piR-4987 expression in breast
cancer tissue
Emmi Kärkkäinen
Master's thesis
University of Eastern Finland
School of Medicine
Biomedicine
October 2015
University of Eastern Finland
Abstract of Master's thesis
Faculty of Health Sciences
Author:
Emmi Kärkkäinen
Title of thesis:
piR-4987 expression in breast cancer tissue
Date:
21.10.2015
Department:
Department of Biomedicine
Supervisors:
Adjunct Professor Jaana Hartikainen, PhD, Associate Professor Arto
Mannermaa
Pages: 64
Abstract
Although multiple susceptibility genes have been identified for breast cancer, the majority of
breast cancer cases are diagnosed without detecting any known cause. Therefore it is essential
to study novel diagnostic and prognostic markers to improve earlier diagnosis and to enable
more accurate prognoses. PIWI-interacting RNAs (piRNAs) are a novel group of small noncoding RNAs that are crucial for the germline genome integrity due to their important role in
transposon control. piRNAs are able to specifically silence genes both transcriptionally and
post-transcriptionally after forming complexes with PIWI proteins. Recently the research of
piRNAs has spread into the field of cancer. The interest to study piRNAs in cancer rose from
the similarities, such as indefinite self-renewal, between germ cells and cancer cells. Multiple
piRNAs have been found to be aberrantly expressed in cancer and it has been proposed that
some of them might serve as diagnostic and prognostic markers. The mechanisms by which
piRNAs are involved in cancer development are still unknown and their roles in cancer need
to be further evaluated.
The aim of this master's thesis was to study the expression of piR-4987 in breast cancer tissue
and to see if the expression pattern is associated with the clinicopathological characteristics
of the breast tumors. Furthermore, we wanted to see if piR-4987 was expressed differently in
triple-negative and estrogen receptor-positive breast cancer cases. To study the expression
quantitative real-time PCR was performed from 95 breast cancer samples with specific piR4987 primers. The expression of piR-4987 was found to be associated with lymph node status
and the tumor stage. Higher expression of piR-4987 was seen in tumors with advanced stage
and tumors that had spread to multiple nearby lymph nodes.
Key words: piRNA, breast cancer, lymph node status
Itä-Suomen yliopisto
Pro gradun tiivistelmä
Terveystieteiden tiedekunta
Tekijä:
Emmi Kärkkäinen
Pro gradun otsikko:
piR-4987 ilmentyminen rintasyöpäkudoksessa
Päivämäärä:
21.10.2015
Laitos:
Biolääketiede
Ohjaajat:
Dosentti Jaana Hartikainen, FT, apulaisprofessori Arto Mannermaa
Sivut: 64
Tiivistelmä
Vaikka useita rintasyövälle altistavia geenejä on pystytty tunnistamaan, suurin osa
rintasyöpätapauksista diagnosoidaan ilman tiedettävää syytä. Sen takia on erityisen tärkeää
tutkia uusia tekijöitä, joiden avulla olisi mahdollista sekä aikaistaa diagnoosia että parantaa
taudin ennustettavuutta. Piwi-vuorovaikuttavat RNAt (piRNAt) kuuluvat pieniin eikoodaaviin
RNA:ihin,
jotka
kontrolloivat
transposonien
aktiivisuutta
ylläpitäen
sukusolulinjan genomin vakautta. piRNAt pystyvät hiljentämään kohteitaan spesifisesti joko
estämällä transkriptiota tai pilkkomalla lähettiRNA-juosteita muodostettuaan PIWIproteiinien kanssa komplekseja. Viime aikoina piRNA-tutkimus on laajentunut myös
syöpätutkimukseen. Mielenkiinto piRNA:iden tutkimiseen syövässä on herännyt sukusolujen
ja syöpäsolujen samankaltaisien ominaisuuksien, kuten loputtoman uusiutumiskyvyn,
johdosta. On havaittu, että moni piRNA on poikkeavasti ilmentynyt syövässä ja on esitetty,
että muutama näistä piRNA:ista voisi toimia myös ennustavana tekijänä. Jotta piRNA:iden
roolit syövässä saadaan selville, tarvitaan lisää tutkimuksia, jotka paljastavat mekanismit,
joilla piRNAt mahdollisesti vaikuttavat syövän syntyyn.
Tämän pro gradun tarkoituksena oli tutkia piR-4987 ilmentymistä rintasyöpäkudosnäytteissä
ja selvittää onko ilmentyminen yhteydessä kasvainten kliinispatologisiin ominaisuuksiin.
Lisäksi
halusimme
selvittää
estrogeenireseptori-positiivisten
onko
ilmentymisessä
rintasyöpätapausten
eroja
välillä.
kolmoisnegatiivisten
Ilmentymistä
ja
tutkittiin
kvantitatiivisen reaaliaikaisen PCR:n avulla 95 rintasyöpänäytteestä. Tutkimuksessa
havaittiin että piR-4987 ilmentyminen on yhteydessä imusolmukelevinneisyyteen ja syövän
levinneisyysasteeseen. Korkeampi piR-4987 ilmentymistaso oli havaittavissa kasvaimissa,
joiden levinneisyysaste oli korkeampi ja jotka olivat levinneet useampaan lähellä olevaan
imusolmukkeeseen.
Avainsanat: piRNA, rintasyöpä, imusolmukestatus
Acknowledgements
This master’s thesis work was carried out at the Department of Biomedicine at the Clinical
Pathology and Forensic Medicine unit, University of Eastern Finland, Kuopio, during the
time 2014-2015.
I am very grateful that I was provided with the opportunity to study this thesis topic. I express
my warm thanks to both my supervisors PhD, Adjunct Professor Jaana Hartikainen, and PhD,
Associate Professor Arto Mannermaa for their professional expertise and guidance. I am
thankful for their great interest in this project and all the help and support I have had
throughout it.
I would like to thank all the people who have contributed to this study including the whole
research group of Professor Veli-Matti Kosma at Clinical Pathology and Forensic Medicine. I
am thankful to Helena Kemiläinen and Eija Myöhänen for the technical assistance.
In addition, I would like to thank my fellow students who have supported and motivated me
throughout this process. I have gotten so much essential support also outside the scientific
community and for that I am thankful to all my friends who have been there cheering me up
and encouraging me. My warmest thanks go to my loving family who have always believed
in me and supported me no matter what. I am forever grateful to have you all in my life.
Abbreviations
AGO
Argonaute
ATM
ATM serine/threonine kinase gene
BRCA1/2
Breast cancer gene 1/2 gene
BRIP1
BRCA1 interacting protein C-terminal helicase 1 gene
CCR4
C-C chemokine receptor type 4 gene
CDH1
Cadherin 1, type 1 gene
cDNA
Complementary DNA
CHEK2
Checkpoint kinase 2 gene
CTAs
Cancer/testis antigens
Creb
cAMP-response element-binding protein 2 gene
DCIS
Ductal carcinoma in situ
ER
Estrogen receptor
ERBB2
Erb-B2 Receptor Tyrosine Kinase 2 gene
ERVs
Endogenous retroviruses
HER2
Human epidermal growth factor type 2 gene
HP1
Heterochromatin protein 1
Hsp90
Heat shock protein 90
H3K9me
Histone 3 lysine 9 methylation
LCIS
Lobular carcinoma in situ
LINE1
Long interspersed nuclear element 1
lncRNA
Long non-coding RNA
LTRs
Long terminal repeats
miRNAs
microRNAs
MRI
Magnetic resonance imaging
ncRNAs
Non-coding RNAs
PALB2
Partner and localizer of BRCA2 gene
PARP
Poly adenosine diphosphate-ribose polymerase
PAZ
Piwi Argonaute Zwille
piRNAs
Piwi-interacting RNAs
PIWI
P-element induced wimpy testis
PR
Progesterone receptor
PTEN
Phosphatase and tensin homolog gene
qPCR
Quantitative real-time polymerase chain reaction
Rasgrf1
RAS protein-specific guanine nucleotide-releasing factor 1 gene
RdRP
RNA-dependent RNA polymerase
RNAi
RNA interference
RT
Reverse transcription
Shut
Shutdown
siRNAs
Short interfering RNAs
SNP
Single nucleotide polymorphism
STK11
Serine/threonine kinase 11 gene
TNM
Tumor-node-metastasis
TP53
Tumor protein p53 gene
UTR
Untranslated region
Zuc
Zucchini
Table of contents
Abstract ..................................................................................................................................
Tiivistelmä ..............................................................................................................................
Acknowledgements .................................................................................................................
Abbreviations ..........................................................................................................................
1. Introduction....................................................................................................................... 1
1.1 Breast cancer ............................................................................................................... 1
1.1.1 Incidence and mortality......................................................................................... 1
1.1.2 Risk factors........................................................................................................... 1
1.1.2.1 Genetic risk .................................................................................................... 1
1.1.3 Diagnosis and subtypes ......................................................................................... 2
1.1.4 Treatment ............................................................................................................. 3
1.1.4.1 Treatment for triple-negative breast cancer ..................................................... 4
1.1.5 Prognostics ........................................................................................................... 4
1.2 Non-coding RNAs (ncRNAs) ...................................................................................... 5
1.2.1 The Argonaute protein family ............................................................................... 5
1.2.1.1 The PIWI subfamily ....................................................................................... 6
1.2.1.1.1 The function of PIWI proteins ................................................................. 7
1.2.2 PIWI-interacting RNAs (piRNAs) ........................................................................ 7
1.2.2.1 21U-RNAs ..................................................................................................... 9
1.2.2.2 piRNA clusters............................................................................................... 9
1.2.3 The biogenesis of piRNAs .................................................................................. 10
1.2.3.1 Localization and the generation of the 5’ terminus ....................................... 11
1.2.3.2 The formation of PIWI-piRNA complexes and trimming ............................. 12
1.2.3.3 The ping pong amplification cycle ............................................................... 13
1.2.4 The functions of piRNAs .................................................................................... 14
1.2.4.1 Post-transcriptional silencing ....................................................................... 14
1.2.4.2 Transcriptional silencing .............................................................................. 14
1.2.4.3 Canalization ................................................................................................. 16
1.2.4.4 Somatic functions......................................................................................... 17
1.3 The roles of PIWI proteins and piRNAs in cancer...................................................... 17
1.3.1 PIWI proteins in cancer ...................................................................................... 17
1.3.2 piRNAs in cancer................................................................................................ 19
1.3.3 The mechanisms of PIWI proteins and piRNAs in cancer development .............. 20
1.3.4 Potential as diagnostic and prognostic markers ................................................... 21
2. The aim of this study ....................................................................................................... 22
3. Materials and methods..................................................................................................... 22
3.1 Samples ..................................................................................................................... 22
3.2 piR-4987 sequence .................................................................................................... 24
3.3 Quantitative real-time PCR ........................................................................................ 24
3.4 Statistical analyses ..................................................................................................... 26
4. Results ............................................................................................................................ 27
4.1 piR-4987 expression levels in breast cancer tissue ..................................................... 27
4.2 Association of piR-4987 expression level with clinical parameters ............................ 29
4.3 Survival analyses ....................................................................................................... 38
5. Discussion ....................................................................................................................... 43
6. References....................................................................................................................... 45
1. Introduction
1.1 Breast cancer
1.1.1 Incidence and mortality
Breast cancer is the most common cancer among women with nearly 1.7 million new cases
diagnosed worldwide in 2012, including the 4477 new cases diagnosed in Finland (Ferlay et.
al 2012; Finnish Cancer Registry). It is the leading cause of cancer death in female population
in less developed countries and the second cause of cancer death in developed countries,
accounting for 14.7% (521,907) of women's overall cancer mortality in the world (Ferlay et.
al 2012). In Finland the breast cancer mortality accounted for 15.2% (877) of the overall
cancer mortality in 2012 (Finnish Cancer Registry). In addition, slightly more breast cancer
cases were diagnosed in less developed countries (883,000) compared to more developed
countries (794,000) (Ferlay et. al 2012).
