein expression level changes could subsequently
affect biological phenotypes. While the RAS genes have been studied for over thirty years, no
successful therapeutics have been developed for the treatment of RAS-driven cancers [23]. Silent
mutations found in the KRAS gene of human tumors have never been thoroughly investigated,
even though they cluster with the KRAS missense mutations in the COSMIC database (Figure 7).
Codon usage in the KRAS gene has been shown to regulate translation rates and has been
implicated for its role in tumorigenesis [57-59]. Moreover, overexpression of WT KRAS has
been observed in several types of cancer [116, 127-132]. There is also an emerging body of
work associating silent mutations with human disease (Table 3), and silent mutations have
recently been shown to act as drivers of human cancer in other oncogenes [19]. However, the
relationship of synonymous codon usage and protein expression in mammalian cells is poorly
understood, and the role silent mutations play in the progression of cancer remains unclear.
In the present study, we sought to clarify the role of silent mutations in cancer, using
NIH/3T3 cells as a model. These easily transfectable mouse cells have been a mainstay of
cancer research over the last thirty years, with 25,032 references in PubMed. Mouse KRAS
protein maintains 99% amino acid sequence identity with human KRAS protein [72], and human
KRAS can activate RAS-related signaling cascades in NIH/3T3 cells [32, 44]. NIH/3T3 cells are
an immortalized, noncancerous, contact-inhibited cell line. Upon transfection with an oncogene,
24
NIH/3T3 cells become transformed, exhibiting neoplastic growth as measured by loss of contact
inhibition, altered morphology, high saturation density in a culture dish, and by expressing signs
of tumorigenicity [32], such as increased migratory and invasive potential.
However, NIH/3T3 cells also have drawbacks. The cells are of mouse origin, and we are
ultimately interested in human cancer. In all of our experiments, the NIH/3T3 cells have a
functioning mouse KRAS gene in addition to the human KRAS gene we are supplying with our
transfections. The cells are also fibroblastic, while the majority of cancers are derived from the
epithelium. Therefore, caution should be used in extrapolating our results to human cancers.
Future studies beyond the scope of this research may include recapitulating the results in this
dissertation in an epithelial, human cell line. Nonetheless, NIH/3T3 cells have served as a
powerful cancer model because of their ability to be transformed in culture by the expression of
single oncogenes, whereas most primary cells or human cell lines require multiple genetic
changes to become transformed or exhibit tumorigenic properties [32]. Transfection of NIH/3T3
cells led to the initial discovery of the first human oncogenes – the RAS proteins [31-32, 82-85,
125-126].
We hypothesized that silent mutations at G12, G13, and G60 (nucleotide positions 36, 39,
and 180, respectively) in the KRAS 4B gene may lead to increased protein expression levels and
a transformed phenotype in NIH/3T3 cells. Because KRAS has an integral role in many
signaling pathways related to cell growth and survival, it is possible any protein expression
increases could manifest themselves in the form of proliferation differences, loss of contact
inhibition, migration changes, and invasion changes. To date, there have been no
experimentally-derived studies focused on silent mutations in a proto-oncogene. The choice of
KRAS 4B as the gene for this research was based on its potential clinical relevance in the era of
25
personalized medicine (such as diagnostic sequencing), because silent mutations in KRAS 4B
have already been observed, and largely ignored, in cancer tissue samples.
In this study, we show that single nucleotide silent mutations found in human cancers in
the KRAS 4B gene lead to protein expression differences when transiently and stably transfected
into NIH/3T3 cells. Cells expressing these silent mutations also differentially activate signaling
cascades. Most interestingly, these silent mutations lead to differences in transformation
potential of NIH/3T3 cells, as measured by differences in proliferation rates, saturation density,
loss of contact inhibition, migration, and invasion. This study contributes to our understanding
of how silent mutations may affect protein expression in mammalian cells, advances our
knowledge of RAS proteins and cancer, and provides a link between silent mutations and
tumorigenic phenotypes in mammalian cells.
MATERIALS AND METHODS
Plasmid Construction
Site-Directed Mutagenesis
The KRAS 4B WT, which contained the nucleotide sequence for wild-type human
KRAS, and KRAS 4B G12V, which contained the nucleotide sequence for a human oncogenic,
aggressive missense mutant KRAS, entry clone plasmids (R999-E01 and R999-E21,
respectively) were kindly provided by Dr. Dominic Esposito (Cancer Research Technology
Program, Frederick National Laboratory for Cancer Research, Frederick, MD) (Figure 8). Sitedirected mutagenesis was performed on the KRAS 4B WT plasmid with the Q5® Site-Directed
Figure 8. Entry Clone Plasmid Constructs. R999-E01 (left) is the entry clone plasmid
containing the human WT KRAS 4B sequence, from which all silent mutations were derived
with site-directed mutagenesis. R999-E21 (right) is the entry clone plasmid containing the
oncogenic human KRAS 4B G12V sequence. attL1 and attL2 are recombination attachment
sites used in Gateway cloning [92]. ori = Origin of replication, SpnR = spectinomycin resistance
gene.
Mutagenesis Kit (New England Biolabs, Inc., Ipswich, MA) to generate the silent mutations at
amino acids G12, G13, G60, G48, G77, and G153 (nucleotide positions 36, 39, 180, 144, 231,
and 453, respectively) with primers (Eurofins MWG Operon LLC, Huntsville, AL) listed in
Table 6. Briefly, the lyophilized primers were first dissolved to 200 µM in reverse osmosis
26
27
(RO) water and then further diluted with RO water to 5 µM. Separate mutagenic polymerase
chain reactions (PCRs) were carried out in 25 µl reactions containing 1 ng R999-E01, 250 nM of
each primer (forward and reverse), and1X Q5® Hot Start High-Fidelity Master Mix (New
England Biolabs, Inc., Ipswich, MA). After an initial 30 second 98°C denaturation, the reactions
were cycled 15 times between a 98°C denaturation step for 10 seconds, an annealing step (see
Table 6 for specific annealing temperatures of each reaction) for 30 seconds, and a 72°C,
extension step for 2 minutes. After cycling, all reactions underwent a final extension at 72°C for
2 minutes. To phosphorylate the 5' hydroxyl group, circularize the plasmid-length PCR
products, and digest the background plasmid, 1 µl of PCR product from each reaction was
incubated for 5 minutes at room temperature in a 10 µl reaction of 1X KLD Reaction Buffer
containing 1X KLD Enzyme Mix (kinase, ligase, Dpn1restriction enzyme) (New England
Biolabs, Inc., Ipswich, MA).
E. coli Transformations and Generation of Purified Plasmid DNA
To transform E. coli cells with the plasmids, 5 µl of KLD mix from each reaction were
added to 50 µl of NEB 5-alpha High Efficiency Competent E. coli cells (DH5α derivative) (New
England Biolabs, Inc., Ipswich, MA) in a 1.5 ml microtube and incubated on ice for 30 minutes.
The cells were heat shocked at 42°C for 30 seconds in a water bath, followed by a 5 minute
incubation on ice. SOC medium (New England Biolabs, Inc., Ipswich, MA) was added to a total
volume of 1 ml for each transformation, and the cells were incubated on a 37°C thermo mixer
(Eppendorf, Inc., Enfield, CT) at 1400 RPM for 1 hour. One tenth (100 µl) of the reaction was
spread onto Luria-Bertani Broth (LB)-spectinomycin (100 µg/ml) (made in-house) plates and
incubated overnight at 37°C. Transforming 2 pg pUC19 (New England Biolabs, Inc., Ipswich,
28
Table 6. Primers Used for Generating Silent Mutations
Amino
Acid/Nucleotide
G12G 36 T→A
G12G 36 T→C
G12G 36 T→G
G13G 39 C→A
G13G 39 C→G
G13G 39 C→T
G60G 180 T→A
G60G 180 T→C
G60G 180 T→G
G48G 144 A→C
G48G 144 A→G
G48G 144 A→T
G77G 231 C→A
G77G 231 C→G
G77G 231 C→T
G151G T→A
G151G T→C
G151G T→G
Primer Sequence
Fwd Primer
5' TAGTTGGAGCTGGAGGCGTAGGCAAGAGTGCCTTGACGATAC 3'
Rev Primer
5' CCACAAGTTTATATTCAGTCATGGGTGCCAACTTTTTTGTAC 3'
Fwd Primer
5' TAGTTGGAGCTGGCGGCGTAGGCAAGAGTGCCTTGACGATAC 3'
Rev Primer
5' CCACAAGTTTATATTCAGTCATGGGTGCCAACTTTTTTGTAC 3'
Fwd Primer
5' TAGTTGGAGCTGGGGGCGTAGGCAAGAGTGCCTTGACGATAC 3'
Rev Primer
5' CCACAAGTTTATATTCAGTCATGGGTGCCAACTTTTTTGTAC 3'
Fwd Primer
5' GAGCTGGTGGAGTAGGCAAGA 3'
Rev Primer
5' CAACTACCACAAGTTTATATTCAGTC 3'
Fwd Primer
5' GAGCTGGTGGGGTAGGCAAGA 3'
Rev Primer
5' CAACTACCACAAGTTTATATTCAGTCATTTAC 3'
Fwd Primer
5' GAGCTGGTGGTGTAGGCAAGA 3'
Rev Primer
5' CAACTACCACAAGTTTATATTCAGTCATTTAC 3'
Fwd Primer
5' ACACAGCAGGACAAGAGGAGTAC 3'
Rev Primer
5' CGAGAATATCCAAGAGACAGG 3'
Fwd Primer
5' ACACAGCAGGCCAAGAGGAGTAC 3'
Rev Primer
5' CGAGAATATCCAAGAGACAGG 3'
Fwd Primer
5' ACACAGCAGGGCAAGAGGAGT 3'
Rev Primer
5' CGAGAATATCCAAGAGACAGGTTTC 3'
Fwd Primer
5' TAATTGATGGCGAAACCTGTCTC 3'
Rev Primer
5' CTACTTGCTTCCTGTAGG 3'
Fwd Primer
5' TAATTGATGGGGAAACCTGTC 3'
Rev Primer
5' CTACTTGCTTCCTGTAGG 3'
Fwd Primer
5' TAATTGATGGTGAAACCTGTCTC 3'
Rev Primer
5' CTACTTGCTTCCTGTAGG 3'
Fwd Primer
5'CTGGGGAGGGATTTCTTTGTG 3'
Rev Primer
5' TCCTCATGTACTGGTCCC 3'
Fwd Primer
5' CTGGGGAGGGGTTTCTTTGTG 3'
Rev Primer
5' TCCTCATGTACTGGTCCC 3'
Fwd Primer
5' CTGGGGAGGGTTTTCTTTGTG 3'
Rev Primer
5' TCCTCATGTACTGGTCCC 3'
Fwd Primer
5' CAAGACAGGGAGTTGATGATG 3'
Rev Primer
5' TCTTTGCTGATGTTTCAATAAAAG 3'
Fwd Primer
5' CAAGACAGGGCGTTGATGATG
Rev Primer
5' TCTTTGCTGATGTTTCAATAAAAG 3'
Fwd Primer
5' CAAGACAGGGGGTTGATGATG 3'
Rev Primer
5' TCTTTGCTGATGTTTCAATAAAAG 3'
Annealing Temp
(°C)
The mutated base to be introduced is underlined and colored in red.
60
60
60
63
66
66
63
63
66
59
58
58
64
64
63
59
59
59
29
7
MA) as a transformation control yielded 121 colonies, or a competency of 6.05 x 10 colony
forming units (cfu)/µg plasmid DNA. The silent mutant-transformed E. coli cells yielded ~1000
colonies on each plate. Cultures from 10 colonies for each construct were grown overnight in 2
inch orbit shakers (Eppendorf, Inc., Enfield, CT) at 37°C, 231 RPM, in 2 ml of Superior Broth
(SB) (Athena Enzyme Systems, Baltimore, MD)-spectinomycin (100 µg/ml) in 24-well blocks
(GreenTree Scientific, Inc., Bloomfield, NY) covered with gas permeable tissue culture plate
seals (GreenTree Scientific, Inc., Bloomfield, NY). To purify the plasmid DNA from the
cultures, cells were centrifuged at 16,000 x g for 2 minutes (Model 5430R, Eppendorf, Inc.,
Enfield, CT), the supernatant was discarded, and plasmid DNA was isolated from the cell pellets
using the QIAprep Spin Miniprep Kit (Qiagen, Hilden, Germany) according to the
manufacturer's protocol. Plasmids were eluted in total volumes of 75 µl in 1X TE (10 mM TrisHCl, pH 8.0, 0.1 mM EDTA). DNA concentrations were typically ~100 µg/ml as determined by
absorbance at 260 nm with a NanoDrop 1000 (Thermo Fisher Scientific, Waltham, MA).
Sanger Sequencing and Plasmid Validation
Eight clones for each plasmid construct (100 ng purified plasmid DNA loaded into each
well) were run on 0.8% agarose gels (Embitec, San Diego, CA) at 100V for 45 minutes buffered
in 1X Tris-Ethylenediaminetetraacetate (EDTA) (TE) containing 0.2 µg/ml Ethidium Bromide
(Sigma Aldrich, St. Louis, MO). Four clones of approximately the correct plasmid size (3260
base pairs (bp) for WT and all silent mutations, 3792 bp for G12V) (see Figure 8) for each
construct were Sanger sequenced in the forward and reverse directions. The purified plasmids
were diluted 1:3 into 500 nM forward or reverse primer (Table 7) and cycle sequenced in the
presence of chain-terminating fluorescent dideoxynucleotides. Successful mutagenesis
30
constructs contained the desired silent mutation in both the forward and reverse direction (Figure
9). One sequence-verified clone for each construct was run on a 0.8% agarose gel at 100V for 45
minutes buffered in 1X TE containing 0.2 µg/ml Ethidium Bromide to confirm the plasmid size
(Figure 10).
Table 7. Sanger Sequencing Primers for Entry Clone Constructs
Sequencing
Primer Name
Primer Sequence
Fwd Primer
DF
5’ CCCAGTCACGACGTTGTAAAACG 3'
Rev Primer
DR
5' GTAACATCAGAGATTTTGAGACAC 3'
Gateway Cloning
KRAS 4B genes from the entry clones were transferred to destination vectors using
Gateway® site-specific recombination (Life Technologies Corp, Carlsbad, CA) as previously
described by performing LR reactions (Figure 11) [92]. Destination vector DNA (pDest720) was
kindly provided by Dr. Dominic Esposito (Frederick National Laboratory for Cancer Research,
Frederick, MD) (Figure 11). To transfer the KRAS 4B controls (WT and G12V) and the silent
mutants into the destination vector, 1 μl of each validated construct (~100 ng) was incubated at
30°C for 1 hour with 120 ng pDest720 and 10 U of LR2 Clonase (Life Technologies Corp.,
Carlsbad, CA) in a total volume of 5 μl. After the incubation, 1 μl of proteinase K (Life
Technologies Corp., Carlsbad, CA) was added and the reactions were incubated at 37°C for 15
minutes. To transform the E. coli with the expression plasmids, 1 μl of each LR reaction was
incubated with 20 μl NEB 5-alpha high efficiency competent E. coli cells in 1.5 ml microtubes.
The cells were heat shocked at 42°C for 30 seconds in a water bath, followed by a 5 minute
incubation on ice. SOC medium was added to a total volume of 100 μl, and the cells were
incubated on a 37°C thermo mixer for 1 hr at 1400 RPM. The entire reactions were spread onto
31
Figure 9. Alignment of Sanger Sequencing Results for Confirmed Constructs. Using ClustalX
2.1, the sequencing results for the forward and reverse reads were aligned. Dots in between
panels denote breaks in the sequence for illustration purposes. Asterisks on the left denote a
nucleotide position whereby all constructs (in both directions) maintain the same base. Lack of
an asterisk along the left, or a dip in the gray bar graph along the right, denote at least one
sequence having a different base at that position. Red = A, Blue = C, Orange = G, Green = T.
32
Figure 10. Agarose Gel Electrophoresis of KRAS 4B WT, G12V, G12G, G13G, and G60G
Silent-Mutant Entry Clone Plasmids. Uncut plasmids containing KRAS 4B WT or the silent
mutations constructs derived from it at G12, G13, and G60 (nucleotide positions 36, 39, and 180,
respectively) migrate at the expected size of 3260 bp. KRAS 4B G12V migrates at the expected
size of 3792 bp. Higher molecular weight bands are nicked and/or dimer plasmid DNA bands.
G12V migrates more slowly because it is in a different vector backbone (see Figure 8). SC =
supercoiled ladder (Life Technologies Corp., Carlsbad, CA).
Figure 11. Site-specific Recombination. Incubating a destination vector and an entry clone in the
presence of LR2 Clonase results in recombination at the att sites, leading to efficient gene
transfer into an expression clone. The KRAS 4B gene takes the place of the CAT/ccdb cassette.
ori = Origin of replication, bla = ampicillin resistance gene, SV40-EM-Zeocin = zeocin
resistance gene under control of an SV40 promoter, CMV = cytomegalovirus promoter.
separate LB + ampicillin (100 μg/ml) plates (made in-house) and incubated overnight at 37°C.
