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DNA Replication Stress as a
Hallmark of Cancer
Morgane Macheret and Thanos D. Halazonetis
Department of Molecular Biology, University of Geneva, 1205 Geneva, Switzerland;
email: [email protected]
Annu. Rev. Pathol. Mech. Dis. 2015. 10:425–48
Keywords
The Annual Review of Pathology: Mechanisms of
Disease is online at pathol.annualreviews.org
oncogenes, tumor-suppressors, genomic instability, TP53, DNA damage,
common fragile sites
This article’s doi:
10.1146/annurev-pathol-012414-040424
c 2015 by Annual Reviews.
Copyright !
All rights reserved
Abstract
Human cancers share properties referred to as hallmarks, among which sustained proliferation, escape from apoptosis, and genomic instability are the
most pervasive. The sustained proliferation hallmark can be explained by
mutations in oncogenes and tumor suppressors that regulate cell growth,
whereas the escape from apoptosis hallmark can be explained by mutations
in the TP53, ATM, or MDM2 genes. A model to explain the presence of the
three hallmarks listed above, as well as the patterns of genomic instability
observed in human cancers, proposes that the genes driving cell proliferation
induce DNA replication stress, which, in turn, generates genomic instability
and selects for escape from apoptosis. Here, we review the data that support
this model, as well as the mechanisms by which oncogenes induce replication
stress. Further, we argue that DNA replication stress should be considered
as a hallmark of cancer because it likely drives cancer development and is
very prevalent.
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INTRODUCTION
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Cancer is defined as an abnormal, uncontrolled growth of tissue. In terms of human health, cancer
accounts for about one quarter of all deaths in developed countries and, therefore, is a major
health issue (1). While there are significant differences between different types of cancers, there
are also properties shared by practically all of them. These properties, referred to as hallmarks
of cancer, include sustained proliferative signaling, evasion of growth suppressors, escape from
apoptosis, tissue invasion and metastasis, limitless replicative potential, sustained angiogenesis,
evasion of immune surveillance, deregulated cellular energetics, genomic instability, and tumorpromoting inflammation (2–4). The number of cancer hallmarks has almost doubled since the term
was originally introduced in 2000 by Hanahan & Weinberg (2), in part, reflecting our increased
knowledge of cancer.
It is evident that certain hallmarks will be more central to cancer development than others.
Identifying these hallmarks and their molecular basis could allow us to formulate a more general
model for cancer development. Obviously, the molecular changes responsible for the indispensable
hallmarks should be present in the vast majority of cancers. In the past few years, the genomes of
thousands of cancers have been analyzed in great detail (5–11). Thus, it is now possible to better
link molecular changes to specific hallmarks and also to gauge the importance of specific hallmarks
on the basis of the frequency of the underlying molecular changes.
Here, we review recent findings in the field, arguing that DNA replication stress is a feature
present in most cancers and, therefore, worthy to be included among the classical hallmarks. Thus,
an emerging view of cancer progression proposes that oncogenes inducing sustained proliferation
also induce DNA replication stress, and that two other hallmarks, escape from apoptosis and
genomic instability, are a consequence of replication stress.
CANCER-DRIVER GENES
Seminal studies in the late 1970s and early 1980s have demonstrated the existence of cellular
genes, termed oncogenes, that drive cancer development (12–14). A large number of oncogenes
have been identified on the basis of two main criteria: being mutated in human cancers and being
able to transform cells when mutated or overexpressed.
Oncogenes constitute one class of cancer-driver genes. A second class of cancer-drivers constitutes genes whose wild-type form suppresses cancer development (14). These genes, referred
to as tumor suppressors, are inactivated by point mutations or deletions in human cancers. Most
tumor suppressor genes are direct antagonists of oncogenes. For example, the protein product of
CDKN2A interacts directly with and inhibits the protein product of the CDK4 oncogene (15–18).
Thus, specific pathways are important in cancer development, and genes that function in these
pathways can be either oncogenes or tumor suppressors, depending on their precise function in
the pathway.
There are multiple mechanisms by which oncogenes and tumor suppressor genes can be activated and inactivated, respectively. Point mutations (single nucleotide substitutions, SNSs) and
somatic copy number alterations (SCNAs) represent two very common mechanisms (5–11). The
genomes of thousands of human cancers have been analyzed, providing frequencies at which
cancer-driver genes are targeted by each mechanism. In regard to SNSs, results from sequencing analysis of 3,281 tumors representing 12 common cancer types show that the TP53 ( p53)
tumor suppressor gene is targeted by SNSs in 42.0% of all cancers (8). PIK3CA, which encodes
the catalytic subunit of PI3K, is a distant second with SNSs in 17.8% of all cancers, followed
by PTEN, APC, VHL, and KRAS, which are mutated in 9.7, 7.3, 6.9, and 6.7% of all cancers,
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50
Frequency of SNS (%)
40
30
20
H1
RB1
NOTC
3
ATM
GATA
2
2A
CDKN
1
SETD
PIK3R
NF1
NAV3
EGFR
1A
PBRM
1
ARID
MLL2
MLL3
KRAS
VHL
APC
A
PTEN
TP53
0
PIK3C
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10
Figure 1
The top 20 genes most frequently targeted by SNSs across 12 human cancer types, representing 3,281
cancers according to Reference 8. The bars are colored green for genes stimulating sustained cell
proliferation (oncogenes), orange for genes inhibiting sustained cell proliferation (tumor suppressors), and
red for genes that function in the DNA damage response pathway (a second class of tumor suppressors). The
bar corresponding to NOTCH1 is colored blue because this gene functions as an oncogene or tumor
suppressor depending on the cell type. For each gene, the percentage of cancers with SNSs targeting the
specific gene is indicated. SNS: single nucleotide substitution.
respectively (Figure 1). Among the 20 cancer-driver genes that are most frequently targeted by
SNSs in humans, three are oncogenes and 17 are tumor suppressors.
In contrast to SNSs, which target a single gene, SCNAs typically involve several genes. Analysis
of thousands of SCNAs in 4,934 tumors representing the same 12 cancer types described above
has led to the identification of peaks of amplified and deleted genomic regions (11). Among the
ten most significantly amplified genomic regions, nine contain established oncogenes (Table 1).
CCND1, which encodes cyclin D1, is the most significantly amplified gene, followed by EGFR,
MYC, TERC, ERBB2, and CCNE1.
Unlike the genomic amplifications, not all genomic deletions target cancer-driver genes. In
fact, only four of the ten most significantly deleted genomic regions encompass established tumor suppressor genes, which in order of statistical significance are CDKN2A/CDKN2B, STK11,
ARID1A, and PTEN. The remaining six regions target very large genes (Table 2). These genes
are large because they contain very large introns, whereas their mRNA is not unusually long. The
tendency of deletions to target very large genes is not limited to the ten most significantly deleted
regions. Among the top 70 recurrently deleted genomic regions, 22 target one of the 100 largest
genes in the genome (11).
It has long been debated whether the very large genes, which are frequently targeted by deletions in cancer, are bona fide tumor suppressors (19–23). In various experimental models, including
knockout mice, inactivation of these genes does not, in general, result in dramatic phenotypes as
far as tumor development is concerned, unlike what is seen when bona fide tumor suppressors
are inactivated. Further, whereas the deletions targeting well-established tumor suppressor genes
are typically homozygous, the deletions targeting very large genes are typically hemizygous and,
thus, a wild-type copy of the gene is retained (9). Another distinction relates to the frequency with
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Table 1 Top ten recurrently amplified genomic regions in human cancers
Amplification
Cancer-
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boundaries
driver
Gene
Gene
boundaries
Gene size
(bp)
mRNA
SNS
frequency
Fragile
size (bp)
(p-value)
site
1
chr11:69,464,719–
69,502,928
CCND1
Onc
chr11:69,455,873–
69,469,242
13,370
4,289
-
6.6e-08
2
chr7:55,075,808–
55,093,954
EGFR
Onc
chr7:55,086,678–
55,279,262
192,585
5,600
-
2.2e-15
3
chr8:128,739,772–
128,762,863
MYC
Onc
chr8:128,748,315–
128,753,680
5,366
2,366
-
-
4
chr3:169,389,459–
169,490,555
TERC
Onc
chr3:169,482,398–
169,482,848
451
451
-
-
5
chr17:37,848,534–
37,877,201
ERBB2
Onc
chr17:37,844,167–
37,884,915
40,749
4,624
-
1.3e-06
6
chr19:30,306,758–
30,316,875
CCNE1
Onc
chr19:30,302,805–
30,315,224
12,420
1,947
-
-
7
chr1:150,496,857–
150,678,056
MCL1
Onc
chr1:150,547,027–
150,552,214
5,188
4,085
-
-
8
chr12:69,183,279–
69,260,755
MDM2
Onc
chr12:69,201,952–
69,239,324
37,373
7,495
-
-
9
chr11:77,610,143–
77,641,464
INTS4
-
chr11:77,589,766–
77,705,771
116,006
3,149
-
-
10
chr8:38,191,804–
38,260,814
WHSC1L1
Onc
chr8:38,127,217–
38,239,872
112,656
5,431
-
-
Table of the top ten recurrently amplified genomic regions in 4,934 tumors from 12 cancer-types and their associated gene according to Reference 11.
