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D 1247 OULU 2014 UNIV ER S IT Y OF OULU P. O. B R[ 00 FI-90014 UNIVERSITY OF OULU FINLAND U N I V E R S I TAT I S S E R I E S SCIENTIAE RERUM NATURALIUM Professor Esa Hohtola HUMANIORA University Lecturer Santeri Palviainen TECHNICA Postdoctoral research fellow Sanna Taskila MEDICA Professor Olli Vuolteenaho SCIENTIAE RERUM SOCIALIUM ACTA U N I V E R S I T AT I S O U L U E N S I S Maria Haanpää E D I T O R S Maria Haanpää A B C D E F G O U L U E N S I S ACTA A C TA D 1247 HEREDITARY PREDISPOSITION TO BREAST CANCER – WITH A FOCUS ON AATF, MRG15, PALB2, AND THREE FANCONI ANAEMIA GENES University Lecturer Veli-Matti Ulvinen SCRIPTA ACADEMICA Director Sinikka Eskelinen OECONOMICA Professor Jari Juga EDITOR IN CHIEF Professor Olli Vuolteenaho PUBLICATIONS EDITOR Publications Editor Kirsti Nurkkala ISBN 978-952-62-0457-4 (Paperback) ISBN 978-952-62-0458-1 (PDF) ISSN 0355-3221 (Print) ISSN 1796-2234 (Online) UNIVERSITY OF OULU GRADUATE SCHOOL; UNIVERSITY OF OULU, FACULTY OF MEDICINE, INSTITUTE OF CLINICAL MEDICINE, DEPARTMENT OF CLINICAL GENETICS; FACULTY OF MEDICINE, INSTITUTE OF DIAGNOSTICS, DEPARTMENT OF CLINICAL CHEMISTRY; BIOCENTER OULU; OULU UNIVERSITY HOSPITAL; NATIONAL GRADUATE SCHOOL OF CLINICAL INVESTIGATION D MEDICA ACTA UNIVERSITATIS OULUENSIS D Medica 1247 MARIA HAANPÄÄ HEREDITARY PREDISPOSITION TO BREAST CANCER – WITH A FOCUS ON AATF, MRG15, PALB2, AND THREE FANCONI ANAEMIA GENES Academic dissertation to be presented with the assent of the Doctoral Training Committee of Health and Biosciences of the University of Oulu for public defence in Auditorium 4 of Oulu University Hospital, on 6 June 2014, at 12 noon U N I VE R S I T Y O F O U L U , O U L U 2 0 1 4 Copyright © 2014 Acta Univ. Oul. D 1247, 2014 Supervised by Professor Robert Winqvist Docent Katri Pylkäs Reviewed by Professor Helena Kääriäinen Docent Pia Vahteristo Opponent Docent Annika Auranen ISBN 978-952-62-0457-4 (Paperback) ISBN 978-952-62-0458-1 (PDF) ISSN 0355-3221 (Printed) ISSN 1796-2234 (Online) Cover Design Raimo Ahonen JUVENES PRINT TAMPERE 2014 Haanpää, Maria, Hereditary predisposition to breast cancer – with a focus on AATF, MRG15, PALB2, and three Fanconi anaemia genes. University of Oulu Graduate School; University of Oulu, Faculty of Medicine, Institute of Clinical Medicine, Department of Clinical Genetics; Faculty of Medicine, Institute of Diagnostics, Department of Clinical Chemistry; Biocenter Oulu; Oulu University Hospital; National Graduate School of Clinical Investigation Acta Univ. Oul. D 1247, 2014 University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland Abstract Around 5−10% of all breast cancer cases are estimated to result from a strong hereditary predisposition to the disease. However, mutations in the currently known breast cancer susceptibility genes account for only 20−30% of all familial cases. Additional factors contributing to the pathogenesis of breast cancer, therefore, await discovery. Aims of this study were to evaluate variations of the AATF and MRG15 genes as novel potential candidates for breast cancer susceptibility, to further examine the prevalence of the cancer-related PALB2 c.1592delT mutation among BRCA-negative high-risk breast cancer families counselled at the Department of Clinical Genetics, Oulu University Hospital, to identify Finnish Fanconi anaemia patients complementation groups as well as causative mutations, and to evaluate the potential role of these mutations in breast cancer susceptibility. The analysis of 121 familial breast cancer cases revealed altogether seven different sequence changes in the AATF gene. However, none of them were considered pathogenic, suggesting that germline mutations in AATF are rare or absent in breast cancer patients. Investigation of the MRG15 gene among familial breast cancer cases revealed seven previously unreported variants, but in silico analyses revealed that none of these variants appeared to modify the function of MRG15. The results suggest that MRG15 alterations are unlikely to be significant breast cancer susceptibility alleles. A previously identified pathogenic PALB2 mutation, c.1592delT, was identified in three patients from a cohort of 62 high-risk BRCA1/2-negative breast cancer patients from the Department of Clinical Genetics. PALB2 c.1592delT mutation testing should thus be a routine part of the genetic counselling protocol, particularly for BRCA1/2-negative high-risk breast cancer patients. Investigation of the complementation groups of Finnish Fanconi anaemia patients revealed a total of six different causative mutations. These mutations were examined further by analysing their prevalence in large cohorts of breast (n=1840) and prostate (n=565) cancers. However, no significant association emerged between cancer predisposition and these FA mutations. Keywords: AATF, breast cancer, DNA damage response, DNA repair, Fanconi anaemia, genetic predisposition to disease, germline mutation, MRG15, PALB2 Haanpää, Maria, Perinnöllinen rintasyöpäalttius – AATF, MRG15, PALB2 ja kolme Fanconin anemian geeniä tutkimuksen kohteena. Oulun yliopiston tutkijakoulu; Oulun yliopisto, Lääketieteellinen tiedekunta, Kliinisen lääketieteen laitos, Perinnöllisyyslääketiede; Lääketieteellinen tiedekunta, Diagnostiikan laitos, Kliininen kemia; Biocenter Oulu; Oulun yliopistollinen sairaala; Valtakunnallinen kliininen tutkijakoulu Acta Univ. Oul. D 1247, 2014 Oulun yliopisto, PL 8000, 90014 Oulun yliopisto Tiivistelmä Arviolta 5−10 prosenttia kaikista rintasyöpätapauksista aiheutuu merkittävästä perinnöllisestä alttiudesta sairauteen. Tällä hetkellä tiedossa olevien rintasyövälle altistavien geenivirheiden ajatellaan kuitenkin selittävän vain noin 20−30 prosenttia kaikista perinnöllisistä tapauksista. On todennäköistä, että uusia tekijöitä, jotka osallistuvat rintasyövän patomekanismiin, on vielä löytymättä. Tämän tutkimuksen tarkoituksena oli arvioida AATF- ja MRG15-geeneissä esiintyvien muutosten mahdollista vaikutusta rintasyöpäalttiuteen, tutkia tarkemmin PALB2 c.1592delT mutaation esiintymistä BRCA-mutaationegatiivisten korkean rintasyöpäriskin potilaiden joukossa (perinnöllisyyspoliklinikka, Oulun yliopistollinen sairaala) ja määrittää suomalaisten Fanconianemiapotilaiden komplementaatioryhmät, sairauden taustalla olevat mutaatiot sekä tutkia näihin mutaatioihin mahdollisesti liittyvää rintasyöpäriskiä. 121 familiaalisen rintasyöpätapauksen analyysissä löytyi yhteensä seitsemän erilaista sekvenssimuutosta AATF-geenissä. Näistä yksikään ei kuitenkaan ollut selvästi patogeeninen. Tuloksen perusteella perinnölliset rintasyövälle altistavat muutokset AATF-geenissä ovat joko erittäin harvinaisia tai niitä ei esiinny lainkaan. MRG15-geenin mutaatioanalyysissä havaittiin seitsemän aikaisemmin raportoimatonta muutosta, mutta in silico -analyysien perusteella millään muutoksista ei ole vaikutusta MRG15-proteiinin toimintaan. Tulosten perusteella on epätodennäköistä, että MRG15-geenin muutokset olisivat merkittäviä rintasyövälle altistavia muutoksia. Jo aiemmin patogeeniseksi todettu PALB2 c.1592delT -mutaatio löydettiin kolmelta niistä perinnöllisyyspoliklinikan korkean syöpäriskin 62 potilaasta, jotka olivat BRCA1/2-geenitestauksessa saaneet normaalin tuloksen. Tulostemme perusteella PALB2 c.1592delT -mutaatiotestaus tulisi Suomessa ottaa osaksi perinnöllisyyspoliklinikoiden tarjomaa tutkimusprotokollaa. Suomalaisten Fanconi-anemiapotilaiden komplementaatioryhmiä selvittävässä tutkimuksessa identifioitiin yhteensä kuusi erilaista tautia aiheuttavaa mutaatiota. Näiden muutosten esiintymistä tutkittiin myös laajoissa rinta- (n=1840) ja eturauhassyöpäaineistoissa (n=565). Tilastollisesti merkittävää assosiaatiota ei kuitenkaan todettu suomalaisten FA-mutaatioiden ja syöpäalttiuden välillä. Asiasanat: AATF, DNA-korjaus, DNA-vauriovaste, Fanconin anemia, ituradan mutaatio, MRG15, PALB2, perinnöllinen rintasyöpäalttius, rintasyöpä 8 Acknowledgements This study was carried out at the Laboratory of Cancer Genetics, Department of Clinical Genetics, Biocenter Oulu, University of Oulu and Oulu University Hospital during 2008–2014. I wish to express my sincere gratitude to all those who participated in this project. My supervisor Professor Robert Winqvist is warmly acknowledged for giving me the opportunity to take my first steps in this fascinating scientific field and to learn so much about cancer research. As a member of his research group, I have had an excellent environment in which to do research. I greatly value his vast knowledge in the field. I am much obliged to my second supervisor Docent Katri Pylkäs; without her expertise and encouragement, I would not have completed this thesis. I especially appreciate her insights, honesty, and readiness to help. Docent Jukka Moilanen, Head of the Department of Clinical Genetics, and Professor Juha Risteli, Head of the Department of Clinical Chemistry, are acknowledged for their supportive attitude towards this PhD study. I also owe my sincere thanks to Jaakko Ignatius and Arja Jukkola-Vuorinen for being the most encouraging follow-up group ever. Every time we met, they had excellent comments and ideas for the future. The official referees Professor Helena Kääriäinen and Docent Pia Vahteristo are thanked for reviewing this thesis and for insightful suggestions for its improvement. My author-editor Carol Ann Pelli is acknowledged for precise language revision of the manuscript. MA Terttu Tatti is acknowledged for the Finnish language revision. My collaborators and co-authors Kristiina Aittomäki, Kristiina Avela, William Foulkes, Helmut Hanenberg, Jaana Hartikainen, A Kallioniemi, Hariet von Koskull, Veli-Matti Kosma, Marketta Kähkönen, Satu-Leena Laasanen, Arto Mannermaa, Katriina Parto, Carly Pouchet, Mervi Reiman, Thomas Rio Frio, Johanna Schleutker and Mark Tischkowitz are sincerely thanked for their valuable contributions to the research projects included in this thesis. I am ever so grateful to all my present and former group members for a supportive and helpful work atmosphere, for collaboration on various research projects and for excellent company: Muthiah Bose, Raman Devarajan, SannaMaria Karppinen, Tuomo Mantere, Jenni Nikkilä, Sini Nurmenniemi, Hellevi Peltoketo, Hannele Räsänen, Szilvia Solyom, Anna Tervasmäki, Mikko Vuorela. Furthermore, Meeri Otsukka, Helmi Konola, Leena Keskitalo and Annika Väntänen are thanked for fantastic technical assistance. Members of the 9 Laboratory of Clinical Genetics and the Department of Clinical Genetics are acknowledged for their assistance. I also thank other scientists and staff from the Kieppi building. This has been a progressive and open-minded place to work. I thank from the bottom of my heart all of my friends for cheering me on during the diffucult times. Their support and company over the years have been very important to me. Erja, Minna, Marja, and Heini; finally, here I am! I thank my dear friends Pauliina, Anna, Tiina, Elisa, Satu, Kisse, Irene, Erika, and many more for sharing with me a rewarding life beyond the field of medicine. To my large family, my aunts Lotta, Minna and Ulla, my mother-in-law Päivi, mummi, my sisters Noora and Tilli and brothers Kassu and Mikael and their wonderful spouses Antti, Toni, Sanna, and Elena, I express my deepest gratitude. You have supported me in my weakest moments. I am especially grateful to my parents Anna-Maija and Mikko for encouraging me to reach for the stars. I have always felt loved. Above all, my heartfelt thanks are owed to my extraordinary and wonderful husband Hannu for his unfailing support, help, and love. You, together with our three miracles Hugo, Mauno and Helka, are the most important things in my life. I love you! All patients and their family members who volunteered to participate in this study are warmly thanked; without you, these projects would not have been possible. Financial support from the University of Oulu, Oulu University Hospital, the National Graduate School of Clinical Investigation, the Cancer Foundation of Northern Finland, the Finnish Cancer Foundation, the Orion-Farmos Research Foundation, the Ida Montini Foundation, the Maud Kuistila Memorial Foundation, and the Emil Aaltonen Foundation is gratefully acknowledged. Turku, April 2014 10 Maria Haanpää Abbreviations aa AATF/CHE1 AML AT ATM ATR amino acid(s) apoptosis antagonizing transcription factor gene acute myelogenous leukaemia ataxia telangiectasia ataxia telangiectasia mutated gene/protein ataxia telangiectasia mutated and Rad3-related gene/protein BRCA1/BRCA1 breast cancer gene/protein 1 BRCA2/FAND1 breast cancer gene 2/gene for Fanconi anaemia subtype D1 BRIP1/BACH1/FANCJ BRCA1-interacting protein C-terminal helicase 1/ Fanconi anaemia subtype J BRCT BRCA1 carboxy-terminal domain CHK1/CHEK1 checkpoint kinase gene/protein 1 CHK2/CHEK2 checkpoint kinase gene/protein 2 chr chromosome CI confidence interval CSGE conformation-sensitive gel electrophoresis C-terminal carboxy-terminal DCIS ductal carcinoma in situ DDR DNA damage response DSB double-strand break ER oestrogen receptor ESE exonic splicing enhancer FA Fanconi anaemia fs frame shift GWAS genome-wide association study HER2/ERBB2 human epiderma growth factor reseptor 2 HNPCC hereditary non-polyposis colorectal cancer HR homologous recombination ICL interstrand crosslink IR ionizing radiation kb kilobase LOH loss of heterozygosity 11 MLH1, -3 MLPA MMC MMR MRE11 MRG15/MORF4L1 MSH2, -6 MSI NBS NBS1/NBS1 N-terminal OR p53/TP53 PALB2 PARP PCR PTEN SNP SSB 12 gene for DNA mismatch repair protein mutL homologue 1 and 3 multiplex ligation-dependant probe amplification mitomycin c mismatch repair gene for meiotic recombination 11 homologue mortality factor 4-like gene/protein 1 gene for DNA mismatch repair protein mutS homologue 2 and 6 microsatellite instability Nijmegen breakage syndrome Nijmegen breakage syndrome gene (nibrin) /protein amino-terminal odds ratio tumour suppressor gene/protein 53 partner and localizer of BRCA2 (FANCN) gene /protein poly (ADP-ribose) polymerase polymerase chain reaction phosphatase and tensin homologue gene/protein single-nucleotide polymorphism singe-strand break List of original publications This thesis is based on the following articles, which are referred to in the text by their Roman numerals: I Haanpää M, Reinman M, Nikkilä J, Erkko H, Pylkäs K & Winqvist R (2009) Mutation analysis of the AATF gene in breast cancer families. BMC Cancer 9(1): 457. II Rio Frio T*, Haanpää M*, Pouchet C, Pylkäs K, Vuorela M, Tischkowitz M, Winqvist R & Foulkes WD (2010) Mutation analysis of the gene encoding the PALB2-binding protein MRG15 in BRCA1/2-negative breast cancer families. J Hum Genet 55(12): 842–843. III Haanpää M, Pylkäs K, Moilanen JS & Winqvist R (2013) Evaluation of the need for routine clinical testing of PALB2 c.1592delT mutation in BRCA negative Northern Finnish breast cancer families. BMC Med Genet 14(1): 82. IV Mantere T*, Haanpää M*, Hanenberg H, Schleutker J, Kallioniemi A, Kähkönen M, Parto K, Avela K, Aittomäki K, von Koskull H, Hartikainen J, Kosma VM, Laasanen SL, Mannermaa A, Pylkäs K & Winqvist R (2014) Finnish Fanconi anemia mutations and hereditary predisposition to breast and prostate cancer. Manuscript. *Shared first authorship. In addition, some unpublished material is presented. 13 14 Contents Abstract Tiivistelmä Acknowledgements 9 Abbreviations 11 List of original publications 13 Contents 15 1 Introduction 17 2 Review of the literature 19 2.1 Cancer ..................................................................................................... 19 2.1.1 Genes in cancer development ....................................................... 21 2.2 General features of breast cancer ............................................................ 23 2.2.1 Epidemiology ............................................................................... 23 2.2.2 Clinical and molecular features .................................................... 24 2.3 Inherited predisposition to breast cancer................................................. 26 2.4 High-risk susceptibility genes ................................................................. 28 2.4.1 BRCA1 ......................................................................................... 29 2.4.2 BRCA2 ......................................................................................... 31 2.5 Other genes associated with increased risk of breast cancer ................... 33 2.5.1 High-risk cancer syndromes ......................................................... 33 2.5.2 Moderate-penetrance susceptibility genes .................................... 35 2.5.3 Breast cancer predisposition genes of uncertain risk .................... 40 2.5.4 Low-penetrance breast cancer predisposition alleles ................... 41 2.6 Susceptibility genes assessed in Finnish clinical genetics services......... 43 2.7 Searching for novel breast cancer susceptibility genes ........................... 43 2.8 Molecular pathways to maintain cellular integrity .................................. 46 2.8.1 DNA damage response pathway ................................................... 46 2.9 Fanconi anaemia ..................................................................................... 47 2.9.1 DNA crosslink repair by the Fanconi anaemia pathway............... 48 2.9.2 FA genes; FANCA, FANCG and FANCI ..................................... 50 2.10 Candidate genes for breast cancer predisposition based on their biological function .................................................................................. 52 2.10.1 AATF ............................................................................................ 52 2.10.2 MRG15 ......................................................................................... 53 3 Aims of the study 55 4 Materials and methods 57 15 4.1 Subjects ................................................................................................... 57 4.1.1 Study I .......................................................................................... 57 4.1.2 Study II ......................................................................................... 58 4.1.3 Study III ........................................................................................ 58 4.1.4 Study IV ....................................................................................... 59 4.2 DNA extraction ....................................................................................... 61 4.3 Mutation detection methods .................................................................... 61 4.3.1 Conformation-sensitive gel electrophoresis (I)............................. 61 4.3.2 High-resolution melt analysis (II, III, and IV) .............................. 61 4.3.3 Direct sequencing (I, II, III, IV) ................................................... 61 4.4 Mitomycin C sensitivity test and complementation group analysis (IV) ............................................................................................ 62 4.5 Statistical and bioinformatical analysis ................................................... 62 4.6 Ethical issues ........................................................................................... 63 5 Results 65 5.1 Mutation screening of the AATF gene (I) ................................................ 65 5.2 Mutation screening of the MRG15 gene (II) ........................................... 65 5.3 Clinical significance of PALB2 c.1592delT screening in BRCAnegative high-risk breast cancer families (III) ........................................ 66 5.4 Complementation groups of Finnish Fanconi anaemia patients and role of causative mutations in breast cancer susceptibility (IV) .......................................................................................................... 67 5.4.1 Finnish FA mutations prevalence in cancer cohorts ..................... 69 6 Discussion 71 6.1 No mutations found in the AATF gene among Finnish breast cancer families (I) ................................................................................... 71 6.2 MRG15 and hereditary predisposition to breast cancer (II) .................... 