Evaluation of the association between common genetic variants and
breast cancer risk
Thèse
Yosr Hamdi
Doctorat en médecine moléculaire
Philosophiae doctor
(Ph. D.)
Québec, Canada
Evaluation of the association between common genetic variants and
breast cancer risk
Thèse
Yosr Hamdi
Sous la direction de:
iii
RÉSUMÉ
Le cancer du sein est la néoplasie la plus fréquente chez la femme. Un ensemble de facteurs génétiques et environnementaux sont impliqués dans cette maladie complexe. Dans le cadre de mes études doctorales, je me suis intéressée à la composante génétique associée au risque de cancer du sein chez les femmes dans la population générale ainsi qu’à la modification du risque pour ce cancer chez des porteuses de mutations des gènes
BRCA1 et BRCA2. Actuellement, environ la moitié de cette composante génétique est
expliquée par une combinaison d'allèles à pénétrance faible, moyenne ou élevée. En outre, de récentes études ont démontré l'implication majeure de certains facteurs génétiques dans la modification du risque de cancer du sein chez des porteuses de mutations de BRCA1 et
BRCA2. Dans le cadre de ce projet, nous avons étudié l’impact potentiel de certains
variants génétiques dans les régions régulatrices de différents gènes et évalué leurs associations avec le risque de cancer du sein. Le projet a été divisé en deux parties : tout d'abord, nous avons évalué l'association directe entre les variants associés avec l’expression allélique différentielle et le risque de cancer du sein, afin d'identifier de nouveaux locus de susceptibilité à ce cancer. En second lieu, nous avons évalué l'impact sur l’expression génique de variants caractérisés au sein des régions promotrices de certains gènes sélectionnés, pour ensuite évaluer l’impact de ces variants sur l’expression génique. En résumé, la première partie de ce projet a conduit à l'identification d'un nouveau locus de faible pénétrance associés au risque de cancer du sein sur le locus 4q21 (rs11099601, odds ratio=1.05, p = 6.4 x 10-6), et deux nouveaux locus (11q22.3 et BRCA1-rs16942) associés avec la modification du risque de cancer du sein chez les porteuses de mutations du gène BRCA1. La seconde partie du projet a permis l'identification de nouveaux variants fonctionnels situés dans les régions promotrices des gènes ESR1, ESR2,
FOXA1, RAP80, NBN et CDC7.
D’autres études d’association dans de plus large cohorte ainsi que d’autres analyses fonctionnelles seront nécessaires pour confimer ces résultats, ce qui permettra de
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les inclure dans les nouveaux outils de prédiction de risque et ainsi assurer une estimation plus précise du risque de cancer du sein.
v
ABSTRACT
Breast cancer is the most common malignancy in women. A set of environmental and genetic factors are involved in this complex disease. This project focused on the genetic components of breast cancer susceptibility and breast cancer risk modification in
BRCA1 and BRCA2 mutation carriers. Currently, about half of the inherited susceptibility
to breast cancer can be imputed to a combination of high-, intermediate-, and low-risk alleles. Thus, many as yet unknown susceptibility loci remain to be identified. Moreover, recent studies have provided evidence for the involvement of genetic risk factors that might considerably modify the risk of developing breast cancer in BRCA1 and BRCA2 mutation carriers. Furthermore, genome-wide association studies have shown that several genetic variants within non-coding gene regions are associated with breast cancer risk. In this project, we focused on regulatory gene variants and their association with breast cancer risk. The project was divided in two parts. In the first section, we evaluated the direct association between single-nucleotide polymorphisms associated with differential allelic expression and breast cancer risk in order to identify new loci of breast cancer susceptibility. In the second part, we evaluated the functional impact on gene expression of variants identified within the promoter regions of selected candidate genes and then, characterize the functional impact of these variants. In summary, the first part of this project has led to the identification of a new low-penetrance locus associated with breast cancer risk on the 4q21 locus (rs11099601; odds ratio=1.05, p= 6.4 x 10-6), and two new modifiers of breast cancer risk in BRCA1 mutations carriers (11q22.3 locus and the wild type allele of BRCA1). The second part of the project allowed us to describe new functional variants within the promoters of the selected breast cancer gene candidates. Other association studies in larger cohorts and further functional analysis will be required to confirm these results, which will allow their inclusion in breast cancer risk prediction tools and thus ensure a more accurate estimation of breast cancer risk.
LIST OF CONTENTS
RÉSUMÉ ... iii
ABSTRACT ... v
LIST OF CONTENTS ... vi
LIST OF TABLES ... x
LIST OF FIGURES ... xii
LIST OF ABBREVIATIONS ... xiv
ACKNOWLEDGMENTS ... xviii REMERCIEMENTS ... xix FOREWORD ... xxi C H A P T E R 1 GENERAL INTRODUCTION ... 1 1. Cancer ... 2 2. Breast cancer ... 3
2.1 Breast cancer origin, development and hormone responsiveness ... 4
2.1.1 Mammary gland morphology and genesis of breast cancer ... 4
2.1.2 Breast cancer as a hormone-dependent cancer: Role of steroid hormones .... 5
2.1.3 Breast cancer molecular subtypes ... 8
2.2 Breast cancer risk factors ... 11
2.1.4 Non-genetic factors: ... 11
2.1.1 Genetic factors: ... 16
2.1 Breast cancer: The genetic component ... 16