The p-values for SNS frequency indicate if a gene is recurrently targeted by single nucleotide substitutions (SNSs) in human cancers. Onc, oncogene.
which well-established tumor suppressor genes and very large genes are targeted by SNSs. The
frequencies of SNSs within the former genes in human cancers are several orders of magnitude
higher than those within the very large genes (Table 2). As described below, very large genes
map to common fragile sites (CFSs) and, therefore, the deletions targeting these genes may be
explained on the basis of DNA replication stress (19, 24, 25).
MOLECULAR FUNCTIONS OF CANCER-DRIVER GENES
It is a reasonable assumption that mutations (SNSs, deletions, amplifications, translocations, etc.)
in cancer-driver genes underlie the hallmarks of cancer. For most genes, it is possible to make
a link with a specific hallmark; therefore, the frequencies by which genes are targeted in cancer
can provide an indication of the importance of the corresponding hallmark. Along these lines, we
matched the genes most frequently targeted by SNSs (20 genes), genomic amplifications (10 genes),
and genomic deletions (10 genes) to a recently described list of cancer hallmarks (3, 8, 11).
It is evident that many genes frequently mutated in human cancers are linked to the two hallmarks relating to cell growth: sustained proliferative signaling and evasion of growth suppressors.
We have argued in the past that these two hallmarks are in fact two sides of the same coin (26). For
example, RB1, which encodes for pRb, has been assigned to the evasion of growth suppressors hallmark, whereas CCND1, which encodes for cyclin D1, would probably be assigned to the sustained
proliferative signaling hallmark (3). Yet, both these genes function in the same molecular pathway
as antagonists of each other (15–18). Accordingly, the hallmarks sustained proliferative signaling
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Table 2 Top ten recurrently deleted genomic regions in human cancers
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Deletion
Cancerdriver
Gene
boundaries
Gene
mRNA
Fragile
SNS
frequency
(p-value)
boundaries
Gene
size (bp)
size (bp)
1
chr9:21,865,498–
22,448,737
CDKN2A
TS
chr9:21,967,751–
21,994,490
26,740
1,251
-
site
4.4e-15
2
chr19:1,103,715–
1,272,039
STK11
TS
chr19:1,205,798–
1,228,434
22,637
3,276
-
2.5e-13
3
chr5:58,260,298–
59,787,985
PDE4D
-
chr5:58,265,866–
59,783,925
1,519,061
8,240
-
-
4
chr6:161,693,099–
163,153,207
PARK2
-
chr6:161,768,590–
163,148,834
1,380,245
4,073
FRA6E
-
5
chr2:139,655,617–
143,637,838
LRP1B
-
chr2:140,988,996–
142,889,270
1,900,275
16,531
FRA2F
-
6
chr8:2,079,140–
6,262,191
CSMD1
-
chr8:2,792,875–
4,852,328
2,059,454
14,340
-
-
7
chr1:7,829,287–
8,925,111
CAMTA1
-
chr1:6,845,384–
7,829,766
984,383
8,444
-
-
RERE
-
chr1:8,412,464–
8,877,699
465,236
8,194
-
-
8
chr1:26,900,639–
27,155,421
ARID1A
TS
chr1:27,022,522–
27,108,601
86,080
8,585
-
1.5e-14
9
chr10:89,615,138–
90,034,038
PTEN
TS
chr10:89,623,195–
89,728,532
105,338
5,547
-
2.2e-15
10
chr16:78,129,058–
79,627,770
WWOX
DEBATED chr16:78,133,310–
TS
79,246,567
1,113,258
2,505
FRA16D
0.092
Table of the top ten recurrently deleted genomic regions in 4,934 tumors from 12 cancer types and their associated gene according to Reference 11. The
p-values for SNS frequency indicate if a gene is recurrently targeted by single nucleotide substitutions (SNSs) in human cancers. TS, tumor suppressor.
and evasion of growth suppressors may be considered as a single sustained proliferation hallmark,
to which more than half of the top 20 genes mutated in human cancer are linked (Figure 2).
The replicative immortality hallmark is also linked to genes frequently mutated in cancer. The
TERC gene, from which the RNA component of the telomerase complex is transcribed, is within
the top ten genes amplified in human cancer (Table 1), whereas the TERT gene, which encodes
the reverse transcriptase subunit of telomerase, is within the top 20 amplified genes (11, 27, 28).
Another hallmark linked to frequently mutated genes is that of escape from apoptosis
(Figure 2). We assign the TP53 gene, the most frequently mutated gene in human cancer
(Figure 1), to this hallmark because TP53 induces apoptosis in response to DNA damage.
However, TP53 can also induce senescence in response to DNA damage, and therefore cells with
mutant TP53 will escape not only apoptosis but also senescence. Accordingly, we prefer to use
the term escape from apoptosis/senescence for this hallmark. Other frequently mutated genes in
cancer that can be linked to the escape from apoptosis/senescence hallmark are ATM, MDM2,
and MCL1. ATM functions upstream of TP53 in the DNA damage response pathway (29–31).
The MDM2 gene, which encodes a ubiquitin ligase that targets p53 for degradation (32), is
among the ten most significantly amplified genes, as is the MCL1 gene, whose protein product
inhibits the proapoptotic protein Bax (33).
Links between the genomic instability hallmark and genes frequently mutated in cancer
have been a matter of controversy. It appears that almost all cancers have genomic instability
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Sustained proliferation
SNS
PIK3CA / PTEN /
APC / KRAS /
EGFR / NF1 /
PIK3R1 /
CDKN2A /
RB1 / NOTCH1
Ampl
CCND1 /
EGFR /
MYC /
ERBB2 /
CCNE1 /
FGFR1
Replicative
immortality
Del
CDKN2A /
STK11 /
PTEN
TERC
SNS
Genomic
instability
Invasion and
metastasis
SNS
SNS
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Chromatin
modifiers
Ampl
ATM
NAV3 ?
MLL3 /
MLL2 /
ARID1A /
PBRM1 /
SETD2 /
GATA3
Ampl
WHSC1L1
Angiogenesis
SNS
VHL
Escape from
apoptosis/senescence
SNS
Ampl
TP53 / ATM
MCL1 / MDM2
Del
ARID1A
Figure 2
Linkage of cancer hallmarks to the most frequent genetic mutations identified in human cancers (top
20 genes targeted by SNSs, top 10 genes focally amplified, and top 10 genes focally deleted) (3, 8, 11). The
genes under the heading “Chromatin modifiers” could not be readily linked to a specific hallmark.
Oncogenes are indicated by green letters, tumor suppressors by red letters, and NOTCH1 by blue letters.
Note that only 4 of the top 10 focally deleted genomic regions contain cancer-driver genes and that only
cancer-driver genes are shown in this figure. As shown in Table 2, the remaining 6 focally deleted genomic
regions contain very large genes that are subject to deletions due to DNA replication stress. SNS, single
nucleotide substitution; Ampl, amplification; Del, deletion.