33
The constructs yielded between 100 and 300 colonies per transformation. An individual colony
for each construct was picked and grown in 50 ml of SB + ampicillin (100 µg/ml) liquid culture
in 250 ml baffled flasks overnight at 37°C, 231 RPM, in an orbital shaker rotating in a 2 inch
orbit. The cultures were then centrifuged at 3,000 x g at 4°C (Model J20-XP, Beckman Coulter,
Brea, Ca) for 10 minutes to pellet the E. coli cells and plasmid DNA was purified from the cell
pellets using the GenElute™ HP Plasmid Maxiprep kit (Sigma Aldrich, St. Louis, MO)
according to the manufacturer’s instructions. Each purified plasmid was eluted in 75 µl 1X TE.
Plasmid size was confirmed for all constructs with 0.8% agarose gel electrophoresis (Figure 12).
Figure 12. Agarose Gel Electrophoresis of eGFP, KRAS 4B WT, G12V, G12G, G13G, and
G60G Silent-Mutant Expression Clone Plasmids. Plasmids containing KRAS 4B WT, KRAS 4B
G12V, or the silent mutations constructs derived from it at G12, G13, and G60 (nucleotide positions 36, 39, and 180, respectively) migrate at the expected molecular weight of 6962 bp. The
enhanced green fluorescent protein (eGFP) plasmid (mock transfection) migrates slightly higher
(7112 bp) because the open reading frame (ORF) is 238 amino acids as opposed to the KRAS
ORF (188 amino acids). SC = supercoiled ladder (New England Biolabs, Inc., Ipswich, MA).
Prediction Programs
Secondary structure and free energy
Secondary structures and free energies of the KRAS coding region were predicted by
entering the mRNA sequence of each construct, from the start codon to the stop codon, into the
34
MFold web server [100, 101]. To examine the local predicted secondary structure and free
energy, the first 61 nucleotides downstream of the start site were used for G12V, G12G and
G13G mutations. Nucleotides 150-211 were used to examine the local predicted secondary
structure and free energy of the G60G mutations.
miRNA
Predictions of miRNA binding sites in the coding region of the KRAS gene were generated
with the SVM-based software tool, MiRPara [103].
Cell Culture
Mouse embryonic fibroblast NIH/3T3 cells were purchased from the American Type
Culture Collection (ATCC, Manassas, VA). NIH/3T3 cells were maintained and propagated at
37°C in Dulbecco’s Modified Eagle Medium (DMEM) (ATCC, Manassas, VA) supplemented
with 10% fetal bovine serum (FBS) (Hyclone, Logan, UT). FBS is a slaughterhouse byproduct
rich in growth factors containing high levels of bovine serum albumin (BSA). The cells were
cultured in a humid atmosphere of 5% carbon dioxide (CO2), 95% air in a Forma Series II Water
Jacketed CO2 Class HEPA Class 100 Incubator (Model 3110, Thermo Fisher Scientific,
Waltham, MA). NIH/3T3 cells were plated in 75 cm2 tissue culture flasks (catalog #430641,
Corning Life Sciences, Inc., Corning, NY) at a density of 3.75 x 105 viable cells/75 cm2 tissue
culture flask, and passaged every three days (~60% confluent). Plating at higher cell densities (5
x 105 viable cells/75 cm2 tissue culture flask) resulted in contact inhibition after 72 hours, altered
morphology, and varied protein expression profiles. All experiments were carried out when cells
were between passage 2 and passage 10, and cell viabilities were maintained ≥90%. All cell
35
®
manipulations were conducted in an ESCO Airstream Class II laminar flow biosafety cabinet
(ESCO Corporation, Portland, OR) inside a locked laboratory that housed no other cell lines.
Cells were harvested with 1 ml 0.25% Trypsin- EDTA (Life Technologies Corp,
Carlsbad, CA), and neutralized with 4 ml fresh, complete culture medium (ratio of neutralization
medium to trypsin solution of 4:1) unless otherwise noted. Serum-deprivation conditions were
generated by culturing cells for 18-24 hours in 20-fold reduced serum concentrations (DMEM +
0.5% FBS for NIH/3T3 cells) or serum-free conditions (DMEM). Unless otherwise noted, cell
number and viability was determined by counting harvested cells in triplicate in 0.2% Trypan
Blue (Bio-Rad, Hercules, CA) in a TC-20™ Automated Cell Counter (Bio-Rad, Hercules, CA),
and the triplicate counts were averaged. Average cell diameter was also measured by the cell
counter. Viability was determined in the cell counter based on the ability of cells to absorb (dead
cells) or not absorb (live cells) Trypan Blue stain.
Cell Line Authentication
NIH/3T3 cells were centrifuged (1 x 106 cells) at 200 x g (Model 5810R, Eppendorf, Inc.,
Enfield, CT) for 5 minutes at 4°C and the supernatant was discarded. Extraction of genomic
DNA was performed with the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) according to
the manufacturer's protocol. Briefly, pelleted cells were resuspended in 1X phosphate buffered
saline (PBS), lysed with a guanidine-based proprietary lysis buffer in the presence of proteinaseK (Qiagen, Hilden, Germany), and heated to 56°C to lyse the cells. Samples were washed, and
the DNA was column purified and eluted with TE buffer (made in house). DNA was quantified
at 260 nm with a NanoDrop 1000.
To verify the NIH/3T3 cells were not contaminated with any human cell lines, the
36
extracted DNA was amplified by PCR using the AmpFℓSTR® Identifiler PCR amplification kit
(Life Technologies Corp., Carlsbad, CA), a short tandem repeat (STR) multiplex assay. PCR
was also performed on a positive control amplicon and several human cell lines concurrently.
The denatured fragments were analyzed on an Applied Biosystems 3130xl Genetic Analyzer
(Life Technologies Corp., Carlsbad, CA) in Hi-Di formamide (Life Technologies Corp.,
Carlsbad, CA) with a molecular weight standard. The fragments were labeled and identified
using GeneMapper 4.0 (Life Technologies Corp., Carlsbad, CA). There was no amplification of
any human STR's in the NIH/3T3 sample, but all human cell lines, which served as a positive
control, yielded a positive result.
To verify the identity of the NIH/3T3 cells, the extracted DNA was amplified and STR
analysis was performed using the mouse cell line authentication assay as previously described
[115]. Electropherogram peaks confirmed the identity of the NIH/3T3 cells (Figure 13), and
reconfirmed there was no visible human cell line contamination.
Figure 13. STR Profile of NIH/3T3 Cells from Mouse Cell Line Authentication Assay. Peaks
define the STR profile of NIH/3T3 cells as described previously [115]. Smaller peaks in front of
or behind the main STR peaks are from polymerase stutter, a PCR artifact commonly seen when
amplifying repeat regions.
37
At periodic intervals spanning the duration of the in vitro experiments (beginning,
middle, end), the cells were analyzed with the PCR-based Venor™ GeM Mycoplasma Detection
Kit (Minerva Biolabs GmbH, Berlin, Germany) to detect potential cell line contamination with
Mycoplasma, Acholeplasma, and Ureaplasma species according to the manufacturer's protocol.
The cells remained negative for Mycoplasma, Acholeplasma, and Ureaplasma contamination
throughout the experiments.
Transient Transfections
All transfections were carried out in 75 cm2 tissue culture (poly-lysine treated) flasks or
tissue culture (poly-lysine treated) six-well plates (Corning Life Sciences, Inc., Corning NY).
Cells were plated the day before transfection at a ratio of 26,667 viable cells per square
centimeter, regardless of vessel type. The day of the transfections, culture medium was
exchanged 1-2 hours before transfection to fresh culture medium (DMEM + 10% FBS).
To be able to monitor transfection efficiency, all transient transfections were cotransfections, in which we transfected both a KRAS construct and an mCherry (a red fluorescent
protein) construct into the cells. Transfection efficiency was monitored with a LSRFortessa
Flow Cytometer (BD Biosciences, San Jose, CA) with a 561 nm laser, a 600 longpass filter, and
a 610/20 bandpass filter. For co-transfections, cells were transfected with FuGENE HD
transfection reagent (Promega Life Sciences, Madison, WI) in Optimem (Life Technologies
Corp, Carlsbad, CA) with a reagent to DNA ratio of 2.5:1 (v/v) at a ratio of 12.5 pg DNA/cell
(6.25 pg KRAS plasmid DNA/cell and 6.25 mCherry pg plasmid DNA /cell). Spent medium
containing the transfection mixture was replaced with fresh medium 24 hours post-transfection.
38
Stable Selections
To select for stably transfected cells, cells were transfected (note these are not cotransfections) with FuGENE HD in Optimem with a reagent to DNA ratio of 2.5:1 (v/v) at a ratio
of 6.25 pg KRAS plasmid DNA/cell. After 48 hours, 6 x 105 viable cells were plated in tissue
culture (poly-lysine treated) six-well plates and propagated at 37°C, 5% CO2 in DMEM + 10%
FBS + 700 µg/ml zeocin (Life Technologies Corp., Carlsbad, CA), for three weeks, passaging
when cells became >60% confluent. Zeocin is an antibiotic that intercalates into DNA and
creates irreparable double-strand breaks. Only cells that are expressing a zeocin-resistance gene,
provided by the plasmid, survived. Fresh zeocin-containing DMEM + 10% FBS was exchanged
for the spent culture medium every three to four days. Stably-selected cells were grown as pools.
Immunoblotting
Immunoblots were performed by loading 20 µg of total protein from a cell lysate per gel
lane. To lyse the cells, culture medium was removed from the tissue culture treated flasks and
cells were washed 2 times with ice cold 1X PBS. Cells were incubated with 8 µl lysis buffer per
square centimeter of surface area for 15 minutes at 4°C before scraping the lysate into a precooled microtube with a cell scraper. Lysis buffer composition was 150 mM NaCl, 20 mM Tris
pH 7.5, 1% Triton X-100, 1 mM EDTA, including cOmplete™, EDTA-Free, Protease Inhibitor
Cocktail Tablets (1 tablet per 10 ml lysis buffer) (Sigma Aldrich, St. Louis, MO) and
PhosSTOP™ phosphatase inhibitors (1 tablet per 10 ml lysis buffer) (Sigma Aldrich, St. Louis,
MO). The insoluble fraction was separated by centrifugation (21,000 x g, 15 minutes, 4°C)
(Model 5430R) and the protein concentration of the soluble fraction was determined by
bicinchoninic acid (BCA) assay (Pierce Biotechnologies, Waltham, MA). All protein
39
concentrations were normalized before loading gels. All SDS-PAGE gels were 12-well or 26well, precast Tris-HCl Criterion gels (Bio-Rad, Hercules, CA), and were 4-15%, 10.5-14%, or
10-20% gradient gels, depending on the size of the interrogated protein. Gels were run in
Criterion Vertical Electrophoresis Cells (Bio-Rad, Hercules, CA) at a constant voltage of 205V
for 50 minutes in Tris-Gly-SDS running buffer (Bio-Rad, Hercules, CA). Gels were transferred
to nitrocellulose membranes using the semi-dry Iblot transfer system (Life Technologies Corp,
Carlsbad, CA) for 7 minutes. Membranes were washed 4 times in 1X tris-buffered saline tween20 (TBS-T) (Bio-Rad, Hercules, CA) before blocking in 3% nonfat dry milk (Bio-Rad, Hercules,
CA) for 1 hour. Membranes were washed again 4 times in 1X TBS-T and incubated against
primary antibodies overnight at 4°C in 3% nonfat dry milk with gentle agitation on a VWR
Rocking Platform (Model 200, VWR International, Radnor, PA). The membranes were then
washed 4 times in 1X TBS-T and then incubated with appropriate secondary antibodies (defined
below) for one hour at room temperature. Membranes were then washed 4 times with 1X TBS-T
and developed after a 2-minute incubation with SuperSignal™ West Femto Maximum
Sensitivity Substrate (Life Technologies Corp, Carlsbad, CA) (for endogenous proteins) or
SuperSignal™ West Pico Chemiluminescent Substrate (Life Technologies Corp, Carlsbad, CA)
(for overexpressed proteins). Anti-KRAS (cat # WH0003845M1) was purchased from Sigma
Aldrich (St. Louis, MO). Anti-Mek1/2 (cat # 9122), anti-phospho-Mek1/2 Ser 217/221 (cat #
9121), anti-Erk1/2 (cat # 9102), anti phospho-Erk1/2 Thr202/Tyr204 (cat # 9101, and E10 cat#
9106), anti-Akt (cat # 9272), anti-phospho-Akt Ser473 (cat # 9271), goat anti-rabbit IgG HRPlinked secondary antibody (cat #7074), and horse anti-mouse IgG HRP-linked secondary
antibody (cat # 7076) were purchased from Cell Signaling Technologies (Danvers, MA). AntiGAPDH (cat #2275-PC-100) was purchased from Trevigen, Inc. (Gaithersburg, MD). Anti-
40
mCherry (cat # 5993-100) was purchased from BioVision, Inc. (Milpitas, CA). Anti-RalA (cat #
240802) was purchased from Cell Biolabs, Inc., San Diego, CA). All primary antibodies were
diluted 1:1000 in 3% nonfat dry milk and all secondary antibody dilutions were 1:2000 in 3%
nonfat dry milk. All immunoblots were imaged on a LAS-4000 intelligent dark box (FujiFilm,
Valhalla, NY). Quantification of band intensity was done using ImageJ software (National
Institutes of Health, Bethesda, MD).
Active Ras Pull-Down
Twelve replicates of each stably-selected cell line were seeded at 3 x 105 viable cells into
two tissue-culture treated six well plates. After an overnight, 37°C, 5% CO2 incubation, culture
medium was removed from the tissue culture treated flasks and cells were washed 2 times with
ice cold 1X PBS. Cells were incubated with lysis buffer (150 mM NaCl, 20 mM Tris pH 7.5,
1% Triton X-100, 1 mM EDTA, including protease and phosphatase inhibitors as described
above) at 4°C for 15 minutes before pooling the lysate from the 12 wells for each cell line into a
pre-cooled (on wet ice) microtube with a cell scraper. The insoluble fraction was separated by
centrifugation (21,000 x g, 15 minutes, 4°C) (Model 5430R) and the protein concentration of the
soluble fraction was determined by BCA assay. The remainder of the assay was performed by
following the instructions in the Active Ras Pull-Down and Detection Kit (Thermo Fisher
Scientific, Waltham, MA). Briefly, all protein concentrations were normalized to 400 ng/μl with
1X Lysis/Binding/Wash Buffer in a total volume of 750 μl (Thermo Fisher Scientific, Waltham,
MA). After thoroughly resuspending the glutathione resin/agarose beads (Thermo Fisher
Scientific, Waltham, MA), 100 μl of the 50% resin slurry was added to the spin cup/collection
tube. Spin cup/collection tubes were centrifuged at 6,000 x g (Model 5430R) for 30 seconds and
41
the flow-through was discarded. GST-Raf1-RBD (80 μg) (Thermo Fisher Scientific, Waltham,
MA) was added to the spin cups containing the glutathione resin (Thermo Fisher Scientific,
Waltham, MA). Diluted lysates (240 μg in 600 µl) were transferred to the spin cups which were
then thoroughly vortexed with a Vortex Genie 2 (VWR International, Radnor, PA). After
sealing the caps of the collection tubes with parafilm (Bemis NA, Neenah, WI), the reactions
were incubated for 1 hour at 4°C with gentle rocking on a VWR Rocking Platform (Model 200).
After incubation, the spin cups were centrifuged at 6,000 x g for 30 seconds (Model 5430R).
The spin cups were transferred to a new collection tube and the resin was washed 3 times with
Lysis/Binding/Wash Buffer by adding 400 μl of buffer to spin cups, inverting, centrifuging at
6,000 x g for 30 seconds (Model 5430R), and aspirating the flow-through. The spin cups were
transferred to a new collection tube and 50 μl of 2X reducing sample buffer (Thermo Fisher
Scientific, Waltham, MA) containing β-mercaptoethanol (Sigma Aldrich, St. Louis, MO) were
added to the resin and incubated at room temperature for 2 minutes before centrifuging the tube
at 6,000 x g for 2 minutes (Model 5430R). The spin cups were discarded and the eluates were
heated for 10 minutes at 70°C. The entire samples were loaded into 10.5-14% Tris-HCl gradient
gels. The gel was electrophoresed for 50 minutes at a constant voltage of 205V before
transferring to a nitrocellulose membrane using the semi-dry Iblot transfer system for 7 minutes.
The membrane was washed 4 times in 1X TBS-T before blocking in 3% nonfat dry milk (BioRad, Hercules, CA) for 1 hour. The membrane was washed again 4 times in 1X TBS-T and
incubated against KRAS antibody (Sigma Aldrich, St. Louis MO, described above in the
Immunoblotting section) overnight at 4°C in 3% nonfat dry milk. The membrane was then
washed 4 times in 1X TBS-T and then incubated with horse anti-mouse IgG HRP-linked
secondary antibody (cat # 7076) (Cell Signaling Technologies, Danvers, MA, described above in
42
the Immunoblotting section) for one hour at room temperature. The membranes were then
washed 4 times with 1X TBS-T and developed after a 2 minute incubation with SuperSignal™
West Femto Maximum Sensitivity Substrate.