72 6.3 PALB2 c.1592delT mutation screening is clinically relevant in high-risk breast cancer patients tested negative for BRCA1/BRCA2 (III) ................................................................................ 73 6.4 Fanconi anaemia cases in Finland and breast cancer predisposition (IV) .................................................................................. 76 6.5 Finding the missing heritability of breast cancer susceptibility .............. 78 7 Concluding remarks and future prospects 81 References 83 Original publications 115 16 1 Introduction Cancer is one of the leading causes of morbidity and death in developed countries. It is a complex disease caused by a combination of genetic, epigenetic, and environmental factors. Up to every third individual develops cancer and every fifth dies from it. Breast cancer is the most common malignancy affecting women. Each year ~1.4 million women are diagnosed with breast cancer and around 500 000 breast cancer-related deaths are reported worldwide (American Cancer Society). In Finland, the respective figures are approximately 4700 new breast cancer cases and some 900 breast cancer-related deaths (Finnish Cancer Registry). Although the great majority of malignancies occur sporadically due to somatically acquired mutations, positive family history is one of the strongest predisposing factors for breast cancer. Around 5–10% of all breast cancer cases are caused by significant hereditary predisposition (Claus et al. 1996, Narod & Foulkes 2004, Parkin 2004). In familial cancer cases, the inherited genetic defects predispose to malignancy. Cancer predisposition can vary from weak to strong depending on the penetrance of the gene defect. (Ponder 2001.) The main indicators for hereditary disease predisposition are familial clustering of breast cancer, tumour development at an early age, bilateral disease, and occurrence of multiple primary tumours in the same individual (Barrett 2010, Marsh & Zori 2002). The major susceptibility genes involved in familial breast cancer are BRCA1 and BRCA2 (FANCD1) (Miki et al. 1994, Wooster et al. 1995). Mutations in these genes account for ~18% of all familial breast cancers (Lalloo & Evans 2012). These genes also predispose to ovarian cancer. A small portion of the familial breast cancer cases are due to gene mutations causing certain rare inherited cancer-predisposing syndromes: TP53 (mutated in Li-Fraumeni syndrome), PTEN (Cowden syndrome), LKB1/STK11 (Peutz-Jeghers syndrome), and CDH1 (hereditary diffuse gastric cancer-syndrome). Mutations in some other known susceptibility genes, including ATM, BRIP1 (BACH1/FANCJ), CHEK2, NBS1, and RAD50 as well as various low-risk factors account for a small fraction of the inherited component of breast cancer. However, mutations in the currently known breast cancer-predisposing genes explain only about 25–30% of the hereditary component. (Antoniou & Easton 2006, Stratton & Rahman 2008, Turnbull & Rahman 2008.) The search for additional candidate genes therefore remains critical. Most cancers contain hundreds or thousands of somatic mutations (Alexandrov et al. 2013, Vogelstein et al. 2013, Loeb 2001). Accumulation of 17 genetic changes leads to transformation of normal cells into cancer cells (Hanahan & Weinberg 2000, Nowell 1976, Ponder 2001). Epidemiological studies have shown that environmental and lifestyle factors, such as smoking, diet, and hormonal factors, increase cancer risk (Peto 2001). It has been suggested that the remaining unexplained breast cancer predisposition be attributed to a polygenic model together with environmental factors (Antoniou & Easton 2006, Stratton & Rahman 2008). Improved knowledge of both the role of cancer predisposition genes in normal tissue and malignancy and the additional hits that occur in many cases to promote tumorigenesis is anticipated to revolutionize the prevention and treatment of cancer by allowing therapeutic intervention at the molecular level (Marsh & Zori 2002). Most of the known breast cancer susceptibility genes are involved in the DNA damage response (DDR) pathway. Therefore, novel breast cancer predisposition genes might be revealed by investigating these genes further. Three principal strategies for identifying breast cancer predisposition factors are genome-wide linkage analysis, mutational screening of candidate genes, and association studies (Turnbull & Rahman 2008). The relatively isolated Finnish population with potentially fewer disease-predisposing genes than in populations of more heterogeneous origin is likely to offer some advantages in the search for additional low- and moderate-penetrance susceptibility genes. The aim of this study was to identify further susceptibility genes by searching for pathogenic mutations in the AATF and MRG15 genes. These genes were chosen based on their involvement in the DNA damage response and their interaction with known cancer susceptibility genes. The prevalence of the previously identified cancer-related PALB2 c.1592delT mutation was evaluated among high-risk breast cancer families identified at the Department of Clinical Genetics, Oulu University Hospital, and who had received genetic counselling for cancer susceptibility. The benefits of further genetic testing of these patients were explored. Finally, Finnish Fanconi anaemia mutations and their relation to breast cancer predisposition were investigated. 18 2 Review of the literature 2.1 Cancer Cancer is characterized by clonal expansion of cells that, become malignant via a series of genetic alterations (Fearon & Vogelstein 1990). These multiple somatic mutations usually affect genes involved in cell differentiation and proliferation. Through accumulation of genetic changes, the cells acquire properties typical of the cancerous phenotype. Hanahan and Weinberg (2000) have proposed six essential physiological changes, the hallmarks of cancer, which occur during the transformation of a normal cell towards a malignant one: self-sufficiency in signals stimulating growth, insensitivity to negative growth signals, evasion of programmed cell death (apoptosis), unlimited replicative potential, capacity for angiogenesis, and tissue invasion and metastasis. In addition, reprogramming of energy metabolism and avoiding destruction by the immune system have been suggested to represent other important qualities of malignant neoplasms. A normal cell also needs two enabling characteristics for tumorigenesis. These are genomic instability (generates random mutations) and an inflammatory state of premalignant and malignant lesions (allows cancer cells to evade immunological destruction). (Hanahan & Weinberg 2011.) These properties give cancer cells a growth advantage over the general cell population (Figure 1). 19 Evading growth suppressors Avoiding immune destrucon Deregulang cellular energecs Resisng cell death THE Sustaining proliferave signalling HALLMARKS Inducing angiogenesis Genome instability and mutaon OF CANCER Enabling replicave immortality Acvang invasion and metastasis Tumourpromong inflammaon Fig. 1. The six hallmarks of cancer appear with a white background, emerging hallmarks with a light grey background and enabling characteristics with a dark grey background. Modified from Hanahan & Weinberg 2000, Hanahan & Weinberg 2011. Cell growth is tightly controlled. Most somatic cells do not have the capacity to divide indefinitely. Based on epidemiological and in vitro experiments, common adult epithelial cancers, such as those of the breast, colorectum and prostate, have been estimated to require at least 5–7 mutations, while cancers of the haematological system may require fewer mutations. (reviewed in Hahn et al. 1999, Stratton et al. 2009, Vogelstein & Kinzler 1993.) Given the multiple defence mechanisms that protect cells from cancer development, this leads to a very low likelihood that a single cell will accumulate the requisite number of independent mutations needed for neoplastic transformation. Therefore, it has been suggested that certain mutations affect genomic stability, thus increasing the mutation rate in order for tumorigenesis to occur within the human lifespan. (Loeb 1991.) Indeed, the mutation frequency has been estimated to be up to 1000fold higher in tumour cells than in normal cells, and the mutation rate is particularly elevated in cancer predisposition syndromes, e.g. in patients with Fanconi anaemia (Araten et al. 2005, Seshadri et al. 1987). Mutations may also 20 result in increased cell proliferation, which would give the mutated cell a growth advantage relative to normal cells (Nowell 1976). Dynamic equilibrium between DNA damage and efficient DNA repair must be maintained; failure will result in malignant growth. Cancer cells can destabilize their genome in at least two different and independent ways: chromosomal instability, which means that most tumour cells have unusual karyotypes with abnormal numbers of chromosomes and many structural rearrangements, and less frequently, microsatellite instability (this was initially described in association with hereditary non-polyposis colorectal cancer, HNPCC) (Aaltonen et al. 1993, Read & Donnai 2001). The latter tumours are chromosomally normal, but DNA testing shows that the normal checks on the accuracy of DNA replication have been compromised (Gervaz et al. 2002). For instance, 21% of ovarian cancer patients with BRCA1 mutations have been reported to exhibit high microsatellite instability, whereas the corresponding proportion for patients with BRCA2 mutations is 6% (Segev et al. 2013). The changes from normal cell to cancer cell include both inactivation of tumour suppressor genes and activation of oncogenes, giving cells a growth advantage (Read & Donnai 2001). 2.1.1 Genes in cancer development Cancer genes can be divided into three categories: oncogenes, tumour suppressor genes and genome stability maintenance (also called caretaker) genes. Each somatic mutation in the cancer cell genome can be classified as either a driver or passenger mutation. Driver mutations are causally implicated in the process, whereas passenger mutations are incidental, irrelevant, and do not provide any particular clonal growth advantage. Mutations in oncogenes or tumour suppressor genes are mostly driver mutations. (Alexandrov et al. 2013, Stratton et al. 2009.) Oncogenes are mutated forms of normal cellular components, protooncogenes. Under normal conditions, proto-oncogenes stimulate cell growth and differentiation. Mutations in proto-oncogenes promote their function, providing cells with a growth advantage. Oncogenes were initially discovered in viral genomes, as they were able to transduce normal cellular genes to become constitutively active, thus inducing tumorigenesis. (Bishop 1981, Stehelin et al. 1976.) The protein products of proto-oncogenes are evolutionarily highly conserved. In human cancer, proto-oncogenes are activated through genetic alterations such as gain-of-function mutations (e.g. point mutations), gene 21 amplifications, and chromosomal rearrangements (Bishop 1991). At the cellular level, oncogenes act dominantly, meaning that mutation in one allele alone can enhance uncontrolled cell proliferation. Inherited mutations in oncogenes are, however, relatively rare, presumably because such mutations remove normal control over cell growth, thereby being lethal during embryogenesis (Frank 2001). Tumour suppressor genes are negative regulators of cell growth (Marshall 1991, Weinberg 1991). They regulate cell proliferation either by controlling cell division or by promoting programmed cell death. The loss-of-function mutations in tumour suppressor genes promote malignancy. The leading evidence for the presence of tumour suppressor genes emerged via studies on the childhood eye tumour retinoblastoma. Knudson (1971) suggested that two mutational events were required for retinoblastoma development. In hereditary cases, one mutation was inherited via the germline of an individual and the second one occurred at the somatic level. In the non-hereditary forms of the disease, by contrast, the two events were both somatic, and thus, less likely to occur. Tumour suppressor genes act recessively, i.e. both alleles need to be mutated. The second hit often involves a gross chromosomal mechanism, resulting in hemi- or homozygosity of the chromosomal region, which then leads to loss of heterozygosity (LOH). Such chromosomal events include deletion, gene conversion, non-disjunctional chromosome loss, and mitotic recombination. LOH can be detected by comparing the genotypes of the tumour and the corresponding normal tissue at a given polymorphic marker (Devilee et al. 2001). Some other possibilities for silencing of tumour suppressor genes are deletion of both alleles (i.e. homozygous deletion) or via epigenetic mechanisms such as transcriptional silencing through promoter hypermethylation. However, mutations in tumour suppressor genes are not always completely recessive since some alternate mechanisms exist. For instance, haploinsufficiency and dominant-negative mutations might require only a single hit. Haploinsufficiency occurs when one allele is insufficient to sustain the full functionality produced by two wild-type alleles (Wilkie 1994) Dominant-negative mutations alter the gene product in such way that it interferes with the function of the wild-type protein, inhibiting its cellular effect (Payne & Kemp 2005). Due to the growing number of tumour suppressor genes and knowledge about the functional roles of the gene products, these genes have been further defined and classified. Genes harbouring loss-of-function mutations can be classified as gatekeepers or caretakers depending on their putative role in the cellular processes (Kinzler & Vogelstein 1997). The latter are also known as genomic stability maintenance genes. Gatekeepers are thought to directly regulate tumour 22 growth by promoting cell death or inhibiting proliferation. In the multistep process of tumorigenesis, each cell type presumably has certain gatekeepers, the inactivation of which is rate-limiting for tumour initiation (Kinzler & Vogelstein 1997). In contrast to gatekeepers, caretakers inhibit tumour growth indirectly by maintaining genomic integrity (Kinzler & Vogelstein 1997). Mutations in caretaker genes increase genetic instability, leading to an elevated mutation rate in all genes, including tumour suppressor genes and oncogenes. Therefore, cancer development is accelerated. Caretakers include genes involved in DNA repair and replication such as mismatch repair (MMR) genes, and BRCA1 and BRCA2 genes (Kinzler & Vogelstein 1998). The former are responsible for recognition and repair of incorrectly paired nucleotides during normal replication (Fishel & Kolodner 1995) and the latter for mitotic recombination, chromosomal segregation, and maintenance of genomic integrity by homologous recombination-mediated DNA double-strand break repair (Farmer et al. 2005, Scully 2000). Normal functioning of genomic stability maintenance genes keeps the number of genetic alterations at the minimum. In addition to gatekeepers and caretakers, there is a third category of tumour suppressors called landscapers. Defects in the landscapers are speculated to contribute to neoplastic transformation by generating an abnormal stromal environment. The genetic defect is not in the transforming cell population itself but rather in adjacent stromal cells, which promotes malignancy of associated cells due to abnormal intercellular signalling. (Kinzler & Vogelstein 1998.) 2.2 General features of breast cancer 2.2.1 Epidemiology Breast cancer is the most common cancer and also the predominant cause of death from a neoplastic disease in women (Ferlay et al. 2013). The lifetime risk of breast cancer is one in eight females (Downs-Holmes & Silverman 2011). Worldwide, it is estimated that 1.38 million women are diagnosed with the disease each year, constituting about 23% of all cancer cases (Globocan 2008 2013). Breast cancer incidence shows marked geographical variation; it is much less common in Asian than Caucasian women. Nevertheless, it is the prevailing cancer in both developed and developing countries. In Finland, the proportion of breast cancer comprises approximately one-third (32.8%) of all female cancers 23 (Finnish Cancer Registry 2013). The annual number of new cancer cases diagnosed is on the rise. In 2011, a total of 4865 new breast cancer diagnoses were made. By the end of that year, some 57 000 individuals who had had breast cancer were still alive. Every year almost 900 breast cancer-related/caused deaths occur, i.e. the age-adjusted mortality rate is 14.6 per 100 000 person-years. The age-adjusted mortality rate has remained virtually unchanged since the 1950s (14–15/100 000 person-years). Thus, a relative decline in breast cancer mortality has been observed due to improved early diagnostics, following increased awareness and the implementation of the population-based mammography screening programme in 1987. The widespread administrations of adjuvant therapies have also supported the decrease in mortality rates. (Ferlay et al. 2013, Finnish Cancer Registry 2013, Mouridsen 1993.) The screening programme is currently directed to women aged 50–69 years and the examination is performed every other year. Almost 90% of invited Finnish women participate in the programme. (National Institute for Health and Welfare (THL) 2013.) 2.2.2 Clinical and molecular features The majority of breast cancer cases (81%) occur in women aged 50 years or over. The risk of breast cancer rises throughout a woman’s lifetime. Besides female gender, age, and family history of the disease, significant risk determinants include several reproductive and hormonal factors, such as early menarche, late menopause, late age at first childbirth, nulliparity or low number of children, short breast-feeding, use of oral contraceptives, and hormone replacement therapy, all of which increase the exposure of breast tissue to oestrogen (Barrett 2010). Oestrogens have an important role in the development and progression of breast cancer. Both direct and indirect mechanisms support oestrogen’s contribution to the initiation and promotion of breast cancer. Furthermore, some oestrogen metabolites have been reported to have genotoxic properties. Breast tissue acting as an intracrine organ with local oestrogen production may also play some role in carcinogenesis, but this is poorly understood (reviewed in Yaghjyan & Colditz 2011). Other breast cancer risk factors are postmenopausal obesity, poor nutrition, alcohol/tobacco consumption, lack of exercise, low socio-economic status, exposure to radiation, and a previous benign breast disease (Downs-Holmes & Silverman 2011, Folsom et al. 1990). Breast tumorigenesis is a multi-step process in which normal breast epithelium evolves via hyperplasia and carcinoma in situ into an invasive cancer. 