2.1.2 Candidate genes: ... 18 2.1.3 Susceptibility genes: ... 18 2.3.2.1 High penetrance: ... 19 2.3.2.1 Moderate penetrance: ... 23 2.3.2.2 Low penetrance: ... 26 2.1.4 Modifier genes: ... 27
2.1.1 Current approaches for identifying novel breast cancer susceptibility genes or loci 39 2.3.2.3 Whole Exome Sequencing (WES): ... 41
2.3.2.5 Collaborative Oncological Gene-Environment Study (COGS): ... 42
2.2 Important pathways involved in breast cancer etiology: ... 44
2.2.1 DNA repair pathway: ... 44
2.1.2 The BRCA Interactome: ... 46
2.1.2.1 BRCA1: ... 46 2.1.2.1.1 BRCA1 A-Complex: ... 49 2.1.2.1.2 BRCA1-B-Complex: ... 50 2.1.2.1.3 BRCA1-C-Complex: ... 50 2.1.2.2 BRCA2: ... 51 2.1.3 Steroidogenesis pathway: ... 52
3. Regulation of gene expression: ... 53
3.1 In-cis regulation: ... 56
3.1.1 Proximal promoters and transcription factors: ... 57
3.1.2 Differential allelic expression and eQTLs: ... 57
3.1.3 Epigenetics and micro RNAs: ... 60
3.1.4 Other non-coding RNAs: ... 61
3.1.5 Distal regulatory elements: ... 62
3.2 Trans-regulation and interchromosomal interactions: ... 62
3.3 Regulatory variants and complex diseases: ... 64
3.4 Linkage disequilibrium and identification of causal variants: ... 67
4. The PhD project at a glance: ... 68
4.1 The contextualization and problematic: ... 68
4.2 Hypothesis: ... 68
4.3 Goal: ... 69
4.4 Specific aims: ... 69
4.5 Main results: ... 70
4.6 Conclusion: ... 72
C H A P T E R 2: ... ASSOCIATION OF BREAST CANCER RISK WITH GENETIC VARIANTS SHOWING DIFFERENTIAL ALLELIC EXPRESSION: IDENTIFICATION OF A NOVEL BREAST CANCER SUSCEPTIBILITY LOCUS AT 4q21. ... 73
1. Résumé: ... 74
2. Manuscript: ... 75
C H A P T E R 3 ASSOCIATION OF BREAST CANCER RISK IN BRCA1 AND BRCA2 MUTATION CARRIERS WITH GENETIC VARIANTS SHOWING DIFFERENTIAL ALLELIC EXPRESSION: IDENTIFICATION OF A MODIFIER OF BREAST CANCER RISK AT LOCUS 11q.22. ... 265
1. Résumé: ... 266
2. Manuscript : ... 267
C H A P T E R 4 FUNCTIONAL ANALYSIS OF PROMOTER VARIANTS IN INVOLVED IN DNA REPAIR, CELL CYCLE CONTROL AND SEX STEROIDS ACTION ... 326
1. Résumé: ... 327
2. Manuscript ... 328
C H A P T E R 5 ABRAXAS (FAM175A) AND BREAST CANCER SUSCEPTIBILITY: NO EVIDENCE OF ASSOCIATION IN THE BREAST CANCER FAMILY REGISTRY ... 365
1. Résumé: ... 366
2. Manuscript ... 367
C H A P T E R 6 COMMON VARIANTS OF THE BRCA1 WILD-TYPE ALLELE MODIFY THE RISK OF BREAST CANCER IN BRCA1 MUTATION CARRIERS ... 409
1. Résumé: ... 410
2. Manuscript: ... 411
C H A P T E R 7 GENERAL DISCUSSION ... 456
1. Synopsis of discussion ... 457
2. New concepts in breast cancer genomics: ... 461
2.1. How to find new breast cancer susceptibility loci: Our own proposal: ... 461
2.2. How to find new modifiers of breast cancer risk in BRCA2 mutation carriers: FOXA1 as a new breast cancer signature gene? ... 463
2.3. What we have learned from BRCA1 and BRCA2? ... 465
3. Evaluation and limitations of the methods used in this thesis study: ... 467
3.1 Association studies: ... 467
3.2. Functional analysis: ... 468
General conclusion ... 470
Appendix 1: Bio-informatics and databases ... 471
Appendix 2: Bio-Statistics, cohorts and Consortia ... 473
LIST OF TABLES
CHAPTER 1
Table 1. Breast cancer risk factors ... 17 Table.2 : Breast Cancer susceptibility genes of high and moderate penetrance ... 29 Table 3: common breast cancer susceptibility loci in the Caucasian population ... 30 Table 4 : Per allele hazard ratios (HR) and 95% confidence intervals (CI) of reported breast
cancer modifier loci among BRCA1 and BRCA2 mutation carriers. ... 40 Table 5 : Examples of the involvement of noncoding regulatory mechanisms in complex
diseases ... 66
CHAPTER 2
Table 1 Associations with breast cancer risk for SNPs showing evidence of differential allelic expression (overall p <0.01)... 120
CHAPTER 3
Table 1 : Associations with breast cancer risk in BRCA1 and BRCA2 mutation carriers for SNPs observed at p<10-2. ... 311 Table 2 : Associations with breast cancer risk by tumour subtype in BRCA1 and BRCA2
mutation carriers. ... 312 Table 3 : Associations with ovarian cancer risk in BRCA1 and BRCA2 mutation carriers for
SNPs observed at p<10-2. ... 313
CHAPTER 5
Table 1: Distribution of cases and controls by study center and by ethnicity in the BCFR ... 372 Table 2: Distribution of ABRAXAS rare variants (i.e. with a minor allele frequency<1% in
the Exome Variant Server (EVS)) identified in the BCFR ... 381 Table 3: Analysis of potentially pathogenic ABRAXAS in-frame deletion or rare missense
substitutions. ... 383 Table 4: Distribution of p.Thr141Ile, p.Ser7Ser and p.Ser11Ser by race/ethnicity. ... 384 Table 5: Stratified analyses of the common SNP rs13125836 (c. 1117G>A, p.Asp373Asn)
CHAPTER 6
Table 1ssociation between rs16942 genotypes on "wild-type" allele of BRCA1 and breast cancer risk restricted to rs16942 homozygotes ... 448 Table 2a Association between rs16942 genotypes on "wild-type" allele of BRCA1 and breast
cancer risk restricted to rs16942 homozygotes ... 448 Table 2b Table 2b: Association between rs16942 genotypes on "wild-type" allele of BRCA1
and breast cancer risk using family based phasing (see Material & Methods) ... 449 Table 3 Association between BRCA1 haplotypes on "wild-type" allele of BRCA1 and breast
cancer risk using family based phasing (see Material and Methods) ... 450
CHAPTER 7
Table.1 : Genomic loci associated with increased breast cancer risk and with some human instability syndromes ... 464
LIST OF FIGURES
CHAPTER 1