Active Ral A Pull-Down
Twelve replicates of each stably-selected cell line were seeded at 3 x 105 viable cells into
two tissue-culture treated six well plates. After an overnight, 37°C, 5% CO2 incubation, the
culture medium was removed from the tissue culture treated flasks and cells were washed 2
times with ice cold 1X PBS. Cells were incubated with lysis buffer (150 mM NaCl, 20 mM Tris
pH 7.5, 1% Triton X-100, 1 mM EDTA, including protease and phosphatase inhibitors as
described) at 4°C for 15 minutes before pooling the lysate from the 12 wells for each cell line
into a pre-cooled (on wet ice) microtube with a cell scraper. The insoluble fraction was
separated by centrifugation (21,000 x g, 15 minutes, 4°C) (Model 5430R) and the protein
concentration of the soluble fraction was determined by BCA assay. The remainder of the assay
was performed by following the instructions in the Ral Activation Assay Kit (Cell Biolabs, Inc.,
San Diego, CA). Briefly, all protein concentrations were normalized to 667 ng/μl with 1X Assay
Lysis Buffer in a total volume of 750 μl). Diluted lysates (240 μg in 600 µl) were transferred to
microtubes, and the volumes were adjusted to 1 ml. The RalBP1 PBD Agarose bead slurry was
thoroughly resuspended by vortexing before adding 40 μl of the resuspended bead slurry to each
tube (Cell Biolabs, Inc., San Diego, CA). The tubes were then incubated at 4°C for 1 hour with
gentle rocking on a VWR Rocking Platform (Model 200). After the incubation, the beads were
pelleted by centrifugation at 14,000 x g for 30 seconds (Model 5430R) and the supernatant was
discarded. Beads were washed 3 times with 500 μl of 1X Assay Buffer by recurrent 14,000 x g
43
30 second centrifugations (Model 5430R) and subsequent aspirations. After the last wash, beads
were pelleted and the supernatant was carefully removed. The samples were resuspended in 2X
LDS loading buffer/TCEP (Cell Biolabs, Inc., San Diego, CA) before incubating samples at
70°C for 10 minutes. The entire samples were loaded into 10.5-14% Tris-HCl gradient gels.
The gel was electrophoresed for 50 minutes at a constant voltage of 205V before transferring to
nitrocellulose membranes using the semi-dry Iblot transfer system for 7 minutes. Gels were
washed 4 times in 1X TBS-T before blocking in 3% nonfat dry milk (Bio-Rad, Hercules, CA) for
1 hour. Gels were washed again 4 times in 1X TBS-T and incubated against Anti-Ral A
overnight at 4°C in 3% nonfat dry milk. The membrane was then washed 4 times in 1X TBS-T
and then incubated with horse anti-mouse IgG HRP-linked secondary antibody (cat # 7076) (Cell
Signaling Technologies, Danvers, MA, described above in the Immunoblotting section) for one
hour at room temperature. The membrane was then washed 4 times with 1X TBS-T and
developed after a 2 minute incubation with SuperSignal™ West Femto Maximum Sensitivity
Substrate.
Human KRAS 4B mRNA Quantification
Purifying Total RNA
Cells were transiently transfected as described above under the transient transfections
heading. Seventy-two hours post-transfection, the spent culture medium was removed from the
tissue culture flasks, the cells were washed with 1X PBS, and 1 ml of TriZOL LS (Life
Technologies Corp, Carlsbad, CA) was added directly to the flask, and the cells were incubated
for 5 minutes at room temperature. Lysates were then scraped from the flasks and aliquoted into
microtubes. After 1–bromo–3–chloropropane (BCP, a chloroform substitute) was added to each
44
microtube (100 μl), the tubes were shaken vigorously for 15 seconds before incubating at room
temperature for 3 minutes. After incubating, the tubes were centrifuged at 15,294 x g for 15
minutes at 2°C (Model 5430R). The aqueous phase was removed and aliquoted into a fresh
microtube containing 500 μl of 100% isopropyl alcohol (Thermo Fisher Scientific, Waltham,
MA). The tubes were incubated at room temperature for 15 minutes before centrifuging at
15,294 x g for 10 minutes at 2°C (Model 5430R). The supernatant was aspirated and 1 ml of
75% ethanol (Pharmco-Aaper, Brookfield, CT) was added to each pellet, and the pellets were
washed by vortexing thoroughly. The tubes were then centrifuged at 5,974 x g for 5 minutes at
2°C (Model 5430R). The ethanol was aspirated, and the pellet was air-dried for 5 minutes in a
laminar flow hood before being dissolved in 50 μl of RNase-free water (Life Technologies
Corp., Carlsbad, CA). Samples were diluted to ~100 ng/μl and run on a 0.8% agarose gel with
0.2 µg/ml ethidium bromide to ensure the integrity of the total RNA (Figure 14).
Figure 14. Agarose Gel Electrophoresis of Total RNA from NIH/3T3 Cells Transiently
Transfected with eGFP, KRAS 4B WT, G12V, G12G, G13G, and G60G Silent-Mutant Entry
Clone Plasmids. Total RNA for all samples shows two distinct bands. The integrity of the total
RNA is similar for each sample.
45
Generating complementary DNA (cDNA) from total RNA
To degrade any residual genomic or plasmid DNA, the samples were treated with 5 U
DNase I in 1X DNase Reaction Buffer (Zymo Research Corp., Irvine, CA) at room temperature
for 20 minutes before a 75°C, 10 minute heat inactivation step. Then total RNA was converted
to cDNA using the High Capacity cDNA Reverse Transcription Kit (Life Technologies Corp.,
Carlsbad, CA) according to the manufacturer’s instructions. Briefly, 50 ng/μl of total RNA was
added to a reaction including 1X RT random primers (Life Technologies Corp., Carlsbad, CA) in
1X RT buffer (Life Technologies Corp., Carlsbad, CA) containing 1 μl of Multiscribe™ Reverse
Transcriptase (Life Technologies Corp., Carlsbad, CA) and 3.2 mM dNTP mix (Life
Technologies Corp., Carlsbad, CA) in a total of 50 μl (2.5 μg of total RNA) for each construct.
To generate the cDNA, the reactions were incubated at 25°C for 10 minutes to anneal and extend
the random primers, followed by 37°C incubation for 120 minutes for synthesis, and then a 85°C
incubation for 5 minutes to eliminate enzymatic activity. The samples were then incubated
overnight at 4°C.
Digital Droplet PCR (ddPCR)
Reactions containing 167 pg of each cDNA in 1X ddPCR Supermix (Bio-Rad, Hercules,
CA) containing 900 nM probe primers (Bio-Rad, Hercules, CA), 900 nM reference primers (BioRad, Hercules, CA), 250 nM FAM probe (Bio-Rad, Hercules, CA), 250 nM VIC probe (BioRad, Hercules, CA) (Table 8), and a hot start polymerase were incubated in 20 μl reactions in a
DG8 cartridge (Bio-Rad, Hercules, CA) with 70 µl of droplet generation oil (Bio-Rad, Hercules,
CA). VIC (maximum excitation 538 nm, maximum emission 534 nm) and FAM (maximum
excitation 494 nm, maximum emission 518 nm) are common fluorescent nucleotide labeling
46
dyes. VIC-labeled glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) primers were
commercially purchased (Life Technologies Corp., Carlsbad, CA) and used for normalization.
Droplets were generated in a QX-100 droplet generator (Bio-Rad, Hercules, CA). After droplet
formation, 40 µl of droplets were aliquoted into a twin.tec 96-well semi-skirted PCR plate
(Eppendorf Inc., Enfield, CT) and incubated at 95°C for 10 minutes in a T100 thermal cycler
(Bio-Rad, Hercules, CA). The reactions then underwent 40 cycles, each cycle consisting of a
94°C, 30 second denaturation step followed by a 60°C, 60 second step annealing/extension step
with a ramp rate of 2°C/second. After cycling, the reactions underwent 98°C incubation for 10
minutes, and then were incubated overnight at 4°C before reading the plate on a QX-200 (BioRad, Hercules, CA) droplet reader and analyzing with QuantaSoft 1.5 software (Bio-Rad,
Hercules, CA).
Table 8. Human KRAS 4B Digital Droplet PCR Primers
Fwd Primer
KRAS 4B
5' GAAGTTATGGAATTCCTTTTATTGAAACA 3'
Rev Primer
KRAS 4B
5' ACATTAGTTCGAGAAATTCGAAAACA 3'
Probe
KRAS 4B
5' 6FAM-ACAGGGTGTTGATGATG-MGB 3'
Proliferation Assays
Cell Titer-Glo® Luminescent Cell Viability Assays
To measure proliferation with Cell Titer-Glo® Luminescent Cell Viability Assays
(Promega Life Sciences, Madison, WI), cells co-transfected with mCherry and KRAS constructs
(as described previously in the Transient Transfections section) were harvested 48-hours post
transfection and were plated in triplicate into eight 96-well tissue culture (poly-lysine treated)
plates (Corning Life Sciences, Inc, Corning, NY) containing 100 µl of DMEM + 10% FBS. One
plate was frozen at -80°C immediately, and the other 7 plates were incubated at 37°C, 5% CO2 in
47
a humidity-controlled incubator. Every 24 hours, one plate was removed from the incubator and
frozen at -80°C. After 7 days, all of the plates were thawed to room temperature, and 100 µl of
Cell Titer-Glo® lysis reagent/buffer (Promega Life Sciences, Madison, WI), were added to each
well and mixed gently by rocking for 2 minutes on a VWR Rocking Platform (Model 200), and
then incubated for 10 minutes. Luminescence was measured in a SpectraMax M5 plate reader
(Molecular Devices, Sunnyvale, CA) with an integration time of 0.5 seconds per well. The
reported luminescent signal is proportional the amount of ATP present, which is directly
proportional to the number of cells in each well.
Growth Curves
To determine the doubling time of transiently co-transfected cells, 1.25 x 105 viable
NIH/3T3 cells were plated into 7 separate 25 cm2 tissue culture-treated flasks (Corning Life
Sciences, Inc, Corning, NY) containing 4 ml DMEM + 10% FBS for each construct 48 hours
post-transfection. To determine the total cell number and viability, one flask for each construct
was harvested each day and cells were counted in duplicate in a TC-20 cell counter in 0.2%
Trypan Blue as described in the Cell Culture section above. Cells were washed in 1X PBS and
then fixed in 2% paraformaldehyde (Sigma Aldrich, St. Louis, MO) for 10 minutes at 37°C. To
determine the number of transfected cells on each day, the fixed cells were then interrogated in a
LSRFortessa flow cytometer and analyzed for mCherry positive percentage with a 561 nm laser,
a 600 longpass filter, and a 610/20 bandpass filter. Because cells which are transiently
transfected lose their plasmids through diffusion during cell division over time, it would be
impossible to tell if a cell was not mCherry positive because it was never transfected or because
it divided and lost the plasmid. Therefore, a plasmid containing the gene for enhanced green
48
fluorescent protein (eGFP) (a green fluorescent protein) was used as a mock co-transfection
control, to which all values were normalized. The mCherry positive percentage was multiplied
by the average cell count for each construct on each day, and then normalized to the
eGFP/mCherry mock co-transfection control (to account for plasmid loss) to determine the
normalized doubling time for cells successfully transfected with each construct. Data were
analyzed with FACSDiva 6.0. The normalized doubling time was recorded as the fastest
doubling time for each construct during the assay.
To determine the doubling time of stably transfected cells, 1.25 x 105 viable cells for each
cell line were plated into 7 separate 25 cm2 tissue culture treated flasks (Corning Life Sciences,
Inc, Corning, NY) containing 4 ml DMEM + 10% FBS. To determine the total cell number and
viability, one flask for each construct was harvested each day and cells were counted in duplicate
in a TC-20 cell counter in 0.2% Trypan Blue as described in the Cell Culture section above. The
doubling time was recorded as the fastest doubling time between days 2 and 5 for each construct
in the assay. Photography was completed by the Scientific Publications, Graphics, and Media
department of the National Cancer Institute.
Focus Forming
For transient transfections, cells were co-transfected as previously described. Forty-eight
hours post-transfection, cells were harvested and counted. 3.4 x 103 viable cells for each
construct were seeded into 96-well plates containing 100 µl of DMEM + 10% FBS in triplicate.
Cells were grown for 8 days at 37°C, 5% CO2, in a humid environment. On day 8, culture
medium was removed, the cells were washed with 1X PBS, and subsequently fixed with a
solution consisting of a 3:1 ratio of methanol (EMD Millipore, Billerica, MA) to glacial acetic
49
acid (Macron Fine Chemicals, Center Valley, PA) for 15 minutes at room temperature. Fixative
was removed and the cells were incubated with 0.1% crystal violet (Sigma Aldrich, St. Louis,
MO) for 15 minutes at room temperature. Crystal violet was removed and cells were washed 3
times with RO water and the plates were dried overnight.
For stably-selected cells, 5 x 104 viable cells for each cell line were seeded in triplicate
into 6-well tissue culture treated plates (Corning Life Sciences, Inc, Corning, NY) containing 4
ml of DMEM + 10% FBS. Cells were grown for 21 days at 37°C, 5% CO2, in a humid
environment. On day 21, culture medium was removed, the cells were washed with 1X PBS,
and subsequently fixed with a fixation solution consisting of a 3:1 ratio of methanol to glacial
acetic acid for 15 minutes at room temperature. Fixative was removed and fixed cells were
incubated with 0.1% crystal violet for 15 minutes at room temperature. Crystal violet was
removed and cells were washed 3 times with reverse osmosis (RO) water and the plates were
dried overnight.
Wound Healing
An equal number of cells (2 x 105 viable cells) were plated into 24-well tissue culture
(poly-lysine) plates containing 0.9 mm coated Cytoselect™ wound healing inserts (Cell Biolabs,
Inc., San Diego, CA). Forty-eight hours post-seeding, wound healing inserts were removed with
forceps. Wound closure was evaluated microscopically each day. At the end of the assay, cells
were washed 3 times with 1X PBS and stained with 400 µl Cell Stain Solution (Cell Biolabs,
Inc., San Diego, CA) for 15 minutes at room temperature. Stain was removed and cells were
then washed 3 times with RO water, and the plates were allowed to dry overnight.
50
Boyden Chamber Migration Assays
Culture medium was exchanged for low-serum medium (DMEM + 0.5% FBS) in our
stably-selected cell lines when the cells were ~60% confluent. After a 20-hour serumdeprivation challenge, cells were harvested, counted, and 1.25 x 104 cells were added to the top
of a Boyden chamber, containing 8 µm pores, in twelve replicates for each construct. Six of the
wells for each construct contained a chemo-attractant (DMEM + 10% FBS) in the bottom
chamber while six of the wells for each construct contained the serum-free medium (DMEM) in
the bottom chamber. The cells were allowed to migrate through the 8 μm pores towards a
chemo-attractant (DMEM + 10% FBS) or culture medium (DMEM) for 24 hours. Cells were
washed, dissociated from the bottom of the Boyden chamber, and incubated with the live celllabeling dye Calcein-AM (Trevigen, Inc., Gaithersburg, MD) for 1 hour. Dead cells cannot
convert the Calcein-AM into a fluorescent molecule. Fluorescence was measured in a
SpectraMax M5 plate reader with 485 nm excitation, 538 nm emission, and a 530 nm cutoff
filter, as determined by the Calcein-AM emission spectrum. Percent migration was calculated by
subtracting the average number of cells which migrated in the absence of a chemo-attractant
(DMEM) from the average number of cells which migrated towards a chemo-attractant (average
of sextuplicates) after 24 hours and dividing by the number of viable cells plated per well (1.25 x
104).
Boyden Chamber Invasion Assays
Culture medium was exchanged for low serum medium (DMEM + 0.5% FBS) in our
stably-selected cell lines when the cells were ~60% confluent. After a 20-hour serumdeprivation challenge, cells were harvested, counted, and 7 x 103 cells were added to the top of a
51
Boyden chamber coated with Basement Membrane Extract (extracellular matrix, Trevigen, Inc.,
Gaithersburg, MD), above the 8 μm pores, in twelve replicates for each construct. Six of the
wells for each construct contained a chemo-attractant (DMEM + 10% FBS) in the bottom
chamber while six of the wells for each construct contained the serum-free medium (DMEM) in
the bottom chamber. The cells were allowed to invade through the extracellular matrix and
move through the 8 μm pores towards a chemo-attractant (DMEM + 10% FBS) or culture
medium (DMEM) for 24 hours. Cells were washed, dissociated from the bottom of the Boyden
chamber, and incubated with the fluorescent live-cell-labeling dye Calcein-AM for 1 hour. Dead
cells cannot convert the Calcein-AM into a fluorescent molecule. Fluorescence was measured in
a SpectraMax M5 plate reader with (485 nm excitation, 538 nm emission, 530 nm cutoff filter),
as determined by the Calcein-AM emission spectrum. Percent invasion was calculated by
subtracting the average number of cells which migrated in the absence of a chemo-attractant
(DMEM) from the average number of cells which migrated towards a chemo-attractant (average
of sextuplicates) after 24 hours and dividing by the number of viable cells plated per well (1.25 x
104).
3D Cell Culture “Top Assay”
An equal number of cells for each cell line (3 x 104 cells) were plated in duplicate wells
of a 3D Culture Matrix™ BME Coated 96 Well Plate (Trevigen, Inc. Gaithersburg, MD) and
overlaid with 100 μl of DMEM + 10% FBS. Cellular self-organization in a physiological
environment of extracellular matrix was monitored and imaged microscopically over a period of
12 days.