24 About 95% of malignant breast tumours are carcinomas from the epithelium of the mammary gland. (Berg & Hutter 1995.) Histologically, the most common breast cancer tumours are infiltrating ductal (75%) and lobular (15%) carsinomas, and less common forms include medullar (1–7%), mucinous (1–2%), tubular (1– 2%), papillary (>1%) and inflammatory carcinomas. The different histological types have different prognoses. For example, lobular breast cancer has a slightly better prognosis than a ductal tumour. Of the rarer subtypes, tubular carcinoma is a well-differentiated carcinoma with an excellent prognosis, whereas rare inflammatory carcinoma has a poor prognosis. (Downs-Holmes & Silverman 2011, Li et al. 2003, Li et al. 2005.) The differentiation of the tumour cells defines the tumour histological grade. Grading is performed using the method by Bloom and Richardson (1957), subsequently modified by Elston and Ellis (1991). The histological grade is based on three features: tubule formation, nuclear pleomorphism, and mitotic count. Eventually, breast cancer stage becomes the most important prognostic factor, forming the basis for selecting patients for different treatment strategies. The staging is performed by TNM classification, which describes the size of the tumour (T), involvement of local lymph nodes (N), and distant metastasis (M). The routine pathological classification of a breast tumour also reveals lymphatic or vascular channel invasion, infiltration into skin, presence and amount of oestrogen (ER) and progesterone (PR) receptors, and expression of the HER2 (also called ERBB2 or NEU) protein. The proliferation rate of tumour cells and the expression of the tumour suppressor protein p53 are also frequently determined. (UICC 2013.) Based on mRNA microarray-based gene expression patterns, breast cancers are often divided into five molecular subtypes: luminal A, luminal B, HER2enriched, basal-like, and normal-like. These subtypes have preferential sites for distant relapse, and the subtype may also be associated with efficacy of systemic cancer therapies. The basal-like breast cancer type includes triple-negative breast cancer (ER-, PR-, HER2-negative), which shows more aggressive clinical behaviour, has the highest cell proliferation rates, and has a poor prognosis. This subtype accounts for 15% of all breast carcinomas. Most breast cancers belong to the luminal A (71%) and B (8%) subtypes, and these tumours are oestrogen- and progesterone receptor-positive and are associated with a more favourable prognosis since they have low cellular proliferation rates. (Hugh et al. 2009, Rouzier et al. 2005, Smid et al. 2008, Sorlie et al. 2001, Wiechmann et al. 2009.) 25 Although breast cancer incidence is increasing, the prognosis has improved, partly because of earlier diagnosis and partly as a result of the use of adjuvant therapies. Four types of standard treatments are used for breast cancer: surgery, radiation therapy, chemotherapy, and hormone therapy. Radiation therapy, chemotherapy, and hormone therapy are often used in conjunction with surgery. The five-year relative survival rate (RSR) is nowadays as high as 86% (Finnish Cancer Registry 2013). Breast cancer also occurs in males, albeit rarely. In 2011, a total of 17 new male breast cancer cases were diagnosed in Finland. This comprises 0.11% of all cancers in men (Finnish Cancer Registry 2013). Germline mutation of BRCA2 is the greatest known risk factor for male breast cancer. An estimated 13% of Finnish male breast cancer patients are BRCA2 mutation carriers. (Syrjäkoski et al. 2004.) 2.3 Inherited predisposition to breast cancer In 1948, Penrose and colleagues observed that in some families breast cancer may have a hereditary basis (Penrose et al. 1948). A genetic influence on breast cancer susceptibility is suggested by twin studies, as the concordance for breast cancer in identical twins (0.28) is more than twice that in dizygotic twins (0.12) (Petrakis 1977). Hereditary breast cancer is classified by a clustering of breast cancers in a family that is substantially higher than the observed incidence in the general population (average incidence in a standard Western population for breast cancer is 88.4/100 000 new cases per year (Globocan 2013). Other factors linked to hereditary breast cancer susceptibility are early disease onset, occurrence of bilateral breast cancer or multiple primary tumours in the same individual, or male breast cancer in the family. Familial breast cancer is usually seen in several generations in a pedigree. (Thull & Vogel 2004.) About 5–10% of breast cancers are caused by a hereditary predisposition to the disease, i.e. a strong familial background of breast and/or ovarian cancer exists (Claus et al. 1996, Narod & Foulkes 2004, Parkin 2004). Interestingly, genetic factors and inherited germline mutations may play a role in up to 27% (0.04–0.41 CI) of breast cancers according to data from the Nordic twin registries (Lichtenstein et al. 2000). First-degree relatives of a breast cancer patient have an approximately twofold risk for breast cancer compared with the general population; thus, positive family history is considered one of the strongest predisposing factors for breast cancer. The risk increases with the number of 26 affected relatives. (Collaborative Group on Hormonal Factors in Breast Cancer 2001, Thompson & Easton 2004.) Breast cancer susceptibility genes have been divided into three different classes: rare high-penetrance genes, rare intermediate/moderate-penetrance genes, and common low-penetrance genes. This classification has been made according to the level of breast cancer risk conferred and the prevalence of disease-causing mutations in the general population. According to the classification proposed by Stratton and Rahman (2008), high-penetrance genes confer a 10- to 20-fold relative breast cancer risk and the mutation frequency in the population is very low. Moderate-penetrance genes generally increase the risk 2- to 4-fold and the frequency is low, and finally, low-penetrance alleles usually confer 1.5-fold risk or less but their frequency in the general population is high. The level of penetrance describes the likelihood that an individual who carries a certain mutation will develop a disease due to its presence. Breast cancer susceptibility genes have been identified by genome-wide linkage analysis and positional cloning, mutation screening/next generation sequencing and genome-wide association studies (GWASs) (reviewed in Turnbull & Rahman 2008). Mutations in all of the currently identified susceptibility genes account only for about 25–30% of familial breast cancers (Ellsworth et al. 2010, Turnbull & Rahman 2008). Hence, much work is still needed to understand the genetic background of breast cancer. More than 70% of high-risk families for inherited genetic predisposition to breast cancer remain without an explanation (Figure 2). 27 Fig. 2. Affected genes in hereditary breast cancer. Modified from (Lalloo & Evans 2012, van der Groep et al. 2011). The polygenic theory of breast cancer susceptibility suggests that the residual unexplained familial cancer may be due to several genetic variants. Each variant alone may cause only a small and often undetectable increase in cancer risk, but together their effect could be sufficient to have a significant input on cancer development. These effects are also likely to be influenced by environmental and epigenetic factors. (Antoniou et al. 2003, Antoniou & Easton 2006, Pharoah et al. 2002.) 2.4 High-risk susceptibility genes Fortunately, mutations in high-penetrance genes at the population level are very rare (<0.1%) since they are associated with a very high breast cancer risk (up to 20-fold). An estimated 10–30% of all breast cancers are attributed to hereditary factors, but only 5–10% of the cases display a strong inherited component, and further, less than one-quarter (22%) of these heritable cases would be explained by mutations in high-penetrance genes transmitted in an autosomal dominant 28 manner (Apostolou & Fostira 2013, Ellsworth et al. 2010). The two most important high-risk genes are BRCA1 and BRCA2, together explaining about 16% of all familial breast cancers (Anonymous 2000, Peto et al. 1999). An example of a pedigree showing an apparently autosomal dominant susceptibility to breast cancer was first described already in 1866 by a French physician, Paul Broca, whose wife’s family contained 10 women in four generations who died of the disease (Broca 1866, Poumpouridou & Kroupis 2011). 2.4.1 BRCA1 By performing a genetic linkage analysis in 23 early-onset breast cancer families, the BRCA1 gene was first localized to chromosome 17q21 (Hall et al. 1990) and subsequently cloned (Miki et al. 1994). The pathogenic mutations in BRCA1 were found to account for about 7–10% of all familial breast cancers (Peto et al. 1999). BRCA1 consists of 24 coding exons and the 7.4 kb transcript encodes a protein of 1863 amino acids. BRCA1 does not have an apparent close homologue in the human genome, not even BRCA2, although both proteins share some characteristic structural features (Thompson & Easton 2004). Highly conserved functional motifs of BRCA1 include some important domains: the N-terminal RING finger domain and nuclear export signal (NES), two BRCT domains at the C-terminus, and a coiled-coil domain preceding the BRCT domains. (Caestecker & Van de Walle 2013, Koonin et al. 1996.) BRCA1 is associated with a series of protein complexes, and numerous proteins are known to bind to the functional domains of BRCA1. Its structure and the binding sites of interacting proteins are shown in Figure 3. The BRCA1 protein is involved in several important cellular pathways maintaining genomic stability, including double-strand break (DSB) repair by homologous recombination (HR), cell cycle checkpoint control, DNA replication, transcription regulation, nucleotide excision repair, protein ubiquitylation, and chromosome duplication, as well as histone deacetylation during chromatin remodelling. Indeed, BRCA1 is involved in several DNA repair pathways, including both DSB and single-strand break repair (reviewed in Wang 2012, Caestecker & Van de Walle 2013). BRCA1 appears to have an early role in the regulation and promotion of HR, which repairs DSBs and interstrand crosslinks (ICL). BRCA1 is phosphorylated in response to DNA DSBs by several kinases, e.g. ATM (ataxia telangiectasia mutated), CHK2, and/or ATR (ataxia telangiectasia Rad3-related). DNA damage triggers the ATM- and ATR-dependent 29 phosphorylation of H2AX (γH2AX), which is required for accumulation of numerous DNA damage response proteins into subnuclear foci at DSBs and for ensuring optimal repair. BRCA1 forms several different types of complexes at sites of damage. At least five different protein complexes are known. Core complex is formed by BRCA1 and BARD1 in the RING domain, which possesses E3 ubiquitin ligase activity. BRCA1 exists as a stable heterodimer with BARD1, and BARD1 is present in all BRCA1 complexes. BRCA1/PALB2/BRCA2 supercomplex is formed through binding of PALB2 with the coiled-coil domain of BRCA1, and it plays a role in homologous recombination-mediated DNA repair. BRCA1-A contains ABRAXAS, RAP80, NBA1/MERIT40, BRE/BRCC45, and BRCC36 proteins, and it is associated with ubiquitylated histones near the sites of DNA damage. The BRCA1-B complex includes BRIP1 and TOPBP1 and this complex is required for replication stress-induced checkpoint control and DNA interstrand crosslinks repair. The BRCA1-C complex consists of CtIP and the MRN (MRE11/RAD50/NBS1) proteins, and it senses DSBs and is responsible for DNA end resection. All three of these complexes (A, B, C) are formed through interactions with the BRCT domains of BRCA1. (Boulton 2006, Huen et al. 2010, Li & Greenberg 2012, Rosen 2013, Roy et al. 2011, Tutt & Ashworth 2002, Wang 2012, Welcsh et al. 2000.) The clinically important mutations of BRCA1 most often target the RING and BRCT domains, and the majority of the mutations are small frameshift insertions or deletions, resulting in prematurely truncated protein products. This means that this kind of mutation, if able to escape nonsense-mediated decay at the mRNA level, generates shortened, non-functional BRCA1 proteins that are far less stable and more susceptible to proteolytic degradation. (Caestecker & Van de Walle 2013, Narod & Foulkes 2004, Thompson & Easton 2004.) There are some founder mutations in specific populations, but generally a preponderance of BRCA1 mutations is rare, and they are reported to occur only in single families (~60% just once) (Thompson & Easton 2004, Turnbull & Rahman 2008). The average cumulative risk for breast cancer in BRCA1 mutation carriers by age 70 years has been estimated to be 65% (95% confidence interval 44–78%) and for ovarian cancer 39% (95% CI 18–54%). The relative risk of breast cancer peaks in the age group 30–39 years, declining thereafter, while ovarian cancer RR estimates show no apparent trend with age. On the other hand, breast cancer incidence in BRCA1 mutation carriers increases with age up to 45–49 years, remaining roughly constant thereafter. (Antoniou et al. 2003.) Bilateral cancer is common in BRCA1 mutation carriers. The estimated population frequency of 30 mutations in this gene is about 1/1000 per gene in the United Kingdom (Turnbull & Rahman 2008). BRCA1-associated breast cancers seem to be of a higher grade, displaying a high degree of pleomorphism and an elevated mitotic frequency. The tumours are often ER-, PR-, and HER2-negative, p53-positive, aneuploid, and of medullary histology. Tumours in BRCA1 carriers share a similar immunohistochemical profile to sporadic basal carcinomas. The data from different studies regarding prognosis of BRCA1-associated breast cancers are confusing, suggesting from better to worse outcome compared with sporadic cancers, although the association of basal cancer with poorer prognosis would support the hypothesis of worse prognosis for patients with BRCA1 mutation. (reviewed in Hodgson 2006, Lakhani et al. 2005, Lalloo & Evans 2012, Mavaddat et al. 2012.) Fig. 3. Schematic structure and interacting proteins of BRCA1 and BRCA2 (more details in the text). The interacting proteins are shown below the BRCA region required for their association (Roy et al. 2011). Presented with permission from the Nature Publishing Group. 2.4.2 BRCA2 The BRCA2 gene was first chromosomally localized by analysing 15 high-risk breast cancer families that did not show linkage to the BRCA1 locus. This 31 genome-wide linkage analysis mapped BRCA2 to chromosome 13q12-q13 in 1994, and the gene was cloned the following year (Wooster et al. 1994, Wooster et al. 1995). Pathogenic mutations in BRCA2 account for approximately 10% of all familial breast cancer cases (Anonymous 2000, Lalloo et al. 2003). BRCA2 is a large gene with 27 exons and spans about 70 kb of genomic DNA and encodes a protein of 3418 amino acids. BRCA2 contains eight BRC repeats between amino acid residues 1009 and 2083, and one DNA-binding domain, which contains a helical domain, three oligonucleotide binding folds, and a tower domain at the C-terminus (reviewed in Roy et al. 2011). The structure of BRCA2, showing also the binding sites of its interacting proteins, is presented in Figure 3. In contrast to the more peripheral roles of BRCA1 in regulation of the core HR machinery, BRCA2 plays a more central role in DNA repair via regulation of the activity of the RAD51 (Turner et al. 2005). BRCA2 has very important functions in DDR since it facilitates HR and is involved in DSB repair. BRCA2 binds to RAD51 through eight evolutionarily conserved RAD51 binding domains, termed the BCR repeats, and a separate motif located at its C-terminal domain. BRCA2 regulates the formation of RAD51 nucleoprotein filaments (Davies et al. 2001, Pellegrini et al. 2002, Sharan et al. 1997). RAD51 is a key protein that coats the processed single-stranded DNA overhangs of DSBs and promotes homologous pairing and strand invasion of these regions during homologous recombination (West 2003). BRCA2 can also bind to single-stranded DNA via a C-terminal domain, the structure of which is critical to the ability of BRCA2 to promote recombination. Following DNA damage and initial DSB processing, BRCA2 re-localizes to the site of DNA damage (Yu et al. 2003, Yuan et al. 1999). BRCA2 acts preferentially at the interface between double-stranded DNA and the MRN-processed single-stranded 3’ overhang to displace replication protein from the overhang and facilitate the loading of RAD51 (Yang et al. 2002, Yang et al. 2005). The RAD51 nucleoprotein filament subsequently catalyses the search for identical target sequences and strand invasion. Binding of RAD51 to BRCA2 is regulated by cell cycle (CDK)-dependent phosphorylation and appears to function as a “switch” controlling recombinational repair activity during the transition from S/G2 to M phase in the cell cycle (Esashi et al. 2005). The average cumulative risk of breast cancer for BRCA2 mutation carriers by age 70 years is 45% (95% CI 31–56%), and for ovarian cancer 11% (2.4–19%). The estimated relative risk of breast cancer among mutation carriers is highest in the youngest age group (20–29 years) thereafter decreasing, while the ovarian 32 cancer RR starts to increase from age 40 until age 59, then decreasing (Antoniou et al. 2003). In addition to breast and ovarian cancer predisposition, BRCA2 is also a Fanconi anaemia (FA) gene. Biallelic mutations in BRCA2 result in FA subtype D1 (OMIM 605724) (Howlett et al. 2002). (see Sections 2.7 and 2.8.2 for more detailed discussion). In contrast, biallelic BRCA1 mutations have been reported convincingly in humans only once, where a woman was diagnosed with earlyonset ovarian cancer and had validated deleterious biallelic mutations in the BRCA1 gene (Domchek et al. 2013). Earlier, it was presumed that biallelic BRCA1 mutations are embryonically lethal (Evers & Jonkers 2006). 2.5 Other genes associated with increased risk of breast cancer 2.5.1 High-risk cancer syndromes Breast cancer is also a component of several cancer syndromes, including LiFraumeni syndrome (OMIM 151623), Cowden syndrome (OMIM158350), and Peutz-Jeghers syndrome (OMIM 175200). These three syndromes are rare, with carrier frequencies <0.1% (Turnbull & Rahman 2008). They explain only around ~2% of the high-risk breast cancer cases, and these high-penetrance genes are associated with a breast cancer relative risk higher than 5 (Bradbury & Olopade 2007, Stratton & Rahman 2008, Thompson & Easton 2004). The p53 tumour suppressor gene, i.e. TP53, is mutated in the Li-Fraumeni syndrome (Malkin et al. 1990, Srivastava et al. 1990), which is characterized by the occurrence of multiple cancers, including childhood soft tissue sarcomas, osteosarcomas, leukaemia, brain tumours, adrenocortical carcinomas, and earlyonset breast cancer. Mutations in TP53 are found in approximately 70% of the LiFraumeni families and predisposition to this syndrome is inherited in a autosomal dominant manner (Malkin et al. 1990, Srivastava et al. 1990). Based on follow-up studies, the lifetime malignancy risk in female mutation carriers is higher and age at onset is lower than in male carriers (Kast et al. 2012, Ross & Hortobagyi 2005). On average, 30% of the female mutation carriers develop breast cancer by the age of 30 years (Malkin et al. 1990, Srivastava et al. 1990) and 50–60% are affected by the age of 45 years (Chompret et al. 2000). The lifetime penetrance of TP53 mutations for cancer approaches 100% (Bradbury & Olopade 2007). However, Li-Fraumeni syndrome accounts for less than 0.1% of all breast cancer cases 33 (Lalloo & Evans 2012). Although only a few germline mutations in TP53 contribute to hereditary breast cancer, somatic inactivation of TP53 in tumours is frequently identified. It is among the most frequently mutated genes in human cancer (Sengupta & Harris 2005). The TP53 gene is generally called the guardian of the genome. Inactivation of p53 prevents the initiation of apoptosis, thus contributing to the establishment and progression of malignancy (angiogenesis and invasion) (Muller & Vousden 2013). Knowledge of the TP53 mutational status could be important when predicting tumour response to radiotherapy (Mirzayans et al. 2012). Gene-profiling of tumour tissue for more precise selection of cancer treatment is already used in a private clinic in Finland (Docrates syöpäsairaala). Multiple hamartomatous lesions in a variety of tissues from all three embryonic layers, especially of the skin, mucous membranes, breast, thyroid, and endometrium are characteristic of Cowden syndrome. The syndrome has been described as early as in 1963 by Lloyd and Dennis (1963) and then PTEN (phosphatase and tensin homologue on chromosome 10) mutations were identified as causative in 1996 (Nelen et al. 1996). It is an autosomal dominant cancer susceptibility syndrome, and mutations of PTEN are found in over 80% of Cowden disease families (Mallory 1995, Nelen et al. 1996, Ross & Hortobagyi 2005). Women with Cowden syndrome have a 25–50% lifetime risk of developing malignant breast disease, with an average age of diagnosis between 38 and 46 years (Brownstein et al. 1978, Starink et al. 1986). Similarly to the TP53, germline mutations in PTEN are rare, but PTEN is frequently inactivated in sporadic cancers. The three most commonly sporadic cancers harbouring mutations in the PTEN gene are glioblastoma, prostate cancer and endometrial cancer (Chow & Baker 2006). PTEN is involved in the regulation of apoptosis and angiogenesis (Hobert & Eng 2009, Ross & Hortobagyi 2005). A serine-theorine kinase encoding the STK11/LKB1 gene (located at 19p13.3) has been found to be mutated in several families with Peutz-Jeghers syndrome (Hemminki et al. 1998). This is an autosomal dominant disorder characterized by multiple gastrointestinal hamartomatous polyps, mucocutaneous pigmentation (especially on the border of lips), and an increased risk for various neoplasms, including breast and gastrointestinal cancer. The cumulative risk for breast cancer was estimated to be 45% (27–68%) by the age of 70 years (Hearle et al. 2006). The function of STK11 is complex. It plays a role in cellular energy metabolism, regulates cellular proliferation, and influences cell polarity, cell growth and p53 mediated apoptosis (reviewed in Beggs et al. 2010). 