(5, 26, 34–36), defined as a higher rate of acquisition of genomic changes per cell division compared to normal cells. In principle, mutations in DNA repair genes could have explained the
genomic instability hallmark, but such mutations are not common in sporadic human cancers
(26). Mutations in DNA damage checkpoint genes are also unlikely to explain the almost universal presence of genomic instability in cancer. Inactivation of TP53 does not lead to genomic
instability under physiological conditions (37, 38). Mutations in ATM are frequent (compared to
other genes) and can lead to genomic instability (39), but in absolute terms the frequency of ATM
mutations is too low to explain why almost all cancers have genomic instability. As discussed below,
the genes driving sustained proliferation may be the ones responsible for the genomic instability
hallmark.
Among the remaining hallmarks, induction of angiogenesis can be linked to mutations in the
VHL gene (40), and invasion and metastasis can be linked to mutations in NAV3, a gene regulating
cell motility (41). However, the tumor promoting inflammation, avoiding immune destruction,
and deregulated cellular energetics hallmarks do not appear to be directly linked to any of the
genes that are among those most frequently mutated in human cancer (Figure 2).
Interestingly, there are several genes frequently mutated in human cancers that cannot be
directly linked to a specific hallmark (Figure 2). These include MLL3, MLL2, ARID1A, PBRM1,
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SET2, GATA3, and WHSC1L1, all of which have the capacity to modify chromatin structure. How
mutations in these genes promote cancer development is not clear. Gene expression profiles, cell
lineage specificity, and/or cell differentiation state might be affected (42). In turn, these changes
could impact cell proliferation, induce metabolic changes, and/or promote invasion and metastasis.
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ORDER OF ACQUISITION OF CANCER-DRIVER MUTATIONS
AND CANCER HALLMARKS
Since the early 1990s, it has become clear that there is some order by which cancer-driver genes
are mutated (43–46). Colon cancer is an ideal system to document this order because lesions
representing various stages of cancer development, ranging from hyperplasia to metastatic cancer,
can be isolated. The first event in the majority of colon cancers appears to be mutations that
inactivate the APC gene, a negative regulator of Wnt signaling (43–47). Inactivation of both
copies of the APC gene appears to be sufficient for development of adenomas with mild dysplasia
(48). The APC mutations are followed by mutations in other growth controlling genes, notably
KRAS, NRAS, GNAS, and AKT1, leading to the development of adenomas with moderate or
severe dysplasia. Subsequently, inactivation of the TP53 tumor suppressor gene and mutations in
other oncogenes, notably in PIK3CA, are associated with progression from adenoma to carcinoma
(43–46, 48).
The bladder is another organ in which lesions representing various stages of cancer development can be isolated and studied. Analysis of early noninvasive lesions (Ta) and later mucosaor muscle-invasive lesions (T1 or T2) reveal the presence of mutations in growth controlling
genes, such as FGFR3 and HRAS, at early stages of cancer development followed by mutations in
TP53 at later stages (49). Similar studies in other tumor types suggest that, generally, mutations
in oncogenes precede TP53 mutations (50).
Extending these observations from gene mutations to cancer hallmarks, one may conclude
that cancer hallmarks are acquired in a specific order. Thus, during cancer development, sustained proliferation would precede evasion from apoptosis/senescence because mutations in genes
implicated in growth control precede mutations in TP53.
TP53 AS A BARRIER TO ONCOGENE-INDUCED DNA DAMAGE
An important question is why mutations in cancer-driver genes are acquired in a specific temporal
order. The p53 tumor suppressor protein has a well-established function in the DNA damage
response (29, 30). In fact, the primordial function of the p53 family might have been to induce
apoptosis in germ cells following DNA damage (51–53). In somatic cells, p53 protein levels increase
in response to DNA damage, leading to activation of target genes that induce cell cycle arrest,
senescence, or apoptosis (54). The precise outcome depends on the cell type, the extent and type
of DNA damage, and other less-well-defined parameters. Activation of p53 in response to DNA
double-strand breaks (DSBs) is dependent on the checkpoint kinase ATM, itself encoded by a gene
that is frequently inactivated in human cancer. In response to DNA damage, ATM phosphorylates
p53, leading to its dissociation from the ubiquitin ligase Mdm2 and, consequently, to increased p53
protein levels (39). Similar to the TP53 and ATM genes, the MDM2 gene is frequently targeted
in human cancers (11). Specifically, MDM2 is amplified, resulting in constitutive p53 degradation
and a DNA damage checkpoint defect.
Taking into account that the ATM/TP53/MDM2 pathway responds to DNA DSBs, we and
others proposed that DSBs are present in precancerous and cancerous cells (55–59). Indeed, colon
adenomas, head and neck squamous cell hyperplasias and dysplasias, and noninvasive Ta bladder
lesions, all of which are early precancerous lesions, have signs of a DNA damage response (DDR).
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The presence of DNA damage in these lesions is not simply a feature of DNA replication. Normal,
nontransformed cells, such as those present in the basal layer of the epidermis and in colon crypts,
replicate as fast as or even faster than precancerous cells, yet do not exhibit a DDR (57, 58).
High-throughput sequencing analysis of colon adenomas and bladder Ta precancerous lesions
reveals mutations almost exclusively in genes related to the sustained proliferation hallmark (48,
49). In turn, this implies that DNA damage is induced, either directly or indirectly, in response to
deregulation of the genes that control cell proliferation. Supporting this argument, activation or
overexpression of oncogenes in tissue culture cells leads to DNA damage within one cell cycle (57,
60–63). Further, in experimental models of human foreskin hyperplasias induced by ectopically
expressing growth factors, a DDR is observed within three weeks of exposure to growth factors (58).
Thus, the model emerging so far suggests that the escape from apoptosis/senescence hallmark
is a response to DNA damage induced by the genes linked to the sustained proliferation hallmark.
Specifically, mutations targeting genes such as PIK3CA, PTEN, APC, KRAS, CDKN2A, CCND1,
EGFR, and MYC that drive cell proliferation would also induce a DDR, leading to activation of
the ATM/TP53/MDM2 pathway and p53-dependent induction of apoptosis or senescence. According to this model, the ATM/TP53/MDM2 pathway serves as a barrier to cancer progression,
which needs to be overcome, as happens, for example, by SNSs targeting TP53 (55–58, 63, 64).
Indeed, in human precancerous lesions, the presence of a DDR precedes the acquisition of TP53
mutations, arguing that DNA damage provides the selection pressure for TP53 inactivation. Further, precancerous lesions that retain functional p53 exhibit high levels of apoptosis or senescence,
whereas lesions in which TP53 has been inactivated are mostly devoid of apoptotic or senescent
cells, even though a DDR is still present (58).
The oncogene-induced DDR is observed whenever cells acquire the sustained proliferation
hallmark, and it does not necessarily require the presence of activated oncogenes. For example,
triple-knockout mouse fibroblasts, in which the genes encoding pRb, p107, and p130 are inactivated, do not require mitogens to proceed through the cell cycle, yet exhibit a robust DDR (65).
Similarly, inactivation of the APC tumor suppressor gene is sufficient to induce a DDR (66, 67).
Thus, an oncogene-induced DDR can be observed either when oncogenes are activated or when
tumor suppressors that regulate cell proliferation are inactivated. Due to lack of a better term,
when we refer to oncogene-induced DNA damage, we also include the DNA damage induced
when tumor suppressors that regulate cell proliferation are inactivated.
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DNA REPLICATION STRESS UNDERLIES ONCOGENE-INDUCED
DNA DAMAGE
Several observations suggest that oncogene-induced DNA damage is secondary to DNA replication stress. DNA replication stress is a term that broadly defines impediments in DNA replication
and generally includes stalling and collapse of DNA replication forks (68, 69). During stalling,
DNA replication is stopped, but the overall structure of the replisome stays intact; once the problem responsible for stalling is resolved, DNA replication can ensue. Depletion of nucleotides is one
way to induce fork stalling. Fork collapse is characterized by a disruption of replisome integrity.
Some or all of the proteins involved in replication may dissociate from the DNA template, and
even the template itself may be processed to generate aberrant DNA structures. Although stalled
and collapsed forks are clearly distinct entities, forks that have stalled for more than a few hours
tend to collapse (70).