52
3D Spheroid Invasion “Embedded” Assay
Stably-selected cells were harvested and resuspended in DMEM + 10% FBS + 1X
Spheroid Formation ECM (Trevigen, Inc., Gaithersburg, MD). An equal number of cells for
each cell line (3 x 103 viable cells per 50 μl DMEM + 10% FBS + 1X Spheroid Formation ECM)
were plated in triplicate for each construct into a 3D Culture Qualified 96 Well Spheroid
Formation Plate (Trevigen, Inc., Gaithersburg, MD) and centrifuged at 200 x g in a swinging
bucket rotor (Model 5810R) for 3 minutes. Cells were incubated at 37°C, 5% CO2 for 72 hours
in a humidity-controlled incubator to promote spheroid formation. After 72 hours, the 96-well
plate was cooled at 4°C for 15 minutes before adding 50 µl of Invasion Matrix (Trevigen, Inc.,
Gaithersburg, MD). The 96-well plate was then transferred to a 37°C incubator for 1 hour to
promote gel formation before 100 µl of DMEM + 10% FBS were overlaid. Cells were incubated
at 37°C, 5% CO2 for 7 days and wells were microscopically imaged each day. Images were
analyzed with ImageJ software (National Institutes of Health, Bethesda, MD) for total surface
area to evaluate 3D cell culture invasion.
Statistical Analysis
Statistical analyses were performed using the Student's t test assuming equal variances in
Microsoft Excel. Data were presented as mean values ± standard deviation. Confidence
intervals above 95% (p values <0.05) were considered significant and denoted with one star in
the appropriate figures. Confidence intervals above 99% (p values <0.01) are denoted with two
stars and confidence intervals above 99.9% (p values <0.001) are denoted with three stars in the
appropriate figures.
RESULTS
The results section is separated into two chapters. Chapter I contains the results of
experiments from transiently transfected NIH/3T3 cells. Chapter II contains the results of
experiments from stably-selected NIH/3T3 cell lines. All experiments in both chapters described
below were done in NIH/3T3 cells that contained a functional mouse KRAS gene, which is 99%
identical (as determined by the amino acid sequence) to the human gene that was introduced into
the cells. The mouse and human KRAS genes both use the same codons at G12, G13, and G60
(GGT, GGC, and GGT, respectively). As is the nature of transient transfections, our transfection
efficiency varied between experiments. Our transfection efficiency did not reach 100%, so all
experiments in Chapter I were from a mixture of transfected and untransfected cells. Moreover,
transient transfections were done with non-replicating plasmids that diffused and were eventually
lost as the transfected cells continued to divide. All experiments were completed within ten days
of the initial transfection. Transient transfections resulted in KRAS protein expression levels
that were much higher than the endogenous mouse KRAS protein expression levels because each
transfected cell potentially contained many copies of the plasmid.
In Chapter II, stably-selected cell lines were constructed by adding a cytotoxic selection
agent (zeocin) to transiently transfected cells for three weeks. Most of the transfected cells did
not integrate the plasmid DNA into their genomic DNA. Those cells, with non-replicating
plasmids containing a zeocin resistance gene, died after the plasmid diffused out. This drug
response allowed us to discriminate against untransfected or transiently transfected cells and
select for the rare cells that had randomly integrated a copy or copies of the plasmid DNA into
their genome, which was replicated with each cell division. All of the surviving cells from
53
54
each construct were pooled together, and each cell line was a mixture of cells that randomly
integrated the identical plasmid into their genomic DNA at presumably different chromosomal
locations. Because most stably-selected cells each contained only one to two copies of
integrated plasmids, stably-selected cell lines resulted in KRAS protein expression levels that
were more similar to endogenous mouse KRAS protein expression levels compared to the
transiently transfected cells.
CHAPTER I
TRANSIENTLY TRANSFECTED NIH/3T3 CELLS
Silent Mutations in Human KRAS 4B Lead to Significant Changes in KRAS Protein
Expression When Transiently Transfected into NIH/3T3 Cells
To evaluate the ability of G12, G13, and G60 silent mutations in the human KRAS 4B
gene to alter KRAS protein expression levels, expression clones containing all possible silent
mutations at each amino acid position, under control of a cytomegalovirus (CMV) promoter
[134], were transiently co-transfected (with mCherry) into NIH/3T3 cells. To ensure the
reproducibility of the results, we performed three independent replicates using different plasmid
preparations, separate freezer vials of NIH/3T3 cells at different passage numbers, and different
lot numbers of transfection reagent and culture medium components. We examined KRAS
protein expression levels with immunoblots on lysates from transfected cells (Figure 15).
We saw significant differences in KRAS protein expression levels across replicates, even
though the amino acid sequence of all silent-mutant constructs was identical and the nucleotide
sequences varied from the WT sequence by only a single nucleotide. Our oncogenic positive
control, KRAS G12V-transfected cells, consistently expressed more KRAS protein than any of
55
Figure 15. KRAS 4B Silent Mutations Alter Protein Expression Levels in Transiently Transfected
NIH/3T3 Cells. Top Panel: Immunoblots from three sets of experiments in which WT KRAS,
oncogenic KRAS (G12V), or silent mutation-containing KRAS (G12G, G13G, G60G) constructs
were transiently transfected into NIH/3T3 cells and harvested 72 hours later. GAPDH from one
experiment is shown as a loading control. Bottom panel: Quantification of the top panel.
NIH/3T3 cells transfected with the various constructs are along the x-axis, and fold increase over
WT KRAS protein expression is listed on the y-axis. The bar graphs are the results of three
independent replicates. (n = three experiments, statistical analysis = two tailed t-test, TwoSample Assuming Equal Variances, * = statistically significant increases in KRAS protein
expression relative to the WT KRAS nucleotide sequence) Equal amounts of protein (20 µg)
from each cell lysate were loaded in each lane.
the silent-mutant or WT-transfected cells. Some of the silent mutant-transfected cells (39 C→G
and 180 T→G) exhibited significant increases in KRAS protein expression relative to the WT
KRAS sequence, whereas other silent-mutant transfected cells expressed significantly less
KRAS protein (36 T→C, 36 T→G, 39 C→T) than WT transfected cells.
To determine if the protein expression level differences between the constructs were due
to differential transfection efficiencies, harvested cells were analyzed for the percentage of
56
mCherry positive cells in a flow cytometer 72 hours after the transfection (Table 9). All
constructs had an mCherry-positive percentage ranging from 27.1 to 32.9% positive. Therefore
Table 9. mCherry Percentages for Each Construct 72 Hours Post-Transfection
Construct
eGFP
WT
G12V
36 T→A
36 T→C
36 T→G
39 C→A
39 C→G
39 C→T
180 T→A
180 T→C
180 T→G
% of
population
expressing
mCherry
28
30.9
30.1
30.5
27.1
29
32.2
32.9
30.7
32.7
29.1
30.5
it was unlikely variable transfection efficiency played a major role in the results. Because the
KRAS protein expression levels varied significantly across the constructs while the mCherry
fluorescence remained relatively constant, we concluded that single-nucleotide, silent mutations
at G12, G13, and G60 altered KRAS protein expression levels when transiently transfected into
NIH/3T3 cells.
KRAS 4B Protein Expression Differences in Transiently Transfected NIH/3T3 Cells Are
Not Due to Codon Frequency of Usage
To determine if the changes in KRAS protein expression among the silent-mutant
transfected cells were due to codon usage preference, we examined the glycine codon usage
frequency in mouse cells [112] (Table 10). The WT KRAS 4B nucleotide sequence contained the
least frequently used glycine codon (GGT) at residue 12, yet the cells transfected with the WT
57
KRAS 4B sequence expressed significantly more protein than the G12G silent-mutant constructs
36 T→C and 36 T→G. Moreover, WT-transfected cells, which possessed the most frequently
used glycine codon (GGC) at residue 13, expressed significantly less protein than the G13G
silent-mutant GGG. Therefore, we were unable to correlate mouse codon usage frequency to
protein expression in NIH/3T3 cells transiently transfected with KRAS silent-mutant constructs.
Table 10. Glycine Codon Usage in Mouse Cells
Glycine Codon Mouse Frequency of
Usage (%)
GGT
18
GGG
23
GGA
26
GGC
33
KRAS 4B Protein Expression Changes in Transiently Transfected NIH/3T3 Cells Are
Partially Due to Differing mRNA Levels
To determine if the changes in protein expression among the silent-mutant transfected
cells were due to differing KRAS mRNA transcript levels, digital-droplet PCR (ddPCR) was
performed on cDNA prepared from total RNA extracted from transiently transfected NIH/3T3
cells, and mRNA transcript levels were analyzed (Figure 16). Although the KRAS transcript
mRNA levels were within ±50% of the amount of mRNA in WT KRAS transfected cells, there
were statistically significant differences between transfected cells. G12V-transfected cells,
which produced the most KRAS protein, maintained mRNA levels similar to WT-transfected
cells. In contrast, 36 T→A and 36 T→C transiently transfected NIH/3T3 cells produced
significantly less KRAS mRNA and less KRAS protein (see Figure 15) than WT-transfected
cells. Two potential reasons for the decreased KRAS mRNA levels could be because fewer
viable cells contained the construct, or because single nucleotide changes influenced mRNA
58
Figure 16. Quantification of KRAS mRNA Level Changes in Transiently Transfected NIH/3T3
Cells. KRAS constructs are listed along the x-axis, and fold increase over WT KRAS mRNA
(normalized to GAPDH mRNA) expression is listed on the y-axis. The bar graphs are means of
two replicates. Each reaction contained 167 pg of total cDNA. (n = two experiments, statistical
analysis = two tailed t-test, Two-Sample Assuming Equal Variances, compared to WT)
stability. Therefore, we concluded that significant mRNA changes may have contributed to
some of the KRAS protein expression level changes seen in the immunoblots. Since the KRAS
mRNA levels in Figure 16 could not fully explain the KRAS protein expression levels (see
Figure 15), it is likely there are additional factors contributing to the changes in KRAS protein
expression.
KRAS 4B Protein Expression Changes in Transiently Transfected NIH/3T3 Cells Are Not
Due to miRNA Binding Sites
It has previously been shown that silent mutations in the coding region of genes can
inhibit a miRNA from binding [17-18, 22]. To investigate the possibility that single-nucleotide,
silent mutations at G12, G13, or G60 could introduce or remove miRNA binding sites [18, 22],
MiRPara [103], a software program that predicts miRNA binding sites in the coding region of
genes based on current knowledge was used to interrogate the sequences. To test the software,
59
sequences from a previously assembled library of KRAS 4B genes were analyzed with the
software, all of which contained the WT KRAS amino acid sequence, but varied greatly in
nucleotide sequence. On average, ~60% of the codons differed from each other and from the
WT KRAS 4B sequence. Of the 41 library members, 8 contained predicted miRNA binding sites.
We found a correlation between predicted miRNA binding sites and lowered KRAS protein
expression, whereby all 8 library members that contained a predicted miRNA binding sites
exhibited decreased KRAS protein expression relative to WT KRAS when transiently transfected
into NIH/3T3 cells (Figure 17). The remaining members of the library with lowered KRAS
protein expression were possibly due to mechanisms independent of miRNA binding discussed
in the introduction. The coding region of the KRAS constructs for the controls (WT and G12V)
and the silent mutants (G12G, G13G, and G60G) were analyzed with the MiRPara software.
There were no predicted miRNA binding sites in any of the sequences. Therefore, it is unlikely
that single-nucleotide, silent mutations at codons G12, G13, or G60 in the KRAS gene introduce
or remove miRNA binding sites. Additionally, G12, G13, and G60 codons are distal from splice
junctions in the KRAS gene.
Figure 17. Cells Transiently Transfected with Various KRAS Silent Mutations Containing
Predicted miRNA Binding Sites have Lowered KRAS Protein Expression as Compared to Cells
Transfected with WT KRAS. Individual KRAS constructs are listed on the x-axis. Fold-increase
over WT is listed on the y-axis. Each KRAS construct has an average of ~100 silent mutations.
The level of protein expression is plotted for each construct when compared to WT KRAS.
Maroon stars indicate library members with predicted miRNA binding sites.
60
KRAS 4B Protein Expression Changes in Transiently Transfected NIH/3T3 Cells May Be
Partially Due to Predicted mRNA Structure and their Associated Free Energies
Silent mutation-induced secondary structure and free energy changes to mRNA have
been associated with changes to protein expression [12, 15]. To look for potential trends
between mRNA secondary structure or free energy with protein expression, we examined the
role silent mutations at G12, G13, and G60 may have had on mRNA structure. We used the
MFold web server [100, 101] to predict the secondary structure and free energy of each
construct. First, the global secondary structure and free energy of the coding region was
determined for each construct using the prediction software (Figure 18). Then, to determine the
local secondary structure and free energy of each construct, 60 bases of flanking sequence were
used; 30 bases upstream of the interrogated base, and 30 bases downstream of the interrogated
base (Figure 19).
Figure 18. Predicted Global mRNA Secondary Structure and Free Energy for Each of the KRAS
Constructs. The predicted secondary structures of the mRNA for the individual constructs are
depicted in the diagram underneath the construct name and free energy. (changes in free
energies are reported as ΔG).
61
Theoretically, the less negative the free energy is (closer to zero), the easier the secondary
structure is to unfold, presumably resulting in more rapid translation rates. The 39 C→G (ΔG =
-117.4 kcal/mol) and 180 T→G (ΔG = -119.1 kcal/mol) constructs, which significantly increased
KRAS protein expression as compared to WT (see Figure 15), had predicted free energies less
negative than that of WT (ΔG = -120.1 kcal/mol). However, the 36 T→G (ΔG = -120.1
kcal/mol), 36 T→C (ΔG = -120.1 kcal/mol), and 39 C→T (ΔG = -119.8 kcal/mol) constructs had
predicted free energies similar to that of WT, yet produced significantly less KRAS protein when
transiently transfected into NIH/3T3 cells. Local predicted free energies for the silent mutations
reflect the global observations. Notably, the 180 T→G global structure (Figure 18) and the 180
T→C local structure (Figure 19) were outliers. We are unsure if these predicted changes to
mRNA secondary structure are relevant.
62
Figure 19. Predicted Local mRNA Secondary Structure and Free Energy for Each of the KRAS
Constructs. The predicted secondary structures of the mRNA for the individual constructs are
depicted in the diagram underneath the construct name and free energy (ΔG).
It is possible that predicted secondary structures and free energy changes from single
nucleotide substitutions may contribute to protein expression changes. However, it is unclear
whether these changes to free energy could manifest in meaningful protein expression changes.
Therefore, in addition to mRNA levels, secondary structure and free energy, there are other
factors involved in determining protein expression level changes.
KRAS 4B Silent Mutations in Transiently Transfected NIH/3T3 Cells Affect Proliferation
Rates of NIH/3T3 Cells in a KRAS Dependent Manner
RAS proteins have a critical role in cell growth and cell division (see Figure 5).
Therefore, we considered the possibility that silent mutant-mediated changes in KRAS protein
expression levels might alter proliferation rates and doubling times of transfected cells. To
investigate the ability of silent-mutant transfected cells to change proliferation rates, we
performed 96-well Cell Titer-Glo® Luminescent Cell Viability assays. This assay used a
luminescent readout that measured ATP production, which was directly proportional to the
number of viable cells in a well [144]. We ranked the transfected cells based on relative
luminescence, and compared cell proliferation rank to KRAS protein expression rank from
Figure 15 (Figure 20).
By plotting increasing proliferation rank along the x-axis, we observed a corresponding
increase in KRAS protein expression levels for the constructs that significantly altered KRAS
protein expression levels (red text). The KRAS 4B constructs that yielded the least KRAS
protein from Figure 15 (36 T→G, 36 T→C, and 36 T→A) when transiently transfected into
63
NIH/3T3 cells resulted in the slowest proliferation rates. Constructs that resulted in higher
KRAS protein expression exhibited increased proliferation rates.
We also performed growth curves using co-transfected (mCherry + KRAS constructs)
cells in tissue culture flasks, with one flask for each construct being harvested and counted each
day over a period of seven days. To control for the background of untransfected cells, cell
counts were determined and multiplied by the percentage of mCherry positive cells for each
construct, as determined by flow cytometry. To account for inevitable plasmid loss that
Figure 20. KRAS Protein Expression vs. Cell Titer-Glo® RLU (relative luminescent units) in
Transiently Transfected NIH/3T3 Cells. Along the x-axis are the KRAS silent-mutant constructs,
ordered from lowest to highest peak RLU ranking. Constructs that significantly altered KRAS
protein expression levels are highlighted in red font. RLU is indicative of proliferation rate.
Along the y-axis is the rank for each construct. Blue bars represent RLU rank and red bars
indicate KRAS protein expression rank.
accompanies cell division in transiently transfected cells, doubling times were normalized to
cells that were mock co-transfected with eGFP and mCherry (Table11).
While the doubling times did not correlate with the Cell Titer-Glo® data across the entire
distribution, there was a trend between low protein expression and limited proliferative status
64
among the G12G constructs (36 T→A, 36 T→C, and 36 T→G, as shown in Figure 15). Given
the data, we concluded silent mutant-directed KRAS protein expression changes influences the
proliferation rates of transiently transfected cells.
Table 11. Doubling Time* of Transiently Transfected NIH/3T3 Cells
*eGFP Normalized Doubling Times as Determined by Growth Curve Analysis.