34 Hereditary diffuse gastric cancer is caused by germline mutations in cell-tocell adhesion protein E-cadherin encoded by gene (CDH1), which is located at chromosome 16q22.1. (Guilford et al. 1998). Mutation carriers have a more than 70% lifetime risk of developing diffuse gastric cancer and a 39–52% risk of lobular breast cancer (Guilford et al. 2010, Kaurah et al. 2007, Pharoah et al. 2001). In cancer development, the most common mechanism of downregulation is promoter hypermethylation of the second copy of the CDH1 gene (Guilford et al. 2010). Loss of E-cadherin affects the maintenance of cell architecture and results in an abnormal orientation of the mitotic spindle (Humar & Guilford 2009). 2.5.2 Moderate-penetrance susceptibility genes Moderate-risk variants have been estimated to account for about 5% of excessive familial breast cancer risk. Carriers of moderate- (also called intermediate-) penetrance alleles have a two- to four-fold risk of developing breast cancer compared with the general population riks of 10% (Hollestelle et al. 2010, Stratton & Rahman 2008). The prevalence of the variants is usually rare, i.e. they have ~1% frequency in the general population, but it varies widely among different geographical or ethnic populations. In contrast to high-risk genes, moderate-risk breast cancer alleles typically have a limited number of variants that confer breast cancer risk. Inheritance of moderate-risk alleles will not cause a highly penetrant disease pattern among families, and therefore, inheritability is not necessarily easy to recognize. Moderate-risk breast cancer genes identified thus far have been discovered through candidate gene association studies, involving evaluation of putative breast cancer genes in cohorts of hundreds of cases and controls. (Hollestelle et al. 2010.) To date, six moderate-risk breast cancer genes have been identified: CHEK2, ATM, BRIP1, NBS1, RAD50, and PALB2. On average, mutations in these genes confer a relative cancer risk between 1.5 and 5, the typical increase in risk being 2- to 3-fold. However, some of them might also harbor mutations that confer higher increased risks, e.g. PALB2 which mainly confers a 2- to 6-fold increased risk, or even higher (Byrnes et al. 2008, Shuen & Foulkes 2011, Southey et al. 2010, Turnbull & Rahman 2008, Walsh & King 2007). The CHEK2 (checkpoint kinase 2) gene is located on chromosome 22q12.1 and encodes a cell cycle checkpoint kinase, which is a key mediator in the DNA damage response. This kinase is responsible for arresting mitosis in response to DNA damage by phosphorylating a number of proteins involved in cellular 35 checkpoint control, including BRCA1, p53, and CDC25C. (Matsuoka et al. 1998, Shuen & Foulkes 2011, Wu et al. 2001.) A founder mutation, 1100delC, which abrogates the kinase domain, has been discovered in Northern European populations (Meijers-Heijboer et al. 2002, Vahteristo et al. 2002). This mutation is associated with a 2.34-fold risk of breast cancer (CHEK2 Breast Cancer CaseControl Consortium 2004). However, a meta-analysis has shown that a carrier of a CHEK2 mutation with a strong family history of breast cancer is at comparable risk of breast cancer to BRCA carriers: an estimated lifetime risk of 37% (Weischer et al. 2008). The ATM (ataxia telangiectasia mutated) gene is located on chromosome 11q22.3 and encodes a checkpoint kinase that plays a role in DNA DSB sensing and signalling. ATM also regulates several tumour suppressors, including p53, BRCA1, and CHEK2. Biallelic (homozygous or compound heterozygous) mutations in this gene are linked to a rare human autosomal recessive disorder called ataxia telangiectasia (AT), which is characterized by progressive cerebellar ataxia, a weakened immune system, hypersensitivity to ionizing radiation, highly increased susceptibility to malignancies, primarily of lymphoid origin, and distinctive dilated blood vessels in the eyes and skin (telangiectasia). (Ahmed & Rahman 2006, Easton 1994, Savitsky et al. 1995, Swift et al. 1976, Thompson et al. 2005.) A heterozygous mutation of ATM does not lead to the AT phenotype, but carriers have an approximately 2.37 relative risk of breast cancer (Renwick et al. 2006, Thompson et al. 2005). Markedly higher risks, up to 15-fold, have also been reported (Chenevix-Trench et al. 2002, Pylkäs et al. 2007). There are many ATM variants that confer a breast cancer risk, including not only all truncating variants but also a variety of missense variants (reviewed in Hollestelle et al. 2010). In the Finnish population germline mutations in ATM have an apparent but limited contribution to familial and sporadic breast cancer predisposition outside AT families (Pylkäs et al. 2007). The gene mutation’s penetrance is approximately 15%, but accurate prediction of which mutation carriers will develop breast cancer is not feasible (Apostolou & Fostira 2013), similar to all other currently known predisposing genes. The BRIP1/BACH/FANCJ gene (BRCA1-interacting protein C-terminal helicase 1) is located in chromosome 17q22-q24 and encodes a DEAH helicase that interacts directly with BRCA1 C-terminal BRCT repeats and has BRCA1dependent roles in DNA repair and checkpoint control (Cantor et al. 2001, Peng et al. 2006). In 2006, truncating BRIP1 mutations were identified in breast cancer families (Seal et al. 2006). Heterozygous female carriers of truncating BRIP1 36 mutations have an approximately two-fold increased breast cancer risk, with higher risks for women younger than 50 years. As expected for a moderate-risk gene, co-segregation of the mutation with the breast cancer phenotype is incomplete (Hollestelle et al. 2010, Seal et al. 2006). BRIP1 germline mutations also confer an increased risk of ovarian cancer (Rafnar et al. 2011). Concurrently, it emerged that biallelic mutations in BRIP1 result in Fanconi anaemia complementation group J (OMIM 609054). This phenotype is different from that caused by biallelic mutations in BRCA2, resulting in a much lower rate of childhood solid tumours (Levitus et al. 2005, Levran et al. 2005, Litman et al. 2005). The MRE11-RAD50-NBS1 (MRN) protein complex plays an important role in primary sensing and early processing of DSBs by promoting ATM’s localization to DSB sites to initiate the DNA damage response. This protein complex integrates DNA repair with checkpoint signalling through ATM, BRCA1, and CHEK2 proteins. (Bartkova et al. 2008, Lavin 2007, reviewed in DzikiewiczKrawczyk 2008). Biallelic hypomorphic germline mutations of NBS1 manifest as Nijmegen breakage syndrome (NBS) (OMIM 251260). NBS is a rare autosomal recessive disorder characterized by microcephaly, immunodeficiency, and increased predisposition to malignancies, especially leukaemia and lymphoma at a young age. Relatives of NBS patients carrying heterozygous mutations are also more prone to cancer development, including breast cancer. (Seemanova 1990, Seemanova et al. 2007.) Mutations in MRE11 lead to an ataxia-telangiectasia-like disorder (OMIM 604391), which is a very rare autosomal recessive disease with ocular apraxia and ataxia in infancy (Palmeri et al. 2013). In contrast to NBS1 and MRE11 mutations, so far only one patient has been reported with biallelic hypomorphic mutations in RAD50. This patient exhibited phenotypes similar to NBS (Lamarche et al. 2010). All three MRN complex genes are suggested to have a role in breast cancer susceptibility. NBS1 variants have been found to be associated with an increased risk of developing cancer; the Slavic founder mutation NBS1 657del5 is particularly implicated in predisposition to breast cancer. It is associated with a 3.1-fold enrichment among breast cancer cases relative to those without the allele (Bogdanova et al. 2008, di Masi & Antoccia 2008, Steffen et al. 2006). For RAD50, the Finnish 687delT founder mutation has been reported to be associated with a 4.3-fold increased breast cancer risk in allele carriers (Heikkinen et al. 2003, Heikkinen et al. 2006). By contrast, the role of MRE11 in breast cancer remains unclear. The potential clinical relevance of the MRE11 and the whole MRN complex in human breast cancer is highlighted by 37 the observation that a subset of basal-like human breast cancers has markedly reduced expression/loss of MRN-complex proteins. Subsequent sequencing of the MRN genes from the tumours of altogether eight patients revealed two germline mutations in the MRE11 gene (Bartkova et al. 2008). However, more studies are needed to determine the role of MRE11 as a breast cancer susceptibility gene. PALB2 PALB2 (partner and localizer of BRCA2) was first identified through its interaction with BRCA2. The PALB2 gene is located in chromosome 16p12 and it consists of 13 exons, which encodes a protein of 1186 amino acids (Xia et al. 2006). The PALB2 structure, starting from the N-terminus, contains a coiled-coil domain, which directly binds to BRCA1 (aa 9-44), followed by two DNA binding sites (P2T1 and P2T3), and a ChAm (chromatin-association) binding motif. Seven WD40-repeats interact with BRCA2 (aa 853-1186), whereas the interaction with RAD51 is mediated through two different molecular sites: aa 1-200 and aa 836-1186. (Bleuyard et al. 2012, Buisson et al. 2010, Dray et al. 2010, Livingston 2009, Oliver et al. 2009, Sy et al. 2009b, Sy et al. 2009c, Zhang et al. 2009a, Zhang et al. 2009b.) PALB2 participates in the regulation of the nuclear functions of BRCA2. Particularly, it promotes the stable intranuclear localization or accumulation of BRCA2, which facilitates BRCA2 functions in homologous recombination or DSB repair and the S phase checkpoint. BRCA2 localization to the damaged sites actually occurs via a PALB2-BRCA1 interaction; thereby PALB2 physically links BRCA1 and BRCA2 proteins to form a “BRCA” supercomplex. BRCA1 has been shown to be an upstream regulator of both PALB2 and BRCA2 in DDR, as BRCA1 promotes their concentration at the sites of DNA damage. Overall, the association between BRCA1 and PALB2 is important for HR-mediated DBS repair, and PALB2 is essential for key nuclear caretaker functions of BRCA2, since it ensures proper BRCA2 nuclear presence. (Sy et al. 2009b, Xia et al. 2006, Zhang et al. 2009a, Zhang et al. 2009b.) Different studies have identified MRG15 as a component of certain chromatin remodelling complexes that bind to PALB2 and have also suggested that this interaction is required for recruiting the entire BRCA supercomplex to the damage sites (Hayakawa et al. 2010, Sy et al. 2009a). Germline mutations in PALB2 are associated with an increased risk of breast cancer (Erkko et al. 2007, Rahman et al. 2007). Mutations have been identified in approximately 1% of hereditary breast cancer families throughout the world. 38 However, the frequencies vary in different populations, ranging from 0.1% to 2.7%, and the average penetrance of deleterious PALB2 mutations is not known with certainty (Tischkowitz & Xia 2010). One of the first two studies showing an association between germline mutations in PALB2 and breast cancer estimated the relative risk to be 2.3. Interestingly, the risk in carriers appeared relatively higher in patients diagnosed at a younger age, but this requires confirmation with additional studies. (Rahman et al. 2007.) A simultaneously published Finnish study suggested that the risk conferred by PALB2 mutations might be significantly higher (Erkko et al. 2007). In support of the Finnish study, a study from Australia reported the hazard ratio of the PALB2 c.3113G>A mutation to be as high as 91% (95% CI 44–100%) by age of 70 years (Southey et al. 2010). Most pathogenic PALB2 mutations detected so far are truncating frameshift or stop codons and are scattered throughout the entire gene region with no hot-spot areas (Poumpouridou & Kroupis 2011). Except for the founder mutations, PALB2 alterations appear to be individually rare and may confer only a small fraction of the familial risk of breast cancer. PALB2 mutations have also been associated with familial pancreatic cancer (Jones et al. 2009). Analogous to BRCA2, PALB2 is also a Fanconi anaemia gene. Soon after PALB2 was discovered, biallelic mutations were identified in eight FA families, which identified PALB2 as a FA gene, named FANCN, causing FA subtype N (FAN). The phenotypes of FA-N and that caused by BRCA2 mutations (FA-D1) are very similar and can be distinguished from classical FA by markedly elevated frequency of early childhood solid tumours such as Wilms’ tumour and medulloblastoma. (Reid et al. 2007, Xia et al. 2007.) The similarity of phenotypes of FA-D1 and FA-N individuals could reflect the close functional relationship that exists between BRCA2 and PALB2, both having vital roles in HR repair, with dysfunction in either one of these proteins leading to fundamental defects in DSB repair, a feature that is not consistent with other FA subtypes. (Reid et al. 2005, Reid et al. 2007.) PALB2 1592delT mutation Several studies worldwide have demonstrated that monoallelic truncating PALB2 mutations are associated with breast cancer susceptibility (Cao et al. 2009, Foulkes et al. 2007, Garcia et al. 2009b, Rahman et al. 2007, Southey et al. 2010). In Finland, one recurrent PALB2 mutation has been reported (Erkko et al. 2007). The prevalence of this PALB2 c.1592delT founder mutation has been 39 approximated to be 1% in unselected breast cancer cases and 2.6% in those with a strong history of breast cancer in the family (Erkko et al. 2008, Heikkinen et al. 2009). The key function of PALB2 is to interact with BRCA2 and to facilitate appropriate communication between BRCA1 and BRCA2 (Hamel et al. 2008, Zhang et al. 2009b), which is apparently disturbed by c.1592delT (Nikkilä et al. 2013). PALB2 c.1592delT is a loss-of-function mutation that, results in a truncated protein product with reduced stability, and consequently, the full-length PALB2 protein levels are significantly decreased in mutation carrier cell lines. Using an epitope-tagged version of the protein, the truncated protein caused by c.1592delT was also shown to have markedly decreased BRCA2-binding affinity. (Erkko et al. 2007, Erkko et al. 2007, Nikkilä et al. 2013.) 2.5.3 Breast cancer predisposition genes of uncertain risk Additional genes associated with hereditary breast cancer predisposition are constantly emerging, but how much they contribute to the actual risk of developing the disease is uncertain. RAD51C is a part of a complex composed of five RAD51 paralogues (RAD51B, RAD51C, RAD51D, XRCC2, XRCC3) involved in DNA repair in both the initial and late stages of HR (Somyajit et al. 2010). A recent study identified biallelic mutations in RAD51C that lead to FAlike disorder (Vaz et al. 2010), and this was followed by a study reporting monoallelic RAD51C mutations associated with increased risk of breast and ovarian cancer (Meindl et al. 2010). In the initial report by Meindl et al. (2010) RAD51C germline mutations were identified in 1.3% of families with both breast and ovarian cancer, but mutation frequency has been varied in subsequent replication studies performed in different populations. Some follow-up studies have identified rare deleterious mutations among breast and/or ovarian cancer families, while others have not found any clearly pathogenic mutations. The level of penetrance has also varied depending on the RAD51C mutation (Akbari et al. 2010, Levy-Lahad 2010, Meindl et al. 2010, Pelttari et al. 2011, Romero et al. 2011, Thompson et al. 2012, Vuorela et al. 2011, Zheng et al. 2010). Based on the numerous studies, the current view is that the prevalence of RAD51C mutations, with the potential exception of founder mutations, is low in the general population. RAD51C mutations have been speculated to significantly increase the risk of ovarian cancer, but not breast cancer, in the absence of ovarian cancer family history, indicating that RAD51C is the first moderate-penetrance susceptibility 40 gene for ovarian cancer. (De Leeneer et al. 2012, Le Calvez-Kelm et al. 2012, Loveday et al. 2012, Osorio et al. 2012, Pelttari et al. 2012, Walsh et al. 2011.) The role of the mismatch repair genes (MHL1, MSH2, MSH6, PMS1 and PMS2) in breast cancer predisposition is still a matter of debate. It is unclear whether mutations in any of these genes confer to an increased risk to breast cancer and if that would be the case, how strong the effect would be. They play a significant role in hereditary non-polyposis colorectal cancer, i.e. Lynchsyndrome (Shanley et al. 2009), but only marginally increase the risk of breast cancer over the population risk in HNPCC patients (Geary et al. 2008). RAP80 and ABRAXAS genes occur in a complex with BRCA1 (BRCA1-A) and they have a critical function in the localizing of BRCA1 to DNA damage foci. (Akbari et al. 2009, Novak et al. 2009, Osorio et al. 2009). Some studies have identified rare mutations in both of these genes that predispose to breast cancer (Nikkilä et al. 2009, Solyom et al. 2012), but these observations have not been replicated (Novak et al. 2009). Neurofibromatosis type 1 (NF1) is another debatable gene. NF1 is a common autosomal dominant disorder characterized by café-au-lait spots, intertriginous freckling and neurofibromas (OMIM 162200) (Rasmussen & Friedman 2000, Sorensen et al. 1986). Reports of an association between NF1 and breast cancer are uncommon. One study suggests that female patients have almost a 5-fold excessive risk of developing breast cancer by the age of 50 years (Sharif et al. 2007). However, few cases have been reported with a combined diagnosis of NF1 and breast cancer due to mutations in both NF1 and BRCA1 genes in the same individual (Campos et al. 2013). In conclusion, further population-based studies are needed to better understand the role of all of these genes in breast cancer predisposition. 