The ability of oncogenes to induce DNA replication stress has been well documented in tissue
culture systems (62, 63). First, oncogene overexpression induces activation of the DNA replication
stress checkpoint, as manifested by activation of ATR, a checkpoint kinase that is similar to ATM,
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but which is activated specifically in response to replication stress. ATR phosphorylates several
substrates, including the checkpoint kinase Chk1 and the single-stranded DNA binding protein
RPA to regulate cell cycle progression and the stability of replication forks under stress (71). Overexpression of oncogenes in nontransformed cells also induces the emergence of nuclear foci containing single-stranded DNA. These foci are present exclusively in cells that are in S phase and are
thought to arise when the activities of the DNA polymerase and the DNA replicative helicase are
uncoupled. Foci containing 53BP1 and phosphorylated histone H2AX are also observed following
oncogene activation indicating the presence of DNA DSBs in these cells. These foci map to nuclear
regions that stain positively for PCNA, further linking their formation to DNA replication (63).
The induction of DNA DSBs following oncogene activation can also be detected by direct
methods, such as pulse field gel electrophoresis of genomic DNA. Using this method, the
oncogene-induced formation of DNA DSBs has been shown to be inhibited by aphidicolin, a
DNA polymerase inhibitor, suggesting that the formation of DNA DSBs is dependent on DNA
replication (63).
The effect of oncogene activation on DNA replication forks has also been studied at the
single-molecule level by the DNA combing technique (72). Cells are labeled consecutively with
two thymidine analogs (iodo- and chloro-deoxyuridine), and then genomic DNA is prepared and
spread on glass surfaces in the form of DNA fibers. DNA segments that have incorporated the
two analogs can be visualized by immunofluorescence, allowing the DNA replication forks to be
classified as progressing/ongoing (incorporation of both analogs with no intervening gap in the
DNA fiber), terminated (incorporation only of the analog that was administered first), or newly
fired (incorporation only of the analog that was administered last). The lengths of the DNA fibers
incorporating each analog can be used to measure replication fork speeds, and when multiple
forks can be visualized on a single fiber, asymmetry in fork progression and interorigin distances
can also be determined. Using this method, activated oncogenes have been shown to induce an
increase in the fraction of terminated forks, a decrease in replication fork speed, an increase in
fork asymmetry, and a decrease in interorigin distance (62, 63, 73–76). Slower fork speeds and
fork asymmetry likely represent fork stalling and/or collapse, whereas the decrease in interorigin
distance may represent compensatory firing of dormant origins and/or deregulated origin firing.
Electron microscopy, another method that allows study of DNA replication forks at the single
molecule level, also confirms the ability of oncogenes to induce DNA replication stress. Oncogene
overexpression induces the formation of aberrant DNA structures that may correspond to reversed
DNA replication forks (77).
Certain regions in vertebrate genomes are particularly sensitive to the presence of DNA replication stress. These regions are referred to as CFSs and are prone to deletions or loss of heterozygosity (LOH) when cells are treated with DNA polymerase inhibitors or when nucleotide pools
become depleted (78, 79). Overexpression of oncogenes in tissue culture model systems induces
genomic deletions or LOH within CFSs that precisely mimic the genomic changes observed when
these cells are treated with aphidicolin or hydroxyurea (62, 80, 81). As described below, CFSs are
very frequently targeted in human precancerous lesions and cancers (57, 58, 62, 82), providing
one of the best arguments in favor of the hypothesis that DNA replication stress is prevalent in
human cancers and drives genomic instability.
MECHANISMS BY WHICH ONCOGENES INDUCE DNA
REPLICATION STRESS
The mechanism or mechanisms by which oncogenes induce DNA replication stress have not been
clearly defined. Yet, this is an important question and many promising leads have emerged from
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the significant effort that has been invested to resolve this question. One should emphasize that it
is possible that different oncogenes induce DNA replication stress via different mechanisms, and
that even a single oncogene may induce replication stress by more than one mechanism.
The process of DNA replication involves discrete steps that occur at different phases of the cell
cycle (83). Following binding of the origin recognition complex to DNA, prereplication complexes
(pre-RCs) are assembled in G1 to render the origins competent for DNA replication (licensed
origins). The pre-RCs mature into preinitiation complexes (pre-ICs), which fire during S phase,
forming replisome progression complexes (RPCs). Broadly speaking, formation of the pre-RCs
is inhibited by CDKs and, thus, origin licensing is restricted to the G1 phase of the cell cycle. In
contrast, formation of the pre-ICs and of the RPCs is dependent on CDK activity and, thus, takes
place at the G1/S transition and in S phase (83–86). Because oncogenes deregulate CDK activity,
the steps described above could potentially be compromised in cancer cells.
One would think that it should be trivial to design experiments that elucidate which of the
steps described above are compromised by oncogenes. In practice, however, this is not easy.
First, our understanding of DNA replication at the molecular level is far from complete, and the
system is too complex to be easily dissected. Second, the tolerance of the replication machinery
to various perturbations is not well understood. Third, some of the available assays are surrogates
for the process of interest. Nevertheless, despite these difficulties, progress has been made toward
understanding how oncogenes induce DNA replication stress.
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Deregulation of Origin Licensing/Firing
One level at which oncogenes may act to induce DNA replication stress is origin licensing and/or
firing. Both these processes are tightly controlled by CDK activity and many oncogenes target
CDKs, either directly or indirectly (84–86). CCNE1, which is amplified in many human cancers
and which encodes for cyclin E1, acts directly on Cdk2, whereas certain tumor suppressors, such
as CDKN2A and CDKN2B, encode for CDK inhibitors (15, 87). Other oncogenes modulate CDK
activity indirectly via growth signaling pathways (14).
In budding yeast, deregulation of CDK activity induces DNA replication stress. Thus, yeast
could provide relevant mechanistic insights. In one study, overexpression of the G1 cyclin Cln2
induced DNA replication stress and genomic instability (88). The mechanism involved inhibition
of pre-RC assembly (origin licensing). In a second study, deletion of the SIC1 gene, a CDK
inhibitor, induced DNA replication stress as revealed by reduced origin licensing and firing and
increased interorigin distance, genomic instability, and mitotic defects probably stemming from
failure to complete DNA replication (89). These effects were mediated by cyclins Clb5/6, which
are active in S phase, rather than by Cln2, the G1 cyclin, because all phenotypes induced by
SIC1 deletion were rescued by Clb5/6 deletion. In yeast, expression of the licensing factor Cdc6
occurs in two waves corresponding to late mitosis and late G1, respectively (90). In the absence
of SIC1, the length of the G1 phase is shortened and the second wave of licensing does not occur,
presumably due to high CDK activity mediated by Clb5/6. Thus, replication stress in yeast lacking
SIC1 may arise from a defect in firing of the origins that are licensed in late G1.
Like SIC1 deletion in yeast, overexpression of cyclin E in human cells shortens the G1 phase
and induces DNA replication stress (57, 63, 73–75, 87, 91). Thus, one might anticipate that
activated oncogenes or, at least, cyclin E might induce DNA replication stress by compromising
origin licensing and consequently origin firing. Unfortunately, not all studies have supported this
prediction.
In one study, overexpression of cyclin E in a human nasopharyngeal epidermoid carcinoma cell
line resulted in a reduced number of nuclear BrdU foci in early S phase cells and in a reduction
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in BrdU fluorescence intensity, suggesting the presence of a smaller number of DNA replication
factories and a reduced rate of DNA synthesis at each factory (91). In parallel, there was reduced
association of the Mcm helicase subunits Mcm4 and Mcm7 with chromatin during G1, suggesting
a defect in origin licensing. However, association of other Mcm subunits, notably, Mcm3 and
Mcm5, with chromatin was not impaired. Because origin licensing involves the loading of Mcm
heterohexameric rings on chromatin, it is hard to see how loading of some subunits would be
compromised, but not of others. The authors explained the discrepancy in loading on the basis of
differences in kinetics. Recent results indicate that in yeast Mcm3,5,7 are loaded before Mcm2,4,6
(92). However, the kinetics of assembly of the various Mcm subunits in human cells remains to
be determined.