Some KRAS 4B Silent Mutations in Transiently Transfected NIH/3T3 Cells Enhance Focus
Formation
To investigate the possibility that cells transiently transfected with silent mutantcontaining constructs exhibit loss of contact inhibition, we performed focus formation assays.
Focus formation assays indicate abnormally proliferating cells, and it is well established that
missense KRAS mutations can transform contact-inhibited NIH/3T3 cells by inducing them to
form foci [31]. In earlier studies, this same focus forming assay led to identification of the first
human oncogenes – the RAS proteins [31-32, 82-85, 125-126]. Using our transiently transfected
cells, we evaluated whether silent mutations could similarly transform NIH/3T3 cells. Several
silent mutant-transfected NIH/3T3 cells led to the formation of foci (Figure 21). eGFP-
65
transfected cells served as a transfection control, and demonstrated the transfection process itself
was not responsible for focus formation. WT transfected cells demonstrated that even in a
transient system overexpressing KRAS 4B under control of a powerful CMV promoter, focus
Figure 21. KRAS Silent Mutations Lead to Focus Formation in Transiently Transfected
NIH/3T3 Cells. Triplicate wells of a 96-well plate were seeded at confluency with transiently
transfected NIH/3T3 cells. After 8 days, culture medium was removed and cells were stained
with crystal violet. Panel A=Controls, Panel B=G12G, Panel C=G13G, Panel D=G60G.
formation with WT KRAS 4B was poor. G12V transfected cells, as expected, formed distinct
foci. 39 C→T, 180 T→A, and 180 T→G transfected cells did not form foci. In contrast, 36
T→C, 36 T→G, 39 C→A, 39 C→G, and 180 T→C transfected cells resulted in focus formation.
36 T→A transfected cells showed limited formation of foci.
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Cells transfected with 39 C→G and 180 T→G expressed significantly more protein than
WT (see Figure 15), yet only 39 C→G transfected cells formed foci. Conversely, 36 T→C and
36 T→G transfected cells expressed levels of KRAS significantly lower than that of WT
transfected cells, yet resulted in focus formation. These data indicate focus formation does not
trend with KRAS protein expression. While the transformation potential of the silent mutanttransfected cells appears to be less than that of G12V, this experiment demonstrates that certain
KRAS 4B transgenes containing the WT amino acid sequence, with one synonymous codon, can
transform transiently transfected NIH/3T3 cells, which has not been previously reported.
KRAS 4B Silent Mutations at Other Glycine Residues Do Not Lead to Substantial Changes
in Protein Expression in Transiently Transfected NIH/3T3 Cells
To this point, we have focused on the most frequently observed KRAS silent mutations in
the COSMIC database, all of which are at glycine residues. These silent mutations are found at
(G12 and G13), or adjacent to (G60/Q61), the location that contains the missense mutations that
lead to constitutive activation and tumorigenesis in humans. It is possible that G12, G13, and
G60 silent mutations are observed in human cancers because of ascertainment bias. These amino
acids are presumably under more scrutiny than the rest of the KRAS protein because of the
known role missense mutations at G12, G13, and Q61 have in driving tumorigenesis. Therefore,
silent mutations may be preferentially found at these locations because that is where researchers
are already looking.
We wanted to investigate if the changes in KRAS protein expression levels and the focus
formation conferred by the silent mutations were due to the particular residue position in the
amino acid sequence or due to the glycine amino acid itself. Therefore, we performed sitedirected mutagenesis at glycine residues in the KRAS 4B gene that are not associated with human
67
cancers and are distal to the amino acids implicated in KRAS-driven tumorigenesis. G48G,
G77G, and G151G constructs (nucleotide positions 144, 231, and 453, respectively), along with
the controls, were transiently co-transfected into NIH/3T3 cells and KRAS protein expression
was examined with immunoblots (Figure 22). The KRAS protein expression differences were
minimal when compared to those in the G12G, G13G, and G60G transfected cells (see Figure
15). As with the previous transient transfections, the G12V positive control yielded the highest
levels of KRAS protein. It can therefore be concluded that it is not silent mutations in the
glycine codon per se, but specifically silent mutations at residues 12, 13, and 60 that affect
KRAS protein expression.
Figure 22. KRAS Silent Mutations in G48G, G77G, and G151G Constructs Do Not Lead to
Substantial Protein Expression Differences in Transiently Transfected NIH/3T3 Cells. Top
Panel: Immunoblot examining KRAS protein elvels in which WT KRAS, oncogenic KRAS
(G12V), or silent mutation-containing KRAS (G48G, G77G, G151G) constructs were transiently
transfected into NIH/3T3 cells and harvested 72 hours later. GAPDH was used as a loading
control. Bottom Panel: Quantification of band intensity. Equal amounts of protein (20 µg) from
each lysate was loaded in each lane.
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KRAS 4B Silent Mutations at Other Glycine Residues Do Not Enhance Focus Formation in
Transiently Transfected NIH/3T3 Cells
To examine the focus forming potential of G48G, G77G, and G151G silent mutations,
the constructs, along with the controls, were transiently transfected into NIH/3T3 cells and
evaluated for focus forming ability (Figure 23). None of the silent mutations at G48, G77, or
G151 exhibited substantial focus formation. Because KRAS 4B silent mutations at glycine
mutations distally located from G12, G13, and Q61 did not substantially alter KRAS protein
expression (see Figure 22) or result in formation of foci (Figure 23), they were not further
investigated.
Figure 23. KRAS Silent Mutations at G48, G77, and G151 Do Not Lead to Substantial Focus
Formation in Transiently Transfected NIH/3T3 Cells. Triplicate wells of a 96-well plate were
seeded at confluency with transiently transfected NIH/3T3 cells. After 8 days, culture medium
was removed and cells were stained with crystal violet. Panel A=Controls, Panel B=G48G,
Panel C=G77G, Panel D=G151G.
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KRAS 4B Silent Mutations (G12G, G13G, G60G) Lead to Variable MAPK and PI3K
Signaling Differences in Transiently Transfected NIH/3T3 Cells
Because there was no correlation between KRAS protein expression and focus formation,
and given the role KRAS plays in the MAPK and PI3K pathways, we investigated if the focus
formation changes we observed with G12G, G13G, and G60G transiently transfected cells were
related to aberrant signaling. Immunoblots were performed on transiently transfected cells and
interrogated for signaling pathway activation by probing for levels of phospho-Erk1/2 (Figure
24) or phospho-Akt (Figure 25) protein, the classical reporters for the MAPK and PI3K
pathways, respectively (see Figure 5).
In three independent experiments, there were no substantial changes in either the
phospho-Erk1/2 levels (MAPK pathway) or the phospho-Akt levels (PI3K pathway) among the
various transfected cells when compared to the WT transfected cells. It was impossible to
determine if the signaling alterations were due to variable transfection efficiencies, percentage of
confluence at the time of harvest, or cell-mediated positive or negative feedback pathways. It is
also possible the variability derived from the transfection process itself. Consistently, G12Vtransfected NIH/3T3 cells expressed high levels of both phospho-Erk1/2 and phospho-Akt,
suggesting the variations were not a result of transfection variability or the transfection process.
It has been established that transient transfections can be cytotoxic [135] or can induce
senescence due to negative-feedback regulation of hyperactive signaling pathways involved in
proliferation [145]. Although we did not evaluate cytotoxicity by calculating the percentage of
dead cells, it is possible that cells transfected with G12V were more resistant to cytotoxic effects,
and therefore all of the highly transfected cells survived and proliferated, overtaking the
untransfected NIH/3T3 cells in a post-transfection 72-hour growth competition, ultimately
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leading to hyperactive signaling as measured by immunoblot analysis. Conversely, highly
transfected WT and silent-mutant cells may have died or senesced and were therefore overtaken
by the untransfected NIH/3T3 cells in a post-transfection 72-hour growth competition. In the
latter scenario, the inconsistent signaling alterations we observed may have been due to steadystate fluctuations among the mixture of untransfected NIH/3T3 cells and WT or silent-mutant
transfected NIH/3T3 cells. The possibility also exists that signaling was being regulated in the
Figure 24. KRAS Silent Mutations Lead to Variable Activation of the MAPK Pathway as
Determined by Phosphorylation of Erk1/2 in Transiently Transfected NIH/3T3 Cells.
Immunoblots examining phospho-Erk1/2 levels from three independent sets of experiments in
which WT KRAS, oncogenic KRAS (G12V), or silent mutation-containing KRAS (G12G,
G13G, G60G) constructs were transiently transfected into NIH/3T3 cells and harvested 72 hours
later. Erk 1/2 was used as a loading control. Equal amounts of protein (20 µg) from each lysate
was loaded in each lane.
WT and silent mutant-transfected cells in a feedback-mediated manner. To examine whether
there was a threshold of transfectable WT KRAS 4B DNA, above which was cytotoxic or
senescence-inducing, immunoblots were run on co-transfections in which decreasing amounts of
WT KRAS 4B DNA were titrated into the transfection mixture, and the difference in DNA
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Figure 25. KRAS Silent Mutations Lead to Variable Activation of the PI3K Pathway as
Determined by Phosphorylation of Akt in Transiently Transfected NIH/3T3 Cells. Immunoblots
examining phospho-Akt levels from three independent sets of experiments in which WT KRAS,
oncogenic KRAS (G12V), or silent mutation-containing KRAS (G12G, G13G, G60G) constructs
were transiently transfected into NIH/3T3 cells and harvested 72 hours later. Akt was used as a
loading control. Equal amounts of protein (20 µg) from each lysate was loaded in each lane.
concentration was made up with increasing levels of mCherry DNA (Figure 26). There was a
correlation between increased mCherry DNA and increased mCherry protein expression.
However, the highest WT KRAS 4B DNA concentration resulted in the least amount of KRAS
protein. This result suggested that transiently transfecting higher amounts of WT KRAS 4B
DNA into NIH/3T3 cells resulted in cytotoxicity or feedback-mediated senescence. Interestingly,
the phosphorylated Erk1/2 levels remained similar across all samples. Because it is possible that
too much WT KRAS 4B DNA led to cytotoxicity or senescence due to hyper-stimulation of
signaling pathways, it is also possible that some silent mutants (36 T-<C, 36 T→G, 39 C→T)
may have expressed significantly lower levels of KRAS protein as compared to the WT sequence
because higher concentrations of those constructs were cytotoxic or cytostatic.
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Figure 26. Increasing WT KRAS Concentrations Result in Bell-shaped KRAS Protein
Expression in Transiently Transfected NIH/3T3 Cells. Immunoblots examining KRAS and
phospho-Erk1/2 levels from cells transiently transfected with decreasing concentrations of
KRAS 4B WT DNA and increasing amounts of mCherry DNA revealed that high levels of
KRAS DNA resulted in low KRAS 4B protein expression and low levels of KRAS DNA
resulted in low KRAS 4B protein expression. The highest KRAS protein expression was seen
when 6.25 µg of KRAS DNA was added to the transfection mixture. Conversely, while KRAS
protein expression levels exhibited a bell-shaped curve as DNA concentration was increased,
mCherry increased in protein expression as DNA was increased. G12V KRAS (far right) was
used as a positive control. Equal amounts of protein (20 µg) from each lysate was loaded in each
lane.
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Summary of Transient Transfection Experiments
With transient transfections, we have seen that some single nucleotide alterations coding
for a synonymous codon significantly alter KRAS protein expression levels, which was
previously unreported. The mechanisms driving the KRAS protein expression changes were
multi-factorial, with mRNA stability and free energy, translation rate, and mRNA levels all
possibly being contributing factors. There are almost certainly other parameters that affected
KRAS protein expression as well. We discovered that the KRAS protein expression level
changes led to altered proliferation rates in NIH/3T3 cells and some cells transiently transfected
with silent mutations exhibited enhanced focus formation in a KRAS protein-independent
fashion. We were unable to see consistent signaling differences in the MAPK and PI3K
pathway. Nonetheless, our transient transfections resulted in provocative observations. To
eliminate any untransfected NIH/3T3 cells and the confounding side effects of transient
transfections, we chose to generate stable cell lines. Having established a system whereby
differences between silent mutations could be observed, moving to these more labor-intensive
stable cell lines was warranted.
CHAPTER II
STABLY TRANSFECTED NIH/3T3 CELLS
KRAS 4B Silent Mutations Result in Enhanced KRAS Protein Expression in Stablyselected NIH/3T3 Cells
We transfected NIH/3T3 cells with the controls and silent-mutant containing constructs,
and stably selected with zeocin for three weeks to obtain antibiotic-resistant cells that had
integrated the plasmid containing the zeocin resistance gene and KRAS construct into their
genome (see Figure 11). After 21 days of zeocin selection, all of the surviving cells from each
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construct were combined as pools and plated at identical densities (1.25 x 10 viable cells/25 cm2
5
tissue culture flask), and the zeocin antibiotic concentration was halved. We evaluated the
KRAS protein expression levels of each cell line with immunoblot analysis at early (P02) and
late (P10) passage (Figure 27, middle panel).
At both early and late passage, NIH/3T3-WT cells expressed the least amount of KRAS
protein and NIH/3T3-G12V cells expressed high levels of KRAS protein. Every silent-mutant
cell line overexpressed KRAS protein by at least two-fold at both early and late passage when
compared to NIH/3T3-WT cells (Figure 27, bottom panel). The protein expression levels at P02
were different than they were at P10, with the exception of NIH/3T3-180 T→G cells. Compared
to P02, many silent-mutant cell lines had decreased KRAS protein expression at P10, while
NIH/3T3-180 T→A cells had increased KRAS protein expression at P10. This KRAS protein
expression profile differed from the one generated for the transient transfections in Figure 15,
potentially related to the bell-shaped curve effect observed for KRAS transient transfections
observed in Figure 26.
The average level of KRAS overexpression in the silent mutant-transfected cell lines
varied from 2.4-fold to 14.3-fold more than NIH/3T3-WT cells (Table 12). The difference in
KRAS protein expression in the early and late passage immunoblots may be indicative of pooled
cell line drift over time, whereby clones possessing a proliferative advantage begin to make up a
larger percentage of the population. In order for the cells to have survived the selection period,
they may have gradually adjusted to their environment over time. When possible, we tried to
conduct all experiments at the earliest possible passage number. No experiments were conducted
on cell lines that had been passaged more than ten times.
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Figure 27. KRAS Protein Expression Levels and Proliferation Rate Changes of Silent-Mutant
Containing Stably-Selected NIH/3T3 Cells. A: Proliferation fold increase of stably-selected
NIH/3T3 cells (compared to WT). B: KRAS immunoblots of stably-selected cells at passage 2
(P02) and passage 10 (P10). C: Densitometry quantification of KRAS immunoblots. (statistical
analysis = t-test, one-tailed, Two-Sample Assuming Equal Variances, based on average KRAS
protein expression between passage 2 and passage 10, asterisks = significant increases in KRAS
protein expression compared to NIH/3T3-WT cells). Equal amounts of protein (20 µg) from
each lysate were loaded in each lane.
KRAS 4B Protein Expression Differences in Stably-selected NIH/3T3 Cells May Be Due to
Codon Frequency of Usage at G12 and G60
KRAS protein expression from stably-selected NIH/3T3 cells trended with codon
frequency of usage at G12 and G60 (Table 12). The WT nucleotide sequence has the least
frequently used glycine codon (GGT) at residues 12 and 60, and NIH/3T3-WT cells produced
the least KRAS protein compared to any other stably-selected cell line. Across all four potential
glycine codons at both G12 and G60, there was an incremental increase in KRAS protein
76
expression with increasing codon usage frequency (GGT < GGG < GGA < GGC) (Table 10).
Paradoxically, the WT nucleotide sequence has a highly used GGC codon at residue 13, yet
changing the glycine codon to any of the other less frequently used glycine codons resulted in
increased KRAS protein expression. Our results showed that the human WT KRAS nucleotide
sequence has the glycine codon at G12, G13, and G60 that resulted in the least amount of KRAS
protein expression.
Table 12. KRAS Protein Expression Levels in Stably Transfected Cells Trend with Glycine
Codon Usage at G12 and G60
Average fold increase over WT as a function of mouse glycine codon usage at each residue. n/a
= WT codon
These data provide evidence that enhancements in KRAS protein expression conferred by
silent mutations in stably-selected NIH/3T3 cells are potentially due to glycine codon frequency
of usage at G12 and G60, but not at G13. Because the literature has demonstrated that
overexpression of WT KRAS protein is associated with several forms of cancer [116, 127-132],
we wanted to further investigate potential tumorigenic phenotypes.
KRAS 4B Silent Mutations in Stably-Selected NIH/3T3 Cells Enhance Proliferation Rates
of NIH/3T3 Cells in a KRAS Influenced Manner
It is known that KRAS plays a critical role in cell growth and cell division (see Figure 5).
Because we observed KRAS overexpression in all silent-mutant NIH/3T3 cell lines, we checked
whether our stably-selected cell lines enhanced proliferation rates by decreasing doubling times.
Therefore, we analyzed growth of the stable cell lines in tissue culture flasks. We prepared
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seven flasks for each cell line and harvested and counted one flask for each cell line each day for
seven days (Figure 27A, Table 13).