2.5.4 Low-penetrance breast cancer predisposition alleles Common low-penetrance alleles comprise the third major group of the landscape of breast cancer susceptibility. They confer very small increases in disease risk, up to 1.5 RR, but their heterozygote allele frequencies are high, ranging from 10% to 90% in the general population (Pharoah et al. 2008, Turnbull & Rahman 2008). The currently known low-penetrance susceptibility alleles were discovered through association studies, either targeted at individual genes on the basis of biological candidacy or, more recently (from 2007), through genome-wide tag SNP searches. A genome-wide association study (GWAS) is a large study that 41 compares the genotype frequencies of hundreds of thousands of common variants distributed throughout the genome between cases and controls in order to identify alleles associated with disease risk. GWASs have thus diminished the need for a good biological understanding of important genes before a disease association can be detected. This approach has identified common genetic variants that confer low-penetrance susceptibility to a variety of different cancers, including breast cancer. (Pennington & Swisher 2012, Trainer et al. 2011) Common variants at 27 loci have been identified to be associated with breast cancer susceptibility. In a very recent study, Michailidou et al. (2013) report a meta-analysis of 9 genome-wide association studies, including altogether 10 052 breast cancer cases and 12 575 controls. SNPs for further genotyping were collected from 41 different studies in the Breast Cancer Association Consortium (BCAC). SNPs selected from large multistage GWASs, SNPs selected for fine mapping of known susceptibility loci, functional candidate SNPs, and SNPs related to other traits were included in this study. The iCOGS array comprised 211 155 SNPs, and data were obtained for 199 961 SNPs after quality control exclusion. This study identified SNPs at 41 new breast cancer susceptibility loci, and based on pre-allele OR estimates these loci explain approximately 5% of the familial risk of breast cancer. (Michailidou et al. 2013). Most of the breast cancerassociated SNPs identified did not reside in the coding regions, unlike highpenetrance mutations, which would be expected to alter the amino acid sequence directly or through regulation of splicing. However, some of the SNPs appear to be associated with an individual gene, many of which have known functions consistent with a role in breast tumorigenesis, such as growth regulation (FGFR2, MAP3K1), DNA repair (RAD51L), apoptosis (CASP8), or hormone signalling (ESR1). For about half of the reported disease risk, associated SNPs occur a long way from any obvious candidate gene, often in regions described as gene deserts. However, further investigations of individual loci have provided initial evidence that these variants may have an effect on long distance chromatin interactions, which in turn can influence gene-expression several hundred kilobases away from the variant site. (Easton et al. 2007, Maxwell & Nathanson 2013, McClellan & King 2010, Pomerantz et al. 2009, Stacey et al. 2007, Trainer et al. 2011.) The low-risk susceptibility alleles detected through GWASs and targeted SNP arrays represent an entirely distinct group from high- and moderate-penetrance alleles. According to the polygenic model, these variants can act synergistically with environmental or lifestyle factors, and together these variants account for a modest fraction of familial breast cancer cases. Current studies reveal that the 42 known common low-risk variants constitute ~9% of the familial risk of the disease. (Latif et al. 2010, Mavaddat et al. 2010, Michailidou et al. 2013, Turnbull et al. 2010.) 2.6 Susceptibility genes assessed in Finnish clinical genetics services Nowadays, when a person with a conspicuous family history of breast and ovarian cancer comes to a Department of Clinical Genetics for genetic counselling, the first step is to draw the pedigree and then verify all cancer cases in the family (to gather the PAD of the tumour and age of diagnosis). If the family fulfils “the Lund criteria” the probability of finding an inherited mutation in BRCA genes can be computed by a specific program (Vahteristo et al. 2001). If this probability is greater than 10%, molecular analysis is offered to the youngest affected family member as part of genetic counselling. The gene test includes sequencing and MLPA (multiplex ligation-dependent probe amplification) to detect large deletions and duplications (Schouten et al. 2002)) for BRCA1 and BRCA2 genes. If the result is negative for these two susceptibility genes, usually no further genetic testing for additional rare cancer predisposing syndromes (e.g. Li-Fraumeni) is offered in Finland, unless indicated by specific findings or family history (i.e. specific spectrum of different cancer types). Some clinics have continued gene tests for research purposes and have uncovered mutations in, for example, CHEK2 and PALB2 genes. 2.7 Searching for novel breast cancer susceptibility genes Genome-wide linkage analyses using large numbers of families without mutations in BRCA1 and BRCA2 have not mapped additional susceptibility loci (Smith et al. 2006). This does not completely exclude the existence of further high-penetrance breast cancer susceptibility genes, but it strongly suggests that, if they exist, they only account for a very small fraction of familial risk (Stratton & Rahman 2008). Some years ago, a popular hypothesis was that a large proportion of the familial cancer risk unaccounted for by known high-penetrace cancer genes would be explained by common genetic variants of low penetrance (polygenic model). Interestingly, although GWASs have identified several low-penetrance SNPs, they explain only a small fraction of familial breast cancer risk (Goldstein 2009). One explanation for the remaining familial cases is that many uinique or very rare 43 mutations exist with moderate or even high penetrance in a variety of genes (McClellan & King 2010). In order that the remaining ~70% of familial breast cancer cases could be explained, further research is necessary. Disease-causing mutations in moderate-penetrance breast cancer susceptibility genes do not generally result in large pedigrees with multiple breast cancer cases, and because their segregation with the disease is incomplete, such susceptibility genes are not easily mapped by genetic linkage analysis. Moreover, uncommon disease-causing alleles are unlikely to be detected by association studies since they exist only in a small number of families. (Stratton & Rahman 2008.) (Figure 4) Fig. 4. Relation of risk allele frequencies, effect sizes (odds ratios) and feasibility of identifying risk variants by common genetic techniques. Generally linkage studies are better for identifying low-frequency alleles with larger effect sizes, whereas association studies are more effective for identifying common variants with small to moderate effects. Current evidence suggests that the residual genetic susceptibility is likely to be due to variants at many loci, each conferring a moderate risk of disease. Candidate gene approaches are likely to fill a large gap in our knowledge if the genetic basis of cancer. Modified from (Zemunik & Boraska 2011) and breast cancer susceptibility genes from (Foulkes 2008). According to present knowledge, common variants with major effects do not exist in breast cancer. 44 One successful strategy for the identification of additional susceptibility factors is a candidate-gene approach, i.e. direct interrogation of genes believed to be strong candidates on the basis of their biological plausibility (Pasche & Yi 2010). Since most of the moderate-risk genes discovered so far are involved in DNA damage response, it is important to investigate DNA repair pathways further in order to find more novel breast cancer susceptibility candidate genes (Meindl 2009, Ralhan et al. 2007). Advanced genomic technologies have completely changed the approach to determining genetic components that constitute traits in breast cancer. Nextgeneration sequencing techniques are continuously being developed. Massive parallel sequencing can be applied to whole-genome, exome and more targeted approaches. Exome sequencing focuses on the 1% of the genome that consists of protein-coding exons and does not require a priori knowledge of which genes are important. (Pennington & Swisher 2012.) As certain disease alleles are known to be enriched in isolated populations (founder mutations), the use of the genetically relatively homogeneous Northern Finnish population should offer advantages in the search for genes associated with familial breast cancer. In addition, identification of new inherited breast cancer susceptibility gene mutations and translation of the research results into clinical utilization may, in the future, impact patients’ treatment strategy and aid in the identification of individuals who will selectively benefit from targeted therapies for their malignancy (Francken et al. 2013). In 2005, potent PARP [poly (ADP-ribose) polymerase] inhibitors were shown to selectively inhibit the growth of cells with defects in either BRCA1 or BRCA2 genes (Lord & Ashworth 2012). Later, the same effect was found for PALB2deficient cells (Buisson et al. 2010). The best-understood role of PARP1 protein is in SSB repair. In normal cells, the effects of PARP inhibition are buffered by homologous recombination, which repairs the resultant DSB. However, effective HR is reliant on functioning BRCA1, BRCA2, and PALB2. When these genes are defective, as they commonly are in tumours of germline mutation carriers, at least in the case of BRCA1 and BRCA2, DSB are left unrepaired and potent PARP inhibitors can cause cell death. This gave rise to a new use for these agents; they are selectively tumour-cytotoxic in BRCA1, BRCA2, and PALB2 mutation carriers. (Bryant et al. 2005, Farmer et al. 2005, Fong et al. 2009, Lord & Ashworth 2012, Tutt et al. 2010.) 45 2.8 Molecular pathways to maintain cellular integrity In normal regenerative tissues, cells grow and divide in response to a myriad of cues. The outer membrane of most cells is in direct contact with the extracellular matrix, fluid, and neighbouring cells. Regulatory signals also arise from intracellular sources. The sequential stages of the cell cycle, particularly S-phase and mitosis, are exquisitely sensitive to damaged chromosomes and to stalled DNA replication forks. Mutations in cancer genes affect the responses of cells to changes in their internal and external environments. Different types of DNA damage are repaired by distinct multiprotein complexes, because the prime objective for every life form is to deliver its genetic material intact and unchanged to the next generation. Each of the ~1013 cells in the human body receives tens of thousands of DNA lesions every day, and if these are not repaired correctly they can lead to mutations that can threaten cell viability. (Bunz 2008, Jackson & Bartek 2009, Lindahl & Barnes 2000.) 2.8.1 DNA damage response pathway A functional DNA damage response pathway is absolutely essential for cell viability. Different types of DNA damage are SSBs and DSBs, DNA-protein cross-links, and damaged bases. Diverse pathways function to repair different types of damage. In mammalian cells, at least four main pathways of DDR exist: nucleotide excision repair (NER), base excision repair (BER), homologous recombination (HR) and non-homologous end-joining (NHEJ). (Bekker-Jensen & Mailand 2010, Hoeijmakers 2001.) The DDR mechanisms encompass pathways of DNA repair, which are relatively lesion-specific. NHEJ and HR are the most important pathways for solving the DSB problem. The repair of DSBs can also include alternative-NHEJ and single-strand annealing (SSA) (Ciccia & Elledge 2010, Price & D'Andrea 2013). NHEJ, which is less accurate than HR, has a dominant role in the G1 phase of the cell cycle, when an intact sister chromatin template is not available and the broken DNA ends are simply ligated together in an efficient but error-prone fashion. More precise error-free HR is used predominantly in late S phase and G2, concomitantly with the appearance of the sister chromatid as a template for the repair. (Downs et al. 2007, Harper & Elledge 2007, McKinnon & Caldecott 2007.) Central to the signal transduction pathways are two phosphatidylinositol 3kinase-like kinases (PIKKs), which transmit the damage response signal through 46 phosphorylation. These signal transduction pathways can activate cell cycle checkpoint arrest or apoptosis. Checkpoints occur at the entry into S phase (the G1/S checkpoint), at the entry into mitosis (the G2/M checkpoint) and during replication (intra-S-checkpoints), thus preventing duplication and segregation of damaged DNA. (Abraham 2004, Kurz & Lees-Miller 2004, Lukas et al. 2004, Shiloh 2003.) Proteins responsible for DSB repair can be categorized into four different groups: DNA damage sensors (MRN complex, KU70/KU80, RPA), transducers (DNA-PK, ATM, ATR), mediators (MDC1, 53BP1, BRCA1, TOPBP1), and effectors (CHK2, CHK1) (Polo & Jackson 2011). 2.9 Fanconi anaemia Fanconi anaemia (FA) is a rare recessive genetic disorder associated with a high frequency of haematological abnormalities, congenital anomalies, and a predisposition to a variety of cancers (Kee & D'Andrea 2012). FA occurs in about one in every 100 000 births (Rosenberg et al. 2011). To date, 16 FA genes have been identified and many more interacting genes discovered (Bogliolo et al. 2013). The majority of FA genes are located on autosomes, with the exception of FANCB, which is on the X chromosome. Biallelic mutations in any of these FA genes share a characteristic clinical and cellular phenotype of hypersensitivity to crosslinking agents and will lead to bone-marrow failure and susceptibility to both acute myeloid leukaemia (AML) and solid tumours. FA proteins work in concert in a common cellular pathway, termed the Fanconi anaemia pathway. These proteins participate in the repair of extraordinarily deleterious lesions and interstrand crosslinks, but also in the maintenance of genomic stability during DNA replication. (Kee & D'Andrea 2012, Kottemann & Smogorzewska 2013, Patel & Joenje 2007, Schlacher et al. 2012.) The FA core complex is composed of eight upstream FA proteins (FANCA, FANCB, FANCC, FANCE, FANCF, FANCG, FANCL, and FANCM), which form a nuclear complex together with accessory proteins (e.g. FAAP20, FAAP24, and FAAP100). This complex possesses intrinsic E3 ubiquitin ligase activity. (D'Andrea 2010.) The primary function of the FA core complex is to monoubiquitinate two FA proteins, FANCD2 and FANCI, after which monoubiquitylated D2-I heterodimer is recruited to sites of DNA damage by FANCJ. These FA-proteins localize to nuclear foci and are functionally associated with the downstream repair factors (Figure 5). The downstream components consist of five different proteins: BRCA2/FANCD1, RAD51C/FANCO, 47 PALB2/FANCN, BRIP1/FANCJ, and BRCA1. These are dispensable for monoubiquitination of the I-D2 complex. FAN1 nuclease is recruited and SLX4 (also known as FANCP) functions as a scaffold for the three nucleases XPFERCC1, MUS81-EME1, and SLX1 that function at the site of DNA damage to make an incision on either side of two covalently linked nucleotides. SNM1A have a role in processing the crosslink after incision. On the incised strand, TLS polymerases are recruited to bypass the unhooked crosslink. The break is then repaired through homologous recombination involving the FA proteins BRCA2, BRIP1, PALB2, and RAD51C. In addition to these FA or FA-associated proteins, the FA pathway network broadly includes other regulatory proteins. The ubiquitin-specific peptidase 1 (USP1) and the USP1-associated protein (UAF1) regulate deubiquitination of FANCD2/FANCI and are required for completion of the FA pathway. (Cohn et al. 2007, Kim et al. 2009, Kim et al. 2011, Knipscheer et al. 2009, Mirchandani & D'Andrea 2006, Niedernhofer et al. 2005, Niedzwiedz et al. 2004, Prasher et al. 2005, Stoepker et al. 2011.) Newly diagnosed FA patients should be subtyped because of clinical variability among subtypes. Mutations in the eight upstream genes are found in approximately 90% of patients (Kee & D'Andrea 2012). Identification of the breast cancer susceptibility gene BRCA2 as FA gene FANCD1 (Howlett et al. 2002) reaffirms the close cooperative relationship between the FA pathway and the breast and ovarian cancer susceptibility BRCA proteins. These tumoursuppressive proteins, BRCA1 (Garcia-Higuera et al. 2001) and BRCA2, act together with other FA proteins in the repair of DNA interstrand cross-links. Subsequent identification of FANCN (also known as the partner and localizer of BRCA2 [PALB2]) (Reid et al. 2007, Xia et al. 2007), FANCJ (also known as BRCA1-interacting helicase 1 [BRIP1/BACH1] (Levitus et al. 2005, Litman et al. 2005), and more recently, FANCO (RAD51C) (Meindl et al. 2010, Vaz et al. 2010) further solidify the close association of breast and ovarian susceptibility genes with FA (Kee & D'Andrea 2012). The current view is that monoallelic mutations in the four downstream members confer susceptibility to breast and ovarian cancer, whereas biallelic mutations in the same genes result in FA (Kottemann & Smogorzewska 2013). 2.9.1 DNA crosslink repair by the Fanconi anaemia pathway DNA interstrand cross-links (ICLs) are extremely deleterious lesions that covalently tether both duplex DNA strands and pose formidable blocks to DNA 48 metabolism. Crosslinked DNA impedes both transcription and replication, and therefore, needs to be removed during all stages of the cell cycle. The FA pathway is not constitutively active in normal cells, but is turned on during the S phase or following DNA damage (Mirchandani & D'Andrea 2006, Taniguchi et al. 2002). The major DNA repair pathway regulated by FA proteins is homologous recombination (HR), a process that repairs DNA DSBs. The FA proteins promote HR activity by different mechanisms, and cells lacking FA proteins are deficient in promoting HR activities. ICL repair requires the tight coordination of several different repair pathways, and it is within this delicately balanced system that the FA pathway has its regulatory role. Recent studies have demonstrated how the FA pathway coordinates three critical DNA repair processes: nucleolytic incision, translesion DNA synthesis (TLS), and HR (Kim & D'Andrea 2012). Downstream FA proteins play an important role in HR, but the upstream proteins are also speculated to be required for HR, although having more minor role (Kottemann & Smogorzewska 2013, Stecklein & Jensen 2012, Kee & D'Andrea 2012). The presence of each FA protein is a prerequisite for proper function and subsequent DNA repair. For example, cells deficient in any of the RAD51 paralogues are sensitive to ICLs and DSBs because of the resulting deficit in homologous recombination (Huang & Li 2013). However, several FA-interacting proteins play non-canonical roles also outside of the classical pathway, which could explain why mutations within different FA genes yield similar, albeit not necessarily identical clinical phenotypes (Romick-Rosendale et al. 2013). 49 Fig. 5. A schematic view of the Fanconi Anaemia pathway activation for ICL repair. ATR-mediated signal activates the FA pathway at the stalled replication forks, leading to the activation of the FA core complex and monoubiquitination of the FANCD2/FANCI heterodimer. The monoubiquitinated D2/I heterodimer recruits FAN1 nuclease and FANCP (SLX4), which associates with several nucleases and then coordinates the action of downstream repair factors. The break is then repaired through homologous recombination involving the FA proteins BRCA2, BRIP1, PALB2, and RAD51C. Data combined from (Kee & D'Andrea 2012, Kitao & Takata 2011, Soulier 2011). 2.9.2 FA genes; FANCA, FANCG and FANCI FANCA and FANCG are part of the FA core complex. As described earlier (Section 2.8.2), the primary function of the FA core complex is to monoubiquitinate two FA proteins, FANCD2 and FANCI, which are expressed as a constitutive heterodimer (Crossan & Patel 2012). (Table 1) 50 Table 1. Three FA genes. Gene FANCA FANCG (XRCC9) FANCI Locus Mutation Amino Protein frequency acids MW (kDa) Notable protein function 16q24.3 ~66% 1455 163 9p13 ~10% 622 70 Scaffold for FA core complex 15q25-26 <2% 1328 150 Monoubiquitinated, forms Scaffold for FA core complex heterodimer with FANCD2 FA-A is the major FA complementation group and the corresponding gene FANCA was cloned in 1996 (Fanconi anaemia/Breast cancer consortium 1996, Lo Ten Foe et al. 1996). It is a large gene consisting of 43 exons. Mutation analysis in FA-A patients has not revealed any mutational hotspots (Savino et al. 1997, Wijker et al. 1999). Fanca-/- cells presented an increase in spontaneous chromosomal damage (22% vs. 4% in wild-type) when MMC was absent (Cheng et al. 2000). FANCG localization was achieved by homozygosity mapping and linkage analysis in FA-G families. FANCG covers 14 exons and the protein shows no homology to known proteins. (Kruyt et al. 1999, Saar et al. 1998, Waisfisz et al. 1999.) Fancg knock-out cells have not only decreased HR capacity for repairing enzymatically induced, site-specific chromosomal DSBs but also increased ionizing radiation (IR)-induced chromosomal aberrations in cells irradiated in late S and G2 phases (Yamamoto et al. 2003). The overall structure of the FANCG protein seems to be critical for the interaction. FANCG has been shown to interact with the RAD51 paralogue protein XRCC3 in the yeast two-hybrid system. (Hussain et al. 2006.) FANCI has 38 exons and its protein contains three nuclear localization and three predicted ATM/ATR phosphorylation motifs. Patient cell lines of complementation group I are deficient in FANCD2 monoubiquitination, show increased chromosomal instability and are hypersensitive to cross-linking agents such as mitomycin C (Dorsman et al. 2007). The phosphorylation of FANCI has been suggested to function as a molecular switch to turn on the FA pathway, but further investigations are required to confirm this (Ishiai et al. 2008). In addition, in FANCA- and FANCG-deficient cell lines, FANCI monoubiquitination was completely abrogated, in contrast, FANCI ubiquitination was restored in complemented cells, that contained an intact FA core complex. (Leung et al. 2012, Mirchandani & D'Andrea 2006.) 