Interestingly, overexpression of cyclin E in U2OS osteosarcoma cells gave opposite results
from those reported with the nasopharyngeal carcinoma cells above (74). The number of IdU
foci was higher in early S phase cells following cyclin E overexpression, and interorigin distance
was slightly decreased, rather than increased, as would be expected if licensing was compromised.
Further, depletion of the licensing factor Cdc6 by siRNA to inhibit origin licensing or inhibition
of Cdc7 to inhibit origin firing suppressed the induction of DNA DSBs in cells overexpressing
cyclin E. If cyclin E overexpression induces increased origin firing, as these experiments suggest,
what could be the mechanism? Cyclin E-Cdk2 phosphorylates and stabilizes Cdc6 (93). This
stabilization is apparently particularly important for origin licensing when quiescent cells are
stimulated to reenter the cell cycle, and it may correspond to the second wave of Cdc6 expression
in yeast. Thus, one could imagine that in cells overexpressing cyclin E, higher levels of Cdc6 might
enhance origin firing. Other oncogenes, such as RAS and MOS, which induce DNA replication
stress, also enhance Cdc6 protein levels, and ectopic expression of Cdc6 is sufficient to induce
DNA replication stress (63). The MYC oncogene may also induce DNA replication stress by
stimulating origin firing, although in this case, the activity of Myc appears to be mediated through
Cdc45, which is involved in formation of pre-IC complexes (76). In conclusion, oncogenes are
likely to induce DNA replication stress by affecting origin licensing and firing, but depending on
the cellular context, origin licensing and firing may be upregulated or downregulated.
If cyclin E overexpression enhances origin licensing, how can this observation be reconciled
with the studies in yeast showing that SIC1 deletion inhibits licensing? One possible explanation is
that deletion of SIC1 leads to enhanced Clb5/6 activity, which are S phase-specific cyclins, whereas
cyclin E functions at the G1/S transition. Thus, Clb5/6 will suppress origin licensing, whereas
cyclin E, at least under certain conditions, may stimulate licensing via Cdc6 stabilization (93).
Shortage of Replication Building Blocks
A second level at which oncogenes can act to induce DNA replication stress is at the level of fork
progression. A decrease in fork speed has been observed in cell systems in which oncogenes, such
as KRAS and CCNE1, have been activated (62, 73–75). This is often accompanied by decreased
interorigin distance (implying increased origin firing), fork asymmetry, and an increased number
of DNA DSBs. A decrease in fork speed has also been observed in primary keratinocytes expressing
the human papillomavirus oncogenes E6 and E7, which target the p53 and pRb tumor suppressor
proteins, respectively (73). Interestingly, E6 and E7 also induced a decrease in deoxynucleotide
levels. This decrease was apparently important for the changes in DNA replication dynamics
and the induction of DNA damage, as addition of deoxynucleosides in the tissue culture media
suppressed, albeit not completely, the decrease in replication fork speed and the induction of DNA
DSBs (73). Exogenously added deoxynucleosides also rescued DNA replication stress in human
fibroblasts overexpressing cyclin E. Interestingly, in both systems, overexpression of the MYC
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oncogene led to an increase in endogenous deoxynucleotide levels and rescued DNA replication
stress. From these results, the authors concluded that deregulated cell cycle entry by oncogenes is
not accompanied by activation of all the pathways needed for proper progression through the cell
cycle. For example, E6/E7 and cyclin E promote entry into S phase without activating nucleotide
synthesis. Entry into the cell cycle with uncoordinated activation of pathways needed for DNA
replication may explain why MYC induces DNA replication stress when overexpressed on its own
(76, 94) but suppresses DNA replication stress when overexpressed in E6/E7-transformed cells
(73).
The concept that DNA replication stress in cancer cells is due to a relative deficiency in building
blocks needed for DNA replication has been further extended by studies of U2OS osteosarcoma
cells treated with MK-1775, a chemical inhibitor of the Wee1 kinase (95). Wee1 inhibits CDKs
and, therefore, Wee1 inhibitors can be used to rapidly induce CDK activity. In this regard, MK1775 mimics oncogenic activation with the advantage of activating CDKs with faster kinetics than
oncogenes. Treatment of U2OS cells with MK-1775 induced a profound decrease in replication
fork speed and induction of DNA DSBs (95). Interestingly, despite the decrease in fork speed,
the overall incorporation of the thymidine analog EdU per cell was increased. By dividing the
total level of EdU incorporation per cell by the average fork speed, the authors calculated that
Wee1 inhibition results in a threefold increase in the number of progressing forks. This very
significant increase was accompanied by a decrease in deoxynucleotide levels, which apparently
became limiting because the decrease in fork speed and the induction of DNA DSBs in this system
were partially rescued by exogenously added deoxynucleosides (95). Thus, these results indicate
that high levels of CDK activity induce DNA replication stress by increasing origin firing, which
in turn depletes the nucleotide pools.
Nucleotides are not the only building blocks whose levels may decrease relative to the number
of replication forks in cells overexpressing oncogenes. DNA replication in cells requires synthesis
of histones and of many other chromatin-associated proteins, as well as of proteins present at
the replisome (96). Thus, an increase in the number of progressing forks may result in a relative
deficiency of any of these proteins, thereby explaining the decrease in replication fork speed.
Suppression of new histone synthesis by targeting factors involved in histone biogenesis slows
fork progression by at least twofold, suggesting that fork speed can be regulated by histone supply
(97). However, DNA DSBs and activation of the replication checkpoint were observed only 48 h
after inhibition of histone biosynthesis, suggesting that limited histone supply needs to be chronic
to induce DNA replication stress (97).
Replisome proteins can also become limiting. In one study, U2OS cells were treated with the
Wee1 inhibitor MK-1775 to enhance origin firing and, in parallel, fork progression was challenged
with hydroxyurea (98). The large number of stalled forks in this setting consumed all the available
RPA, leading to fork collapse and formation of DNA DSBs. Studies in yeast have also demonstrated
that certain proteins involved in origin firing, such as Sld2, Sld3, Sld7, and Cdc45, can be limiting
(99, 100). In fact, the limited availability of these proteins is functionally important, as it controls
the timing of origin firing. Whether replisome proteins become limiting in cancer cells remains
to be determined.
As discussed above, either uncoordinated activation of pathways needed for DNA replication
or increased number of progressing forks could account for the relative lack of factors needed for
DNA replication in cancer cells. However, an alternative possibility is that this relative lack may
be secondary to a shortened G1 phase. Cells typically grow in size in G1 and have checkpoints to
ensure that they do not enter S phase if their size is too small (101). TOR is involved in such a
checkpoint, which, however, can be overcome by high levels of CDK activity (102). Overexpression
of CCNE1, CCND1, or MYC and activation of RAS, RAF, or SRC drive premature entry into S
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phase (75, 87, 91, 103–105), suggesting that cells start replicating their DNA with a smaller than
normal capacity for protein synthesis. Under these conditions, the cells may be unable to sustain
a normal rate of DNA replication.
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Interference Between Replication and Transcription
DNA replication utilizes the same template as transcription, creating the potential for interferences between these two processes. Indeed, analysis of replication origins and transcription units
across evolution suggests that organisms have evolved mechanisms to limit such conflicts (106). In
Escherichia coli, transcription units are codirectional with progressing forks, suggesting the need to
avoid head-on collisions (107). In yeast, highly transcribed genes are also replicated codirectionally with transcription (108). However, in human cells, the mapping of origins does not suggest a
preference for codirectionality between transcription and replication (109). Nevertheless, human
cells might regulate the spatio-temporal program of origin firing, so as to avoid conflicts between
DNA replication and transcription (110–112). Oncogenes might disrupt this program either by
affecting origin firing, slowing fork progression, or by changing the length of the cell cycle phases
(shorter G1, longer S phase), resulting in genomic loci being transcribed and replicated at the
same time.
As discussed above, CFSs are the genomic loci that are most susceptible to genomic rearrangements in the presence of oncogene-induced DNA replication stress (58, 62, 63, 82). CFSs correspond to very large genes (24, 25), and due to their large size, transcription of these genes spans
the G1 and S phases of the cell cycle and can even extend into the next cell cycle (113). In turn,
this means that transcription and replication occur concurrently on the same template. Analysis
of aphidicolin-induced chromosomal breaks within five CFSs in two different cell lines revealed
a perfect correlation between the presence of breaks and transcription. Further, the breakpoints
mapped to the region of the gene being transcribed in S phase, suggesting that the breakpoints
were due to conflicts between transcription and replication (113).