1.1.2 Risk factors
In Finland the lifetime risk for breast cancer is 1.12, which means that 12% of women will
develop breast cancer by the time they turn 90 (Finnish Cancer Registry, based on the
incidence in 2005-2009). The risk is increased with higher age and is affected also by alcohol
consumption and lifetime exposure to estrogen. For example, early age at menarche, use of
post-menopausal hormone therapy, giving birth the first time at later age, and not giving birth
at all, which all are surrogates for life-time estrogen exposure, are known to increase the risk
of breast cancer. (Joensuu et al., 2013). In addition, about 30% of breast cancers are known to
be caused by mutations in identified risk genes (Shiovitz and Korde, 2015). If one of a
woman’s first-degree family members has been diagnosed with breast cancer, the risk of
developing breast cancer herself is doubled compared to women with no hereditary risks. The
risk is even higher if the first-degree family member is male or multiple members of the
family have been diagnosed with the disease. (McPherson et. al 2000).
1.1.2.1 Genetic risk
Breast cancer is a complex disease which develops due to genetic and epigenetic alterations
leading to aberrant gene expression. The initiation and development of cancer involve the
silencing of tumor suppressor genes and the activation of oncogenes by mutations and
1
epigenetic alterations including DNA methylation, histone modifications, and chromatin
remodeling. The functions of tumor suppressor genes vary from the regulation of cell growth,
proliferation and differentiation to the repair of DNA and induction of apoptosis. In contrast,
oncogenes function in the opposite way stimulating cell growth and differentiation and
preventing apoptosis. The changes in the gene expression of tumor suppressor genes and
oncogenes during carcinogenesis lead to tumor growth and the development of metastasis.
(Lo and Sukumar, 2008).
The risk of developing breast cancer is associated with different genetic variants that can be
classified as high-, moderate- or low-risk variants; for example, a patient with the deleterious
allele of a widely studied tumor suppressor gene BRCA1 has a 10-30 fold increased risk of
getting breast cancer. Breast cancer caused by the mutated high-risk genes including breast
cancer gene 1 (BRCA1), breast cancer gene 2 (BRCA2), phosphatase and tensin homolog
(PTEN), tumor protein p53 (TP53), cadherin 1, type 1 (CDH1), and serine/threonine kinase
11 (STK11) account for about one quarter of all inherited breast cancer cases and these
mutations increase the lifetime risk up to 80%. Mutations in multiple genes, such as
checkpoint kinase 2 (CHEK2), ATM serine/threonine kinase (ATM), partner and localizer of
BRCA2 (PALB2), and BRCA1 interacting protein C-terminal helicase 1 (BRIP1), have been
determined to moderately increase breast cancer risk doubling the risk. The moderate-risk
genes are responsible for only a few percentages of breast cancer cases. In addition more
frequently found low-risk variants have been identified to affect breast cancer development in
combination with each other when multiple low-risk single nucleotide polymorphisms
(SNPs) are detected. (Shiovitz and Korde, 2015). The number of known low-risk SNPs
detected can be used to evaluate the patients’ risk of developing breast cancer since the risk
has been found to increase as the number of these SNPs increases (Mavaddat et al., 2015).
Although to date over 90 SNP loci have been discovered to be connected with breast cancer
susceptibility (Michailidou et al., 2015), the mechanisms causing breast cancer have yet to be
entirely determined due to the fact that about 70% of breast cancers are diagnosed as sporadic
without any identified gene mutation (Shiovitz and Korde, 2015).
1.1.3 Diagnosis and subtypes
When diagnosing breast cancer firstly a clinical breast exam is performed to find out any
abnormalities in the breast tissue or lymph nodes. To further investigate the probability of
breast cancer multiple different imaging methods, such as mammogram (an X-ray of the
2
breast), ultrasound exam and MRI (magnetic resonance imaging) are generally used. If an
abnormal mass is found, a biopsy is taken to study the malignancy of the cells. There are
different types of biopsy procedures available including fine needle aspiration biopsy, core
needle biopsy, and surgical biopsy. To evaluate the progression of the diagnosed breast
cancer the quantity of estrogen-, progesterone- and human epidermal growth factor type 2
(HER2, also known as Erb-B2 Receptor Tyrosine Kinase 2; ERBB2) receptors in the tumor
are tested. Moreover, the tumor is staged to determine the tumor-node-metastasis (TNM)
status, which includes the determination of tumor size (T), the occurrence of cancerous tissue
in the lymph nodes (N) and metastases (M). The earlier the diagnosis is made the better the
prognosis usually is, therefore it is important to study new potential diagnostic markers.
(Joensuu et al., 2013).
Breast cancer can be classified into various subtypes by functional, histological, and
molecular features. Breast tumors can be divided into two groups; in situ carcinoma and
invasive carcinoma. Invasive carcinoma means that the cancer has spread to the surrounding
tissues while in the in situ carcinoma the abnormal cells with cancerous features are detected
only in the place of origin. In situ carcinoma can be further classified based on histological
appearance into ductal or lobular subtype. Ductal and lobular breast cancers are developed
due to the abnormalities in the lining of the milk ducts and in the lobules (milk glands) of the
breast, respectively. Ductal carcinoma in situ (DCIS) is more frequently diagnosed than
lobular carcinoma in situ (LCIS) and include comedo, papillary, micropapillary, solid, and
cribiform subtypes. The major types of invasive breast tumors include infiltrating ductal,
invasive lobular, ductal/lobular, tubular, medullary, mucinous, and papillary subtypes, from
which infiltrating ductal carcinoma accounts for the majority of invasive tumors. The
molecular subtypes of breast cancer are determined by the expression levels of estrogen
receptors (ER), progesterone receptors (PR), and HER2 receptors. Basal-like, also known as
triple-negative (ER-, PR-, HER2-), HER2-enriched (HER2+), luminal A (ER+ and/or PR+,
HER2-), luminal B (ER- and/or PR-, HER2+), claudin low (ER-, claudin-), and normal
breast-like (with the gene signature of adipose tissue) are molecular subtypes of breast
tumors. (Malhotra et al., 2010).
1.1.4 Treatment
The currently used treatments for breast cancer include surgery, chemotherapy, radiation
therapy, hormonal therapy, and targeted therapies. Chemotherapy is a widely used cancer
3
treatment that is based on chemical agents that destroy rapidly dividing cells, thus affecting
also variety of normal cells in addition to the targeted cancer cells. The destruction of
normally rapidly dividing cells causes unpleasant side-effects, which is why it is necessary to
develop alternative treatments. The hormone therapy is not effective in patients with negative
hormone receptor status, but it is used as an adjuvant treatment for patients who express ER
and PR. For example, tamoxifen is a frequently used anti-estrogen drug that blocks the ERs,
thus inhibiting the binding of estrogen. In addition, the production of estrogen can be affected
with aromatase inhibitors which are effectively used treating post-menopausal patients. A
monoclonal antibody trastuzumab (Herceptin), which identifies and interferes with HER2
receptors, can be used as a targeted treatment for patients with HER2 gene amplification or
overexpression. Some of the treatments for breast cancer can cause rare but serious side
effects such as increased risk of cancers in uterus (tamoxifen) and cardiomyopathy
(trastuzumab). (Joensuu et al., 2013).
1.1.4.1 Treatment for triple-negative breast cancer
Even though there are a variety of treatments available for breast cancer, there still are
multiple subtypes that lack an effective treatment and in these cases the prognosis is usually
poor. HER2-enriched breast cancer is the second most aggressive subtype, and even though
trastuzumab can be used to treat some patients, some have been shown to develop resistance
to the drug (Lavaud and Andre, 2014). The poorest prognosis is usually associated with
triple-negative breast cancer in which the tumor growth is independent of hormone receptors,
hence the tumor does not respond to the hormonal therapy or the drugs targeting HER2.
Chemotherapy still being the most effective treatment for triple-negative breast cancer, the
ongoing research for new targeted treatments is extensive. For example, some promising
results have been obtained from clinical trials using angiogenesis-targeting drugs and poly
adenosine diphosphate-ribose polymerase (PARP) inhibitors. However, none of the novel
targeted drugs have been approved for clinical use and a wider understanding of the
molecular features of triple-negative tumors is required before an optimized treatment can be
developed. (Tomao et al., 2015).
1.1.5 Prognostics
The prognosis of breast cancer is dependent on multiple factors. The histological
classification, the definition of the molecular features of the tumor, and tumor staging are
4
important for the prediction of recurrence and progression of the disease. In addition, the
classification enables the choice of the right treatment. By defining the genetic and epigenetic
patterns of the tumor it is possible to diagnose the disease earlier, make more accurate
prognoses, and develop new targeted therapies. (Malhotra et al., 2010).