Table 13. Doubling Times for Silent-Mutant NIH/3T3 Cell Lines and Controls
Average Fold-Increase of
Peak
KRAS Protein Over WT
Doubling
Cell Line
Cell Line
Time (hr)
NIH/3T3-WT
1
47.4
NIH/3T3-36 T→G
3.2
37.2
NIH/3T3-39 C→A
3.4
33.8
NIH/3T3-36 T→A
5.4
28.6
NIH/3T3-39 C→T
6.1
27.8
NIH/3T3-39 C→G
5.8
23.8
NIH/3T3-180 T→A*
4.0
20.2
NIH/3T3-180 T→G*
2.4
20.2
NIH/3T3-180 T→C
13.4
19.5
NIH/3T3-G12V
16.6
18.6
NIH/3T3-36 T→C
14.3
15.7
Doubling Times were recorded as the peak doubling time between Day 2 and Day 5. Asterisks
represent cell lines where KRAS protein expression and doubling time do not trend together.
NIH/3T3-WT cells maintained the slowest doubling time and NIH/3T3-G12V cells
maintained a rapid doubling time. NIH/3T3-36 T→C cells had a more rapid peak doubling time
than NIH/3T3-G12V cells. We found that all of the silent-mutant cell lines increased
proliferation rates by decreasing peak doubling times from between 27% (NIH/3T3-36 T→G) to
more than 300% (NIH/3T3-36 T→C) compared to NIH/3T3-WT cells. The three cell lines
which produced the most KRAS protein (see Figure 27) had the most rapid peak doubling times
(NIH/3T3-180 T→C, NIH/3T3-G12V, and NIH/3T3 36 T→C). Conversely, the cell line which
produced the least protein had the longest doubling time (NIH/3T3-WT). KRAS protein
expression trended with more rapid doubling time in 9 out of 11 instances (NIH/3T3-180 T→A
and NIH/3T3-180 T→G being the exceptions).
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In addition to the large differences in doubling time, there were cell line variations in the
peak number of cells per 25 cm2 tissue culture-treated flask (Table 14, Figure 28). High
saturation density, or the ability of a cell line to accumulate large numbers of cells in a culture
dish, is a property of transformed cells [32]. NIH/3T3-WT cells formed a confluent monolayer
at Day 4 and had the lowest saturation density (5.88 x 105 cells per 25 cm2 tissue culture-treated
flask). In contrast, NIH/3T3-G12V cells reached the highest saturation density (79.7 x 105 cells
per 25 cm2 tissue culture-treated flask). All of the silent-mutant containing cell lines reached
saturation densities higher than that of NIH/3T3-WT cells and lower than that of NIH/3T3-G12V
cells, with increased cell densities that ranged from 73% (NIH/3T3-36 T→A) to more than 372%
(180 T→G) over NIH/3T3-WT cells.
Incidentally, we noted that only NIH/3T3-G12V cells became smaller during the course
of the assay, with a mean diameter of ~5 µm on day 7 (diameter for NIH/3T3 cells is ~12-16
µm). Taken together, the proliferation and cell density data indicate silent-mutant cell lines have
more rapid doubling times than NIH/3T3-WT cells and can reach higher cell densities per unit
area.
Table 14. Peak Cells Per Flask for Silent-Mutant Cell Lines and Controls
Cell Line
Peak Cells per T25 (x 105)
NIH/3T3-WT
5.88
NIH/3T3-G12V
79.7
NIH/3T3-36 T→A
10.2
NIH/3T3-36 T→C
16.1
NIH/3T3-36 T→G
12.4
NIH/3T3-39 C→A
12.6
NIH/3T3-39 C→G
14.0
NIH/3T3-39 C→T
18.2
NIH/3T3-180 T→A
14.8
NIH/3T3-180 T→C
14.6
NIH/3T3-180 T→G
21.9
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Figure 28. Silent-Mutant Cell Lines Reach Higher Cell Densities than NIH/3T3-WT Cells in 25
cm2 Tissue Culture (TC) Flasks. NIH/3T3-WT cells were the most contact-inhibited cell line
while NIH/3T3-G12V were the least contact-inhibited cell line, as measured by the peak number
of cells per flask. The x-axis represents days in the growth curve assay, after seeding each flask
at 1.25 x 105 cells/flask. The y-axis represents the number of cells in a flask at each day. Panel
A=Controls, Panel B=G12G, Panel C=G13G, Panel D=G60G. Vertical scales are different in
Panel A, compared to Panels B-D.
KRAS 4B Silent Mutations in Stably-Selected NIH/3T3 Cells Result in Enhanced Colony
Formation
Loss of contact inhibition is one way in which cells can achieve abnormally high cell
densities. NIH/3T3 cells, when transformed with a RAS oncogene, lose contact inhibition and
form distinct foci [32]. To investigate whether stably-selected NIH/3T3 cell lines exhibited
decreased contact inhibition, we performed focus forming assays, in which cells were plated in
triplicate in six-well plates and incubated for 21 days without medium changes (Figure 29).
NIH/3T3-WT cells resulted in almost no colony formation, while NIH/3T3-G12V cells
formed almost 200 foci per well (Figure 29). Morphologically, NIH/3T3-G12V foci were small
and mostly round, while some silent mutation containing cell lines (NIH/3T3-36 T→G,
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Figure 29. Silent-Mutant NIH/3T3 Cell Lines Result in Amorphous Colony Formation.
Triplicate wells of 6-well plates were seeded (5 x 104 cells/well) with equal numbers of cells.
After 21 days the culture medium was removed and the cells were fixed A. Cells were stained
with 0.1% crystal violet. B. After staining, a threshold was determined and colonies larger than
5 pixels were counted in each well with ImageJ software. Triplicates were averaged for each cell
line. (n = three technical replicates, statistical analysis = t-test, one-tailed, Two-Sample Assuming Equal Variances, compared to NIH/3T3-WT cells). C. Immediately before culture medium was removed and cells were fixed and stained, representative microscopic images were captured (4X objective, 104X total magnification) for each cell line using an EVOS FL microscope.
NIH/3T3-39 C→T, and NIH/3T3-180 T→G) formed over 100 amorphous colonies (Figure29A29C). NIH/3T3-180 T→C cells were the only cell line that dissociated from the wells after
forming a confluent monolayer (~1 week into the assay) in all three wells, and the cells floated in
the culture medium as a sheet, without evidence of any cellular debris for the remainder of the
assay (an additional two weeks) (Figure 29C). The sheets of cells were removed when the
culture medium was removed and the cells were washed prior to staining. Focus formation for
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NIH/3T3-G12V and amorphous colony formation for silent-mutant cell lines did not correlate
with the levels of KRAS protein expression. In conclusion, some NIH/3T3 silent-mutant cell
lines can form amorphous colonies in a focus forming assay.
KRAS 4B Silent Mutations in Stably-selected NIH/3T3 Cells Result in Migration
Differences
We wanted to investigate the ability of KRAS silent mutations to confer migratory
properties on NIH/3T3 cells. Cell migration can be assessed with wound healing assays or with
Boyden chambers. Wound healing assays rely on cell movement to close a gap in a monolayer
caused by scratching a pipette tip across a layer of confluent cells. The rate at which cells
migrate into the empty space can be measured qualitatively or quantitatively. "Scratching" can
cause considerable damage to the cells at the leading edge of the wound front, so we used
"wound assay inserts" that were present in the wells before the cells were initially plated in our
wound healing assays. The inserts were specially treated to prevent cells from growing
underneath or on the sides of the insert. Equal numbers of cells were applied to both sides of the
wound insert. After the cells grew to confluency, the wound insert was removed and we
qualitatively analyzed wound closure (Figure 30).
NIH/3T3-WT cells took longer to close the wound than mock transfected cells (eGFP).
The lighter purple staining in NIH/3T3-WT cells was a result of the lower cell density at which
NIH/3T3-WT cells reach contact inhibition. NIH/3T3-G12V cells have a propensity to form
small foci as shown above (Figure 29), making it difficult to assess wound closure. NIH/3T3180 T→A and NIH/3T3-180 T→C cells facilitated the most complete wound closure within 53
hours (Figure 30A). Compared to the NIH/3T3-eGFP and NIH/3T3-WT controls 70 hours,
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NIH/3T3-36 T→C, NIH/3T3-180 T→A, and NIH/3T3-180 T→C have most successfully closed
the wound (Figure 30B). NIH/3T3-WT, NIH/3T3-36 T→A, NIH/3T3-36 T→G, NIH/3T3-39
C→A, NIH/3T3-39 C→G, NIH/3T3-39 C→T, and NIH/3T3-180 T→G cells did not fully close
the wound within 70 hours.
Wound healing assays allowed us to determine whether the cell lines exhibited different
migration patterns, and if they migrated as individual cells or as a sheet. However, it is difficult
to distinguish between proliferation and wound closure with wound healing assays, and even
minimal cell damage from removing a wound assay insert can cause differential cell death. We
therefore assessed the ability of the cell lines to migrate towards a chemo-attractant using
Boyden chamber migration assays. The bottom of a Boyden chamber contains pores (8 µm)
which cell lines can migrate through individually if an appropriate chemotactic gradient exists
(Figure 31, top panel). Our chemotactic gradient contained a 20-fold excess of FBS in the
bottom chamber (10%). After 24 hours of serum deprivation, we placed an equal number of
cells from each cell line in the top of the Boyden chamber in sextuplicate and allowed the cell
lines to migrate towards the chemo-attractant for 24 hours (Figure 31, bottom panel). NIH/3T3G12V and NIH/3T3-36 T→C cells were significantly more migratory towards a chemoattractant than NIH/3T3-WT cells. The error bars are possibly large for the NIH/3T3-G12V cells
because of their small cell diameter, or because of their propensity to grow as foci, as seen in the
wound healing assay (Figure 30). However, the assay ended within 24 hours of the cells being
applied to the chambers, it is unlikely there was sufficient time for foci formation to play a
substantial role in the observed variability. NIH/3T3-36 T→G, NIH/3T3-39 C→G, NIH/3T3-39
C→T, and NIH/3T3-180 T→G were significantly less migratory than NIH/3T3-WT cells.
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Figure 30. Silent-Mutant NIH/3T3 Cell Lines Show Changes in Wound Healing Ability. Cell
lines containing different silent mutations were monitored for their wound closing ability in
tissue culture wells, and stained with Cell Stain Solution. A. Cells were stained 53 hours postwound (4X objective, 56X total magnification) using an EVOS XL Core microscope. B. Cells
were stained 70 hours post-wound (4X objective, 56X total magnification) using an EVOS XL
Core microscope.
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Figure 31. Silent-Mutant Cell Lines Show Changes in Migration Patterns Towards a Chemoattractant. Top Panel: A diagram depicting the setup of the Boyden chamber migration assay.
Bottom Panel: 1.25 x 104 cells were plated in the top of a Boyden chamber and their chemotaxis
ability was monitored after 24 hours in a Boyden chamber migration assay. Percent migration is
displayed on the y-axis the cell lines are along the x-axis. (n = six replicates, statistical analysis
= t-test, two-tailed, Two-Sample Assuming Equal Variances, asterisks = significant increases in
migration compared to NIH/3T3-WT cells)
The Boyden chamber migration assay showcases the heterogeneity and diversity that can
be obtained from cell lines that differ by only one single, silent mutation, whereby one cell line
(NIH/3T3-36 T→C) was significantly more migratory than NIH/3T3-WT cells and four cell
lines (NIH/3T3-36 T→G, NIH/3T3-39 C→G, NIH/3T3-39 C→T, and NIH/3T3-180 T→G)
85
were significantly less migratory than NIH/3T3-WT cells. There seemed to be an inverse
relationship between amorphous colony formation and migration for the silent-mutant cell lines.
The cell lines that formed >100 amorphous colonies (NIH/3T3-36 T→G, NIH/3T3-39 C→T, and
NIH/3T3-180 T→G) in the focus forming assay (Figure 29) were all statistically less migratory
than NIH/3T3-WT cells, our negative control, in the Boyden chamber assay (Figure 31).
Conversely, the only silent-mutant cell line that was significantly more migratory than NIH/3T3WT cells (NIH/3T3-36 T→C) was contact-inhibited in the focus forming assay (Figure 29). We
conclude that G12, G13, or G60 KRAS silent mutations alter the migratory potential in stablyselected NIH/3T3 cell lines.
KRAS 4B Silent Mutations in Stably-selected NIH/3T3 Cells Result in Enhanced Invasive
Potential
To assess the capability of the stably-selected NIH/3T3 cells to confer invasive properties
upon cells, we interrogated invasion with three separate, independent assays.
Boyden Chamber Invasion Assays
The first invasion assay is similar to the Boyden chamber migration assay, except the Boyden
chambers were overlaid with extracellular matrix (basement membrane extract) before the cells
were applied. Aggressive, transformed cells secrete collegenases and matrix metalloproteases
that degrade the extracellular matrix. We applied equal numbers of cells to the chambers and the
cells were allowed to degrade the extracellular matrix, and then move into and through the
matrix and pores for 24 hours (Figure 32). This degradation and movement is in response to the
same chemo-attractant and chemotactic gradient we used in the Boyden chamber migration assay
86
illustrated in the top panel of Figure 31 and 32. The NIH/3T3-G12V positive control and all
silent-mutant cell lines were more invasive than the NIH/3T3-WT cells, six of which exhibited
statistical significance.
Figure 32. Silent-Mutant Cell Lines Show Enhanced Invasion Towards a Chemo-attractant.
Top Panel: A diagram depicting the setup of the Boyden chamber invasion assay. Bottom
Panel: 7 x 103 cells were plated in the top of a Boyden chamber and their chemotaxis ability was
monitored over 24 hours in a Boyden chamber invasion assay. Percent invasion is displayed on
the y-axis and the cell lines are along the x-axis. (n = six replicates, statistical analysis = t-test,
one tailed, Two-Sample Assuming Equal Variances, asterisks represent statistically significant
increases in invasiveness as compared to NIH/3T3-WT cells)
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3D Extracellular Matrix Coated Plate Assay (Top Assay)
Using rigid, tissue-culture treated (poly-lysine) plastic surfaces on which cells proliferate
as a monolayer is a limitation of in vitro cancer models. Three-dimensional cell culture allows
cells to grow in aggregates, more accurately representing the in vivo micro-environment [118].
To evaluate the contributions of silent mutations to growth in three dimensions in a
physiologically relevant environment, and to further understand the invasive phenotype, stablyselected NIH/3T3 cell lines were grown in a 96-well plate coated with extracellular matrix
formulated for three-dimensional growth. The manner in which different cells organize and
interact with each other is indicative of aggressiveness [140, 141]. We analyzed each cell line
microscopically over a period of twelve days (Figure 33).
Although all of the cell lines initially formed a monolayer, the NIH/3T3-WT cells
underwent a self-organization distinct from that of any other cell line. Qualitatively, the
NIH/3T3-G12V cell line formed large colonies with extensive protrusions through several focal
planes while the NIH/3T3-WT cells formed the smallest colonies. All of the silent-mutant cell
lines formed larger colonies than NIH/3T3-WT cells with different levels of movement and
protrusion formation into and through the matrix, indicated by cell growth in multiple focal
planes.
3D Spheroid Invasion Assay
The third invasion assay we investigated was a three-dimensional spheroid
invasion assay. In this assay, one spheroid was formed per well in a low-adherent, round bottom
96-well culture plate, and then extracellular matrix was added to each well and the cells were
allowed to invade out from the spheroid through the extracellular matrix. Three-dimensional
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Figure 33. Silent-Mutant Cell Lines Show More Aggressive Self-Organization As Compared to
NIH/3T3-WT Cells in an Extracellular Matrix After 12 Days. 3 x 104 cells were plated into 3Dqualified, reduced growth factor extracellular matrix in DMEM + 10% FBS in duplicate and
allowed to proliferate and invade the extracellular matrix for 12 days. Cell lines invade the
matrix differently as assessed by the different colony morphologies, resulting in differential
colony size and density. One of two wells is shown for each cell line. Cells were imaged after
12 days (4X objective, 56X total magnification) using an EVOS XL Core microscope.
89
spheroids more closely recapitulate the similar morphologies, proliferation rates, survival
signals, and hypoxic conditions of tumors in vivo [119-121]. Additionally, with one spheroid per
well, we can quantify the surface area for each of the spheroids. Spheroids were first formed for
each cell line by plating equal numbers of cells into round bottom wells. We grew the cells in a
specialized medium containing laminin for 72 hours to promote spheroid formation. After 3
days, we overlaid an extracellular matrix and analyzed the spheroid in each well over a ten day
period for the cells' ability to invade an extracellular matrix (Figure 34).
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Figure 34. Silent-Mutant Cell Lines Show Enhanced Invasive Potential in 3D Spheroid Assays
as Compared to NIH/3T3-WT Cells After 10 Days. 3 x 103 cells were plated in triplicate, formed
into spheroids and allowed to proliferate into an overlaid extracellular matrix for 10 days.
Increased size and a dense spheroid core are indicative of an invasive phenotype. One of three
images for each cell line is shown. Spheroids were imaged (4X objective, 56X total
magnification) using an EVOS XL Core microscope. Surface area was measured in triplicate
wells for each cell line and averaged. The average surface area and statistical significance is in
the top right of each photograph. (n = three replicates, statistical analysis = t-test, one-tailed,
Two-Sample Assuming Equal Variances, asterisks represent statistically significant increases in
migration as compared to NIH/3T3-WT cells).