The role of transcription on oncogene-induced DNA replication stress was directly examined
in a subsequent study utilizing U2OS cells overexpressing cyclin E (74). Short-term treatment of
these cells with cordycepin, an RNA-specific chain terminator that inhibits transcription elongation, rescued slow fork progression and induction of DNA DSBs, although not completely.
The rescue was attributed to alleviation of conflicts between transcription and replication because
during the transient treatment of cells with cordycepin, cyclin E levels were not affected.
Interference between transcription and replication may also explain the presence of DNA
replication stress at specific early-replicating regions of the genome, referred to as early-replicating
fragile sites (ERFS) (114). ERFS were initially mapped as genomic loci prone to undergo DNA
damage in cells that enter S phase in the presence of hydroxyurea. These same sites were then
shown to be fragile when the MYC oncogene was overexpressed. ERFS correspond to highly
transcribed regions of the genome and genetic manipulation of one such site so as to reduce
expression rendered this site resistant to breakage.
How interference between transcription and replication leads to DNA replication stress is not
well understood (106, 110). One possibility is collisions between the transcription and replication
machineries. Alternatively, RNA:DNA hybrids formed during transcription might impede fork
progression (115). Supporting this latter model, depletion of topoisomerase 1 (Top 1) mimics
oncogene-induced DNA replication stress in the sense that it slows fork speed, decreases interorigin distance, enhances fork asymmetry, and induces chromosomal breaks at CFSs (116). In this
setting, Top1 is thought to release the DNA supercoiling that accompanies transcription and in
so doing prevents the formation of nascent RNA:DNA hybrids.
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PATTERNS OF GENOMIC INSTABILITY INDUCED BY DNA
REPLICATION STRESS
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One of the earliest observations linking DNA replication stress to genomic instability was the
appearance of chromosomal breaks following treatment of cells with aphidicolin (78). These
breaks were observed preferentially at specific chromosomal sites, termed CFSs. Subsequently,
comparative genomic hybridization analysis revealed the presence of genomic deletions mapping
to the CFSs, suggesting that the chromosomal breaks may result from an inability to complete
DNA replication (19, 80, 117, 118).
Several models have been proposed to explain why DNA replication stress leads to genomic
deletions preferentially within CFSs. One model proposes that CFSs are sites of interference
between replication and transcription. As discussed above, CFSs correspond to very large genes
that are transcribed throughout the cell cycle, implying that DNA replication cannot be dissociated temporally from transcription (113). Thus, under conditions of replication stress, the
transcriptional machinery would collide with slowly progressing forks, even when transcription
and replication are codirectional. Another model proposes that in CFSs the density of replication
origins is low (119). Thus, when DNA replication is challenged, there would be a scarcity of
dormant origins to rescue the replication defect. A third model proposes that CFSs correspond to
genomic regions that are intrinsically difficult to replicate (120, 121). Thus, any further perturbation in DNA replication would result in an inability to replicate these genomic regions. Another
contributing factor to the sensitivity of CFSs to DNA replication stress is the fact that CFSs are
late-replicating regions (79, 122). Thus, any form of DNA replication stress that slows down replication could result in cells entering mitosis with the CFSs not having been fully replicated (123).
The presence of unreplicated DNA at CFSs and other genomic regions has the potential to
also induce broad changes in chromosome structure and number by interfering with mitosis.
Specifically, regions of unreplicated DNA may form ultrafine anaphase bridges, which interfere
with chromosome segregation during mitosis, resulting in DNA damage in the next cell cycle and
genomic instability (124, 125).
Another type of genomic change induced by DNA replication stress is tandem segmental
genomic duplications. Such duplications are observed more frequently when DNA replication
stress is induced by ionizing radiation (IR) or oncogenes than when it is induced by aphidicolin or
hydroxyurea (75, 126). The difference may relate to the fact that IR and oncogenes induce fork
collapse, whereas aphidicolin and hydroxyurea induce primarily fork stalling. Collapsed forks are
processed into one-ended DNA DSBs, which are then repaired by a specific repair pathway, breakinduced replication (BIR), which is a form of homologous recombination (127, 128). According
to one model, BIR may produce tandem genomic duplications when the collapsed fork being
repaired is near a progressing fork (75, 129).
In addition to changes in chromosome structure, DNA replication stress has the potential
to induce SNSs. Stalling or collapse of replication forks results in DNA being single-stranded
for protracted periods of time; during this time, damaged bases cannot be repaired efficiently,
resulting in SNSs (48). Single-stranded DNA also arises during repair of collapsed replication
forks by BIR because in BIR the two strands of DNA are not coordinately replicated. Thus, in
yeast, replication by BIR is associated with about a thousand-fold increase in mutation rates, as
compared to normal replication (130, 131).
GENOMIC INSTABILITY PATTERNS IN HUMAN CANCERS
A comparison of the genomic instability patterns induced by DNA replication stress to those
present in human cancers can help answer the question whether replication stress is a major
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source of genomic instability in cancer. Other sources of DNA damage, such as reactive oxygen
species (ROS) (132, 133), telomere dysfunction (134–136), and mitotic defects (137, 138), will, of
course, also contribute to the genomic instability patterns present in cancers.
Not all genomic changes observed in human cancers are equally informative in terms of the
underlying mechanisms leading to genomic instability. Mutations that drive cancer progression
may be induced at a low frequency but be very prevalent in human cancers because they are
selected. Mutations in oncogenes and tumor suppressors would fall into this category. It is almost
evident that the loci containing these genes are not exceedingly more susceptible to mutagenesis
than the rest of the genome. Yet, due to selection pressures, the p values for SNSs within these loci
are very high (Tables 1 and 2). However, mutations that do not confer a selective advantage for
growth, the so-called passenger mutations (5), are indicative of the mechanisms driving genomic
instability. Thus, when considering the genomic instability patterns present in cancer, we focus on
the passenger mutations. The distinction between cancer-driver and passenger mutations applies,
of course, to all types of mutations, including SNSs and SCNAs, both of which are reviewed here.
At the chromosomal level, practically all cancers have changes in chromosome structure, which
are typically accompanied by changes in chromosome number (35). Many of the changes in
chromosome structure are SCNAs: amplifications (mostly duplications) and deletions (Figure 3).
SCNAs can be recurrent or nonrecurrent. We consider these two classes separately because, as
described below, many of the recurrent SCNAs involve oncogenes or tumor suppressors and,
therefore, have been selected.
First, in regard to the recurrent SCNAs, three-fourths involve a chromosomal segment (focal SCNAs), whereas the remaining one-fourth involves an entire chromosome arm (arm-level
SCNAs). The focal SCNAs can be further subdivided into those internal to the chromosome (fourfifths) and those that are telomere-bound (one-fifth) (11). The internal SCNAs encompass the ten
most common amplifications and the ten most common deletions present in human cancers (11).
Their distribution in the genome is presented in Tables 1 and 2. The most significantly amplified regions correspond to oncogenes and, therefore, their high recurrence rate can be explained
by the selection advantage they confer. Accordingly, they are not very informative in regard to
mutagenic mechanisms. Of the ten most common deletions, four map to tumor suppressor genes
and, therefore, have also been selected. However, the remaining six map to very large genes, including CFSs (Figure 3). It is, indeed, remarkable that CFSs are subject to deletions with similar
frequencies as tumor suppressor genes, even though the loss of CFSs is not thought to provide a
selective advantage for growth. The high recurrence rate of focal deletions targeting very large
genes and CFSs is not limited to the ten most common deleted regions. Of the top 49 recurrent
internal chromosomal deletions, 21 target one of the 100 largest genes in the human genome (11).
Taken together, these results suggest that DNA replication stress contributes significantly to the
induction of focal deletions in human cancers (19).