1.2 Non-coding RNAs (ncRNAs)
The protein-coding part of the genome, accounting for less than 2% of the genome, has been
extensively studied, whereas the non-coding DNA was first referred as "junk DNA" without
contribution to biological processes (Alexander et al., 2010). Due to the development of
advanced technologies such as RNA sequencing the biological functions of non-coding
RNAs (ncRNAs) were brought to light leading to the broad research of their biological
importance. ncRNAs can be divided into two major groups according to their transcript size;
small ncRNAs and long ncRNAs (lncRNAs). Small ncRNAs are transcripts less than 200 bp
and they can be grouped into different classes based on their origins, including microRNAs
(miRNAs), short interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs). (Mercer
et al., 2009; Mattick and Makunin, 2006). They have been shown to regulate vital processes
for cell growth and development via transcriptional and post-transcriptional gene silencing
(Carmell et al., 2002). Among these small ncRNAs piRNAs have been the least studied in
general and in association with diseases.
1.2.1 The Argonaute protein family
The proteins of the Argonaute family are about 100 kD in size and have important roles in the
development. Some of them are also needed for the determination whether stem cells
continue self-renewing or begin to differentiate. In addition, the proteins have been shown to
interact with small ncRNAs having important roles in the RNA interference (RNAi).
(Carmell et al., 2002). They are known to bind small RNA molecules which are required for
the recognition of their target sequences through base-pairing (Matranga et al., 2005; Miyoshi
et al., 2005; Rand et al., 2005). The animal Argonaute protein family consists of P-element
induced wimpy testis (PIWI) and ARGONAUTE (AGO) subfamilies, all of the protein
members being constructed of four domains; N-terminal, Mid, Piwi Argonaute Zwille (PAZ),
and PIWI. The PAZ and PIWI domains are the most important for RNAi as they are
responsible for the binding of RNA and the cleavage of RNA, respectively. (Hutvagner and
Simard, 2008; Song et al., 2003; Ma et al., 2005). The ubiquitous miRNAs and siRNAs are
5
known to interact with the proteins of AGO subfamily while the mostly germline specific
piRNAs associate with the PIWI subfamily of Argonautes (Carmell et al., 2002).
1.2.1.1 The PIWI subfamily
Similarly to miRNAs/siRNAs and piRNAs, the proteins of the AGO subfamily are expressed
in a variety of tissues whereas the PIWI subfamily proteins are somewhat specifically
expressed in the germ cells (Carmell et al., 2002). The PIWI protein subfamily is conserved
across species and the human (Homo sapiens) members include PIWIL1/HIWI,
PIWIL2/HILI, PIWIL3/HIWI3, and PIWIL4/HIWI2 proteins (Sasaki et al., 2003). Mouse
(Mus musculus) and fruit fly (Drosophila melanogaster) have three PIWI proteins: Mili,
Miwi, and Miwi2 and piwi, aubergine (aub) and ARGONAUTE 3 (AGO3), respectively
(Table 1) (Hutvagner and Simard, 2008; Kuramochi-Miyagawa et al., 2001; Carmell et al.,
2007). The fruit fly PIWI proteins are expressed differently in the cells, piwi being expressed
primarily in the nuclei of the germ cells and somatic ovary cells, whereas aub is mostly
localized in the cytoplasm of the germ cells (Cox et al., 2000; Harris and Macdonald, 2001;
Brennecke et al., 2007). Like aub, AGO3 is also expressed in the cytoplasm of germ cells, but
it has been shown to localize in the somatic cap cells of the germarium as well. Both aub and
AGO3 have been shown to be strongly expressed in an electron-dense cytoplasmically
localised perinuclear structure called nuage, which is essential in the generation of piRNAs.
(Brennecke et al., 2007). In human, similarly to fruit fly, the highest expression levels of all
the four human PIWI proteins are found in the germline (Sasaki et al., 2003).
Table 1. The PIWI-proteins expressed in fruit fly, mouse and human.
Organism
PIWI proteins
Fruit fly
piwi
aubergine
ARGONAUTE 3
Mouse
Mili
Miwi
Miwi2
Human
PIWIL1/HIWI
PIWIL2/HILI
PIWIL3/HIWI3
PIWIL4/HIWI2
6
1.2.1.1.1 The function of PIWI proteins
The mutated forms of the genes coding PIWI proteins have been widely studied to gain
insight into their biological relevance. The piwi gene is essential for the asymmetric division
of the germline stem cells and for the development of gametes in fruit fly; mutated piwi is
known to cause sterility in both females and males (Cox et al., 2000; Cox et al., 1998; Lin
and Spradling, 1997). Mutations in the fruit fly piwi, aub and AGO3 genes conclude in the
increased activity of transposable elements in the germline, which is a potential cause for the
abnormal generation of gametes (Vagin et al., 2004; Kalmykova et al., 2005; Li et al., 2009).
Corresponding defects in fertility have been suggested also in other species including humans
(Cox et al., 1998; Qiao et al., 2002; Houwing et al., 2007; Das et al., 2008). Deficiencies in
the mouse homologues Mili and Miwi2 are known to enhance the expression of
retrotransposons, such as long interspersed nuclear element 1 (LINE-1), and disturb the germ
cell development resulting in the sterility in males, but not in females (Carmell et al., 2007;
Aravin et al., 2007; Kuramochi-Miyagawa et al., 2008). All of the PIWI proteins expressed in
fruit flies and Mili and Miwi2 in mice are known to interact with piRNAs. In normal
conditions the human homologue for piwi, HIWI protein, is found to be expressed only in the
germline having roles in the generation of germ cells (Qiao et al., 2002). Even though the
HILI and HIWI2 protein levels are also the highest in the germline, lower levels of
expression are observed in multiple somatic tissues as well. HIWI2 has been proposed to be
involved in gene regulation via post-transcriptional mechanisms. (Keam et al., 2014).
Furthermore, aberrant expression of HIWI2 and HIWI3 has been demonstrated to be risk
factors for male infertility having effects on the production of gametes (Gu et al., 2010).
1.2.2 PIWI-interacting RNAs (piRNAs)
piRNAs were first discovered in mouse germline cells by four independent studies in 2006
(Grivna et al., 2006; Girard et al., 2006; Watanabe et al., 2006; Aravin et al., 2006). The
small ncRNAs of this novel class can easily pass through the cell membrane and are more
stable than miRNAs and siRNAs due to their length of 26-32 nucleotides. They are named
after their association with PIWI proteins with which they form complexes that regulate the
activity of transposable elements, modify chromatin state, and maintain germ cell genome
integrity. Contrary to miRNAs and siRNAs, which are always antisense in relation to their
target sequences, piRNAs can be either sense or antisense. (Grivna et al., 2006; Girard et al.,
2006; Watanabe et al., 2006; Aravin et al., 2006; Vagin et al., 2006). The PIWI proteins
7
preferably bind to either antisense or sense transcripts in relation to the piRNA targets; piwi
and aub form complexes mainly with 5’ uridine containing piRNAs mapping antisense to
their targets while AGO3 prefer piRNAs mapping sense to their targets (Brennecke et al.,
2007; Gunawardane et al., 2007). These small ncRNAs lack specific structural motifs which
has made it harder to identify all of the RNA molecules belonging to the piRNA group.
However, most of them can be characterized by the 5’ uridine bias and the 2’-O-methyl
modified nucleotide at the 3’ end of their transcript (Figure 1). (Grivna et al., 2006;
Watanabe et al., 2006; Aravin et al., 2006; Horwich et al., 2007; Kirino and Mourelatos,
2007). The 2’-O- methylation has been proposed to function as a protective structure
preventing the degradation of piRNAs (Houwing et al., 2007; Faehnle and Joshua-Tor, 2007).
Also the majority of the human germline piRNAs have been shown to possess the
characteristics of piRNAs (Ha et al., 2014). piRNAs are expressed most abundantly in the
germline, but a smaller population has also been found to be expressed in the soma
(Brennecke et al., 2007; Aravin et al., 2003; Lau et al., 2006).
Figure 1. The proposed structure of piRNAs. piRNAs are characterized by a monophosphate in the 5'
terminus and a 2'-O methyl group at the 3' terminus.
The mouse piRNAs can be divided into two different groups based on the stage of meiosis;
pre-pachytene and pachytene piRNAs, which interact with Mili/Miwi2, and Mili/Miwi
proteins, respectively. Pachytene is one of the stages of meiosis during which the crossingover and the genetic exchange of the chromosomes takes place and at this stage there is a
huge amount of piRNAs present in the germline. The pre-pachytene piRNAs are
predominantly of transposon origin whereas pachytene piRNAs are transcribed from the
multiple piRNA clusters. (Kuramochi-Miyagawa et al., 2008; Girard et al., 2006; Lau et al.,
2006; Aravin et al., 2008; Gan et al., 2011).
8
1.2.2.1 21U-RNAs
The piRNAs of roundworms (Caenorhabditis elegans) consist of a specific pool of 21
nucleotides long molecules called 21U-RNAs, which have been found to be derived from
large non-coding regions located in the chromosome IV (Das et al., 2008; Ruby et al., 2006;
Batista et al., 2008). Although the length of these RNAs differs from that of piRNAs of other
animals, the piRNA characteristics including the 5’ uridine bias, a monophosphate at the 5’
terminus, and a 2 -O-methyl group at the 3’ terminus are also present in 21U-RNAs (Ruby et
al., 2006). The 21U-RNA regions contain an upstream motif which is needed for the
biogenesis of 21U RNAs functioning as a promoter for their transcription (Ruby et al., 2006;
Cecere et al., 2012). Although the 21U-RNAs have been shown to function as transposon
silencers, the mechanism which is used differs from that of fruit fly and mouse piRNAs. The
transposon regulation by 21U-RNAs does not require the PIWI endonuclease activity but the
targets are repressed by activating the generation of endogenous siRNAs with the
contribution of the RNA-dependent RNA polymerase (RdRP). (Das et al., 2008; Batista et al.,
2008; Bagijn et al., 2012).
1.2.2.2 piRNA clusters
With the use of advanced techniques such as deep RNA sequencing the majority of
mammalian and fruit fly piRNAs have been mapped to clusters throughout the genome
mainly consisting of unannotated and heterochromatin regions containing also transposable
elements and their remnants (Brennecke et al., 2007; Girard et al., 2006; Aravin et al., 2006).