NIH/3T3-WT cells were the least invasive, as measured by total surface area of the
spheroids, and NIH/3T3-G12V cells formed the largest spheroids. In this assay, all of the silentmutant containing cell lines were more invasive than NIH/3T3-WT cells. Three independent
assays resulted in all silent mutations at G12, G13, or G60 being more aggressive than NIH/3T3WT. We therefore concluded that silent mutations at G12, G13, and G60 increase the invasive
potential of stably-selected NIH/3T3 cells.
Silent Mutations in Human KRAS 4B Lead to MAPK Signaling Differences in StablySelected NIH/3T3 Cells
We examined the influence silent mutations have on the MAPK pathway and the
associated impacts on the observed biological effects of proliferation, contact inhibition,
migration, and invasion. We compared the amounts of KRAS protein expression in the stable
cell lines with the amounts of activated (GTP-bound) KRAS and with levels of MAPK pathway
signaling (phospho-Mek1/2 and phospho-Erk1/2) (Figure 35). One lysate was used to measure
active KRAS and phospho-Erk1/2, while a second lysate was used for all the immunoblots of the
remaining MAPK components. The control lanes (C-raf, total Mek1/2 and total Erk1/2) were
highly consistent across the cell lines, indicating changes in phosphorylation are not due to
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increases in synthesis of these pathway proteins. We do not understand the origin of the upper
phospho-Mek1/2 band in the G12V cell line.
NIH/3T3-G12V cells displayed high levels of active KRAS and increased signaling in the
MAPK pathway as indicated by increased phospho-Mek1/2 and phospho-Erk1/2. However, we
did not observe any consistent trends connecting amounts of KRAS protein expression to active
KRAS, phospho-Mek1/2 and phospho-Erk1/2 for the silent-mutant cell lines. For example,
NIH/3T3-180 T→G cells only modestly overexpressed KRAS protein (2.4-fold overexpression),
yet had higher levels of phospho-Erk1/2 than NIH/3T3-G12V cells. However, NIH/3T3-180
T→ G cells showed lower, not higher, levels of activated (GTP-bound) KRAS compared to
Figure 35. Silent-Mutant Cell Lines Show Altered Levels of MAPK Activation. Top Blot: Total
KRAS protein from Figure 27. Second Blot: Active KRAS from a GST-RBD pulldown. Third
Blot: C-Raf levels remain relatively constant for all cell lines. Fourth Blot: Phospho-Mek1/2
levels vary across different cell lines. Fifth Blot: Total Mek1/2 levels are consistent across all
cell lines. Sixth Blot: Phospho-Erk1/2 levels vary across different cell lines in a similar fashion
to phospho-Mek1/2. Seventh Blot: Total Erk1/2 levels are consistent across all cell lines.
Eighth Panel: GAPDH is used as a loading control. Equal amounts of protein (20 µg) from each
lysate were loaded in each lane. Equal amounts of protein (240 μg) were used for the active
(GTP-bound) RAS-RBD pulldown assays.
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NIH/3T3-G12V. This result prompted two additional assays of phopho-Erk1/2 (from different
passages on separate cell preparations at separate plating densities at different levels of
confluency), shown in Figure 36. These data confirmed the reproducibly high levels of phosphoErk1/2 in the NIH/3T3-180 T→G cell line even when KRAS protein levels were low (Figures
35). The inverse relationship was seen in the case of NIH/3T3-39 C→G cells, whereby higher
KRAS protein expression was seen with low phospho-Erk1/2.
As signaling through the MAPK pathway is currently understood, we were thus not able
to identify a unifying pattern linking the tumorigenic phenotypes in the silent-mutant cell lines to
the observed changes in activation of MAPK effectors. We sought additional understanding by
analyzing other pathways associated with KRAS signaling.
Figure 36. Silent-Mutant Cell Lines Show Substantial Phospho-Erk1/2 Differences. Top Blot:
Phospho-Erk1/2, Passage 2, 3.75 x 105 cells plated in a 75 cm2 TC treated flask, harvest time =
72 hr. Middle Blot: Phospho-Erk1/2, Passage 6, 1 x 105 cells plated in a 6-well TC treated plate,
harvest time = 48 hr, Passage 10, 3 x 105 cells plated in a 6-well TC treated plate, harvest time =
18 hr. Bottom panel: Quantification of the three blots using ImageJ software. Bar graphs
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represent averages across the replicates. Along the y-axis is the fold increase over NIH/3T3-WT
cells of phospho-Erk1/2 and along the x-axis are the different cell lines. (n = three replicates,
statistical analysis = t-test, one-tailed, Two-Sample Assuming Equal Variances, asterisks
represent statistically significant increases in phospho-Erk1/2 levels as compared to NIH/3T3WT cells). Equal amounts of protein (20 µg) from each cell lysate were loaded in each lane.
Silent Mutations in Human KRAS 4B Lead to PI3K Signaling Differences in StablySelected NIH/3T3 Cells
To understand the influence silent mutations have on the PI3K pathway, we performed
immunoblots to analyze the activation status of the downstream PI3K effector Akt (Figure 37).
Total Akt protein levels remained relatively constant for all of the cell lines, and although there
were differences in phospho-Akt levels, none of those differences were statistically significant
between replicates. As expected, the higher amounts of NIH/3T3-G12V KRAS protein
corresponded with high levels of phospho-Akt. This correlation did not extend uniformly to the
KRAS silent-mutant cell lines. For example, high KRAS expression of NIH/3T3-39 C→G and
NIH/3T3-39 C→T cells had low levels of phospho-Akt, while the lower expressing NIH/3T3180 T→G and NIH/3T3-36 T→G cell lines showed higher phospho-Akt. Thus, similarly to the
effects of silent mutations on MAPK signaling, PI3K pathway signaling could not be understood
in any unified way with respect to the silent-mutant cell lines.
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Figure 37. Silent-Mutant Cell Lines Show Altered Levels of PI3K Activation. Phospho-Akt
immunoblots demonstrating PI3K pathway activation across biological replicates. First Blot:
Total KRAS protein from Figure 27. Second blot: Phospho-Akt varied across the samples.
Third Blot: Total Akt levels remain relatively constant across the samples. Fourth Blot: GAPDH
is used as a loading control. One of two experiments is shown. Equal amounts of protein (20
µg) from each cell lysate were loaded in each lane.
Silent Mutations in Human KRAS 4B Lead to Differences in RalA Expression and Ral-GEF
Signaling in Stably-selected NIH/3T3 Cells
Increased expression of RalA has been found in some human cancers [122, 123], and
activation of RalA is important in tumor initiation and growth in human, but not mouse, cancer
models driven by mutant KRAS [122, 123]. Given the essential role RalA activation plays in
transformation in human cells, we therefore investigated whether silent mutations in KRAS
affected expression or activation of the Ral-GEF pathway effector RalA (Figure 38).
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Figure 38. Silent-Mutant Cell Lines Show Altered Ral-GEF Activation as Measured by
Expression and Activation of RalA. A: Immunoblots, Top Blot: Total KRAS protein from Figure
27. Second Blot: Active RalA from a RalBP-PBD agarose beads pulldown. Third Blot: Total
RalA, Passage 10, 3.75 x 105 cells plated in a 75 cm2 TC treated flask, harvest time = 72 hr
Fourth Blot: Total RalA, Passage 2, 3 x 105 cells plated in a 6-well TC-treated plate, harvest time
= 18 hr. Fifth Blot: GAPDH was used as a loading control. B: Total RalA Protein Expression
from two replicates were averaged from densitometry readings using ImageJ software. The xaxis represents the different cell lines and the y-axis represents the fold-increase over NIH/3T3WT cells. (statistical analysis = t-test, one-tailed, Two-Sample Assuming Equal Variances,
asterisks represent statistically significant increases in total RalA signaling compared to
NIH/3T3-WT cells) C: Quantification of Active RalA pulldown using densitometry averages
from ImageJ software. The x-axis represents the different cell lines and the y-axis represents the
fold-increase over NIH/3T3-WT cells.
All of the silent-mutant cell lines expressed similar or greater amounts of RalA protein
compared to NIH/3T3-WT cells. However, the levels of activated (GTP-bound) RalA were
similar to or lower than those in NIH/3T3-WT cells. These trends paralleled the data for
NIH/3T3-G12V cells, whereas RalA protein was high and activated RalA was low. Since the
literature suggests that the Ral-GEF pathway is less important in mouse models of cancer
[122,123], how these observations in mouse cells relate to transformation of human cells is
uncertain.
DISCUSSION
In this study, we provide evidence that stably-selected NIH/3T3 cells containing any
silent mutation at G12, G13, and G60 in the human KRAS 4B gene leads to overexpression of
KRAS protein as compared to NIH/3T3-WT cells (Figure 27). We also show that our silentmutant cell lines proliferate more rapidly than NIH/3T3-WT cells (Table 13). Furthermore, cell
lines containing our silent mutations reach higher cell densities than NIH/3T3-WT cells (Table
14). Moreover, all of the silent-mutant cell lines are more invasive than NIH/3T3-WT cells in
three independent cell invasion assays (Figures 32-34). However, silent mutation-directed
overexpression of KRAS protein was only associated with loss of contact inhibition in some
instances (Figure 29). Additionally, we did not find an association between KRAS
overexpression and migration (Figure 27, Figure 31). The results of all experiments with the
stable cell lines are summarized in Table 15.
KRAS is More Highly Conserved than HRAS, Particularly at G12, G13, and G60
It was surprising that any silent mutation at G12, G13, or G60 led to an overexpression of
KRAS protein, which was further associated with increases to proliferation rate, saturation
density, and invasive potential. Current literature supports the notion that codon usage is under
selective pressure during evolution [149, 152-153]. It is possible that KRAS has been
evolutionarily conserved to adopt a nucleotide sequence that minimizes protein expression, and
is sufficient to maintain homeostasis between critical signaling pathways, while avoiding the
uncontrolled growth and proliferation that is frequently associated with cancer. Codon usage
varies by only 20% between mice and humans in the KRAS gene [148, 155], even though the two
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97
Table 15. Summary of Results
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species diverged more than 90 million years ago [147, 154]. In contrast, codon usage varies by
35% between the human and mouse HRAS (Harvey RAS) genes. We found that mice, rats, pigs,
and humans all maintain similar glycine codon usage (Table 17), and have conserved the same
glycine codons in their respective KRAS genes at G12 (GGT), G13 (GGC), and G60 (GGC)
(Figure 39A) [148]. In contrast, HRAS genes for the same organisms vary in codon usage
between organisms at G12, G13, and G60 (Figure 39B). Moreover, by comparing G12, G13,
and G60 codon usage of KRAS and HRAS genes from 57 different species, the KRAS codons
varied by only 8% (14/170), while the HRAS codons varied by 52% (61/117) (Table 16) [148].
Finally, by comparing the G12, G13, and G60 codons to the G48, G77, and G151 codons within
the KRAS gene among the different species, G48, G77, and G151 codons had more variability
(8% versus 13%, respectively) [148, 155]. These data suggest KRAS is under more selective
pressure than HRAS, particularly at G12, G13, and G60. Moreover, G12, G13, and G60 codons
in the KRAS gene are under more selective pressure than some other glycine codons within the
KRAS gene.
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Figure 39. Alignment of KRAS and HRAS Genes From Different Species. Using ClustalX 2.1,
the mRNA sequences for human, mouse, rat, and pig KRAS and HRAS genes were aligned.
Asterisks on the top of each panel denote a nucleotide position whereby all organisms maintain
the same base. Lack of an asterisk along the top, or a dip in the gray bar graph along the bottom,
denote at least one sequence having a different base at that position. A. Alignment of KRAS
coding DNA from four different organisms. B. Alignment of HRAS coding DNA from four
different organisms. Red boxes indicate G12/G13 and G60 codons. Red = A, Blue = C, Orange
= G, Green = T.
KRAS Protein Expression
Overexpression of WT KRAS protein has been found in human head, neck, gastric,
endometrial, lung, ovarian, bladder, and colorectal cancers [116, 127-132]. We show that the
WT human KRAS nucleotide sequence contains the glycine codons that result in the lowest levels
of KRAS protein expression at G12, G13, and G60 in stably-selected NIH/3T3 cell lines, and
any silent mutations at those residues result in KRAS over-expression (Figure 27, Table 12).
Every G12, G13, and G60 silent-mutant cell line we generated led to at least a two-fold
overexpression of KRAS protein as compared to NIH/3T3-WT cells (Table 12). Some glycine
codons appear to be more influential than others in altering KRAS protein expression levels,
because we only observe detectable changes with silent mutations at G12, G13, and G60 (Figure
15) in our transient transfections, and not at G48, G77, or G151 (Figure 22). However, we never
made stable cell lines for G48, G77, or G151 silent mutations. The positions at which we show
silent mutations lead to overexpression of KRAS protein in NIH/3T3 cells are at, or proximal to,
the residues that frequently undergo missense mutations that are thought to drive human cancers
(G12, G13, Q61) (Figure 7).
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Table 16. G12, G13, and G60 Codon Usage Comparisons for KRAS and HRAS Across Species
Codon variations between organisms are in red and underlined. Black boxes indicate unreliable
or nonexistent sequencing data. [147-148, 154-155] mya = million years ago.
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In agreement with previous reports associating protein expression to codon usage [5, 16],
KRAS protein expression level variations directed by silent mutations in stably-selected
NIH/3T3 cells trend with mouse glycine codon frequency of usage at G12 and G60 for all four
glycine codons (Table 12), implying some residues may be similarly influential. Conversely, at
G13, the WT KRAS nucleotide sequence contains the most frequently used glycine codon, yet we
see an increase in KRAS protein expression with all silent mutations. This observation may be
explained by codon pair bias [9] which is possibly driven by a conserved CpG motif. It is
possible that mRNA secondary structure and changes to free energy play a yet undefined role in
the expression of KRAS protein. In summary, our data show that a single nucleotide change
coding for a synonymous codon can enhance KRAS protein expression in NIH/3T3 cells, which
has not been previously reported.
In human cells, the HRAS isoform has been reported to express 20-fold more protein
than oncogenic KRAS when transiently and stably overexpressed, and 5-fold more protein when
expressed from the endogenous promoter after genomic integration with AAV infection [57].
These large differences in protein expression are due to ribosomal stalling at underrepresented or
rare codons in KRAS that reduce the amount of KRAS protein expression [57, 59]. Others have
observed similar results with WT HRAS and WT KRAS [Nicole Fer and Kanika Sharma,
personal communication]. G12, G13, and G60 are conserved amino acids in H-, N-, and KRAS
isoforms. However, in contrast to the WT human KRAS gene, which minimizes KRAS protein
expression at each residue (GGT at G12, GGC at G13, GGT at G60) in our stably-selected
NIH/3T3 cells, the WT human HRAS gene uses the glycine codons [57] that result in the highest
possible KRAS protein levels at each residue position in our experiments (GGC at codon 12,
GGT at codon 13, and GGC at codon 60) (Table 12, Figure 39B). This is in agreement with
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current literature reporting opposing codon biases between genes within a related gene family
[149]. Because mouse and human codon glycine codon usages are similar (Table 17), it is
plausible that the codons at G12, G13, and G60 in human WT HRAS contribute to the increased
protein expression compared to WT KRAS in human cells.
Table 17. Comparison of Mouse, Human, Rat, and Pig Glycine Codon Usage
Glycine Mouse Frequency Human Frequency Rat Frequency Pig Frequency
Codon
of Usage (%)
of Usage (%)
of Usage (%)
of Usage (%)
GGT
18
16
17
14
GGG
23
25
24
24
GGA
26
25
25
26
GGC
33
34
34
36
Proliferation and Saturation Density
It is well established that the KRAS gene is intimately involved in cell growth and
proliferation (Figure 5) [32]. Because uncontrolled cell growth is a characteristic of human
cancers [31, 32, 74-77], and these silent mutations are found in human cancers (Figure 7), we
hypothesized that the enhanced KRAS protein expression we observed might impact the growth
rate of the silent-mutant NIH/3T3 cells. All of our silent-mutant cell lines resulted in more rapid
doubling times than NIH/3T3-WT cells (Figure 27 and Figure 28, Table 13). In 9 out of 11
instances, gradual increases in KRAS protein expression trended with gradual increases in
proliferation rates (Figure 27, Table 13).
NIH/3T3-WT cells grow into a confluent monolayer and then cease proliferating. In
order to determine if the more rapid proliferation rates resulted in uncontrolled cell growth, we
compared the total number of cells per unit surface area of our silent-mutant cell lines to
NIH/3T3-WT cells. In a 25 cm2 tissue culture-treated flask, NIH/3T3-WT cells formed a
confluent monolayer at a cell density lower than that of any other silent-mutant cell line, and the
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silent-mutant cell lines reached cell densities 73% to 370% higher than that of NIH/3T3-WT
cells (Table 14, Figure 28). We found that overexpression of KRAS protein from silent
mutations not only was associated with increases to proliferation rates, but also with increased
saturation density, a characteristic of cancer cells.
Cellular Invasion
The major difference between benign and malignant tumors is the tendencies of the cells
in malignant tumors to invade adjacent tissue [77]. In order to investigate whether KRAS silent
mutations increased the invasive potential of our mouse cell lines, we performed three separate
invasion assays; the Boyden chamber assay (Figure 32), the 3D cell culture assay (Figure 33),
and the 3D spheroid invasion assay (Figure 34). In every invasion assay, our silent-mutant cell
lines were more invasive than NIH/3T3-WT cells. In the 3D spheroid invasion assay, which
more closely exhibits similar morphologies, proliferation rates, survival signals, and hypoxic
conditions to tumors in vivo [119-121], all cell lines were significantly more invasive than the
NIH/3T3-WT cells. Our results indicate that silent mutant-directed overexpression of KRAS is
associated with increased invasive potential in NIH/3T3 cells.