Figure 1. Breast architecture and mammary gland cells ... 7 Figure 2. Developmental stages of the mammary gland and breast cancer origins ... 9 Figure 3. Worldwide breast cancer estimated incidence and mortality rates in 2012 (World health organization, International Agency of research on cancer, IARC, 2012) ... 13 Figure 4 : Breast cancer susceptibility loci: relative risk and minor allele frequency connected with these loci ... 21 Figure 5. VUS diagrams of human BRCA1 and BRCA2 genes with the location and frequency of all missense variants in these two genes listed in the Breast Cancer Information Core database ... 24 Figure 6. Distribution of breast cancer risk in the general population and in affected cases…45
Figure 7. Main mechanisms of DNA double strand breaks repair: non-homologous end joining and homologous recombination ... 47 Figure 8. Model for BRCA1 recruitment in double strand DNA breaks. ... 48 Figure 9. Human steroidogenic and steroid-inactivating enzymes in peripheral intracrine tissues. ... 54 Figure 10. Allelic Imbalance ... 59 CHAPTER 2
Figure 1. Regional plots of breast cancer risk association at 4q21 ... 128 Figure 2. Functional annotation of the 4q21 locus ... 129 Figure 3. Boxplots representing differential expression of HELQ (A), MRPS18C (B), FAM175A (C) and HPSE (D) in breast tissues ... 130 Figure 4. Boxplots representing expression levels of HELQ (A), MRPS18C (B), FAM175A (C) and HPSE (D) in the 5 molecular subtypes (PAM50 classifier) of breast primary tumors. ... 131
Figure 5. Manhattan plots of association for the eQTL results at the 4q21 locus in normal breast and breast cancer tissue. ... 132 Figure 6. Boxplots representing the most significant eQTL results for variant rs11099601 in normal breast tissue and breast tumor datasets. ... 133 CHAPTER 3
Figure 1. Manhattan plot depicting the strength of association with breast cancer risk in BRCA1 mutation carriers for all imputed and genotyped SNPs across the 11q22.3 locus bound by hg19 coordinates chr11:107990104_108173189. ... 314 Figure 2. Functional annotation of the 11q22.3 locus. ... 315 CHAPTER 4
Figure 1. Inter-clones variability observed in transient transfection assays. ... 353 Figure 2. Gene promoter haplotype activity assessed by gene reporter assays.. ... 354 Figure 3. Representative EMSA analysis showing DNA–protein interactions in the promoter region of the selected genes. ... 354 CHAPTER 5
Figure 1. ABRAXAS multiple-sequence alignment. ... 398 Figure 2. p.Gly39val and p.Thr141Ile ABRAXAS mutants have defects in γ-H2AX formation ... 399 Figure 3. Functional assays assessing the impact of variant rs145796091 c.21G>A (p.Ser7Ser) on transcriptional activity and splicing efficiency in the MCF7 breast cancer cell line ... 400
CHAPTER 6
Figure 1. n Haplotypes and linkage disequilibrium structure of the BRCA1 gene. ... 452 Figure 2. Study specific hazard ratios between rs16942 genotypes on wild-type allele of BRCA1 and breast cancer risk. ... 453 Figure 3. Representative luciferase reporter assays of major BRCA1 haplotype constructs in HeLa cell line. ... 454 Figure 4. Representative EMSAs illustrating allelic DNA-protein interactions in the promoter region of BRCA1. ... 455
LIST OF ABBREVIATIONS
AR androgen receptor
AI allelic imbalance
BCAC Breast Cancer Association Consortium
BIC Breast Cancer Information Core
BRCT BRCA C-terminal domain
BM basal membrane
CDK cyclin dependent kinase
cDNA complementary deoxyribonucleic acid
CHIP chromatine immunoprecipitation
CI confidence interval
CIMBA Consortium of Investigators of Modifiers of BRCA1/2
CLL chronic lymphocyte leukemia
COGS Collaborative Oncological Gene-environment Study
CRM cis regulatory elements
CS Cowden syndrome
cSNP coding single nucleotide polymorphism
DAE differential allelic expression
DCIS ductal carcinoma in situ
DHEA dehydroepiandrosterone
DHEA-S dehydroepiandrosterone sulfate
DHS DNase-hypersensitive sites
DNA deoxyribonucleic acid
DSB double-strand breaks
EGFR epidermal growth factor receptor
E1 estrone
E2 estradiol
EMSA electrophoretic mobility shift assays
eQTL expression quantitave trait locus
ER estrogen receptor
ERT estrogen replacement therapy
ET estrogen therapy
FHT forkhead associated
FOXA1 Forkhead box protein A1
FRR familial relative risk
GWAS genome-wide association studies
Her2 human epidermal growth factor receptor 2
HR homologous recombination
HRT hormone replacement therapy
HSD Hydroxysteroid dehydrogenases
IBCCS International BRCA1/2 Carrier Cohort Study
kb kilobase
KRT keratins
LCIS lobular carcinoma in-situ
LD linkage disequilibrium
LFS Li-Fraumeni syndrome
LncRNA long non-coding ribonucleic acid
Lob lobules
NER Nucleotide excision repair
NHEJ non homologous end joining
MAF minor allele frequency
miRNA micro ribonucleic acid
MMR mismatch repair
OCAC Ovarian Cancer Asoociation Consortium
PARPi poly ADP ribose polymerase inhibitors
PJS Peutz-Jegher syndrome
PMD Percent mammographic breast density
PR progesterone receptor
RING really interesting new gene
RNA ribonucleic acid
RR relative risk
rSNP regulatory single-nucleotide polymorphism
SNP single-nucleotide polymorphism
TCGA The Cancer Genome Atlas
TF transcription factor
TNBC triple negative breast cancer
TSS transcription start site
UDP Uridine 5'-diphospho
VUS variants of uncertain significance
WES whole exome sequencing
Genes names listed in this thesis are the official gene symbol as listed in NCBI database (www.ncbi.nlm.nih.gov/LocusLink)
My darling mother, Zohra My dear brother, Maher
For my lovely daughter, Tajalli
ACKNOWLEDGMENTS
I would like to thank my supervisor, Dr. Jacques Simard, not only for his intellectual guidance, but also for his unfailing emotional support and encouragement. Many thanks to Dr. Penny Soucy, Dr. Martine Dumont, Stéphane Dubois, Guy Reimnitz, Martine Tranchant, and Marie-Cécile Symons. Without their assistance, this research would not have been possible. The support and constructive criticism of my fellow lab mates has been instrumental in shaping this project.