In addition, some piRNAs are generated from the 3' untranslated regions (UTRs) of protein
coding genes and minority of the clusters are found to be located in euchromatin regions
(Brennecke et al., 2007; Robine et al., 2009). While most of the fruit fly piRNA clusters
function specifically in the germline, some clusters such as the flamenco cluster, which was
initially found to participate in the regulation of the gypsy retrotransposon, are found to be
expressed in the somatic cells nearby the germ cells (Brennecke et al., 2007; Pelisson et al.,
1994; Prud'homme et al., 1995; Malone et al., 2009). The piRNA clusters can be divided into
two types of clusters according to their ability to generate piRNAs from either both strands or
from a single strand. Both strands are used as templates for piRNAs in most of the clusters,
but for example the flamenco cluster produces piRNAs from a single strand (Brennecke et al.,
2007; Houwing et al., 2007; Girard et al., 2006). The invasion of novel transposons into the
genome results in the adaptation of piRNAs through the production of novel piRNAs
9
targeting these newly introduced transposons, as it has been suggested that the novel
transposons are attracted by the piRNA clusters (Brennecke et al., 2007). Until recently the
research of piRNAs has been highly focused on the model organisms and not much is known
about the functions of human piRNAs. It has been shown, however, that the piRNAs in
human adult testicular germ cells are derived from multiple loci including regions containing
transposable elements, lncRNA genes, and protein coding genes. Human piRNAs are more
frequently derived from the 3’ UTRs of protein coding genes compared to mouse piRNAs,
and the same genes have been found to generate piRNAs in both of these species. In addition,
the majority of human piRNAs are mapped to clusters varying in size (1-276kb). (Ha et al.,
2014).
1.2.3 The biogenesis of piRNAs
piRNAs are suggested to be produced from single-stranded RNA precursors without the need
of the Dicer endoribonuclease, in contrast to miRNAs and siRNAs which are generated from
double-stranded RNA molecules in a Dicer-dependent way (Brennecke et al., 2007; Houwing
et al., 2007; Vagin et al., 2006; Lee et al., 2004; Hoa et al., 2003; Saito et al., 2005). The
production of piRNAs occurs through two distinct biogenesis pathways; primary processing
(primary pathway) and the ping pong amplification cycle (secondary pathway) (Figure 2). In
addition to the primary processing the ping pong amplification cycle has been suggested to be
active to some extent also in the human germline (Ha et al., 2014). Since the fruit fly AGO3
and aub are expressed specifically in the germline secondary piRNAs are not produced in
gonadal somatic cells. In turn, the primary processing pathway is known to function both in
germline and female gonad somatic cells where the primary piRNA-producing complexes are
formed between the piRNAs and piwi proteins. (Saito et al., 2009). In fruit fly the primary
piRNAs are thought to be formed from long single-stranded precursors from the transposonrich piRNA clusters (Figure 2A) (Brennecke et al., 2007; Girard et al., 2006). The piRNAs
that are transcribed from the 3’ UTRs of protein coding genes are produced by the piwidependent primary pathway without entering the ping pong amplification cycle (Brennecke et
al., 2007; Robine et al., 2009). The generation mechanisms of piRNAs have been studied
most precisely in fruit flies so in the next chapters the biogenesis of piRNAs is described
concentrating on fruit flies.
10
Figure 2. The primary and secondary biogenesis of piRNAs in fruit fly. A. Majority of piRNAs are
generated from piRNA clusters consisting of long double-stranded RNA and from regions containing
transposons and protein coding genes. B. The piRNA transcripts are guided into the nuage. C. The
primary pathway begins with the cleavage of the precursor transcript by an enzyme with endonuclease
activity; possibly Zucchini (Zuc). D. Chaperone proteins Shutdown (Shu) and Hsp83 are thought to be
involved in the next step of forming the piwi/aubergine (aub)-piRNA complexes. E. The piRNA
precursor transcript is trimmed at the 3' terminus by an unknown enzyme with exonuclease activity.
The methyltransferase Hen1 is responsible for the 3' terminus 2-O-methylation which is the last step
of primary pathway. F-I. aub-piRNA complexes are able to go through the secondary pathway.
Modified from Luteijn and Ketting, 2013.
1.2.3.1 Localization and the generation of the 5’ terminus
Multiple factors have been suggested to have roles in the guidance of the piRNA transcripts
to the part of the cell where the biogenesis takes place (Figure 2B). These factors include a
heterochromatin protein 1 (HP1) subfamily member Rhino, a nuclear DEAD box helicase
UAP56 and a nuage-expressed protein Vasa. (Klattenhoff et al., 2009; Keller et al., 2012).
Due to the evidence that the nuclear UAP56 colocalizes with Rhino, and Vasa is localized at
the same site but on the other side of the nuclear membrane, it has been thought that the
11
UAP56 and Rhino participate in the transportation of the transcripts through the nuclear pores
into the cytoplasmic nuage, where Vasa is able to bind them (Zhang et al., 2012).
To become maturated the primary piRNAs are processed in the electron-dense perinuclear
nuage, where aub and AGO3 are known to be highly expressed (Brennecke et al., 2007; Lim
and Kai, 2007). A variety of piRNAs that target multiple different transposons are produced
through primary processing which includes the generation of the 5' terminus, the formation of
the PIWI-piRNA complexes, and the modification of the 3' terminus (Figure 2C-E). The 5’
terminus generation is conducted in distinct ways in the primary and secondary biogenesis
pathways. During the ping pong amplification cycle the 5’ terminus is created by the PIWI
proteins themselves via cleavage of the primary piRNA transcripts (Figure 2F/I). (Brennecke
et al., 2007; Gunawardane et al., 2007). Although the mechanism by which the 5’ terminus is
generated in the primary pathway is still unclear, it is known that the precursor strands are
cleaved at uridine residues in preference to other residues creating the characteristic uridine
bias at the 5' end of the anti-sense primary piRNAs (Girard et al., 2006; Aravin et al., 2006;
Lau et al., 2006; Lau et al., 2006). Multiple studies have defined the relevance of a protein
called Zucchini (Zuc) in the piRNA biogenesis and it is expected to be responsible for the
creation of the 5’ terminus during primary pathway (Figure 2C) (Pane et al., 2007;
Nishimasu et al., 2012). The defined crystal structures of fruit fly Zuc and its mouse
homologue MitoPLD imply that in addition to the ability to cleave single-stranded nucleic
acids they show phospholipase activity, which suggests that they might be involved in the
piRNA biogenesis also by producing phosphatidic acid in the outer mitochondrial membrane,
thus having an impact on the recruitment or activation of the nuage components (Huang et
al., 2011; Watanabe et al., 2011). Even though Zuc and the mouse homologue MitoPLD have
been shown to be important for the piRNA processing their exact function remains to be
solved (Pane et al., 2007; Watanabe et al., 2011; Olivieri et al., 2010).
1.2.3.2 The formation of PIWI-piRNA complexes and trimming
After the 5’ terminus generation the piRNA transcripts form complexes with PIWI proteins
(Figure 2D). The fruit fly aub and piwi proteins favor the binding of 5’ terminus uridine base
of piRNA precursors whereas AGO3 binds preferably to adenine at position 10 (Brennecke et
al., 2007; Gunawardane et al., 2007). The mechanism of forming these PIWI-piRNA
complexes is thought to involve the help of chaperone proteins, especially the heat shock
protein Hsp90 and its homologues (Figure 2D), similarly to the miRNA- and siRNA-AGO
12
protein complexes (Johnston et al., 2010; Iwasaki et al., 2010). The fruit fly Hsp90-associated
chaperone Shutdown (Shu) has been found to be crucial for the formation of the PIWIpiRNA complexes in both primary and secondary pathways (Olivieri et al., 2012).
Furthermore, also the mouse homologue FKBP6 has been implicated to the secondary
biogenesis of piRNAs (Xiol et al., 2012). Following the formation of PIWI-piRNA
complexes the 3’ terminus of the molecule is trimmed by an unknown enzyme with
exonuclease activity (Figure 2E). The enzyme is known to be a magnesium-dependent 3’-5’
exonuclease which is thought to function by trimming the 3’ terminus nucleotide tail outside
the complex. (Kawaoka et al., 2011). The trimming process is tightly associated with the 3'
end ribose 2’O methylation catalyzed by the methyltransferase Hen1, which finalizes the
primary processing (Figure 2E) (Saito et al., 2007; Kamminga et al., 2010). The piwi/aubpiRNA complexes are then able to recognize the complementary targets followed by the
endonucleolytic cleavage or chromosome remodeling of the target sequences (Brennecke et
al., 2007).
1.2.3.3 The ping pong amplification cycle
After the primary processing, piRNAs bound to aub are able to enter the ping pong
amplification cycle in the germline (Figure 2F). The ping pong cycle amplifies the piRNAs
suppressing the actively expressing transposons and also enables the adaptation to new
transposable elements in piRNA clusters. It has been discovered that a group of
complementary antisense and sense piRNAs are overlapped by 10 nucleotides which
indicates that the transposon transcript is cleaved at a site 10 nucleotides apart from the 5' end
of the primary piRNA. The mRNA cleavage by aub generates a transcript containing
adenosine at the 10th position which then forms a complex with AGO3 (Figure 2G). This is
followed with the modification of the 3' end leading to the creation of a secondary sense
piRNA (Figure 2H). The resulting sense piRNA can then recognize antisense transcripts
leading to the formation of more antisense piRNAs which can be further loaded into aub
(Figure 2I). The PIWI-piRNA complex formation and trimming are similar in both primary
and secondary pathway. (Brennecke et al., 2007; Gunawardane et al., 2007). A DEAD box
protein-encoding Spindle-E and a nuage-expressed Maelstrom protein are needed for the
generation of secondary piRNAs in the germline (Malone et al., 2009; Lim and Kai, 2007).
13
1.2.4 The functions of piRNAs
The PIWI proteins have been found to locate either in the cytoplasm or in the nucleus which
led to the discovery that the PIWI-piRNA complexes are able to repress their targets through
both transcriptional and post-transcriptional mechanisms (Brennecke et al., 2007; Grivna et
al., 2006; Aravin et al., 2008; Brower-Toland et al., 2007). In multiple species piRNAs target
mainly transposable elements even though they are also capable of silencing protein-coding
genes (Brennecke et al., 2007; Ha et al., 2014; Robine et al., 2009). In human multiple
piRNAs have been shown to be produced from genomic regions containing recently inserted
long terminal repeats (LTRs) and endogenous retroviruses (ERVs), which has led to the
suggestion that these piRNAs might have roles in the regulation of these elements
particularly in human testis (Ha et al., 2014). Furthermore, human piRNAs have been shown
to be derived from pseudogenes, indicating that they might be involved in the regulation of
the functional gene copies of these pseudogenes (Pantano et al., 2015).