51 2.10 Candidate genes for breast cancer predisposition based on their biological function Given the numerous breast cancer predisposition genes that are part of the BRCA/FA signalling machinery and involved in genomic integrity maintenance, all related factors are good candidates for breast cancer susceptibility genes, until disproven. In addition, besides the FA genes, all of the other genes involved in other critical biochemical pathways, such as signal transduction pathways that transmit checkpoint signals in response to DNA damage, replication blocks and spindle damage, have been proposed as candidates for cancer susceptibility. (Elledge 1996, Nathanson & Weber 2001, Ralhan et al. 2007, Yoshida & Miki 2004.) The candidate gene approach involves the systematic screening of entire genes for disease-causing variants in cancer cases, and the frequency of the observed mutations is compared with that of controls. The genes are chosen on the basis of a priori knowledge of their biological activity. The usage of familial rather than population-based breast cancer cases is expected to increase the power for mutation detection (Antoniou & Easton 2003). 2.10.1 AATF AATF (apoptosis-antagonizing transcription factor, also known as CHE1 and Traube) is an evolutionarily conserved RNA polymerase II binding protein involved in the regulation of gene transcription. The AATF gene is located at chromosome 17q11.2-q12. It encodes a phosphoprotein containing 558 amino acids and consists of 12 exons. (Fanciulli et al. 2000)(Lindfors et al. 2000). It contains a leucine zipper motif, several phosphorylation sites for different kinases, a nuclear localization signal motif, three nuclear receptor binding motifs, and several four-nucleotide repeats (Lindfors et al. 2000, Passananti et al. 2007). The functions of AATF are essential for early embryogenesis and cell proliferation (Bruno et al. 2002, Thomas et al. 2000). One significant function of AATF is to promote cellular transcription; it acts as an adaptor that links specific transcription factors to the general transcription apparatus. Furthermore, due to its interaction with various important components of the cell survival machinery, e.g. anti-apoptotic factors, guch as XIAP, and pro-apoptotic factors, such as Dlk, Par-4, and NRAGE, AATF has been found to play an important role in DNA damage response, cell cycle checkpoint control, and also chromatin remodelling (Jagut et al. 2013, Kaul & Mehrotra 2007, Passananti et al. 2007). In addition to pro52 proliferative function, AATF exhibits strong anti-apoptotic activity, and this protein is downregulated during apoptosis (De Nicola et al. 2007, Guo & Xie 2004, Page et al. 1999). In response to DNA damage, AATF relocates to the TP53 promoter to increase transcription of this gene, thereby contributing to the increase in p53 protein levels after DNA damage (Bruno et al. 2006). The p53 protein plays a critical role in the cellular response to DNA damage and other stresses by inhibiting proliferation or by inducing apoptosis. The p53 is the most frequent target for genetic alterations in human cancer. (Bruno et al. 2010, Hopker et al. 2012.) Centrosomes are part of a network that integrate cell cycle arrest and repair signals. Crucial regulators of DDR, such as the checkpoint kinases ATM, ATR, Chk1, and Chk2 as well as the tumour suppressors p53 and BRCA1, have been found to localize to the centrosomes (Ciciarello et al. 2001, Oricchio et al. 2006). Centrosomes integrate G2/M checkpoint control and repair signals in response to genotoxic stress (Zhang et al. 2007). Depletion of AATF prevents centrosomal recruitment of the checkpoint kinase Chk1 and leads to abnormal centrosome amplification, accumulation of multinucleated cells and abnormal spindle formation. In conclusion, AATF is critical at the spindle assembly checkpoint. (Sorino et al. 2013.) 2.10.2 MRG15 Human MRG15 (MORF4-related gene on chromosome 15) was first identified as a member of the MORF4/MRG family of novel transcription factors. Of seven known family members, only three are expressed (MORF4, MRG15, and MRGX). MORF4 induces senescence in a subset of human tumour cell lines, and it is a truncated version of MRG15. In contrast to MORF4, MRG15 and MRGX are positive regulators of cell division. MRG15 is the largest of these three, encoding a 323 amino acid protein. MRG15 has an ATP-GTP binding region, followed by a helix-loop-helix and a leucine zipper at the C terminus. MGR15 also encodes a bipartite nuclear localization signal (NLS) flanked by phosphorylation sites. MRG15 is broadly evolutionarily conserved from yeast to mammals and even plants, suggesting it must have a fundamental activity in some cellular process. (Bertram & Pereira-Smith 2001, Chen et al. 2010, Pena & Pereira-Smith 2007, Tominaga & Pereira-Smith 2002, Tominaga et al. 2005.) MRG15 protein specifically binds to Lys36-methylated histone H3 (Zhang et al. 2006) and has an established role in transcriptional regulation (Carrozza et al. 53 2005). In particular, MRG15 and MRGX are integral components of the NuA4/Tip60 histone acetyltransferase (HAT) and histone deacetylase (HDAC) complexes (Doyon et al. 2004, Hayakawa et al. 2007). Several lines of evidence suggest that MRG15 and its related proteins are involved in DNA-repair processes (Garcia et al. 2007, Nakayama et al. 2003). MRG15 binds directly to a key component of the machinery for DSB repair, PALB2 (Sy et al. 2009a). Furthermore, MRG15 is required for HR and resistance to MMC. MRG15 participates in the response to DSBs by recruiting the BRCA complex to sites of damaged DNA (Hayakawa et al. 2010). Results in human, mouse, and C. elegans models delineate molecular and functional relationships with BRCA2, PALB2, RAD51, and RPA1 (Takashi et al. 2009), suggesting a role for MRG15 in the repair of DNA DSBs. An MRG15 mutant lacking the C-terminal chromo domain was unable to interact with PALB2. Furthermore, a Mrg15-deficient murine embryonic fibroblast showed reduced formation of Rad51 nuclear foci. (Martrat et al. 2011.) Based on the role that both these genes AATF and MRG15 have in DDR, it is possible that their mutations could predispose to cancer. 54 3 Aims of the study The currently identified breast cancer susceptibility genes only account for about 25% of familial breast cancer patients. Thus, the vast majority of cases cannot be explained by any known predisposing factors. Numerous additional predisposing genes are speculated to await discovery. The majority of known susceptibility genes have been reported to be involved in the maintenance of genomic stability via the DNA damage response. Other genes involved in the same pathways may therefore be good candidate genes for familial breast cancer susceptibility. In this work, the AATF and MRG15 genes were evaluated as potential candidates as both are known to act in critical cellular pathways. Moreover, PALB2 and other Fanconi anaemia (FA) genes are previously known to be breast cancer susceptibility genes but their clinical significance has not been thoroughly investigated in the Finnish population. Specific aims of the studies are as follows: 1. 2. 3. 4. To identify potential cancer-predisposing mutations in the AATF gene and to evaluate their involvement in breast cancer susceptibility. To screen MRG15 for conventional mutations and to assess their potential role in breast cancer predisposition. To evaluate whether Finnish PALB2 c.1592delT founder mutation testing should be part of routine clinical counselling by investigating a cohort of high-risk breast cancer patients at the Department of Clinical Genetics, Oulu University Hospital. The patients had previously tested negative for BRCA1 and BRCA2 mutations. Specifically, the aim was to determine whether PALB2 c.1592delT mutation analysis would give the patients some direct additional advantage if this test was included in routine aetiological search of clinical determinants for familial breast cancer susceptibility. To identify all current Finnish FA patients and to determine their diseaseassociated complementation groups and the causative mutations, and further, to investigate the putative role of these mutations in breast and prostate cancer susceptibility. 55 56 4 Materials and methods 4.1 Subjects 4.1.1 Study I Index patients from 121 breast or breast and ovarian cancer families from Northern Finland were included in the mutation screening of the AATF gene. For statistical purposes, one index patient from each family was chosen according to the youngest age of breast cancer onset. Mutations were screened in the coding regions and the exon-intron flanking sequences of the AATF gene. The families derived geographically from the Northern Ostrobothnia Health Care District, and were categorized as high- and moderate-risk families. The inclusion criteria for high-risk families were as follows: 1. 2. Three or more breast and/or ovarian cancer cases in first and second-degree relatives. Two cases of breast and/or ovarian cancer in first- and second-degree relatives, of which at least one with early age of disease onset (<35 years), bilateral disease or multiple primary tumours. The remaining families were considered moderate-risk families with two cases of breast or breast and ovarian cancer in first- or second-degree relatives. The total number of high-risk families was 71 and moderate-risk families 51. All of the high-risk families were previously screened for germline mutations in BRCA1, BRCA2, CHK2, and TP53 (Allinen et al. 2001, Huusko et al. 1998, Huusko et al. 1999, Rapakko et al. 2001). In addition, the families had been screened for mutations in RAD50, MRE11, ATM, NBS1, BRIP1/BACH1 and BARD1 genes (Heikkinen et al. 2003, Heikkinen et al. 2005, Karppinen et al. 2003, Karppinen et al. 2004). The healthy control samples were from consecutive anonymous (only gender, age, and place of blood donation were known) Finnish Red-Cross blood donors originating from the same geographical region as the familial breast cancer cases. All control individuals were cancer-free at the time of blood sample donation. Donor health status was not followed. The age of the blood donors varied between 18 and 65 years, the average being 42 years. 57 4.1.2 Study II The patient material in this study was the same as in Study I, with the execption that the number of analysed Northern Finnish breast cancer patients was higher, 148. This included 99 high-risk and 49 moderate-risk families. Study II also included 84 index patients of breast/ovarian cancer families originating from Canada. Of these, 45 were French-Canadian and 9 Ashkenazi Jewish families. The total number of families analysed was 232. The average age at diagnosis for the index cases was 48 years, and 97% of probands presented with breast cancer. The classification and the actual number of participating patients were as follows: 1. 2. 3. 179 (77%) of the 232 families had three or more affected individuals. 44 families (19%) had two affected individuals. Nine index cases (4%) presented with either breast cancer at age under 30 years or bilateral cancer, but with no family history. 4.1.3 Study III Subjects were selected among the individuals (n=223) who had been in contact with the Oulu University Hospital, Department of Clinical Genetics, between 1997 and 2011. Inclusion to the study was in accordance with the following criteria of high-risk hereditary breast cancer (“the Lund criteria”): 1. 2. 3. 4. 5. The individual or her first-degree relative (only female family members were included when defining first-degree relatives) had breast and/or ovarian cancer at age under 30 years. Two first-degree relatives in the family had breast and/or ovarian cancer and at least one of the cancers had been diagnosed at age under 40 years. Three first-degree relatives in the family had breast and/or ovarian cancer and at least one of the cancers had been diagnosed at age under 50 years. Four or more relatives had breast and/or ovarian cancer. The same individual had both breast and ovarian cancer. Individuals with bilateral breast cancer were considered to have two separate cancers. BRCA1- or BRCA2-positive mutation status was an exclusion criterion; 16 individuals were excluded based on this. Of the initial 223 individuals, 101 met the inclusion criteria based on their pedigree data; 10 were deceased and the remaining 91 were invited to participate. Seventy individuals responded (70/91 = 77%) and provided us with information on their family history of cancer. Chart 58 review led to the further exclusion of 14 individuals who did not meet the selection criteria. Altogether, the Northern Finnish 1997–2011 study cohort tested for PALB2 c.1592 carrier status consisted of 62 (56 alive and 6 deceased, who had participated in one of our previous studies on PALB2 (Erkko et al. 2007)) affected females (Figure 5). 10 were deceased but 6 of them had been tested for PALB2 mutation previously 233 individuals contacted the genetic counselling unit because of suspected breast/ovarian cancer 101 had a major family history of cancer and were negative for mutations in BRCA1/BRCA2 122 did not meet study criteria 70 of 91 individuals responded to the study invitation Altogether 62 eligible index patients were analysed for PALB2 mutation status Chart review of updated family history data excluded a further 14 individuals Fig. 6. Flow chart summarizing the numbers of patients at different stages of the inclusion process in Study III. 4.1.4 Study IV An attempt to collect all known Finnish FA patients was performed by contacting clinicians (clinical genetic/paediatrician) to inquire about patients with suspected or confirmed diagnosis of FA. In addition, all genetic laboratories were contacted to find out if they had performed chromosomal analysis for suspected cases. The patients were collected as a part of a collaborative study. Three patients had been referred for FA clinical testing e.g. diepoxybutane (DEB) and mitomycin C (MMC) sensitivity test by Pediatric Oncology, Tampere University Hospital and one by Family Federation of Finland. Additionally, five anonymous cell lines created during the years 1979–1993 from individuals with suspected FA (Department of Clinical Genetics, Helsinki University Central Hospital) were collected. These cell lines were subjected for MMC sensitivity testing by cell survival assay and only one showed positive and was included in the study. 59 The Northern Finnish familial cohort consisted of 164 index cases from breast or breast-ovarian cancer families. The inclusion criteria were the same as in Study I. An additional young breast cancer cohort was included, consisting of 82 cases from Northern Finland who were diagnosed with breast cancer at an age of ≤40 (from 25 to 40 years, with median 38 years). These young patients were unselected for a family history of the disease. The prevalence of FA mutations was tested also in the Northern Finnish breast cancer cases who had been operated on at Oulu University Hospital in 2000–2007 (n=508–813, depending on the tested mutation). These patients were unselected for age at diagnosis as well for family history of breast cancer. The Northern Finnish control samples (n=517) were derived from anonymous cancer-free female Finnish Red Cross blood donors who had originated from the same geographical region as the patient cohorts. The Southern Finnish familial cohort included index cases from 87 hereditary breast and ovarian cancer families from the Pirkanmaa Health Care District. All of these individuals had been founder mutation-negative by minisequencing of 28 known Finnish BRCA1/BRCA2 mutations and by protein truncation test of exon 11 for BRCA1 and exons 10 and 11 for BRCA2. The samples had been collected from individuals who had visited the Tampere University Hospital Genetics Outpatient Clinic between January 1997 and May 2008. The Southern Finnish unselected breast cancer cohort included 694 breast cancer cases unselected for family history of cancer and was recruited through the Tampere University Hospital. Samples from 659 anonymous ancestry matched healthy female Finnish Red Cross blood donors were used as controls. The Eastern Finnish cohort (Kuopio University Hospital), comprising 494 patients with breast cancer from the Kuopio Breast Cancer Project (KBCP), was utilized for genotyping of FANCG mutations. These patients originated from the Northern Savo region and were diagnosed at Kuopio University Hospital in 1990–1995. Serving as controls were 468 female subjects selected from the National Population Register. This additional cohort was available only for FANCG mutations genotyping. The prostate cancer cohort included 565 prostate cancer index patients from Southern Finland (Pirkanmaa Health Care District). All familial prostate cancer cases came from families with two or more affected members (the youngest affected male from each family was included in the analysis). Serving as controls were 469 unaffected males from the same geographical region. 60 4.2 DNA extraction Genomic DNA from peripheral blood lymphocytes was extracted by a standard phenol-chloroform method or by using the Purgene D-50K purification kit (Gentra, Minneapolis, MN, USA). 4.3 Mutation detection methods 4.3.1 Conformation-sensitive gel electrophoresis (I) Mutation screening of the AATF was done using conformation-sensitive gel electrophoresis (CSGE). This method was used to scan the coding regions and exon-intron boundaries of candidate genes. The assay is based on denaturating gel separation of amplicons with conformation changes due to mismatches in the double-stranded DNA. This results in different migration patterns between homoand heteroduplexes (Ganguly et al. 1993, Körkkö et al. 1998). 4.3.2 High-resolution melt analysis (II, III, and IV) Mutations in the protein encoding regions and exon-intron boundaries of the candidate genes were searched for by high-resolution melting (HRM) analysis. This is a post-PCR analysis method for identifing nucleic acid sequences that is based on detecting small differences in PCR melting (i.e. dissociation) curves. Wild-type and heterozygous samples can be differentiated in the melting plots. (Reed & Wittwer 2004.) 4.3.3 Direct sequencing (I, II, III, IV) Samples with band shifts in CSGE or deviant melting curves in HRM (I, II, III) were reamplified and sequenced with the Li-Cor IR2 4200-S DNA Analysis system (Li-Cor Inc., Lincoln, NE, USA) or with capillary sequencing using ABI3130xl Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). Sequencing was also used as a primary method to detect mutations in sequences not suitable for analysis with CSGE or HRM. In study IV, after identification of the complementation groups, the underlying gene mutations of each patient were studied further by sequencing. For Li-Cor, the Sequi Therm EXEL II DNA 61 Sequencing kit-LC (Epicentre Technologies, Madison, WI, USA) and for ABI the Big Dye Terminator kit v1.1 (Applied Biosystems) were used. 4.4 Mitomycin C sensitivity test and complementation group analysis (IV) Based on the hypersensitivity of FA cells to ICL, the FA status of clinically suspected patients was confirmed with chromosomal dieposybutane (DEB) mitomycin C (MMC) sensitivity test from peripheral blood lymphocytes (German et al. 1987). All the confirmed FA cases were subjected to complementation group analysis (Chandra et al. 2005). For FA complementation group determination, five patient cell lines were established. Cells were transduced with retroviral vectors containing normal cDNAs of FANCA, FANCB, FANCC, FANCE, FANCF, FANCG, or FANCL and analysed for cell cycle arrest upon treatment with MMC and for restoration of FANCD2 monoubiquitination. (Hanenberg et al. 2002.) 