I would also like to thank the members of my Advisory Committee, Dre. Francine Durocher, Dr. Yohan Bossé and Dre. Catherine Laprise for their invaluable comments, suggestions, and support.
Dr. Richard Poulin for the scientific editing of the introduction of this thesis.
To my dear parents Zohra and Ahmed Hamdi, my sisters and brothers, especially Maher Hamdi and Yasser Hamdi. I owe them much gratitude for their unending love, support and encouragement.
To my husband, Abdennaceur Aouini, and my daughter Tajalli, I thank you for your patience, encouragement and interest in my research. Without your support, this thesis would never have come to fruition.
REMERCIEMENTS
Par respect pour votre langue maternelle. Je tiens à vous exprimer mes remerciements en français, Je vous adresse d’abord mes excuses pour avoir plutôt utilisé l’anglais pour la rédaction de ma thèse, et je mentionne que, comme le dit Anatole France, « La langue française est une femme et cette femme est si belle, si fière, si modeste, si hardie, si touchante, si voluptueuse, si chaste, si noble, si familière, si folle, si sage, qu'on l'aime de toute son âme, et qu'on n'est jamais tenté de lui être infidèle».
Je tiens à remercier Dr. Jacques Simard, pour sa supervision et pour l’excellente formation que j’ai reçue au sein de son équipe. Il a été pour moi une véritable source d’inspiration; j’ai toujours été émue par son parcours scientifique et par son intérêt pour la science, qu’il a bien su me communiquer. De plus, je serai toujours reconnaissante pour sa compréhension et son soutien durant les périodes difficiles par lesquelles j’ai passé au cours de mes études doctorales. Bref, merci infiniment!
Un grand merci également à Dr. Penny Soucy et Dr. Martine Dumont, qui m’ont accompagnées de très près au cours de ces dernières années, pour leur encadrement et leurs expertises qu’elles ont partagée généreusement avec moi
Je tiens aussi à exprimer ma reconnaissance à Marie-Cécile Symons, pour son soutien administratif, ses conseils, son excellente habileté; elle était plus qu’une collègue pour moi, elle était une amie proche!
Merci également à Stéphane Dubois, Guy Reimnitiz et Martine Tranchant pour leurs regards critiques et pour les discussions scientifiques intéressantes qu’on a eues ensemble; j’ai eu la chance de côtoyer Stéphane et de discuter et échanger plusieurs idées sur le projet avec lui. J’ai beaucoup apprécié le calme et la bienfaisance de Guy. Je dois énormément à Martine Tranchant : elle m’a formée avec beaucoup de patience et de constance.
Par la même occasion, j’aimerais bien remercier tous ceux que j’ai côtoyés durant ces dernières années, et notamment toute l’équipe de la Dr. Francine Durocher. Ce fut un
vrai plaisir d’échanger avec eux sur les actualités ainsi que sur plusieurs domaines, incluant les sciences.
Merci au Dr. Arnaud Droit et à son équipe pour leur aide en bioinformatique. Merci au
Dr. Mohammed Lajmi lakhal et à son équipe pour leur soutien sur des questions biostatistiques.
Je veux également, exprimer ma gratitude à mes proches : à mes parents, à mes sœurs et à mes frères qui m’ont grandement soutenue; leur support moral et financier m’a été d’une grande valeur.
Un grand merci à mon mari Abdennaceur Aouini, tant pour les moments de réjouissance que pour les moments de doute, pour son amour, son affection et son soutien. J’apprends beaucoup de sa sagesse et de sa vision des choses.
Finalement, merci à ma fille Tajalli, pour tout le changement qu’elle a apporté en moi; sa venue m’a apporté beaucoup de confiance en moi, d’amour et d’espoir!
FOREWORD
“I do not carry such information in my mind since it is readily available in books. The value of a college education is not the learning of many facts but the training of the mind to think.” (Albert Einstein)
This work has been performed in the Cancer Genomics Laboratory, Department of molecular medecine of the Centre de recherche du centre hospitalier universitaire de
Québec (CRCHU de Québec-Université Laval), as part of the requirements for the
molecular medecine program of the faculty of medicine, Université Laval.
This thesis is composed of 7 chapters including 5 publications in the field of human genomics research, and more specifically, on the genetics of breast cancer.
The publication described in CHAPTER 2 has been published for in Oncotarget Journal. The second manuscript (CHAPTER 3) was published the Breast Cancer research and
treatment Journal (2016). The third publication (CHAPTER 4) will be submitted soon.
The fourth paper (CHAPTER 5) was published in PLOS one journal. Finaly, the fifth publication (CHAPTER 6) has been published in the Human Molecular Genetics.
Note that the order of manuscripts included in this thesis does not respect the chronological order of publication in order to facilitate the presentation of the two parts of my project: evluation of the association of genetic variants with breast cancer risk (chapter 2, 3) and assessment of functional effect of breast cancer candidate genes (chapter 4, 5 and 6).
For each chapter composing the body of this thesis, Dr. Jacques Simard coordinated the development of the study, the design of the cohorts and revision of the manuscripts.
For Chapter 2 and 3, I was responsible of the study design, performed data analysis and drafted the manuscript. Dr. Penny Soucy helped with writing the manuscript and data analysis. Dr. Arnauld Droit and Audrey Lemaçon performed bioinformatic analysis. Dr. Tomi Pastinen and Dr.Véronique Abdoue provided interesting data on genes and variants involved in differential allelic expression. Dr. Silje Nord performed eQTL
analysis in chapter 2 and 3. The presence of BCAC (Breast Cancer Association Consortium) and CIMBA (Consortium of Investigators of Modifiers in BRCA1 and BRCA2) in the authors' list of Charpter 2 and Chapter 3 respectively reflects the involvement of our international collaborators, in collecting DNA samples, genotyping assays and revision of the manuscripts as a part of the COGS Collaborative Oncological Gene Envirnment Study.