1.2.4.1 Post-transcriptional silencing
The post-transcriptional mechanism of silencing transposons is a quite well-known process
including the recognition and cleavage of the target sequences by the PIWI-piRNA
complexes. The piRNA guides the complex to its target by base-pairing with a
complementary sequence after which the PIWI protein is able to induce the cleavage of the
target transcript. (Brennecke et al., 2007; Grivna et al., 2006). The majority of germline
piRNAs have been found to be fully complementary with their transposon targets. However,
it is unclear whether perfect base-pairing between piRNAs and all of their targets is required
for the suppression of the target. In roundworms it has been shown that even imperfect basepairing could be enough to trigger the cleavage of their targets, whereas Miwi and piwi have
been found to cleave only highly complementary sequences. (Bagijn et al., 2012; Reuter et
al., 2011; Huang et al., 2013).
1.2.4.2 Transcriptional silencing
The piRNA-mediated transcriptional silencing through epigenetic modifications has been
described in fruit flies, mice and roundworms. The most studied epigenetic factors include
histone modifications and DNA methylation which regulate gene expression by modulating
the chromatin state. In fruit flies the piwi and aub proteins have been shown to have a role in
the formation of the closed chromatin at target sequences (Pal-Bhadra et al., 2004; Le
14
Thomas et al., 2013). The mechanisms by which piwi affects the histone modifications of the
bound target occurs via association with suppressive marks of the chromatin, the
heterochromatin protein 1 (HP1) and histone 3 lysine 9 methylation (H3K9me), blocking the
binding of the RNA polymerase (Figure 3A-C). It has been suggested that the recruitment of
HP1 by piwi results in the recruitment of the histone methyltransferase Su(var)3-9, which in
turn results in the methylation of H3K9 in heterochromatin regions. (Brower-Toland et al.,
2007; Pal-Bhadra et al., 2004; Ross et al., 2014). The formation of closed chromatin is not
random; piwi proteins and HP1 are guided to the target site by piRNAs which form
interactions either with RNA or DNA with high degree of complementary in euchromatin and
heterochromatin regions, respectively (Figure 3A/D) (Huang et al., 2013). In euchromatin
the order of associations between piwi, HP1 and Su(Var)3-9 is not clear, but the interactions
between these factors lead to the silencing of the target similarly as in heterochromatin
regions (Figure 3E). In addition to the formation of repressed chromatin state the piRNAassociated epigenetic regulation can lead to active chromatin state (Yin and Lin, 2007).
Furthermore, the mouse Mili and Miwi2 proteins have been demonstrated to enhance DNA
methylation of the promoters of transposon sequences through the function of DNA
methyltransferases (Kuramochi-Miyagawa et al., 2008; Aravin et al., 2008). The piRNAs'
ability to induce DNA methylation has been shown to exceed to non-transposon sequences
such as RAS protein-specific guanine nucleotide-releasing factor 1 (Rasgrf1) in mouse germ
cells controlling genomic imprinting (Watanabe et al., 2011). Moreover, piRNAs have been
found to be present in sea hare (Aplysia) neurons where they contribute in the regulation of
cAMP-response element-binding protein 2 (Creb2) promoter by facilitating DNA
methylation, having effects on long term memory (Rajasethupathy et al., 2012). The
transcriptional silencing mechanism of roundworm piRNAs has similar features to those of
fruit flies and mice as it also includes the association of piRNAs and the chromatin stateregulating proteins (Ashe et al., 2012; Shirayama et al., 2012).
15
Figure 3. The proposed mechanisms of piRNA mediated transcriptional silencing. A. In closed
chromatin regions PIWI-piRNA complexes are guided to the target site by piRNAs, which recognize
and bind complementary DNA sequences. B. After the binding of piRNA, piwi associates with the
heterochomatin protein 1 (HP1) which in turn associates with the histone methyltransferase Su(Var)39 leading to the methylation of histone 3 lysine 9 (H3K9). C. The suppressive chromatin state formed
by these interactions prevents the binding of Polymerase II (Pol II) silencing the target sequence. D.
In open chromatin regions the silencing mechanism is similar but piRNAs bind to emerging RNA
transcripts instead of DNA. E. The order of the interactions between Piwi, HP1 and Su(Var)3-9 is not
known, but these interactions are known to be sufficient in silencing the target sequence by repressing
the chromatin. Modified from Ross et al., 2014.
1.2.4.3 Canalization
The piRNAs' capability of affecting epigenetic factors has been linked to a process called
canalization. In 1942 C. Waddington introduced a term called canalization which is a
phenomenon that inhibits the genetic and environmental variation on phenotype by epigenetic
modifications. The heat shock protein 90 (Hsp90) has been discovered to be important in
canalization in both fruit flies and plants (Queitsch et al., 2002; Tariq et al., 2009). The role
of ncRNAs in developmental robustness has been demonstrated in fruit fly where miR-iab-45p has been shown to regulate the process of normal development (Ronshaugen et al., 2005).
It has been suggested that canalization and piRNA transposon silencing are connected as
Hsp90 has been shown to influence the piRNA-mediated transposon suppression in fruit flies
(Specchia et al., 2010). More recently, the mechanism by which canalization is mediated by
Hsp90 has become clearer due to the discovery that Hsp90 and its accessory protein Hop
form complexes with piwi, possibly regulating the activity of piwi by taking part in the final
steps of piwi biogenesis (Gangaraju et al., 2011).
16
1.2.4.4 Somatic functions
PIWI proteins are known to function also in the soma as they are known to be expressed in
the somatic cells surrounding germ cells, and piwi has been found to be functional in the fruit
fly eye (Brennecke et al., 2007; Brower-Toland et al., 2007). The studies of piRNAs have
been primarily concentrating on their germline functions including their essential roles in
gametogenesis and suppression of transposon activity and mobility (Aravin et al., 2006; Lau
et al., 2006), but recent studies have shown that a small number of piRNAs are also present in
the mouse hippocampus, and in many other mammalian somatic tissues including mouse
pancreas and macaque epididymis (Brower-Toland et al., 2007; Lee et al., 2011; Lee et al.,
2011; Yan et al., 2011). One of the piRNAs found to be expressed in the brain tissue has been
suggested to have a role in the spinal cord development of mice (Lee et al., 2011).
Furthermore, piRNAs have been found to target the fruit fly embryonic Nanos, a maternal
effect gene required for the formation of the anterior-posterior axis, via translational
regulation. The regulation is thought to occur by interactions between piwi-piRNA complex
and RNA binding protein Smaug. Smaug is needed for the function of the deadenylase C-C
chemokine receptor type 4 (CCR4) which is responsible for the degeneration of Nanos
mRNA. (Rouget et al., 2010). It has been suggested that through the interaction with Smaug
and CCR4 piRNAs may be involved also in the translational suppression of other genes
besides Nanos (Semotok et al., 2005). In addition, as was mentioned before, piRNAs have
been found to have important function in sea hare neurons affecting the formation of memory
(Rajasethupathy et al., 2012). All of these studies indicate that in addition to their crucial
functions in the gonads, piRNAs may have roles in many important mechanisms in numerous
different somatic tissues.
1.3 The roles of PIWI proteins and piRNAs in cancer
1.3.1 PIWI proteins in cancer
It has been known for a long time that the defects in the PIWI-piRNA complex cause sterility
(Carmell et al., 2007; Cox et al., 1998; Lin and Spradling, 1997; Aravin et al., 2007;
Kuramochi-Miyagawa et al., 2008) but more recently multiple studies have evaluated the
roles of PIWI proteins and piRNAs in tumorigenesis. One of the human PIWI proteins,
HIWI, has been shown to be overexpressed in numerous human tumors including seminomas
(Qiao et al., 2002), sarcomas (Taubert et al., 2007), gliomas (Sun et al., 2011), gastric (Wang
17
et al., 2012), pancreatic (Grochola et al., 2008), colorectal (Zeng et al., 2011), esophageal (He
et al., 2009), and liver cancers (Zhao et al., 2012). Moreover, the overexpression of another
human PIWI protein, HILI, has been detected in seminoma (Lee et al., 2006), breast (Liu et
al., 2010), cervical (He et al., 2010), and colon cancers (Li et al., 2012). The HIWI and HILI
proteins have been shown to enhance tumor growth by affecting the proliferation and
apoptosis of cancerous cells (Taubert et al., 2007; Lee et al., 2006). HILI has been also shown
to be associated with the invasive type of colon cancer (Li et al., 2012). In addition to HIWI
and HILI, the expression levels of HIWI3 and HIWI2 have also been studied in gastric cancer
(Wang et al., 2012). Even though the PIWI proteins have been studied in multiple cancers
and they have been found to be aberrantly expressed in tumor tissues (Table 2), the
expression pattern studies are not sufficient to conclude that the overexpression of PIWI
proteins causes the development of tumors and functional studies are needed to assess the
role of PIWI proteins in cancer.
Table 2. The PIWI proteins that have been found to be aberrantly expressed in different types of
human cancer.
Reference
PIWI protein
Cancer
PIWIL1/HIWI
Seminomas
Sarcoma
Qiao et al. 2002
Taubert et al., 2007
Glioma
Sun et al., 2011
Gastric cancer
Wang et al. 2012
Pancreatic cancer
Grochola et al., 2008
Colorectal cancer
Zeng et al., 2011
Esophageal cancer
He et al., 2009)
Liver cancer
Zhao et al., 2012
Seminoma
Lee et al., 2006
Breast cancer
Liu et al., 2010
Cervical cancer
He et al., 2010
Colon cancer
Li et al., 2012
PIWIL3/HIWI3
Gastric cancer
Wang et al., 2012
PIWIL4/HIWI2
Gastric cancer
Wang et al., 2012
PIWIL2/HILI
18
1.3.2 piRNAs in cancer
In addition to PIWI proteins also piRNAs have been shown to be present in cancer cells such
as HeLa cells (Lu et al., 2010), and in different human tumors including cervical
mesothelium, gastric, colon, lung, liver, and breast cancer tissues (Cheng et al., 2011a).