4.5 Statistical and bioinformatical analysis Carrier frequencies between patients and healthy controls were compared using Pearson’s Chi-Square or Fisher’s exact test (I, II, IV) with SPSS version 16.0– 20.0 for Windows (SPSS Inc., Chicago, USA). All p-values were two-sided. In Studies I and II, all alterations were tested for possible pathogenicity by PolyPhen software (Ramensky et al. 2002) and were checked with NNSplice software for potential effects on splicing (Reese et al. 1997) (Reed & Wittwer 2004)ESEfinder 2.0 software (Cartegni et al. 2003) was used to determine whether the exonic variant was located in ESE (exonic splicing enhancer) sequences and could therefore influence in ESE function. For Study II, also in silico analyses were performed using accurate splicing prediction software: BDGP (Reese et al. 1997), NetGene 2 server (Brunak et al. 1991, Hebsgaard et al. 1996), and GENESCAN (Burge & Karlin 1997). Analysis of the 3’UTR was performed by using TargetScanHuman 5.1 software (Lewis et al. 2005). 62 4.6 Ethical issues Investigations aiming to find new breast cancer susceptibility genes may lead to discoveries which improve genetic counselling, help early diagnostics in relatives, improves understanding of breast cancer and may eventually lead to new treatment for breast cancer. Thus this study has an ethically sound aim. All participating individuals gave informed consent for using their pedigree data and blood specimens in a study on cancer susceptibility gene mutations. Each DNA sample was labelled with a research code, and samples were handled anonymously during the analyses. Results from the analyses in Studies I, II, and IV were only used for research purposes, and no information was given to the participating individuals. In contrast, in Study III a separate invitation to participate in the study was issued and a new informed consent obtained. Participants had the opportunity to choose whether they wanted to know their mutation status or not, and those requesting the information were informed by a personal letter. Genetic counselling was provided, if desired, for identified mutation carriers. Appropriate research permissions to perform the study have been obtained from the Ethics Committee of Oulu University Hospital (88/2000 and 12/2011) as well as from other participating University Hospitals. The study protocol was approved by the Ministry of Social Affairs and Health (46/07/98). 63 64 5 Results 5.1 Mutation screening of the AATF gene (I) Screening for germline mutations in AATF in 121 index patients with breast/ovarian cancer revealed altogether seven different changes (Table 2). Only one of the observed changes was exonic. The alteration c.739G>T in exon 4 resulted in an Ala247Ser amino acid substitution. All other variants were intronic. Of the total of seven changes, only two were previously reported; five were novel. To evaluate possible pathogenicity of the observed changes, their frequencies were compared between cases and healthy population controls. The novel exonic alteration was observed at similar frequencies in both cases and controls (p=0.70). Although it resulted in an amino acid change, PolyPhen software analysis predicted the effect to be neutral. Details and occurrence of the observed nucleotide variants are shown in Table 2. Table 2. Observed sequence variations in the AATF gene. Controls P-value (OR, 95% CI) Previously Exon/ Nucleotide Effect on Carrier Intron change protein frequency (%) known (+) or Familial cases unknown (-) alteration Ex4 c.739G>T p.Ala247Ser 1.7 (2/121) 1.3 (4/317) Int3 c.694+35A>C None 4.1 (5/121) 9.1 (30/328) 0.08 (0.4, 0.2–1.1) c.694+48T>G None 3.3 (4/121) 0.9 (3/328) 0.09 (3.7, 0.8–16.8) - c.832+17C>T None 0.8 (1/121) 0.3 (1/317) 0.48 (2.6, 0.16–42.4) - c.832+39C>T None 0.8 (1/121) - (0/317) Int11 c.1619+29A>C None 2.5 (3/121) 0.3 (1/325) Int12 c.1670+42C>T None 20.7 (25/121) Int4 5.2 0.70 (1.3, 0.2–7.1) +; rs8067751 0.28 (NA) - 0.06 (8.2, 0.8–80.0) - 23.5 (72/307) 0.53 (0.9, 0.5–1.4) +; rs11653434 Mutation screening of the MRG15 gene (II) In the MRG15 gene, altogether 21 variants were identified in affected index individuals from 232 breast or breast/ovarian cancer families (Table 3). Of these variants, 17 were intronic changes, 3 were coding SNPs, and 1 was localized in the 3’UTR. Six of the 17 intronic variants as well as the variant located in the 3’UTR were novel, and they were not referenced in either dbSNP or Ensembl SNP databases. Each of these seven variants was detected in less than 1% of the 65 patients, suggesting that they were rare and potentially harmful cancer-associated variants. To gain further insight into possible disadvantageous effects of these seven non-referenced variants, in silico analysis using accurate splicing prediction BDGP, NetGen 2 server, and GENESCAN software was performed. None of these intronic changes were, however, predicted to impact the splicing of premRNA. Further, analysis of the 3’UTR by using TargetScanHuman 5.1 software revealed that the site where this variant resides is not a known target of the miRNAs. Consequently, it is very unlikely that this variant has any effect on the regulation of MRG15 mRNA expression. Table 3. Observed sequence changes in the MRG15 gene. Sequence variant Protein change No. of times observed Additional information c.421+35C>T Int4-5 7 rs16970187 c.590-26T>C Int6-7 3 rs4778952 c.616-79T>A Int7-8 18 rs10519215 c.721A>G N191S 1 rs73477676 c.807-144T>C Int9-10 1 Not referenced c.807-133T>C Int9-10 1 Not referenced c.824C>A A225A 18 rs1435163 c.868A>G K240R 18 rs61734867 c.895+32A>G Int10-11 1 rs74024473 c.895+38A>G Int10-11 1 rs56816206 c.1068+12A>G Int11-12 2 rs16970207 c.1069-45C>A Int11-12 1 Not referenced c.1153+95T>A Int12-13 11 rs10519216 c.1154-185T>A Int12-13 1 Not referenced c.1154-43T>C Int12-13 19 rs12438433 3’UTR 1 Not referenced c.1238+161G>C 5.3 Clinical significance of PALB2 c.1592delT screening in BRCAnegative high-risk breast cancer families (III) Altogether 56 living breast cancer patients who tested negative for BRCA1 and BRCA2 mutations were included in the PALB2 c.1592delT screening study. Among these index patients, two were found to carry the heterozygous PALB2 c.1592delT mutation (2/56=3.6%). In addition, the mutation status was known for 66 six other previously tested but recently deceased patients. Among these individuals, one more mutation carrier was observed. Therefore, altogether 4.8% (3/62) of the individuals belonging to the Northern Finnish 1997–2011 study cohort and counselled at the Department of Clinical Genetics at Oulu University Hospital were carriers of the PALB2 c.1592delT allele. The average age of disease onset among mutation carriers in the current study was 48 years. Tumour characteristics of PALB2 c.1592delT mutation carriers were obtained from pathology records (Table 4). All tumours were histological ductal, and both oestrogen and progesterone hormone receptor statuses were positive. Table 4. Tumour characteristics and family history of cancer among identified PALB2 c.1592delT mutation carriers. Family ID Cancer Histo- TNM Er/Pr Grade Her2 p53 Ki67 Other cancers in the logy family Fam A Br(63) Ductal T2N0M0 Er+/Pr+ 2 neg Neg 2 Fam B Br(43) Ductal TisN0M0 Er+/Pr+ 1 neg NA 0 Br(44), Br(73) Br(30), Br(53), Br(65), Br, Br, Lung, Ov(60), Panc, Sarc, Skin, Sto Fam C Br(39) Ductal T2N0M0 Er+/Pr+ 3 NA Neg 2 Br(67), Br(68), Ov(71), Panc, Ut(36), Ut Er, oestrogen receptor; Pr progesterone receptor; Her2, human epidermal growth factor receptor 2; p53, tumour protein 53; Ki67, antigen Ki67; Br, breast cancer; Ov, ovarian cancer; Panc, pancreatic cancer; Sarc, Sarcoma; Sto, stomach cancer; Ut, Uterine cancer, NA, not available. 5.4 Complementation groups of Finnish Fanconi anaemia patients and role of causative mutations in breast cancer susceptibility (IV) In Study IV, all of the five analysed Finnish FA patients were confirmed to belong to previously described FA complementation groups: FA-A (three patients), FA-I (one patient), and FA-G (one patient). In total, six different FA mutations were identified in these patients (see Table 5) 67 Table 5. Observed mutations among Finnish FA patients. Complementation Gene mutations Additional information group FA-G FANCG c.832insG and c.1076+1G>A compound heterozygous FA-I FANCI c.3041G>A* and c.2957_2969del *rs140404896 compound heterozygous FA-A FANCA c.3348-1G>A homozygous Described in FA patient in compound heterozygous state (Chandrasekharappa et al. 2013) FA-A FANCA c.3348-1G>A homozygous FA-A FANCA c.-4403_1084-126del Heterozygous mutation reported in familial homozygous breast cancer (Solyom et al. 2011) The mutation in the FA-G patient was compound heterozygous. One allele showed a c.832insG mutation in exon 7, which leads to a frameshift (p.Glu275Glyfs) and further to a truncated protein product. The other FANCG allele harboured a c.1076+1G>A mutation, which affects a splice site of exon 8. This leads to an in-frame deletion of 18 nucleotides at the mRNA level (c.1059_1076del) and abolishes 6 amino acids of FANCG’s third TRP domain. TRPs are 34-amino acid repeat motifs functioning as scaffolds that mediate protein-protein interactions (Blom et al. 2004). The FANCI patient was also compound heterozygous with regard to diseaseassociated mutations. FANCI c.2957_2969del (p.Val986Alafs) leads to a truncated protein product missing part of exon 26 and all of exons 27–38. FANCI c.3041G>A was previously referenced (rs140404896), and it leads to a p.Cys1014Tyr missense mutation in exon 27, changing an evolutionarily highly conserved amino acid. Based on the analysis with PolyPhen, this substitutional change probably has damaging consequences on protein function with a score of 0.995. SIFT software predicts that it is damaging with a score of 0.02. All three FA-A patients were homozygous for their mutations. One of them had a large deletion of FANCA c.-4403_1084-126del (FANCA ex1-ex12del), which removes the promoter and the first 12 exons of the gene. This allele has previously been described in a familial breast cancer case and is predicted to result in a null allele (Solyom et al. 2011). The two other FA-A patients were siblings and they both had the same mutation. They were homozygous for the FANCA c.3348-1G>A mutation, which leads to skipping of exon 34 (c.3348_3408) at the mRNA level and to an in-frame deletion of 20 amino acids. 68 5.4.1 Finnish FA mutations prevalence in cancer cohorts The association of the observed Finnish FA mutations with breast cancer susceptibility was studied using familial and unselected breast cancer cohorts. Altogether two FA mutation carriers were observed in familial cases: one FANCA ex1-ex12del (1/321, 0.3%) and one FANCI c.2957_2969del (1/333, 0.3%) carrier. The first one has previously been described in a family where the index case had breast cancer at the age of 50 years and her father was diagnosed with pancreatic cancer at the age of 65 years, and they were both carriers of this FANCA ex1ex12del mutation (Solyom et al. 2011). From the unselected patient material, three more FANCA ex1-ex12del carriers were identified (3/1495, 0.2%). One of them had breast cancer at the age of 33 years and had a family history of lung cancer (three first-degree relatives, smoking status unknown). Another unselected patient had breast cancer at the age of 52 years, and her aunt and uncle were diagnosed with pancreatic and lung cancer, respectively, but their carrier status was unknown. The third FANCA ex1-ex12del carrier from the unselected cohort had breast cancer at the age of 71 years, and no other cancer history was reported in her family. None of these unselected cases had additional samples from relatives available for mutation testing. The prevalence of this FANCA ex1ex12del was also tested among healthy controls, and the result was somewhat surprising. Two mutation carriers were identified (2/1175, 0.17%), but at least one of them was very young (<25 years) at the time of blood donation. FANCI mutation c.2957_2969del was observed in a patient with both ovarian (at 69 years) and breast cancer (at 72 years). The patient’s mother was suspected of having a benign ovarian tumour, and the mother’s sister and her daughter both had cervical cancer. Other samples from family members were not available to test for mutation segregation. Two FANCI c.2957_2969del carriers were also observed in the unselected breast cancer cohort (2/1191), but also among healthy controls (2/896). The remaining FA mutations, FANCA c.3384-1G>A, FANCI c.3041G>A, FANCG c.1076+1G>A, and FANCG c.832insG, were observed in either unselected cases or controls, or both, but their individual frequencies remained very low, and no significant difference emerged between cases and controls. No FANCG c.1076+1G>A mutations were observed in familial or unselected cases, but one carrier was identified among the controls (0.09%). In contrast FANCG c.832insG was observed in one unselected case (0.06%), but not in healthy controls (table 6). 69 Table 6. FA mutation frequencies in breast cancer cohorts and in healthy female controls. FA mutation Carrier frequencies and statistics Familial/young Unselected Unaffected breast cancer breast cancer females 1/321 (0.3%) 3/1495 (0.2%) 2/1175 (0.2%) P-value (OR; 95% CI) F (Familial/Young), U (Unselected) FANCA ex1-12dela FANCA 0/321 (0%) 1/1495 (0.1%) 1/1175 (0.1%) c.3384-1G>A FANCI c.2957_2969del (F) 0.5 (1.8; 0.1–20.3) (U) 1.0 (1.2; 0.2–7.1) (F) 1.0 (NA) (U) 1.0 (0.8; 0.05–12.6) 1/333(0.3%) 2/1191 (0.2%) 2/896 (0.2%) (F) 1.0 (1.3; 0.1–14.9) (U) 1.0 (0.8; 0.1–5.3) FANCI 0/333 (0%) 1/1191 (0.1%) 2/896 (0.2%) c.3041G>A FANCG c.832insG (F) 1.0 (NA) (U) 0.6 (0.4; 0.03–4.1) 0/317 (0%) 1/1716 (0.06%) 0/1264 (0%) (F) 1.0 (NA) (U) 1.0 (NA) FANCG c.1076+1G>A 0/317(0%) 0/1714 (0%) 1/1165 (0.09%) (F) 1.0 (NA) (U) 0.4 (NA) a FANCA ex1-12del screening partially reported in Solyom et al. (2011), consisted of 100 familial breast cancer cases, 540 unselected cases, and 124 controls from Northern Finland. The one mutation-positive family was identified in the previous study. NA, not available 70 6 Discussion 6.1 No mutations found in the AATF gene among Finnish breast cancer families (I) A significant fraction of familial breast and/or ovarian cancer cannot be explained by mutations in the currently known susceptibility genes. AATF encodes a phosphoprotein required for maintaining genomic integrity and cell cycle checkpoint control (Kaul & Mehrotra 2007, Lindfors et al. 2000). Based on its important biological role, it was hypothesized that mutations in this gene might predispose to cancer. To our knowledge, this study is the first to explore the role of AATF in breast cancer susceptibility. The whole coding region and exon-intron boundaries of the AATF gene were screened for germline mutations. Although several sequence variants were found, none are likely to be pathogenic. The only observed exonic change c.739G>T (p.Ala247Ser), was novel, but it was located outside the functionally important protein domains. Furthermore, this alteration was found at similar frequencies (ca. 1%) in both cases and controls, suggesting that no relationship exists between this alteration and a predisposition to cancer. In addition, none of the six intronic changes seemed to affect consensus splicing sequences. As similar frequencies were found in cases and controls, none of the observed changes are likely to be associated with cancer predisposition. Only one missense change was observed in the 12 exons of AATF, reflecting extreme conservation of the coding regions of this gene. This preservation could result from its essential and unique cellular function. Overall, our results provided no evidence of significant involvement of AATF alterations in familial breast cancer susceptibility. However, further research is needed to confirm these findings in other populations and cancer types. Interestingly, the role of AATF gene in breast cancer has recently been studied in vitro (Sharma 2013). In that study, the RNomics (small non-mRNAs) of the AATF gene were analysed in relation to the pathogenesis of breast cancer by AATF gene silencing and by measuring its effect on the cellular proliferation and apoptosis induction in human breast cancer cells. The findings suggested that AATF might be a suitable molecular target for therapeutic interventions for the cure of cancers. AATF silencing in breast cancer cells can inhibit proliferation, induce apoptosis, modulate transcription of multiple apoptosis-relevant genes and 71 regulate oestrogen expression in breast cancer cells. (Sharma 2013.) This highlights the fact that AATF was a good candidate gene, despite the lack of germline mutations. 6.2 MRG15 and hereditary predisposition to breast cancer (II) To the best of our knowledge, this study is the first to search for MRG15 mutations in breast cancer patients. The maintenance of genomic integrity and cell-cycle checkpoint control is dependent on the functioning of MRG15. It directly binds to PALB2 and this interaction is essential for homologous recombination regulation during DNA repair. (Smith et al. 2013, Sy et al. 2009a.) Based on its biological role, it was hypothesized that mutations in the MRG15 gene might contribute to hereditary predisposition to breast cancer. The whole coding region of this gene was systematically screened for mutations in breast cancer families. No clearly deleterious sequence alterations were observed. Thus, no evidence for strong (i.e. high-/moderate-penetrance) breast cancer predisposing mutations in MRG15 emerged. In this study, HRM and direct sequencing were used in the mutation search, and this methodological combination should readily detect all possible deleterious mutations. The studied cohort consisted of 232 patients derived from both Northern Finland and Canada. Although no mutations were observed in MRG15 in this study, further studies of larger patient cohorts might still uncover some very rare disease-related changes in this gene. However, based on our results, it seems more likely that the MRG15 gene does not make any sizeable contribution to hereditary breast cancer susceptibility. Interestingly, after our study was published, Martrat et al. (2011) explored the link between MRG15 and risk of breast cancer by searching novel components in the DNA damage repair signalling pathway. They also evaluated the existence of alterations or mutations of MRG15 in both FA and breast cancer patients, but no mutations were identified. They pointed out that the role of MRG15 is significant in the control of genomic stability, but a weak association could not be ruled out between potential low-penetrance MRG15 variants and breast cancer risk among BRCA2 mutation carriers. (Martrat et al. 2011.) However, further research is needed to confirm these findings and to better understand the role of MRG15 in tumorigenesis. In both of the two studies discussed above (I and II), no deleterious mutations in the genes investigated were found. Obviously, the selection of the candidate 72 gene is one of the most determining steps in this kind of targeted mutation analysis. Most of the candidate genes are chosen solely on the basis of their function, their association with known cancer predisposition-related pathways, or their relatedness to other known susceptibility genes, but often the precise biological functions of these genes remain obscure. However, it is possible that the function of the additional predisposing genes is unrelated to previously identified pathways, and therefore, will not be identified through the traditional candidate gene approach focusing on these. Equally important is the material studied. While the Finns represent a genetically isolated population, making disease-related founder mutations easier to find, the sample size is often limited and geographically may come from a relatively restricted area. Candidate gene association studies have been a pioneer in the field of genetic epidemiology, identifying risk alleles and their associations with various diseases. The method does, however, have some limitations. There is mild uncertainty whether the results in general portray disease susceptibility of a common variant or whether they represent certain ancestral differences existing by chance between the mixes of test or control populations. A lack of statistical power may also occur due to small sample size (Patnala et al. 2013). Further, unaffected sisters might provide a more appropriate comparison group for modern case-control studies than unrelated population controls, giving more valid relative risk estimates (Milne et al. 2011). 