For Chapter 4, I performed functional assays, data analysis and I drafted the manuscript. Martin Lecler and Dr. M’hamed Lajmi lakhal performed biostatistical analysis. Dr. Martine Dumont helped in data analysis and helped in writing the manuscript. Dr. Penny Soucy participated in study coordination and manuscript revision, Pauline Cassart, Manon Ouimet and Dr. Daniel Sinnett performed electrophoretic shift mobility assays, while Martine Tranchant, Stéphane Dubois and Guy Reimnitz helped in functional assays.
In Chapter 5 and because of the interesting results presented in Chapter 2 regarding the identification of a variant in the FAM175A gene as associated with breast cancer risk, we evaluated the association with breast cancer susceptibility of exonic variations identified on the FAM175A gene. Anne Laure Renault performed mutation screening and drafted the manuscript. Dr. Fabienne Lessueur and Dr. Sean V. Tavtigian participated in alignments, scoring and in silico analysis of missense substitutions. Dr. Penny Soucy coordinated the study and revised the manuscript. I participated by supervising Anne Laure during her Master project by orienting her study on FAM175A gene and by revising the manuscript. Yan Coulombe, Dr. Sylvie Desjardins, Dr. Stéphane Gobeil and Dr. Jean Yves Masson performed functional assays. The Breast Cancer Family Registry is also quoted to have provided the genomic DNA of 2,453 women and their personal data.
In Chapter 6, Dr. David G. Cox performed genotyping and datation study and
analysis, Dr. Jacques Simard and Dr. Olga Sinilnikova coordinated association study and
the design of the cohorts. Dr. Daniel Sinnett coordinated the functional part of the manuscript. I performed functional gene reporter assays and in silico predictions of transcription factor binding sites. Dr. Penny Soucy helped in the revision of the
manuscript. The other participating authors of Chapter 6 represent the valuable contribution of the largest international collection of BRCA1 and BRCA2 mutation carriers, CIMBA.
C H A P T E R 1
CHAPTER 1: GENERAL INTRODUCTION
1.
Cancer
Worldwide, almost 14 million new cases of cancer and about 8.2 million cancer related deaths were reported in 2012. In Canada, an estimated 196, 900 new cancer cases (excluding 78, 300 non-melanoma skin cancers) and 78,000 deaths from cancer will occur in 2015. Of the newly diagnosed cases, more than half will be lung, colorectal, prostate and breast cancers (1). The remarkable increase in the number of new cancer cases is mostly due to the growing and aging Canadian population. However, cancer mortality rates declined significantly worldwide. On average, the annual decline was ≥2% for the following cancers: prostate cancer, lung cancer, larynx and colorectal cancers in males, and breast and cervical cancers in females, with stomach cancer and non-Hodgkin lymphoma being of comparable frequency in both sexes. In western countries, cancer mortality rates declined considerably, a reflection of the remarkable progress made in cancer prognosis and treatment in these countries (2). However, the National cancer Institute showed that 70% of the world’s cancer deaths occur in Africa, Asia, central and south America.
Cancer is a class of diseases characterized by out-of-control cell growth. Damaged cells divide uncontrollably to form lumps or masses of tissue called tumors (except in the case of leukemia, where cancer interferes with normal blood function by abnormal cell division in the bloodstream) (3). Normal cells in the body follow an orderly sequence of growth, division, and death. Unlike healthy cells, cancer cells do not experience programmed cell death (i.e. apoptosis) and instead, continue to grow and divide while building up a tumor. Tumors that stay at the site of origin and demonstrate limited growth are generally considered as benign and are not usually life-threatening (2), whereas malignant tumor cells are able to invade nearby tissues and spread to other parts of the body.
Scientists have reported the discovery of an important clue as to why cancer cells spread (3). Indeed, certain molecular interactions between cells and the extracellular
matrix cause them to extricate themselves from the original tumor site, to move away and then to reattach to a new site. This discovery was important because cancer-related mortality is mainly due to the appearance of metastatic tumors, i.e. masses that grow from cells that have traveled from their original site to another part of the body. Indeed, only ~10% of cancer deaths are caused by the primary tumors themselves (4-5).
There are over 100 different types of cancer, which are classified according to the initially affected cell types. However, only five broad groups are used to classify cancer (1):
• Carcinomas are characterized by cells that cover the surface of internal and external organs, such as lung, breast, and colon cancer.
• Sarcomas are characterized by cells that are located in the bone, cartilage, fat, connective tissue, muscle, and other supportive (i.e. mesenchymal) tissues.
• Lymphomas are cancers that originate from lymph node and immune system tissues.
• Leukemias are cancers that stem from the bone marrow and that often accumulate in the bloodstream.
• Adenomas are cancers that arise in the thyroid, pituitary gland, adrenal glands, and other glandular tissues.
2.
Breast cancer
Breast cancer is both the most common and the most deadly cancer in women worldwide with an estimated one million new cases occuring annually (6). In Canada, over 25, 000 new cases of breast cancer are diagnosed annually and more than 5, 000 Canadian women die of the disease every year (7).
In recent years, major progress has been reported in clinical and biological breast cancer research. This progress has led to a better understanding of almost all aspects of this malignancy. Indeed, breast cancer usually begins either in lobular or ductal tissues and may also originate from the stromal tissue, which include the fatty and fibrous connective tissues of the breast (8). Nowadays, it is clear that lobular differentiation, cell
proliferation, hormone responsiveness and DNA mutations are the main factors governing breast tumor development.