Moreover, multiple studies have demonstrated aberrant expression patterns of piRNAs in
numerous cancers compared to the matched normal tissues (Table 3) (Cheng et al., 2011a;
Cheng et al., 2012; Esposito et al., 2011; Law et al., 2013; Huang et al., 2013). In some cases
the expression levels of the studied piRNAs have been found to be associated with some of
the clinicopathological features of the tumors. For example, piR-651 has been suggested to
act as an oncogene in tumorigenesis and its expression levels are associated with TNM stages
in gastric cancer (Cheng et al., 2011a). On the other hand, piRNAs have been shown to have
potential to act as tumor suppressors; piR-823 has been found to be downregulated in gastric
cancer tissues and the aberrant expression has been shown to enhance tumor growth (Cheng
et al., 2012). In addition, in plasma cell myeloma piR-823 expression has been demonstrated
to be higher in cancer tissue compared to normal tissue, and has been suggested to act as an
oncogene, which indicates that piRNAs might have different roles in different kind of tumors
(Yan et al. 2015). Multiple piRNAs have been discovered to have an aberrant expression in
breast cancer. These piRNAs include piR-651, piR-4987, piR-20365, piR-20485, piR-20582,
and piR-19825 which all have been shown to be overexpressed in breast cancer compared to
normal breast tissue. (Cheng et al., 2011a; Huang et al., 2013). Furthermore, piR-17458 has
been shown to be underexpressed in ductal breast tumors compared to normal breast tissue
(Cheng et al., 2011a; Cheng et al., 2012; Huang et al., 2013). The piR-4987 expression has
been linked to lymph node positivity as it was determined that the overexpression of piR4987 correlates with the formation of metastasis in the nearby lymph nodes in breast cancer
(Huang et al., 2013).
19
Table 3. The piRNAs that have been demonstrated to be aberrantly expressed in human cancer.
piRNA
Expression pattern
Cancer
Reference
piR-651
Overexpressed
Gastric cancer
Cheng et al. 2011a
Cheng et al. 2011a
Colon cancer
Lung cancer
Cheng et al. 2011a
Breast cancer
Cheng et al. 2011a
Cervical mesothelium
Cheng et al. 2011a
Liver cancer
Cheng et al. 2011a
Underexpressed
Gastric cancer
Cheng et al. 2012
Overexpressed
Plasma cell myeloma
Yan et al. 2015
piR-4987
Overexpressed
Breast cancer
Huang et al. 2013
piR-20365
Overexpressed
Breast cancer
Huang et al. 2013
piR-20485
Overexpressed
Breast cancer
Huang et al. 2013
piR-20582
Overexpressed
Breast cancer
Huang et al. 2013
piR-19825
Overexpressed
Breast cancer
Huang et al. 2013
piR-17458
Underexpressed
Breast cancer
Huang et al. 2013
piR-Hep1
Overexpressed
Liver cancer
Law et al. 2013
piR-823
1.3.3 The mechanisms of PIWI proteins and piRNAs in cancer development
The similarities in the proliferation mechanisms of germ cells and cancer cells have
suggested that PIWI proteins and piRNAs might be involved in the development of tumors
(Simpson et al., 2005). The same factors contributing to the self-renewal capacity of germ
cells may be used by the tumor cells as well. Especially the cancer/testis antigens (CTAs)
have been studied extensively, because they have been found to be expressed in multiple
tumors, whereas normally they are expressed only in the germline (Simpson et al., 2005;
Cheng et al., 2011b). The exact mechanisms of PIWI in tumorigenesis remain to be studied
but it has been suggested that the overexpressed PIWI proteins and piRNAs might use their
capability of inducing closed chromatin by modifying tumor suppressor genes epigenetically,
thus repressing their functions. In addition, PIWI proteins coupled with piRNAs could
facilitate tumor development by activating oncogenes and repressing tumor suppressor genes
in a post-transcriptional manner. (Suzuki et al., 2012). The aberrantly expressed piRNAs are
thought to have effects on the proliferation and motility of the cancer cells (Cheng et al.,
2011a; Cheng et al., 2012; Huang et al., 2013). In addition, given their importance in
transposon silencing the down-regulation of piRNAs can lead to increased transposon
20
activity, which increases mutation rate, which in theory might contribute to the development
of cancer.
1.3.4 Potential as diagnostic and prognostic markers
After the discovery of their possible roles in cancer development PIWI proteins and piRNAs
have been described as potential diagnostic and prognostic markers of cancer (Wang et al.,
2012; Cheng et al., 2011a; Cheng et al., 2012; Huang et al., 2013). One advantage of using
piRNAs as diagnostic markers is their higher stability compared to e.g. shorter miRNA
transcripts, which might enable the detection and isolation of piRNAs from non-invasive
sources such as blood and urine (Cui et al., 2011). The potential uses in therapies include the
silencing of oncogenes by piRNA-induced degradation of their mRNAs or by the formation
of closed chromatin in the regulatory regions. Furthermore, the piRNAs that possibly act as
oncogenes could be silenced through siRNA mediated suppression. (Mei et al., 2013).
21
2. The aim of this study
The purpose of this experiment was to identify a potential piRNA biomarker candidate for
breast cancer by studying the expression of piR-4987 in breast cancer tissues, and the
possible associations between the expression levels and clinicopathological features such as
lymph node positivity. Furthermore, the differences in piRNA expression between triplenegative and ER-positive breast cancers were studied.
3. Materials and methods
3.1 Samples
The RNA samples (stored at -70°C) used in this study had been previously extracted from
fresh-frozen tissue samples of breast cancer cases in the Kuopio Breast Cancer Project
(Mannisto et al., 1996; Mitrunen et al., 2000; Pellikainen et al., 2003; Hartikainen et al.,
2005; Peltonen et al., 2013). The tissue samples were collected from women who had been
operated in Kuopio University Hospital between April 1990 and December 1995. In total 516
breast cancer cases were included in the project. Written informed consents were obtained
from all of the patients and a consent approval has been given by the joint ethics committee
of Kuopio University and Kuopio University Hospital (written consents 1/1989 and 61/2010).
A total of 95 RNA samples of patients with invasive breast tumors were used in this study
including triple-negative (n=18) and estrogen receptor-positive (n=63) breast cancer cases. In
about 59% of these patients (n=56) the cancer had spread to the lymph nodes. A summary of
the clinicopathological characteristics of the patients is presented in Table 4.
22
Table 4. The clinicopathological characteristics of the 95 studied patients.
Clinical parameters
n (%)
ER status
Positive
Negative
63 (66.32)
32 (33.68)
PR status
Positive
Negative
54 (56.84)
41 (43.16)
HER2 status
Positive
Negative
Not defined
14 (14.74)
72 (75.79)
9 (9.47)
Triple-negative
Yes
No
18 (18.95)
77 (81.05)
TNM status
I
II
III
IV
Not defined
40 (42.11)
43 (45.26)
6 (6.32)
5 (5.26)
1 (1.05)
Grade
I
II
III
15 (15.79)
39 (41.05)
41 (43.16)
Stage
I
II
III
IV
29 (30.53)
53 (55.79)
8 (8.42)
5 (5.26)
Histology
Ductal
Lobular
Medullar and mixed
67 (70.53)
21 (22.10)
7 (7.37)
Lymph node status
N0
N1
N2
39 (41.05)
51 (53.69)
5 (5.26)
Metastasis
Yes
6 (6.32)
No
88 (92.63)
Not defined
1 (1.05)
ER= estrogen receptor, PR= progesterone receptor, HER2= human epidermal growth factor type 2, TNM=
tumor-node-metastasis
23
3.2 piR-4987 sequence
The
sequence
of
piR-4987
(Table
5)
was
obtained
from
the
piRNABank
(http://pirnabank.ibab.ac.in/) using human genome build 37. It was submitted to Custom
TaqMan® Small RNA Assay Design Tool on the Life technologies (Grand Islands, NY)
website to obtain a custom-designed TaqMan® Small RNA Assay with optimized primers
and probes for both reverse transcription (RT) and quantitative real-time polymerase chain
reaction (qPCR) reactions.
Table 5. The sequence and accession codes for piR-4987.
piRNA name
NCBI/piRNABank
Accession number
NCBI/piRNABank
Sequence
piR-44984/piR-4987
DQ576872.1/hsa_piR_004987
tcgccgtgat cgtatagtgg ttagtactct g
3.3 Quantitative real-time PCR
To validate and quantify piR-4987, the analysis was performed in two steps; first the RNA
samples were transcribed into complementary DNA (cDNA) in the RT reaction and then the
cDNA was quantified with qPCR.
The RT was performed according to the recommended protocol of the manufacturer using the
reagents from TaqMan® MicroRNA Reverse Transcription Kit (Life Technologies) and the
piR-4987-specific RT primer obtained from the custom TaqMan® Small RNA Assay (Life
Technologies). The RT was performed also with the primer for RNU48 (TaqMan MicroRNA
Assays, Life technologies) which was used as an endogenous control. Ten nanograms of the
total RNA was used in the synthesis of cDNA for each 15- l RT reaction containing 7 l of
master mix, 3 l of 5X RT primer, and 5 l of RNA sample. All RT reactions were carried out
with UNO-Thermoblock (Biometra, Göttingen, Germany). The thermal program for the
reactions was 30 minutes at 16°C followed by 30 minutes at 42°C and 5 minutes at 85°C
after which the temperature was dropped to 4°C. The cDNA samples were stored at -20°C
until preparing of the qPCR reactions.
The piR-4987 and RNU48 levels were quantified by qPCR using TaqMan® Universal PCR
Master Mix (no AmpErase UNG) (Life Technologies) and the specific primers and probes
24
provided by Life Technologies, following the protocol instructions of the manufacturer. Each
20-µl reaction contained 1µl of 20X TaqMan® Small RNA assay mix, 1.33µl of cDNA, 10µl
of master mix and 7.67µl of nuclease-free water. A cDNA sample from noncancerous breast
tissue was used as a calibrator. Standard curves were constructed for both piR-4987 and
RNU48 before analyzing the expression levels of the samples for validating the assays of the
target gene and endogenous control for the
CT method; ideally, the amplification
efficiency of both genes should be equal. The amplification efficiencies for piR-4987 and
RNU48 were 94.1% and 80.3%, respectively (Figures 4 and 5). All qPCR reactions were run
with Mx3000P Real-Time PCR System (Stratagene, La Jolla, CA) with three replicate
reactions for each sample and each point of the standard curve. The parameters for qPCR
were as follows: 10 minutes at 95°C, followed by 45 cycles of 15 seconds at 95°C and 60
seconds at 60°C. The means of the sample replicates’ CT (threshold cycle) values were
calculated and used in the
CT method to determine the relative expression values, which
were then used in the statistical analyses. In the
CT method the ratio of piR-4987 in studied
samples relative to the calibrator sample (noncancerous breast tissue) were calculated, using
the RNU48 as reference.