Telomere-bound SCNAs scored lower on the list of significantly recurrent SCNAs than the
internal SCNAs, in the sense that none of the ten most common focal amplifications or deletions
present in human cancers are telomere-bound (Tables 1 and 2). Further, among 21 recurrent
telomere-bound chromosomal deletions, only one targets one of the largest genes in the human
genome and none targets a bona fide tumor suppressor gene. This indicates that the mechanisms
leading to the establishment of telomere-bound SCNAs differ from those leading to the establishment of internal SCNAs (Figure 3). Telomere dysfunction can, of course, lead to the emergence
of telomere-bound SCNAs via the proposed breakage-fusion-bridge cycle mechanism (134–136,
139, 140).
Not all chromosomal rearrangements observed in human cancers are recurrent. A list of
nonrecurrent SCNAs in ovarian and breast cancers reveals that segmental head-to-tail tandem
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Recurrent SCNAs
Arm-level
Telomerebound
Focal
Ampl
?
Del
Ampl
Del
Associated with WGD
Dysfunctional telomeres
Ampl
Cancer-drivers
Del
Very large genes
(DNA replication stress)
and cancer-drivers
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Internal
Nonrecurrent SCNAs
Transl
Transl
Del
Del
Ovarian
Tandem
Dupl
Breast
Tandem
Dupl
Ampl
Ampl
Inv
Inv
Figure 3
Prevalence of recurrent and nonrecurrent SCNAs in human cancers. (Top) Distribution of recurrent SCNAs
across 12 human cancer types, representing 4,934 cancers according to Reference 11. The height of the bars
is proportional to the prevalence of the indicated SCNA and the putative mechanism responsible for each
type of SCNA is also indicated. (Bottom) Prevalence of nonrecurrent SCNAs in human ovarian and breast
cancers, according to References 141 and 142, respectively. The height of the bars is again proportional to
the prevalence of the indicated SCNA. Ampl, amplification; Del, deletion; Dupl, duplication; Inv, inversion;
Transl, translocation; SCNA, somatic copy number alteration; WGD, whole genome duplication.
duplications with microhomology junctions represent the most common type (141, 142). In
one experimental system of oncogene-induced replication stress, repair of collapsed forks by
BIR led to this type of duplication, suggesting that the duplications observed in human cancers
are induced in response to fork collapse (75). Other common types of nonrecurrent SCNAs in
ovarian and breast cancers are amplifications, deletions, translocations, and inversions (Figure 3).
Genomic instability in human cancers also occurs at the single nucleotide level. Depending on
the sequence context, in which nucleotide changes occur, several mutational signatures have been
identified (6). The most prevalent signature involves substitution of cytosines by thymines in the
context of CpG dinucleotides. Because cytosines are often methylated in the context of CpGs, the
mutations probably arise by spontaneous deamination of a methylated cytosine to a thymine (143).
Interestingly, the distribution of CpG to TpG substitutions in human cancers is not random.
Very large genes contain twice as many CpG to TpG mutations per megabase of genomic DNA as
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the rest of the genome (48, 144–146). This distribution may be explained by the presence of DNA
replication stress. The very large genes correspond to the late-replicating regions of the genome
and the CFSs (24, 25, 79). Collapsed DNA replication forks at these regions could be repaired
by BIR, which is mutagenic (130, 131). A second mechanism could relate to DNA persisting
in a single-stranded form for protracted periods of time, as a consequence of fork stalling or
collapse (48). During this time, methylated cytosines may become spontaneously deaminated to
form thymines (143). In the context of single-stranded DNA, these thymines do not generate a
base pair mismatch and are not repaired. In conclusion, the distribution of SNSs in human cancer
genomes suggests that at least some of the SNSs in human cancers may arise as a consequence of
DNA replication stress.
The two main signatures of genomic instability that are linked to DNA replication stress,
chromosomal deletions and SNSs targeting very large genes and late-replicating regions, are also
present in human precancerous lesions. In fact, the preference for genomic instability targeting
these regions appears to be even higher in the precancerous lesions than in the advanced cancers,
suggesting that DNA replication stress is an important driver for cancer development (48, 57,
58, 147).
SYNTHESIS AND CONCLUDING REMARKS
Our understanding of cancer has improved dramatically during the past few decades. One important contribution, representing the work of numerous researchers, is the identification of
phenotypes and molecular changes that are shared by almost all cancers (2–4). In turn, this knowledge has permitted the formulation of models that try to explain cancer development. Within the
context of this review, we have focused on oncogene-induced DNA replication stress and whether
it can serve as a driver for cancer progression. Clearly, other drivers, such as dysfunctional telomeres, mitotic defects, and ROS, are also important for cancer development, but, here, we only
briefly touched upon them because their roles in cancer progression have been recently reviewed
by others (133, 137, 148).
The results reviewed here suggest that it may be possible to integrate cancer phenotypes
and molecular changes to explain some aspects of cancer development (Figure 4). The first
step in cancer development involves mutations in genes regulating cell growth (oncogenes and
tumor suppressors). These mutations underlie the sustained proliferation hallmark. Interestingly,
precancerous lesions exhibit DNA replication stress, which we propose should be considered as
a hallmark of cancer because it is present in almost all cancers from the earliest stages. Given
the ability of oncogenes to induce DNA replication stress in various model systems and the
general absence of mutations in DDR genes in precancerous lesions, the mutations driving cell
proliferation must also be responsible for the DNA replication stress hallmark (Figure 4). DNA
replication stress and the ensuing DNA damage have two major consequences for the biology of
the precancerous lesions. First, they contribute to the genomic instability hallmark, which can
fuel cancer progression, and second, they activate a DDR, which activates ATM and TP53 (149).
A second step in cancer development involves suppression of the DDR. Activation of TP53
by DNA damage leads to apoptosis or senescence, thereby curtailing growth of the precancerous
lesion. In turn, this selects for mutations conferring an escape from apoptosis/senescence hallmark
(Figure 4). Mutations targeting the TP53, ATM, or MDM2 genes are primarily responsible for
establishment of this hallmark because they can suppress DDR-induced apoptosis and senescence
without compromising the DNA replication checkpoint per se, on which cancer cells rely to
stabilize and repair their damaged replication forks. We note that, traditionally, the escape from
apoptosis/senescence hallmark only referred to apoptosis, but DDR-induced senescence is also
very prevalent in human precancerous lesions (63, 150).
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Sustained
proliferation
TERC /
TERT
Replicative
immortality
Genomic
instability
(CIN/SNS)
Oncogenes/
tumor suppressors
regulating growth
Precancerous
lesions
DNA
replication
stress
TP53 /
ATM /
MDM2
Escape from
apoptosis/
senescence
Cancers
Cancer progression
Figure 4
Oncogene-induced DNA replication stress model for cancer development. Mutations in genes that regulate cell growth are responsible
for two hallmarks of cancer: sustained proliferation and DNA replication stress. The latter hallmark induces genomic instability and
selects for escape from apoptosis/senescence, whereas sustained proliferation leads to short telomeres and, eventually, to the
establishment of the replicative immortality hallmark.
The acquisition of the escape from apoptosis/senescence hallmark may be linked to progression
of precancerous lesions to invasive cancers and to increased levels of genomic instability, as cells
with excessive DNA damage are no longer eliminated by TP53-dependent apoptosis or senescence
(63).
The sequence of events described here links some of the most pervasive hallmarks of cancer
(sustained cell proliferation, DNA replication stress, genomic instability, and escape from apoptosis/senescence) to the most common mutations present in cancer (targeting the genes regulating
cell growth and TP53; Figures 1 and 4). Of course, this model represents a simplified view of a
specific aspect of early cancer development. Dysfunctional telomeres also contribute significantly
to the genomic instability present in cancers and also provide selection pressure for inactivating
TP53 (Figure 4). Further, this model does not attempt to explain the acquisition of the other
hallmarks of cancer not shown in Figure 4. We hope that further work will eventually permit the
translation of our newly acquired knowledge into effective therapies.
DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that
might be perceived as affecting the objectivity of this review.
442
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ACKNOWLEDGMENTS
The authors thank J. Bartek and S.K. Sotiriou for comments on the manuscript. Research in the
laboratory of the authors is supported by grants from the Swiss National Science Foundation and
the European Commission.