2.1
Breast cancer origin, development and hormone responsiveness
2.1.1 Mammary gland morphology and genesis of breast cancerThe mammary epithelium is a bilayered structure consisting of an inner continuous layer of luminal epithelial cells and an outer layer of contractile myoepithelial cells. The epithelial bilayer is polarized; the apical layer (luminal epithelial cells) faces the lumen of the ducts and the alveoli, and the basal layer (myoepithelial cells) is in close contact with a laminin-rich basal membrane (BM) (9). This gland represents a model for investigating how functional and structural homeostasis is achieved by undergoing cycles of development, differentiation, and apoptosis during the adult life of the organism. These cyclic changes involve dramatic shifts in the structure and function of the tissue, and are regulated through complex multi-hormonal and growth factor signaling pathways (10) (Figure 1). Indeed, in both normal mammary glands and breast cancer cells, steroid hormones, among which estrogens (e.g. estradiol (E2), estrone (E1), etc.) and progestins (mainly progesterone) play crucial roles in tissue function (11). They regulate mammary gland development at puberty and during pregnancy, and are associated with the initiation, development, and progression of breast cancer (12). Thus, the microenvironment of mammary tissues is intimately involved in the initiation and maintenance of estrogen and progesterone responsiveness. From birth to the onset of puberty, few changes occur in the mammary gland, and mammary tissues are essentially identical in both males and females. However, during puberty the female mammary gland is exposed to the production of the ovarian steroid hormones, E1 and E2. The mammary response to these estrogens consists initially in the formation of clusters of 6 to 11 ductules per lobule, which is identified as type 1 (lob1) at this stage (Figure 2). Lob1 lobules progress to the lob2 stage in the postpubertal virgin gland. Once pregnancy occurs, elevated levels of estrogens and progesterone, another ovarian steroid hormone, as well as various pituitary hormones stimulate lob1 and lob2 to progress to type 3 (lob3). Lob3 lobules are formed by the epithelial expansion of existing pubertal alveoli to a total of ~80 small lobules per
alveolus. These changes prime the mammary gland for milk secretion from the alveoli, which are now called secretory lobules type 4 (lob4). Finally, with the cessation of lactation, alveoli collapse and the mammary gland regresses apoptotically to its resting, pre-pregnancy state, reverting to lob3 and lob2, while retaining a more extensive framework of branching than lob1 (13). Thus, the adult female mammary gland experiences recurrent cycles of regulated growth, differentiation and apoptosis. Russo and Russo (12) have observed that specific morphological types of breast cancer are linked to specific breast structures or developmental stages of the mammary gland. For example, the most common type of breast malignancy, ductal carcinoma, corresponds to the lob1 stage. Similarly, lobular carcinomas in situ are found in lob2, benign breast lesions originate in lob3, and lactating adenomas arise in lob4-stage cells. They concluded from these observations that less functionally differentiated breast cells (lob1) are more susceptible to give rise to the most undifferentiated types of neoplasm, suggesting that the developmental stage of the breast appears to affect the likelihood of neoplastic transformation. Some other independant studies support the latter hypothesis, such as those that demonstrate the higher risk of malignancy in nulliparous and late parous women (14).
2.1.2 Breast cancer as a hormone-dependent cancer: Role of steroid hormones
Different studies showed that hormones are of significant importance in maintaining malignant cell homeostasis and growth in various types of cancers (15). In 1896, Beatson made an important discovery by showing that the removal of the ovaries caused the regression of breast cancer (16). This classic work is especially noteworthy because it was made before the discovery of endocrine gland secretion. Soon afterwards, it was found that many, albeit not all women with mammary cancer benefited from oophorectomy. While studying induced hormonal imbalance in men with advanced mammary cancer, Farrow and Adair (17) observed that orchiectomy was followed by a regression of the neoplasm.
Currently, it is well known that estrogens and progesterone promote proliferation and differentiation in the normal breast epithelium. They function via binding to their corresponding intracellular receptors, estrogen receptor (ER) and progesterone receptor (PR), respectively, which are members of the nuclear hormone receptor superfamily. In fact, biochemical evidence for the existence of cellular receptors for steroid hormones was first demonstrated by the use of radiolabeled estrogens and examination of specific binding within estrogen-responsive tissues (Glascock and Hoekstra, 1959; Jensen and Jacobson, 1960, 1962). Two forms of ER are known to exist, ERα and ERβ which exhibit distinct tissue-specific expression patterns and biological roles (18-19). ERα is a ligand-activated transcription factor composed of several domains important for hormone binding, DNA binding, and activation of transcription and is more abundant in breast, endometrial, ovarian, and hypothalamus tissues than ERβ.
This latter is also expressed in the mammary gland and in some breast cancers (20-21), but its specific function is still largely unknown. ERβ binds DNA in a manner similar to ERα, i.e. as a homodimer interacting with estrogen response elements (EREs) (22-25). Likewise, two forms of PR are also known to exist, PR-a and PR-b, but unlike the ER subtypes, which are separate genes, these isoforms are transcribed from two distinct transcription start sites (TSSs) within the same gene (26).
In addition to estrogens and progesterone, there are many additional contributing factors that regulate mammary cell behavior, such as the epidermal growth factor receptor (EGFR) family. Signals through receptors of that family are required for normal mammary gland development. Ligands for EGFR (e.g.ERBB2 also known as human Her2), are overexpressed in a significant proportion of breast cancers, and elevated expression of particular EGFR subunits is strongly associated with a poorer clinical outcome. Moreover, there is strong evidence for crosstalk between growth factors and steroid hormones (27). Estrogens and progesterone can regulate the synthesis of EGFR subunits (28-30). Conversely, numerous studies have also shown that steroid hormone receptors can be activated by growth factors.
Figure 1. Breast architecture and mammary gland cells
The basic components of a mature mammary gland are the alveoli (hollow cavities, a few millimeters large) lined with milk-secreting cuboidal cells and surrounded by myoepithelial cells. These alveoli join to form groups known as lobules. Each lobule has a lactiferous duct that drains into openings in the nipple. The myoepithelial cells excrete the milk secreted by alveolar units into the lobule lumen and toward the nipple. The major part of the breast structure is represented by fatty tissues.
2.1.3 Breast cancer molecular subtypes
The molecular classification of breast cancer originates from the unsupervised hierarchical clustering analysis of complementary DNA (cDNA) microarray data by Perou’s group, which revealed the existence of four major intrinsic molecular subtypes according to steroid hormone receptor status : luminal A, luminal B, basal-like and HER2 type (human epidermal growth factor receptor 2) (31). Other less common molecular subtypes have also been described, including androgen-positive (or negative) breast cancer; normal breast-like, apocrine molecular type and claudin-low type (32). Breast cancers that do not fall into any of these subtypes are often listed as unclassified.