Figure 4. The standard curve for piR-4987. R Squared (RSq) value was 0.993 and the efficiency of
the amplification 94.1%. The slope was -3.472.
25
Figure 5. The standard curve for RNU48 endogenous control. R Squared (RSq) value was 0.995 and
the efficiency of amplification 80.3%. The slope was -3.905.
3.4 Statistical analyses
The statistical analyses were performed using the version 21 of SPSS Statistics for Windows
(SPSS Inc., Chicago, IL, USA). In all of the analyses P values less than 0.05 were considered
significant. Log2-transformation was done for the fold change values so they could be used in
analyses that require normally distributing values. The log2-transformed expression values
were then divided into groups according to quarters and median. The number of cases in each
group was the following; for the quarter groups n=24, 24, 24, and 23 and for the median
groups n=47 and 48. The lymph node status variable was divided into three groups; N0, N1
and N2 (n=39, 51, and 5, respectively). In addition, the lymph node status was divided into
positive (n=56) and negative (n=39) groups. Also the tumor stage variable was divided into
three groups; the first corresponding to stage I tumors, the second to stage II tumors and the
third to combined stage III and IV tumors (n=29, 53 and 13, respectively). Furthermore, the
TNM status variable was divided into three groups; I, II and III/IV (n=40, 43, and 11,
respectively).
Pearson Chi-Square tests and Fisher’s exact tests (2-sided) (cross tabulations) as well as
nonparametric tests, using either Mann-Whitney U-test or Kruskal-Wallis test, were
performed to analyze the possible associations between the expression levels and
26
clinicopathological variables. Breast cancer survival analyses were conducted with KaplanMeier method using Log-Rank, Breslow and Tarone-Ware tests. The breast cancer survival
was determined based on the time between the diagnosis and death due to breast cancer. In
addition, multivariate Cox regression survival analyses were performed with covariates
including the lymph node status, tumor grade, TNM status, histology, ER-, and HER2 status.
Box-and-whiskers plots were created plotting the log2-transformed piR-4987 expression
values against the histological type of the tumor, lymph node status, stage, triple-negativity,
and ER status.
4. Results
4.1 piR-4987 expression levels in breast cancer tissue
The expression levels of piR-4987 were increased in most of the breast tumor samples
compared to the noncancerous calibrator sample (Figure 6). In 85 (80.75%) of the samples
the fold change was at least 1 and in 34 samples (32.3%) at least 10. The fold change values
ranged from 0.1 to 58.1. The mean of the values was 9.4 and the median 5.5. The frequencies
of piR-4987 log2-transformed expression levels of the samples are shown in Figure 7.
27
piR-4987 fold change
60
50
40
30
20
10
1365
1904
1547
1505
971
1682
268
1064
1746
1596
1176
1756
467
218
1299
1680
616
1390
1795
1732
1151
1559
410
1370
611
1029
698
1734
569
694
520
1319
1353
750
689
910
1810
349
1384
370
813
818
566
1491
1618
1677
715
903
0
Figure 6. The ratio of piR-4987 expression levels of 95 breast cancer tissue samples determined with qPCR assay. The fold change values are shown in the yaxis and the sample IDs in the x-axis. All of the sample IDs are not shown.
28
Figure 7. The frequencies of the log2-transformed piR-4987 expression values.
4.2 Association of piR-4987 expression level with clinical parameters
The associations between the categorical log2-transformed expression values and
clinicopathological variables are shown in Tables 6 and 7. Triple-negativity (P= 0.032 and
0.039) and tumor stage (P= 0.020 and 0.021) were found to be significantly associated with
the piR-4987 expression level divided in two groups according to the median (Table 7). The
associations between other clinicopathological variables and the categorized log2transformed expression values failed to reach statistical significance (Tables 6 and 7).
29
Table 6. The comparisons of the clinicopathological variables with piR-4987 log2-transformed values
divided into groups according to quartile percentiles.
n
Clinical variable
P value
Tot.
<25%
25-50%
50-75%
>75%
63
32
17
6
12
12
19
5
15
9
54
41
15
8
12
12
15
9
12
12
14
72
3
19
4
18
2
19
5
16
18
77
5
18
8
16
2
22
3
21
40
43
11
12
9
2
7
16
1
7
12
4
14
6
4
15
39
41
3
10
10
3
9
12
4
11
9
5
9
10
29
53
13
7
15
1
7
16
1
5
14
5
10
8
6
67
21
7
19
4
0
15
4
5
16
6
2
17
7
0
39
51
5
9
14
0
10
14
0
8
14
2
12
9
3
6
88
0
23
1
23
2
21
3
21
ER status
Positive
Negative
PR status
Positive
Negative
HER2 status
Positive
Negative
Triple-negativity
Yes
No
TNM status
I
II
III/IV
Grade
I
II
III
Stage
I
II
III/IV
Histology
Ductal
Lobular
Medullar and mixed
Lymph node status
N0
N1
N2
Metastasis
Yes
No
Pearson ChiSquare
Fisher's exact
test (2-sided)
0.149
0.157
0.596
0.592
0.626
0.630
0.124
0.135
0.083
0.074
0.963
0.971
0.088
0.085
0.079
0.123
0.260
0.288
0.324
0.441
ER= estrogen receptor, PR= progesterone receptor, HER2= human epidermal growth factor type 2, TNM=
tumor node metastasis, Tot.= total number of samples
n= number of cases in each group used in the analysis
P values obtained from Pearson Chi-Square and Fisher’s exact test (2-sided)
30
Table 7. The comparisons of the clinicopathological variables with piR-4987 log2-transformed values
divided into groups according to median.
n
Clinical variable
P value
Total
<2.65
(median)
>2.65
(median)
63
32
29
18
34
14
54
41
27
20
27
21
14
72
7
37
7
35
18
77
13
34
5
43
40
43
11
19
25
3
21
18
8
15
39
41
6
19
22
9
20
19
29
53
13
14
31
2
15
22
11
67
21
7
34
8
5
33
13
2
39
51
5
19
28
0
20
23
5
6
88
1
46
5
42
ER status
Positive
Negative
PR status
Positive
Negative
HER2 status
Positive
Negative
Triple-negativity
Yes
No
TNM status
I
II
III/IV
Grade
I
II
III
Stage
I
II
III/IV
Histology
Ductal
Lobular
Medullar and mixed
Lymph node status
N0
N1
N2
Metastasis
Yes
No
Pearson ChiSquare
Fisher's exact
test (2-sided)
0.346
0.390
0.906
1.000
0.924
1.000
0.032
0.039
0.173
0.186
0.695
0.732
0.020
0.021
0.289
0.292
0.64
0.76
0.091
0.203
ER= estrogen receptor, PR= progesterone receptor, HER2= human epidermal growth factor type 2, TNM=
tumor node metastasis, Total= total number of samples
n= number of cases in each group used in the analysis
P values obtained from Pearson Chi-Square and Fisher’s exact test (2-sided)
P values <0.05 marked in bold
31
In addition to the Chi-Squared test and categorized piR-4987 expression levels, significant
association between the piR-4987 expression level and the tumor stage (P= 0.022) was
observed also using uncategorized log2-transfromed expression values (Table 8).
Furthermore, a significant association was found between the uncategorized log2-transformed
expression values and the lymph node status (P= 0.030) (Table 8). The associations between
the uncategorized log2-transformed piR-4987 expression values and other clinicopathological
variables, including the histological type of the tumor (Figure 8), failed to reach significance
(Table 9).
Table 8. The significant associations between the uncategorized piR-4987 expression levels and
clinicopathological variables.
Clinical variable
n
P value
Test
Lymph node status
N0
N1
N2
Stage
I
II
III/IV
0.030
Kruskal-Wallis
0.022
Kruskal-Wallis
39
51
5
29
53
13
P values <0.05 marked in bold.
32
Table 9. The associations between the uncategorized piR-4987 expression levels and
clinicopathological variables.
Clinical variable
n
P value
Test
ER status
Positive
Negative
PR status
Positive
Negative
Metastasis
0.581
Mann-Whitney U
0.071
Mann-Whitney U
0.263
Kruskal-Wallis
0.490
Kruskal-Wallis
0.470
Kruskal-Wallis
0.053
Mann-Whitney U
40
43
11
Histology
Ductal
Lobular
Medullar/ mixed
Mann-Whitney U
15
39
41
TNM status
I
II
III/IV
0.657
18
77
Grade
I
II
III
Mann-Whitney U
39
56
Triple-negative
Yes
No
0.769
14
72
Lymph node status
Positive
Negative
Mann-Whitney U
54
41
HER2 status
Positive
Negative
0.676
63
32
67
21
7
Yes
6
No
88
ER= estrogen receptor, PR= progesterone receptor, HER2= human epidermal growth factor type 2, TNM=
tumor-node-metastasis
33
Figure 8. The piR-4987 expression level in different histological types of the tumors.
The tumor stage was observed to significantly associate with the levels of piR-4987. The boxand-whiskers plot shows that the piR-4987 expression seems to be increased in the tumors
with higher stage (stage III-IV) compared to the lower stage (Figure 9).
Figure 9. The association between the piR-4987 expression level and tumor stage.
34
The significant association between the uncategorized log2-transformed expression values
and lymph node status indicates that piR-4987 expression levels might be associated with
lymph node positivity. The box-and-whiskers plot with N0, N1 and N2 groups implies that
tumors that have spread to multiple lymph nodes (N2) express higher levels of piR-4987
(Figure 10). However, when the lymph node status was divided in two groups, positive
(N1&N2) and negative (N0), no difference between the expression levels can be seen (Figure
11).
Figure 10. The association between the piR-4987 expression level and lymph node status. N0= cancer
has not spread to nearby lymph nodes, N1= cancer has spread to one to three nearby lymph nodes,
N2= cancer has spread to multiple nearby lymph nodes.
35
Figure 11. The piR-4987 expression level in tumors with negative and positive lymph node status.
Association between the categorized log2-transformed expression values and triple-negativity
was also observed (Table 7). The box-and-whiskers plot indicate that non-triple-negative
tumors might have higher piR-4987 levels compared to the triple-negative tumors even
though no significant result was obtained for triple-negativity using the uncategorized log2transformed expression values (Figure 12). Supporting this finding, the expression levels
seem to be higher in the ER-positive tumors compared to the ER-negative tumors (Figure
13). However, the association between ER status and the piR-4987 expression level was not
found to be significant (Tables 6, 7 and 9).