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Contents
Annual Review of
Pathology:
Mechanisms of
Disease
Volume 10, 2015
The Roles of Cellular and Organismal Aging in the Development of
Late-Onset Maladies
Filipa Carvalhal Marques, Yuli Volovik, and Ehud Cohen ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 1
Driver and Passenger Mutations in Cancer
Julia R. Pon and Marco A. Marra ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !25
Leukocyte Chemoattractant Receptors in Human Disease
Pathogenesis
Brian A. Zabel, Alena Rott, and Eugene C. Butcher ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !51
Pathobiology of Transfusion Reactions
James C. Zimring and Steven L. Spitalnik ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !83
The Emerging Picture of Autism Spectrum Disorder:
Genetics and Pathology
Jason A. Chen, Olga Peñagarikano, T. Grant Belgard, Vivek Swarup,
and Daniel H. Geschwind ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 111
SWI/SNF Chromatin Remodeling and Human Malignancies
Julien Masliah-Planchon, Ivan Bièche, Jean-Marc Guinebretière,
Franck Bourdeaut, and Olivier Delattre ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 145
The Role of Endoplasmic Reticulum Stress in Human Pathology
Scott A. Oakes and Feroz R. Papa ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 173
Engineered In Vitro Disease Models
Kambez H. Benam, Stephanie Dauth, Bryan Hassell, Anna Herland, Abhishek Jain,
Kyung-Jin Jang, Katia Karalis, Hyun Jung Kim, Luke MacQueen,
Roza Mahmoodian, Samira Musah, Yu-suke Torisawa,
Andries D. van der Meer, Remi Villenave, Moran Yadid,
Kevin K. Parker, and Donald E. Ingber ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 195
A Clearer View of the Molecular Complexity of Clear Cell
Renal Cell Carcinoma
Ian J. Frew and Holger Moch ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 263
v
PM10-FrontMatter
ARI
4 December 2014
13:12
Emerging Concepts in Alzheimer’s Disease
Harry V. Vinters ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 291
AA Amyloidosis: Pathogenesis and Targeted Therapy
Gunilla T. Westermark, Marcus Fändrich, and Per Westermark ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 321
Hepatitis C Virus–Associated Cancer
Ming V. Lin, Lindsay Y. King, and Raymond T. Chung ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 345
Diseases of Pulmonary Surfactant Homeostasis
Jeffrey A. Whitsett, Susan E. Wert, and Timothy E. Weaver ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 371
Annu. Rev. Pathol. Mech. Dis. 2015.10:425-448. Downloaded from www.annualreviews.org
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The Inflammasomes and Autoinflammatory Syndromes
Lori Broderick, Dominic De Nardo, Bernardo S. Franklin, Hal M. Hoffman,
and Eicke Latz ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 395
DNA Replication Stress as a Hallmark of Cancer
Morgane Macheret and Thanos D. Halazonetis ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 425
Birth and Pathogenesis of Rogue Respiratory Viruses
David Safronetz, Heinz Feldmann, and Emmie de Wit ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 449
Protein Glycosylation in Cancer
Sean R. Stowell, Tongzhong Ju, and Richard D. Cummings ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 473
Pathobiology of Severe Asthma
Humberto E. Trejo Bittar, Samuel A. Yousem, and Sally E. Wenzel ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 511
Genetics and Epigenetics of Human Retinoblastoma
Claudia A. Benavente and Michael A. Dyer ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 547
Indexes
Cumulative Index of Contributing Authors, Volumes 1–10 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 563
Cumulative Index of Article Titles, Volumes 1–10 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 567
Errata
An online log of corrections to Annual Review of Pathology: Mechanisms of Disease articles
may be found at http://www.annualreviews.org/errata/pathol
vi
Contents
ANNUAL REVIEWS
It’s about time. Your time. It’s time well spent.
Now Available from Annual Reviews:
Annual Review of Virology
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Annu. Rev. Pathol. Mech. Dis. 2015.10:425-448. Downloaded from www.annualreviews.org
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Editor: Lynn W. Enquist, Princeton University
The Annual Review of Virology captures and communicates exciting advances in our understanding of viruses
of animals, plants, bacteria, archaea, fungi, and protozoa. Reviews highlight new ideas and directions in basic
virology, viral disease mechanisms, virus-host interactions, and cellular and immune responses to virus infection,
and reinforce the position of viruses as uniquely powerful probes of cellular function.
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TABLE OF CONTENTS:
• Inventing Viruses, William C. Summers
• Polydnaviruses: Nature’s Genetic Engineers, Michael R. Strand,
Gaelen R. Burke
• PHIRE and TWiV: Experiences in Bringing Virology to New Audiences,
Graham F. Hatfull, Vincent Racaniello
• Human Cytomegalovirus: Coordinating Cellular Stress, Signaling,
and Metabolic Pathways, Thomas Shenk, James C. Alwine
• Viruses and the Microbiota, *OYPZ[VWOLY49VIPUZVU1\SPL27MLPɈLY
• Vaccine Development as a Means to Control Dengue Virus
Pathogenesis: Do We Know Enough? Theodore C. Pierson,
Michael S. Diamond
• Forty Years with Emerging Viruses, C.J. Peters
• Role of the Vector in Arbovirus Transmission, Michael J. Conway,
Tonya M. Colpitts, Erol Fikrig
• Balance and Stealth: The Role of Noncoding RNAs in the Regulation
of Virus Gene Expression, Jennifer E. Cox, Christopher S. Sullivan
• Thinking Outside the Triangle: Replication Fidelity of the Largest RNA
Viruses, Everett Clinton Smith, Nicole R. Sexton, Mark R. Denison
• The Placenta as a Barrier to Viral Infections,
Elizabeth Delorme-Axford, Yoel Sadovsky, Carolyn B. Coyne
• Cytoplasmic RNA Granules and Viral Infection, Wei-Chih Tsai,
Richard E. Lloyd
• Archaeal Viruses: Diversity, Replication, and Structure, Nikki Dellas,
Jamie C. Snyder, Benjamin Bolduc, Mark J. Young
• AAV-Mediated Gene Therapy for Research and Therapeutic Purposes,
R. Jude Samulski, Nicholas Muzyczka
• Three-Dimensional Imaging of Viral Infections, Cristina Risco,
Isabel Fernández de Castro, Laura Sanz-Sánchez, Kedar Narayan,
Giovanna Grandinetti, Sriram Subramaniam
• Mechanisms of Virus Membrane Fusion Proteins, Margaret Kielian
• New Methods in Tissue Engineering: Improved Models for Viral
Infection, Vyas Ramanan, Margaret A. Scull, Timothy P. Sheahan,
Charles M. Rice, Sangeeta N. Bhatia
• Oncolytic Poxviruses, Winnie M. Chan, Grant McFadden
• Live Cell Imaging of Retroviral Entry, Amy E. Hulme, Thomas J. Hope
• Herpesvirus Genome Integration into Telomeric Repeats of Host
Cell Chromosomes, Nikolaus Osterrieder, Nina Wallaschek,
Benedikt B. Kaufer
• Parvoviruses: Small Does Not Mean Simple, Susan F. Cotmore,
Peter Tattersall
• Viral Manipulation of Plant Host Membranes, Jean-François Laliberté,
Huanquan Zheng
• IFITM-Family Proteins: The Cell’s First Line of Antiviral Defense,
Charles C. Bailey, Guocai Zhong, I-Chueh Huang, Michael Farzan
• Naked Viruses That Aren’t Always Naked: Quasi-Enveloped Agents
of Acute Hepatitis, Zongdi Feng, Asuka Hirai-Yuki, Kevin L. McKnight,
Stanley M. Lemon
• In Vitro Assembly of Retroviruses, Di L. Bush, Volker M. Vogt
• .S`JHU,UNHNLTLU[I`=PY\ZLZ!9LJLW[VY:^P[JOLZHUK:WLJPÄJP[`
Luisa J. Ströh, Thilo Stehle
• The Impact of Mass Spectrometry–Based Proteomics on Fundamental
Discoveries in Virology, Todd M. Greco, Benjamin A. Diner,
Ileana M. Cristea
• Remarkable Mechanisms in Microbes to Resist Phage Infections,
Ron L. Dy, Corinna Richter, George P.C. Salmond, Peter C. Fineran
• Viruses and the DNA Damage Response: Activation and Antagonism,
Micah A. Luftig
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