Researchers studied how molecular breast cancer subtypes might become useful in planning treatments and in developing new therapies. Indeed, prognosis and treatment decisions are chiefly guided by hormone receptor and HER2/neu status (33). The complex profile of each subtype is determined by using the molecular and genetic information from tumor cells. Most breast cancers are luminal tumors (34). The general appearance of luminal tumor cells is close
to that of breast cancer cells originating from the inner (luminal) cells that line mammary ducts.Two subtypes of luminal breast cancer are now well known; luminal A and luminal B
Luminal A
Luminal A tumors tend to be ER positive (ER+) and PR positive (PR+), HER2/neu-negative (HER2-) with a low to moderate tumor grade. Luminal breast cancers have a gene expression signature that includes estrogen receptor 1 (ESR1), GATA-binding protein 3 (GATA3), forkhead box protein A1 (FOXA1), B-cell chronic lymphocytic leukemia (CLL)/lymphoma 2 (BCL-2), X-box binding protein 1 (XBP1), and the myeloblastosis gene (MYB), which are highly characteristic of luminal epithelial cells of a normal breast duct. Of the four subtypes, luminal A tumors tend to have the best prognosis, with fairly high survival rates and low recurrence rates. Because luminal A tumors tend to be ER and/or PR positive, treatment for these tumors are often associated with hormone therapy (35).
Figure 2. Developmental stages of the mammary gland and breast cancer origins The adult female mammary gland experiences recurrent cycles of regulated growth, differentiation, and apoptosis. Estrogens and progesterone play a central role in this process. The cycles that occur in the mammary gland can be divided into several stages: puberty, pregnancy, lactation, and involution. Each stage can be characterized by the relevant structure of the gland, called lobules or lobs. The development of breast cancer is characterized by the gain or loss of discrete cellular functions, a characteristic which has been used to classify breast tumors into specific morphological types. Thus, the common type of breast malignancy, ductal carcinoma, corresponds to lob1, the lobular carcinoma in situ is found in lob2, benign breast lesions originate in lob3, and lactating adenomas arise in lob4. The arrows used in the figure mean an increase in the estrogen and progesterone levels. (Russo et al. Breast Cancer Res Treat, 1992).
ESTROGENS PROGESTERONE PUBERTY (Lob1>Lob2) PREGNANCY (Lob3) LACTATION (Lob4) INVOLUTION (Lob3>Lob2) Lactating adenomas Benign breast lesion Ductal carcinoma Lobular carcinoma GROWTH APOPTOSIS
Luminal B
Luminal B tumors tend to be ER+ and/or PR+ with a high percentage of Ki67 positive. Only 12 to 15% of luminal B tumors have TP53 mutations, a factor that includes a high number of actively dividing cancer cells and/or HER2/neu-positive cells. Luminal B cancers differ from the luminal A type by their lower levels of luminal gene expression, by higher levels of proliferation-associated gene expression, and by their worse clinical outcome. Moreover, women with luminal B tumors are often diagnosed at a younger age than those with luminal A tumors (36-37). Finally, compared to luminal A tumors, luminal B malignancies tend to present factors associated with a poorer prognosis, including poorer tumor grade, larger tumor size, lymph node-positivity and TP53 gene mutations. In some studies, women with luminal B tumors have shown fairly high survival rates, albeit lower than those presenting luminal A tumors.
Basal-like breast cancer:
Basal-like breast cancer is characterized by the expression of the basal gene signature, which includes keratins (KRT5, KRT6 and KRT17) (38). In the absence of treatment, patients with basal-like breast cancer face a poor clinical outcome, particularly in the first 5 years after diagnosis (39). Although basal-like subtype is often considered as triple-negative breast cancer (TNBC) for ER, PR, and HER2 expression, basal-like disease and TNBC do not completely overlap (40).
HER2 type:
The HER2-positive type of breast cancer seems to strongly promote the growth of cancer cells (41). In about 20% of breast cancers, tumor cells express an excess of HER2 due to various mechanisms, including transcriptional upregulation and gene amplification. These elevated levels of HER2 can occur in many types of cancer other than breast cancer (e.g. prostate, colon and pancreas) (42). HER2 positive breast tumors tend to be more aggressive and are less responsive to hormone treatment than other types of breast cancer. However, treatments that specifically target HER2 such as Trastuzumab (Herceptin) and Lapatinib (Tykerb) are very effective therapeutically.
2.2
Breast cancer risk factors
Different cancers have different specific risk factors. However, the fact of having one or several risk factors for a given disease does not imply that this disease will be developped with certainty. Most women who possess one or more breast cancer risk factors never develop the disease, while many women with breast cancer have no known risk factors (other than being a woman and growing older) (43).
As a multifactorial disease, many risk factors are associated with breast cancer. They are divided into two main categories: non genetic and genetic factors. Indeed, breast cancer risk vary over time due to environmental factors, aging or personal lifestyle, such as smoking, drinking and diet.
2.1.4 Non-genetic factors: Gender:
The mere fact of being a woman is the main risk factor for developing breast cancer. Men can also develop this disease but it is about 100 times more frequent in women than in men (44). This situation probably arises from the fact that men produce lesser amounts of the female hormones (i.e. estrogens and progesterone), which can promote breast cancer cell growth.
Aging:
The risk of developing breast cancer increases with age. About one out of eight invasive breast cancers are found in women younger than 45, while about two-thirds of all invasive breast cancers are found in women aged 55-years old or more (45).
Race and ethnicity:
Overall, Caucasian women are slightly more likely to develop breast cancer than African-American women, although the latter are more likely to die of this cancer (46). However, in women younger than 45 years, breast cancer is more common in African- American women. Asian, Hispanic, and Native-American women have a lower breast cancer incidence and mortality rates (47) (Figure 3).
Dense breast tissue
Percent mammographic breast density (PMD) is defined as the proportion of a mammographic image occupied by radiodense tissue, largely stromal and epithelial tissues, appearing as white regions on the mammogram, as opposed to non-dense fatty tissue. Women with denser breast tissue (i.e. higher PMD) have more glandular and less fatty tissue, and have a higher risk of breast cancer.
Women with dense tissue in >75% of the breast have been shown to be at a 4 to 5 folds increased risk of breast cancer as compared with women with mostly fatty breasts (48-49). Recent studies have shown that this breast cancer risk factor is due to genetic variations. Indeed, a meta-analysis of five genome-wide association studies (GWAS) reported an association with between breast density and rs10995190, a variant on the zinc finger protein-365 (ZNF365) (combined p-value= 9.6 × 10-10) (50).