36
Figure 12. The piR-4987 expression level in triple-negative and non-triple-negative tumors.
Figure 13. The piR-4987 expression level in tumors with positive and negative estrogen receptor (ER)
status.
37
4.3 Survival analyses
No significant results were found in the survival analyses using Kaplan-Meier or Cox
regression when evaluating the effects of piR-4987 expression levels on breast cancer
survival (Tables 10-13). However, the survival plot obtained from Kaplan-Meier analysis
with the log2-transformed expression values in two groups according to median indicates that
the higher expression levels seem to be associated with poorer survival up to 15 years
(Figure 14). Furthermore, a similar trend is seen in the Cox regression plots where patients
with the highest piR-4987 expression seem to have lower survival rate (Figures 15 and 16).
Table 10. Kaplan Meier survival analysis according to the piR-4987 expression levels.
piR-4987 expression level
n
< median
> median
47
48
< 25%
23
25-50%
24
50-75%
24
> 75%
24
P value
Log-Rank
Breslow
Tarone-Ware
0.431
0.130
0.205
0.525
0.298
0.378
Figure 14. Breast cancer survival (Kaplan-Meier) plot with the log2-transformed piR-4987 expression
values in two groups according to median.
38
Table 11. Cox regression survival analysis with the log2-transformed piR-4987 expression values
according to quartile percentiles. Lymph node status, tumor grade, TNM status, histological type, ERand HER2 status were included in the analysis .
95% CI for Exp(B)
Clinical variable
Wald
Sig.
HR
Lower
Upper
Lymph node status
Negative
Positive
Ref.
8.941
0.003
4.511
1.680
12.112
ER status
Positive
Negative
Ref.
2.043
0.153
2.030
0.769
5.362
HER2 status
Negative
Positive
Ref.
0.423
0.516
1.412
0.499
3.995
Histology
Medullar and mixed
Ductal carcinoma
Lobular carcinoma
5.168
Ref.
0.038
1.298
0.075
0.852
3.025
0.169
0.451
4.301
20.316
TNM
I
II
III/IV
2.021
Ref.
0.212
2.021
0.364
1.260
2.366
0.472
0.722
3.360
7.758
Grade
I
II
III
3.651
Ref.
3.234
3.393
0.161
3.577
4.624
0.892
0.907
14.345
23.584
Log2 piR-4987
<25%
25%- 50%
50%- 75%
>75%
2.260
Ref.
0.457
0.020
1.696
1.447
0.930
1.999
0.496
0.334
0.705
4.224
2.587
5.667
0.846
0.255
0.645
0.155
0.072
0.065
0.520
0.499
0.889
0.193
ER= estrogen receptor, HER2= human epidermal growth factor type 2, TNM= tumor-node-metastasis, Ref=
reference category, HR= hazard ratio of breast cancer death, Exp(B) value from Cox regression analysis
P-values >0.05 are marked in bold.
39
Table 12. Cox regression survival analysis with the log2-transformed piR-4987 expression values
according to median. Lymph node status, tumor grade, TNM status, histological type, ER- and HER2
status were included in the analysis.
95% CI for Exp(B)
Clinical variable
Wald
Sig.
HR
Lower
Upper
Lymph node status
Negative
Positive
Ref.
8.733
0.003
4.337
1.639
11.475
ER status
Positive
Negative
Ref.
2.601
0.107
2.217
0.843
5.833
HER2 status
Negative
Positive
Ref.
1.428
0.232
1.812
0.684
4.800
Histology
Medullar and mixed
Ductal carcinoma
Lobular carcinoma
5.628
Ref.
0.063
1.373
0.060
0.818
2.881
0.170
0.491
3.938
16.918
TNM
I
II
III/IV
1.822
Ref.
0.076
1.743
0.402
1.136
2.145
0.459
0.691
2.812
6.657
Grade
I
II
III
2.330
Ref.
1.966
2.117
0.312
0.161
0.146
2.380
2.947
0.708
0.687
8.000
12.640
Log2 piR-4987
< median
> median
Ref.
0.113
0.737
1.129
0.555
2.297
0.802
0.241
0.783
0.187
ER= estrogen receptor, HER2= human epidermal growth factor type 2, TNM= tumor-node-metastasis, Ref=
reference category, HR= hazard ratio of breast cancer death, Exp(B) value from Cox regression analysis
P-values >0.05 are marked in bold.
40
Table 13. Cox regression survival analysis with the log2-transformed piR-4987 expression values
according to the most expressed (>75%) and others (<75%). Lymph node status, tumor grade, TNM
status, histological type, ER- and HER2 status were included in the analysis.
95% CI for Exp(B)
Clinical variable
Wald
Sig.
HR
Lower
Upper
Lymph node status
Negative
Positive
Ref.
8.727
0.003
4.169
1.617
10.750
ER status
Positive
Negative
Ref.
2.337
0.126
2.106
0.810
5.472
HER2 status
Negative
Positive
Ref.
0.915
0.339
0.619
0.232
1.654
Histology
Medullar and mixed
Ductal carcinoma
Lobular carcinoma
5.101
Ref.
0.096
1.132
0.078
0.781
2.618
0.164
0.445
3.728
15.406
TNM
I
II
III/IV
1.638
Ref.
0.361
1.623
0.441
1.333
2.109
0.521
0.669
3.410
6.648
Grade
I
II
III
3.235
Ref.
2.820
3.014
0.198
0.093
0.083
3.143
4.010
0.826
0.836
11.963
19.234
Log2 piR-4987
< 75%
> 75%
Ref.
1.627
0.202
1.799
0.730
4.437
0.757
0.287
0.548
0.203
ER= estrogen receptor, HER2= human epidermal growth factor type 2, TNM= tumor-node-metastasis, Ref=
reference category, HR= hazard ratio of breast cancer death, Exp(B) value from Cox regression analysis
P-values >0.05 are marked in bold.
41
Figure 15. Cox regression breast cancer survival plot with log2-transformed piR-4987 expression
values in four groups according to quartile percentiles. Lymph node status, tumor grade, TNM status,
histological type, ER- and HER2 status were included in the analysis.
Figure 16. Cox regression breast cancer survival plot with log2-transformed piR-4987 expression
values according to the highest expression (>75%) and the others (<75%). Lymph node status, tumor
grade, TNM status, histological type, ER- and HER2 status were included in the analysis.
42
5. Discussion
The research of PIWI proteins and piRNAs in cancer has just recently began and even
though the expression levels of PIWI proteins and some of the piRNAs have been studied in
numerous cancers a lot more studies are needed to evaluate their exact functions in cancer. In
addition to functional studies it would be important to study the expression patterns of
multiple piRNAs in the context of different cancer types to identify novel diagnostic and
prognostic markers. The aim of this master's thesis was to study the expression pattern of
piR-4987 in breast cancer and to see if it is associated with the clinicopathological
characteristics.
The expression of piR-4987 was increased in most of the samples compared to the normal
breast tissue sample, which indicates that piR-4987 might be a potential diagnostic marker.
However, more normal breast tissue samples need to be included in the study before stating
that increased piR-4987 expression is a feature of breast cancer tissue. In the standard curves
there is a difference in the amplification efficiency between piR-4987 and RNU48 (94.1% and
80.3%, respectively) which may affect the accuracy of the results.
The lymph node status was found to be significantly associated with the levels of piR-4987,
and higher levels of piR-4987 were associated with breast tumors that had spread to multiple
lymph nodes (N2). This finding is in agreement with a study that concluded that higher levels
of piR-4987 were correlated with the positive lymph node status (Huang et al., 2013). Here
however, no difference was seen in the expression levels of piR-4987 when the lymph node
status was divided into negative and positive tumors. Due to the quite large deviations that
are seen in the box-and-whisker plots and the small sample size, more comprehensive studies
are needed to confirm the association between piR-4987 and the invasiveness of breast cancer
into the nearby lymph nodes.
Related to the tumors' invasiveness into the lymph nodes, higher piR-4987 expression was
found to be linked to the higher stages of the tumor. It seemed that tumors staged III or IV
had increased levels of piR-4987. However, the association is not clear and again more breast
tumor samples need to be studied to see if these characteristics are linked together.
Even though no significant associations were found between ER-status and piR-4987
expression levels, the box-and-whiskers plot showed a small difference between the
expression levels in ER positive and negative tumors. The piR-4987 expression levels seemed
43
to be slightly lower in the ER negative tumors compared to the positive tumors, which is in
consistence with the finding that a weaker expression of piR-4987 was seen in triple-negative
tumors. This might indicate that the piR-4987 expression levels may be associated with the
receptor status of breast cancer. Due to the low amount of triple-negative tumor samples,
these findings need to be confirmed by using a larger sample amount.
Because no significant associations between breast cancer survival and piR-4987 levels were
found, no prognostic value of this piRNA was uncovered. However, the breast cancer
survival plots indicate that piR-4987 could be a potential prognostic marker with higher
expression levels indicating a more aggressive type of breast cancer. Also moderate increase
in the expression levels seems to affect breast cancer mortality even though the groups
between the 25th and 75th percentiles are switched and partially overlap in the Cox
regression plot with the expression values according to quartile percentiles.
For future directions there are multiple issues that need to be solved according to piRNAs and
cancer development. First, as was said before, the aberrantly expressed piRNAs need to be
identified to improve the diagnosis and prognosis of cancers. Secondly, the mechanisms by
which PIWI proteins and piRNAs might affect tumor initiation and development remain
unknown and there are only a few suggestions how their functions can lead to cancer
development. It has been demonstrated that the activity of transposons is increased in
cancers, and the role of piRNAs in maintaining genome stability by silencing transposons in
the germline might be extended into the somatic tissues as well. However, the expression
levels of the studied piRNAs have been found to be elevated in multiple cancers which
suggest they might have a role in the regulation of genes that drive cancer development
instead. Since human piRNAs are known to be processed from protein coding genes,
pseudogenes, and lncRNAs it is logical to suppose that piRNAs are involved in the regulation
of oncogenes and tumor suppressor genes. To confirm this hypothesis the possible oncogenes
and tumor suppressor genes that are regulated by piRNAs need to be identified. In addition, it
is unknown if the aberrant expression of PIWI proteins and piRNAs is the direct cause of
cancer or if the aberrant levels result from something else that is initially leading to the cancer
development.
44
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