6.3 PALB2 c.1592delT mutation screening is clinically relevant in high-risk breast cancer patients tested negative for BRCA1/BRCA2 (III) The interpretation of new findings should be applied in clinical genetic services for the benefit of the majority of women who currently have no explanation for their breast cancer susceptibility (Southey et al. 2013). As with any test designed to identify risk factors in the general population, genetic tests for cancer susceptibility present considerable social and ethical challenges. Many factors must be taken into account before introducing new genetic markers into clinical cancer genetics. Careful evaluation is particularly important in the case of alleles with moderate- or low-penetrance risk. In addition, the limited methods for early detection and surveillance of certain cancers, e.g. breast cancer vs. pancreatic tumours, might pose a problem (Foulkes 2008). 73 The current guidelines for deciding which patients should be tested and which tests performed were updated several years ago. There are differing opinions about whether, when, and how we should increase the list of genetic susceptibility markers used in routine clinical care (Ripperger et al. 2009). Recent clinical recommendations and guidelines already display slight differences across European countries (Gadzicki et al. 2011). Biochemical evidence and candidate gene association studies have recently indicated that BRCA1, BRCA2, and PALB2 are the key breast cancer susceptibility factors, functioning together in the same important DNA damage response pathway. PALB2 has emerged as a third major cancer susceptibility factor, as mutations in this gene have been detected worldwide in most familial breast cancer cohorts tested. Most pathogenic PALB2 mutations identified to date are truncating frameshift or nonsense mutations and are found in different parts of the gene without hot-spot areas (Bogdanova et al. 2011, Erkko et al. 2007, Foulkes et al. 2007, Garcia et al. 2009b, Hellebrand et al. 2011, Rahman et al. 2007, Southey et al. 2010) Currently, patients attending clinical genetic services and seeking advice about their family history of breast cancer are routinely offered genetic testing for BRCA1 and BRCA2, but not for PALB2 (Southey et al. 2013). However, based on present knowledge, clinical translation of PALB2 is now timely. On average, PALB2 gene mutations confer moderate lifetime risks of breast cancer, but some mutations in this gene are associated with high breast cancer risks. These mutations are comparable to the average risk associated with BRCA2 mutations. The cumulative risk of the PALB2 c.1592delT mutation has been estimated to be 40% (95% CI 17–77) by the age of 70 years, which is almost as high as for mutations in BRCA2 (45%, 95% CI 31–56) (Erkko et al. 2008, Southey et al. 2010). In the first study reporting PALB2 c.1592delT in the Finnish population, the age of cancer onset for mutation carriers appeared to be somewhat lower than for average population-based breast cancer cases, but still slightly higher than for BRCA1/2 mutation carriers. However, this finding did not reach statistical significance (Erkko et al. 2008). In a second study from Southern Finland, the average age of first breast cancer among c.1592delT carriers was 53.1 years (33.4–79.9), in contrast to 45.2/47.4 years among BRCA1/BRCA2 carriers (Heikkinen et al. 2009). All three groups displayed younger age at disease onset than the average age of diagnosis in the population in general (61 years) (National Cancer Institute: SEER 2013). The frequency of different mutations in PALB2 shows great variability, and ranging from 0.1% to 2.7% worldwide. The 74 Finnish founder mutation has a relatively high frequency, ranging from 0.2% in healthy controls to 1.8% in unselected breast cancer cases (Erkko et al. 2007), particularly considering that the 19 most common founder mutations in BRCA1/2 combined account for 1.8% of the unselected cases in Finland (Syrjäkoski et al. 2000). The PALB2 mutation frequency of 4.8% observed in our current clinicalbased study was slightly higher than that reported in the previous study, where c.1592delT was found in 2.6% of familial breast cancer cases with a strong family history of the disease (Erkko et al. 2007), but this could also be due to the relatively small number of families eligible for the analysis. For women carrying a susceptibility factor and their relatives who might also be mutation carriers, knowing their mutation status is clinically and prognostically important. Identified mutation carriers should be kept informed about optimal breast cancer screening, prevention, or treatment strategies that could provide a clinical benefit for them. Our data, together with that of other corresponding studies (Southey et al. 2013), advocate the use of PALB2 gene mutational testing in non-BRCA families in both diagnostic and predictive testing. A strength of Study III was that it focused on one well-known mutation. We know that the c.1592delT mutation causes genomic instability in its carriers, demonstrated by a significant increase in the total number of spontaneous chromosomal rearrangements. The significance of this mutation for the impairment of genomic instability is supported by the results from its recent molecular and functional assessment. (Nikkilä et al. 2013.) Personalized medicine for women carrying PALB2 germline mutations might also be feasible in the short term (Southey et al. 2013). In PALB2 c.1592delT mutation carriers, PALB2 acts as a haploinsufficient tumour suppressor. LOH might not always need to be a prerequisite for malignant transformation since the c.1592delT truncation allele is apparently already on its own sufficient for such development. This is highly valuable information for developing targeted therapeutic approaches. (Nikkilä et al. 2013.) PALB2-deficient cells have been shown to be sensitive to PARP inhibitors, which selectively target cells deficient in homologous recombination DNA repair, but only when both alleles are missing or dysfunctional (Buisson et al. 2010). PARP inhibitors seem not to be suitable for those PALB2 mutation carriers whose tumours are negative for LOH (Tuma 2009). On the other hand, a patient with advanced pancreatic cancer revealed biallelic inactivation of the PALB2 gene in the tumour tissue and received customized treatment with mitomycin C. This gave a dramatic response and a remarkable clinical outcome (Villarroel et al. 75 2011). Together these findings demonstrate the potential utility of specific drugs in PALB2 mutation carriers as well as the clinical relevance of providing tailored therapy for improving outcomes. Testing for this mutation in high-risk breast cancer patients and in carriers’ siblings could influence the clinical outcome in many ways, e.g. earlier detection of the malignancy in the context of tailored surveillance programmes. The aim of this study was to translate the discoveries of basic science into clinical practice, thus improving patient care. It is important to note that findings of studies on cancer susceptibility have a great impact on patients and their families, including future offspring. A detailed informed consent is therefore crucial. 6.4 Fanconi anaemia cases in Finland and breast cancer predisposition (IV) The link between Fanconi anaemia and hereditary susceptibility to breast cancer has made all FA genes particularly attractive candidates for cancer-predisposing genes. Involvement of upstream FA genes in breast cancer susceptibility is, however, questionable because the link has thus far been established only for certain homologous recombination-related downstream factors (Howlett et al. 2002, Levran et al. 2005, Reid et al. 2007, Vaz et al. 2010, Xia et al. 2007). This pathway has prompted several mutational screening studies aimed at identifying additional breast cancer-predisposing FA genes. The rarity of the FA syndrome has complicated any conclusive analysis, as natural selection maintains a low prevalence of the clearly deleterious FA alleles. This study reports the first mutation confirmed FA patients in Finland, altogether five patients. All of the identified complementation groups, FA-A, FAG, and FA-I, have been described previously. FANCA is the most commonly mutated FA gene also in Finland. All FA genes identified encode proteins that are part of either the core complex (A, G) or the D2-I complex (I), but not part of the downstream branch in the FA pathway. Three of the FA patients (FA-G, FA-I, and one FA-A patient) manifested typical FA symptoms, whereas two brothers with FA-A showed somewhat milder phenotypes. These brothers were both homozygous for the FANCA c.3384-1G>A splicing mutation, leading to in-frame deletion of 20 amino acids. Some speculation centres around the defective protein retaining partial functionality, thus explaining the milder phenotype, but this has not been tested in functional studies. Curiously, this same mutation has recently 76 been reported in a compound heterozygous state in another FA patient outside Finland (Chandrasekharappa et al. 2013). To evaluate the association of identified FA mutations with cancer susceptibility, their prevalence in breast and prostate cancer cohorts and in gender-matched controls was tested. All seemed to be recurrent alleles in the Finnish population and their prevalence did not significantly differ between cancer cases and controls. In the case of FANCAex1-12del, the family history of both breast and pancreatic cancer in two of the mutation-positive breast cancer cases is suggestive of an effect on cancer predisposition in these families, but no firm evidence for this could be shown. Furthermore, whereas no clearly pathogenic mutations in the majority of the FA core complex or D2-I complex have been identified in familial breast cancer re-sequencing efforts (Garcia et al. 2009a, Garcia et al. 2009b, Seal et al. 2003), we did observe deleterious alleles in affected cases, but they occured at similar frequencies also in unaffected individuals. This indicates that the tested, clearly deleterious, heterozygous mutations in the FANCA, FANCG, and FANCI genes do not act as high- or moderate-risk alleles for breast or prostate cancer. However, since these alleles seem to be very rare, some low-penetrance effects cannot be excluded. Our results further strengthen the exclusive role of FA/BRCA pathway downstream genes in cancer predisposition. Interestingly, even though the Finnish FANCN/PALB2 c.1592delT founder mutation exhibits a relatively high frequency in our population, no Finnish FA patients with this mutation were identified. This indicates that PALB2 c.1592delT in biallelic state leads to a very severe phenotype (Reid et al. 2007, Xia et al. 2007) or might even be embryonically lethal. Despite the lack of association with cancer susceptibility, this study provides clinically relevant and intriguing information about the FA complementation groups and mutations found in Finland. The clinical diagnosis of FA is not always easy to make, particularly in cases with atypical clinical features (Liu et al. 2013). Compared to the found prevalence of heterozygous healthy persons the actual number of diagnosed cases seems quite limited. Maybe FA is underdiagnosed. According to genereviews only a minority of the FA patients shows any kind of dysmorphological features (Genereviews). This study revealed that FA-A, which is the most common FA subtype worldwide, also appears to be the predominant subtype in Finland. However, this fact should considered with caution, as the number of diagnosed and genetically tested Finnish FA patients is quite limited. 77 6.5 Finding the missing heritability of breast cancer susceptibility Over the past few years, the term “missing heritability” has been used to described the situation that most variants identified thus far confer relatively small increments in breast cancer risk and explain only a minor proportion of familial clustering, leading to the question of how the remaining cases can be explained (Manolio et al. 2009). Although GWA studies have been successful in identifying common variants involved in complex diseases, such as cancer, for the majority of complex traits <10% of the genetic variance is explained by common variants (Eichler et al. 2010). Despite a tremendous amount of work, the candidate gene approach to uncover new breast cancer susceptibility genes has offered limited success – even in cases that initially appeared quite promising. At present, known susceptibility genes are thought to be responsible for less than one-third of familial breast cancer cases. Although we believe that most of the known susceptibility genes function in the maintenance of genomic integrity, we cannot be sure that the missing genes will be related to similar biological pathways. Obviously, the missing heritability is a far more complicated issue than is currently realized and its understanding requires a more comprehensive assessment. It has been suggested that much of the missing heritability lies in gene-gene interactions. In a Mendelian disorder, one main gene acting in concert with other gene variants might be involved (Kaiser 2012). Recently, seven leading geneticists speculated about where the missing heritability might be found (Eichler et al. 2010). Perhaps a myriad of common variants of small effect does explain the vast majority of genetic effects predicted by heritability estimates, even though we cannot detect them individually. Further, the heritability could be due to the joint action of numerous loci of small effect. Gene-environment interactions may be important as well, but some susceptibility variants might confer risk only when inherited from a specific parent (parent-of-origin effect). Epigenetic effects beyond imprinting, such as DNA methylation and histone modifications, are examples of the complex relationship between genotype and phenotype. The discovery of non-coding microRNAs has revealed a new mechanism of translational regulation, and SNPs associated with breast cancer susceptibility have been shown to alter microRNA gene regulation. It is also reasonable to presume that coding sequence variations could synergistically act through protein-protein interactions and protein-DNA interactions in transcriptional networks and biochemical systems. One further hypothesis is that 78 a significant portion of the missing heritability is due to neither single common variants nor single rare variants, but rather to rare combinations of common variants. Finally, the possibility that some heritability comes from entirely unforeseen sources is something to look forward to exploring in the future. (Eichler et al. 2010.) 79 80 7 Concluding remarks and future prospects The main purpose of this thesis was to elucidate the background of familial breast cancer susceptibility. Currently, only ~30% of hereditary breast cancers can be explained by mutations in known breast cancer susceptibility genes. The detailed action mechanisms of these mutations and their exact penetrance remain largely obscure. New familial breast cancer predisposing factors need to be identified alongside further evaluation of those already recognized. When sufficiently validated, the knowledge gained in research laboratories should be transferred into clinical practice. Resolving the factors contributing to tumorigenesis, such as uncovering new predisposing alleles, will ultimately lead to a better understanding of cancer development, disease progression, and treatment. The putative candidate genes chosen for this study were AATF and MRG15. They were chosen because of their biological functions in the maintenance of genomic integrity and/or their interactions with known susceptibility gene products. The PALB2 c.1592delT mutation was evaluated as a clinical tool for diagnostic aetiology in high-risk breast cancer families. The DNA samples of known Finnish FA patients were studied in order to identify their complementation groups and the causative mutations. Additional evaluation was carried out to determine whether these FA gene mutations are enriched in breast and prostate cancer patient series. Based on the results of each study, the following observations and conclusions were drawn: 1. 2. 3. 4. No clearly pathogenic mutations were found in the AATF gene. The contribution of AATF germline mutations to breast cancer predisposition thus appears rare or absent. Germline mutations in the MRG15 gene do not make any sizeable contributions to familial breast cancer, at least not in the populations studied. The PALB2 c.1592delT founder mutation is known to be associated with a six-fold increased breast cancer risk. Based on our results, PALB2 c.1592delT should be included in the routine scheme of gene tests in genetic counselling, particularly for BRCA1/2-negative high-risk breast cancer patients. Mutation carriers should have tailored surveillance programmes. The complementation groups and gene mutations of Finnish Fanconi anaemia patients were identified, but no relationship between FA mutations and breast or prostate cancer susceptibility was observed, suggesting that deleterious 81 FANCA, FANCG, and FANCI mutations are not high- or moderate-risk alleles for breast or prostate cancer. To summarize, this study shed light on the background of familial breast cancer and forged some novel paths in a clinical setting. However, more research is needed to better understand tumorigenesis and to uncover all genetic factors as well as other factors predisposing to breast cancer. A considerable proportion of the remaining familial breast and/or ovarian cancer cases could be due to the multiplicative effect of various low- to moderate-penetrance genes, in combination with environmental and lifestyle factors. 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Kallio, Miki (2014) Muuttuuko lääketieteen opiskelijoiden käsitys terveydestä peruskoulutuksen aikana : kuusivuotinen seurantatutkimus Book orders: Granum: Virtual book store http://granum.uta.fi/granum/ D 1247 OULU 2014 UNIV ER S IT Y OF OULU P. O. B R[ 00 FI-90014 UNIVERSITY OF OULU FINLAND U N I V E R S I TAT I S S E R I E S SCIENTIAE RERUM NATURALIUM Professor Esa Hohtola HUMANIORA University Lecturer Santeri Palviainen TECHNICA Postdoctoral research fellow Sanna Taskila MEDICA Professor Olli Vuolteenaho SCIENTIAE RERUM SOCIALIUM ACTA U N I V E R S I T AT I S O U L U E N S I S Maria Haanpää E D I T O R S Maria Haanpää A B C D E F G O U L U E N S I S ACTA A C TA D 1247 HEREDITARY PREDISPOSITION TO BREAST CANCER – WITH A FOCUS ON AATF, MRG15, PALB2, AND THREE FANCONI ANAEMIA GENES University Lecturer Veli-Matti Ulvinen SCRIPTA ACADEMICA Director Sinikka Eskelinen OECONOMICA Professor Jari Juga EDITOR IN CHIEF Professor Olli Vuolteenaho PUBLICATIONS EDITOR Publications Editor Kirsti Nurkkala ISBN 978-952-62-0457-4 (Paperback) ISBN 978-952-62-0458-1 (PDF) ISSN 0355-3221 (Print) ISSN 1796-2234 (Online) UNIVERSITY OF OULU GRADUATE SCHOOL; UNIVERSITY OF OULU, FACULTY OF MEDICINE, INSTITUTE OF CLINICAL MEDICINE, DEPARTMENT OF CLINICAL GENETICS; FACULTY OF MEDICINE, INSTITUTE OF DIAGNOSTICS, DEPARTMENT OF CLINICAL CHEMISTRY; BIOCENTER OULU; OULU UNIVERSITY HOSPITAL; NATIONAL GRADUATE SCHOOL OF CLINICAL INVESTIGATION D MEDICA