Focus Forming and Migration
We also performed classic focus formation assays on our silent-mutant cell lines. The
NIH/3T3-G12V cells formed distinct foci whereas the NIH/3T3-WT cells instead formed a
confluent monolayer (Figure 29). None of the silent-mutant cell lines formed distinct foci like
NIH/3T3-G12V cells. However, some, but not all, of the silent-mutant cell lines formed
amorphous colonies counted in our ImageJ software program. The cell lines that overexpressed
KRAS protein the most (NIH/3T3-36 T→C and NIH/3T3-180 T→C) (Figure 27, Table 12) did
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not form amorphous colonies, while the ones that overexpressed KRAS protein the least
(NIH/3T3-36 T→G and NIH/3T3-180 T→G) did form amorphous colonies.
We assessed the migratory properties of our silent-mutant cell lines with both a
qualitative wound healing assay (Figure 30) and a quantitative Boyden chamber migration assay
(Figure 31). One silent-mutant cell line was significantly more migratory than the NIH/3T3-WT
cells in the Boyden chamber migration assay, and that cell line did not form amorphous colonies.
The cell lines that formed amorphous colonies in the focus forming assay (Figure 29) were
significantly less migratory than the NIH/3T3-WT cells.
The results of the focus formation assay and the migration assays highlight the diverse
and heterogeneous responses we observed. These responses are similar to the diverse and
heterogeneous responses seen with different RAS isoforms (Table 4), and different
characteristics of specific missense mutations within a particular RAS isoform, both of which are
poorly understood. Moreover, in RAS research, the causative feedback mechanisms and
signaling accommodations being made by the cell lines are not well understood. Feedback
mechanisms play a critical role in human cancers and complicate attempts to interpret signaling
data from in vitro experiments. While we observed significant differences in both our focus
forming and migration assays, we are uncertain what is driving these changes.
Signaling Pathways
In an attempt to better explain the differences we observed, we decided to interrogate the
three pathways associated with RAS-driven tumorigenesis (Figure 5). First we examined GTPbound KRAS, Raf, Mek, and Erk, effectors of the MAPK pathway, in which we found one
silent-mutant cell line (NIH/3T3-180 T→G) hyperactivated phospho-Erk1/2 more than our
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positive control NIH/3T3-G12V cells (Figure 36). Additionally, NIH/3T3-39 C→G significantly
down-regulated phoshpo-Erk1/2 when compared to NIH/3T3-WT cells, as measured by
phospho-Erk1/2. We next investigated the PI3K pathway. While we observed differences in the
PI3K signaling as measured by phospho-Akt (Figure 37) in our silent-mutant cell lines as
compared to NIH/3T3-WT cells, we could not connect PI3K signaling to protein expression,
proliferation, migration, invasion, or loss of contact inhibition. Lastly, we interrogated the RalGEF pathway. While we observed differences in both expression and activation (as measured by
RalA or active RalA, respectively) (Figure 38), our data do not tell a story consistent with our
other assays.
We provide evidence that silent mutant-directed enhancements to KRAS protein
expression levels are altering signaling pathways associated with tumorigenesis and altering
tumorigenic phenotypes. However, our results do not support any one signaling pathway being
wholly responsible for the observed phenotypes of G12, G13, or G60 silent-mutant NIH/3T3 cell
lines. In agreement with others [32, 109, 111], we think it is likely these phenotypes reflect the
integrated output of several RAS signaling pathways that are associated with aggressive
transformation, many of which are not fully understood.
By using active RalA, phosphorylated Akt, and phosphorylated Erk 1/2 as surrogate
readouts for Ral-GEF, PI3K, and MAPK signaling, respectively, we found the ratio of RalGEF:MAPK:PI3K for each cell line to be indicative of amorphous colony-forming ability (Table
18). Cell lines with signaling ratios on either extreme as compared to NIH/3T3-WT cells formed
amorphous colonies in our focus forming assay. NIH/3T3-36 T→C cells, with signaling ratios
less extreme, were migratory, but did not form amorphous colonies. Cell lines with signaling
ratios similar to that of NIH/3T3-WT cells did not form amorphous colonies and were not
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migratory. While there is an association between integrated signaling ratios and colony
formation, it is unclear if these ratios are predictive. Notably, NIH/3T3-G12V cells are the only
cells to form colonies and be migratory.
Table 18. Ratio of Active RalA to Phospho-Erk to Phospho-Akt as it Relates to Colony
Forming and Migration
Tumorigenic Index
We propose a tumorigenic index based on the results in Figure 15 which equally weights
proliferation, migration, 3D spheroid invasion, and amorphous colony formation (Figure 40),
although it is unknown (and perhaps unlikely) if these are equal contributors to tumorigenesis.
NIH/3T3-WT cells do not exhibit any tumorigenic phenotypes. All G12, G13, or G60 silent
mutations exhibit multiple tumorigenic phenotypes while NIH/3T3-G12V cells are the only cell
line to exhibit every tumorigenic phenotype. In contrast, the NIH/3T3-WT cell line is the only
cell line that does not exhibit any tumorigenic phenotype. All silent-mutant cell lines have
tumorigenic indexes higher than that of the NIH/3T3-WT cells. We think the oncogenic positive
control has a substantially higher tumorigenic index because not only does that cell line
overexpress KRAS protein, but those cells are also GAP-insensitive.
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Figure 40. Silent-Mutant Cell Lines Exhibit Altered Tumorigenic Potential. Tumorigenic Index
is calculated based on proliferation, amorphous colony forming, migration, and invasion data.
All parameters are weighted equally and data are normalized to WT cells.
Model
We propose a working model in which the WT KRAS nucleotide sequence has been
evolutionarily conserved to minimize KRAS protein expression, particularly at codons G12,
G13, and G60. Any possible synonymous codon changes at these positions, such as the silent
mutations observed in human cancer patients, (Figure 7) lead to overexpression of KRAS protein
in NIH/3T3 cells. The increased KRAS protein expression alters critical signaling pathways,
which is associated with increases in proliferation, saturation density, and invasion. These
signaling pathway alterations are also associated with changes to migration potential and colony
formation (Figure 41).
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Figure 41. Working Model for Silent-Mutant Induced Alterations to Tumorigenic Potential in
the KRAS gene in NIH/3T3 Cells. The WT KRAS nucleotide sequence has been evolutionarily
conserved to minimize protein expression, especially at G12, G13, and G60. Any silent mutation
at those positions leads to overexpression of KRAS protein, altered signaling pathways, and
subsequent increases in proliferation, saturation density, and invasion in NIH/3T3 cells. Colony
formation and migration are also affected. The G12, G13, and G60 degenerate nucleotides are
colored and underlined. The WT codons at those locations are red, and the silent mutations we
introduced are green.
Future Experiments
We used previously available mRNA structure and free energy prediction programs,
coupled with codon frequency of usage to understand the KRAS protein expression differences
we observed. Going forward, it would be interesting to do ribosome or polysome profiling to
more closely examine the translation rates of our KRAS gene set. To understand mRNA
stability, silent-mutant cell lines could be treated with actinomycin D, which binds DNA at
transcription initiation complexes, inhibiting transcription. Inhibiting new mRNA production
with actinomycin D and then calculating and comparing KRAS mRNA turnover rates in the cell
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lines carrying different KRAS silent mutations over a time course would contribute to our
understanding of KRAS mRNA turnover.
Previous research has shown that substituting rare codons for more frequently used
codons in proteins that are co-translationally folded can affect the final folding con-formation of
the protein [98, 136]. Co-translational folding is possible given that KRAS is an α/β protein
[51], and α/β proteins are most often co-translationally folded in eukaryotic cells [50]. If there
were folding differences in KRAS protein because of silent mutations, it is possible there would
be differences in protein half-life or in posttranslational modifications. Treating cells with
cycloheximide, which inhibits translation, would halt new protein synthesis. KRAS protein
levels could be examined over a time course to understand how KRAS protein half-life differs, if
at all, between the different silent-mutant cell lines. Additionally, native gels could be run and
differences in KRAS banding patterns could indicate differences in post-translational processing.
There are tissue-specific differences in codon usage throughout the body [142]. It has
previously been shown that particular KRAS missense mutations are overrepresented in cancers
of different tissue origin, yet the reasons for these tissue-specific preferences are largely
unknown [23]. It would be intriguing to investigate if certain silent mutations are more
frequently associated with cancers in particular tissues based on tissue-specific glycine codon
usage and corresponding KRAS protein expression differences. It is possible that protein
expression plays a role in these tissue-specific preferences for both missense and silent
mutations.
We are unaware of any studies examining the protein expression levels of KRAS
missense mutations in any detail. We think it would be interesting to look at the common
missense KRAS mutations found in human cancers and investigate the role protein expression
110
levels might play in the subsequent tumorigenic phenotypes. Using an inducible expression
system, KRAS protein expression levels of missense mutants could possibly be adjusted to
express protein at a level more similar to WT KRAS. We could then experimentally determine if
tumorigenic phenotypes were decreased or increased with decreased or increased protein
expression of the tumor-promoting missense KRAS mutations.
We focused most of our research at silent mutations at the glycine codons G12, G13, and
G60, because silent mutations in those codons have been observed in human cancers [61, 62]
(Figure 7). Other glycine locations throughout the KRAS gene that we investigated with transient
transfections did not seem to have large effects on KRAS protein expression or focus formation.
We think it is likely, however, that there are other silent mutations which regulate WT KRAS
protein expression levels, especially given that the KRAS gene is enriched for rare codons [5759]. While others have focused on missense mutations, we question whether silent mutations at
other locations in KRAS can cause overexpression of KRAS protein and are associated with
cancer. By substituting in more frequently used codons at those locations, KRAS overexpression
may lead to increased tumorigenic phenotypes.
Our studies focus on NIH/3T3 cells, a fibroblastic, murine cell line. Investigating how
silent mutations at G12, G13, or G60 would affect protein expression in human, epithelial cells,
from which >90% of human cancers are derived, and then evaluating the cancer hallmarks is an
intriguing possibility. Going forward, it would be useful to understand the role G12, G13, and
G60 silent mutations in KRAS play in "WT KRAS” human cell lines. An additional tool to
evaluate tumorigenesis of silent mutations in human cells is Calu-6 cells, a lung cancer cell line
that contains a G60G silent KRAS mutation (180 T→C) in addition to a missense Q61 mutation.
In our stably-selected mouse cell lines, that particular mutation (NIH/3T3-180 T→C cells)
111
increased KRAS protein expression levels more than 13-fold on average, was significantly more
migratory, and increased proliferation by over 300% when compared to NIH/3T3-WT cells
(Table 13). It is possible that reversion of the silent mutation GGC to the WT GGT codon would
reduce some of the tumorigenic potential of this cell line. It would also be interesting to
investigate whether reversion of the Q61 mutation to Q would reduce the tumorigenic potential
of the cell line. With the advent of CRISPR technology, these types of experiments are
becoming increasingly achievable [146].
Silent mutations in the KRAS gene in colorectal cancers, in at least one publication, seem
to be more frequently observed than any of the missense mutants [69]. In this cited study, the
most frequently observed mutation among 61 colorectal cancer patients was a silent 39 C→T
mutation (G13G). Unfortunately, the FDA approved therascreen® KRAS RGQ PCR Kit
marketed by Qiagen was used to diagnose these patients, and the kit, like all of the others we
examined that are clinically available, does not detect silent mutations at G12, G13, or G60.
These mutations were only revealed after subsequent Sanger sequencing and PCR techniques. It
is unclear why all of the silent KRAS silent mutations observed in this study were 39 C→T
mutations. Perhaps there are tissue-specific differences in colorectal tissue whereby 39 C→T
cells have a survival or proliferative advantage. In relation to these clinical studies, we found
NIH/3T3-39 C→T cells exhibited a transformed phenotype as measured by amorphous colony
formation, increased proliferation rate, increased cell density, increased invasive potential, and
significantly increased signaling through the Ral-GEF pathway, a requirement for human
malignant transformation [122].
It has previously been observed that colorectal cancers with overexpression of WT KRAS
protein due to KRAS gene amplifications are resistant to EGFR monoclonal antibody therapy
112
[116]. Current mutational screening technologies are used to determine if the use of an EGFR
inhibitor would be contraindicated. These diagnostics ignore silent mutations, which may result
in KRAS overexpression. Therefore, KRAS overexpression, as a result of silent mutations at
G12, G13, and G60, may go undetected. It would be interesting (although costly) to examine
whole exome sequencing data from cancer patients in a cohort study, to determine if there is a
significant overabundance of KRAS silent mutations at G12, G13, or G60 that have been
previously diagnosed as "wild-type." It would also be worth investigating cancers not frequently
associated with KRAS mutations to see if those cancers possess silent KRAS mutations. A small
study (n=20) revealed that 20% of AML patients possessed silent KRAS mutations at G12 or
G13, while none of the patients possessed missense mutations [102].
The RAS proteins have been termed “undruggable” [23], in part because of the failure to
develop an FDA-approved RAS targeted therapeutic despite intense research efforts. Going
forward, it is possible that specific drugs to mutant KRAS proteins with G12, G13, or Q61
missense mutations will become available in the clinic. It is these missense mutations that lead
to a state of constitutive activation (GTP-bound) of KRAS and hyperactive signaling.
Significant progress has been made in developing small molecule inhibitors for the active site of
mutant KRAS G12C, which renders it permanently inactive [143]. There is no published
evidence that KRAS is a co-translationally folded protein, and KRAS can be partially refolded in
vitro without chaperones (Matthew Holderfield, personal communication). If the silent
mutations at G12, G13, and G60 in KRAS do not alter protein conformation, we think it is likely
that the silent mutations observed in human cancers do not alter the GTP hydrolysis of KRAS,
and the tumorigenic phenotypes we are observing in NIH/3T3 cells are because of increases in
protein expression.
113
If differences were seen in KRAS protein half-life among the silent mutation versions in
the proposed cycloheximide study above, that would provide preliminary evidence that the
proteins may be folding differently. It would then be interesting to determine if the silent
mutations observed in the KRAS gene of human cancers have altered GTP hydrolysis rates as
compared to the WT protein. Investigating differential GAP, GEF, and effector binding would
also be warranted in such an instance. Because we think it is more likely our observations are
due to overexpression, cancers containing silent mutations will likely not be susceptible to
therapeutics targeting the active site of missense mutant KRAS protein.
This research establishes a novel role for KRAS silent mutations at G12, G13, and G60
contributing to tumorigenic phenotypes in NIH/3T3 cells and uncovers a previously overlooked
aspect of cancer research. These studies also suggest our current KRAS diagnostics in the clinic
do not detect mutations with potentially important health implications. The immediate impact of
this research could be in diagnostics because of the failure of clinical tests to detect silent
mutations. In humans, it is possible that silent mutations in the KRAS gene at G12, G13, and
G60 lead to tumorigenic phenotypes in a manner analogous to the manner in which WT KRAS
overexpression is thought to lead to cancer through gene amplification. Moreover, colorectal
cancers overexpressing WT KRAS protein are resistant to the standard treatment with EGRF
monoclonal antibody inhibitors [128]. Because a large percentage of colorectal cancer patients
have been observed to have silent mutations at G13 [69] and these mutations are not detected by
FDA approved kit-based diagnostics [65-69], and because patients with gene amplifications of
WT KRAS are resistant to EGFR monoclonal antibody treatments [116], silent-mutant directed
KRAS overexpression may be partially responsible for the clinical failure of EGFR inhibitors.
If the tumorigenic phenotypes of KRAS silent mutations can be recapitulated in
114
mammalian cells or in vivo, we suggest that going forward, all diagnostic kits which detect
missense KRAS mutations also should be designed to differentiate between these silent
mutations. Additionally, we suggest FDA approved kits already available be redesigned or
retrofitted to include silent mutations at G12, G13, or G60 in their panel of detectable mutations.
For the present, Sanger sequencing provides an alternative technology to detect silent mutations.
These results provide evidence that synonymous codon changes in the KRAS gene are not
"silent." Many or most proteins can be affected by silent mutations [7]. With therapeutic
proteins being altered by as much as 80% from their native nucleotide sequence [7], the effect of
silent mutations should be taken into account.
This study begins to clarify the role silent mutations in the KRAS gene may have in
cancer, shifting a biological paradigm by providing strong in vitro evidence that previously
ignored silent mutations at G12, G13, and G60 in the KRAS gene lead to KRAS overexpression.
This enhanced KRAS protein expression affects signaling cascades and increases cancerassociated phenotypes in NIH/3T3 cells. Every tumorigenic phenotype we assessed (enhanced
proliferation, saturation density, colony formation, migration, and invasion) was affected by
KRAS silent mutant-mediated increases in protein expression.
This research was focused on KRAS, yet there are many other drivers of cancer.
Currently, most cancer research has centered around missense mutations, and to a lesser extent,
epigenetic changes. KRAS silent mutations are already observed at an abnormal rate in human
cancers, and overexpression of WT KRAS has been found in many types of cancer. Our data
provide substantial empirical evidence that silent mutations play a prominent role in tumorigenic
phenotypes in vitro, and we strongly suggest that these mutations should be monitored in the
clinic.
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