Another study examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large consortium identified two breast cancer susceptibility variants, namely LSP1-rs3817198 and RAD51L1-rs10483813, that are associated with mammographic measures and in the same direction as the breast cancer association (51). Subsequently, another genetic locus (12q24-rs1265507) was found to be associated with PMD (p-value= 1.03 × 10-8) (52).
Menstrual period: early menarche-late menopause:
Women who started menstruating at an earlier age (i.e. before age 12) and/or underwent menopause at a later age (i.e. after age 55) may have a slightly higher risk of breast cancer (53). This increased risk may be due to a longer lifetime exposure to estrogens and progesterone (54).
Previous chest radiation:
Women who had radiation therapy of the chest area as treatment for another cancer as children or young adults have a significantly increased risk for breast cancer. This varies with the patient's age at the time of radiation exposure (55). Indeed, the risk of developing breast cancer from chest radiation is at its highest when radiotherapy is administered during adolescence, however, radiation treatment after age 40 does not seem to increase
Figure 3. Worldwide breast cancer estimated incidence and mortality rates in 2012 (World Health Organization, International Agency of research on cancer, IARC-2012)
breast cancer risk. If chemotherapy was also received, it may have stopped ovarian hormone production for some period of time, thereby lowering the risk.
Childbirth (parturition) and nulliparity:
Women who have never experienced childbirth or who have had their first child after age 30 have a slightly higher risk of developing breast cancer (56). Pregnancy reduces the total number of lifetime menstrual cycles for a woman, which may explain its protective effect.
Hormone therapy after menopause:
Hormone therapy with estrogens (often combined with progesterone) has been used for many years to help relieving the symptoms of menopause and preventing osteoporosis (57). This treatment is known under various names, such as postmenopausal hormone therapy (PHT), hormone f therapy (HRT), or menopausal hormone therapy (MHT). There are two main types of hormone therapy. For women who still have a uterus, both estrogens and progesterone are generally used in combination, which is known as combined hormone therapy. For women who have undergone uterectomy, estrogens alone can be used. This is commonly known as estrogen replacement therapy (ERT) or simply estrogen therapy (ET). Using combined HT after menopause increases the risk of developing breast cancer. It may also increase the chances of dying from breast cancer. This increase in risk can be observed with as few as two years of use. Combined HT also increases the likelihood that the cancer may be found at a more advanced stage (58). However, there is no evidence that the use of estrogens alone after menopause increases the risk of developing breast cancer. In fact, women who have previously had their uterus removed and who take estrogen actually have a lower risk of developing breast cancer (59). Moreover, when used on a long-term basis (i.e. > 10-year period), ET has been found to increase the risk of ovarian cancer (60).
• Recent oral contraceptive use:
Studies have found that women using oral contraceptives have a slightly greater risk of breast cancer than women who have never used them. This risk seems to vanish over time once contraceptive use is stopped (61-62).
• Depot-medroxyprogesterone acetate (DMPA; Depo-Provera):
DMPA is an injectable form of a synthetic progestin that is given at three-month intervals as a method of birth control. Women currently using DMPA seem to experience an increased breast cancer risk, although the latter increase disappears after more than five years of cessation of DMPA use (63).
Breastfeeding
Some studies suggest that breastfeeding might slightly lower breast cancer risk, especially if breastfeeding duration extends to 1½ to 2 years (64). One explanation for this apparent effect on breast cancer risk may be that breastfeeding reduces the total number of lifetime menstrual cycles, i.e. for the same reason that late menarche and early menopause reduce the risk of breast cancer.
Excess weight and obesity
Excess body weight or obesity after menopause increases breast cancer risk. Before menopause, ovaries are the main sites of estrogen production, whereas adrenal glands and adipose tissue produces relatively small amounts of estrogens. After menopause, the relative contribution of fat cells in estrogen production increases considerably (65). Thus, excessive amounts of adipose tissue after menopause may increase the risk of breast cancer by raising estrogen levels above average values. Furthermore, overweight women tend to have higher circulating insulin levels that have also been associated with several cancers, including breast cancer (66).
Tobacco smoke
For a long time, no association between cigarette smoking and breast cancer could be demonstrated. In recent years, however, some studies have found that smoking might increase the risk of breast cancer. This increased risk more specifically affects particular categories, such as women having started smoking at a relative young age (67). Nevertheless, the International Agency for Research on Cancer concluded in 2009 that there is limited evidence that tobacco smoking causes breast cancer (68). The evidence on the effect of second-hand smoke on breast cancer risk in human studies is controversial,
at least in part because the association between smoking and breast cancer is itself still unclear.
2.1.1 Genetic factors:
Epidemiological studies have led to the development of genetic instead of environmental models to explain the occurrence of familial breast cancers (69). It has been shown that having two first-degree relatives (mother, sister, or daughter, etc) with breast cancer increases that risk by about three-fold (70). Moreover, women with a male breast cancer family history (father, brother or cousin, etc) also have an increased risk of this cancer. Although, the exact relative risk of the family history of male breast cancer is still undetermined (71). In addition, twins studies indicated that the familial risk of breast cancer is largely the result of an inherited susceptibility due to the combined effects of multiple genetic variants (72). Thus, taken together, studies on breast cancer in twins as well as the hereditary distribution of breast cancer among families suggest that genetic factors predominantly explain the familial aggregation observed for breast cancer incidence.
A measure of this breast cancer familial clustering is the familial relative risk (FRR), defined as the ratio of the risk of developing a disease for a relative of an affected individual to the same risk observed in the general population. The FRR for breast cancer varies with the age at cancer diagnosis in the index case and the age of the relative (73). For example, FRR decreases from more than five-fold in women younger than 40, with a relative younger than 40 years at time of diagnosis, to 1.4 fold in women older than 60 with a relative diagnosed over the age of 60 (74). The FRR increases progressively with the number of affected relatives (75-76).
Overall, a substantial percentage (5-10 %) of all breast cancer cases are thought to be hereditary and resulting directly from gene mutations (77).
2.1
Breast cancer: The genetic component
Breast cancer is a complex disease with a strong heritable component. Genes involved in this disease are divided into 3 main groups: candidate, susceptibility and modifier genes. Moreover, among breast cancer susceptibility alleles, three classes, with different levels of risk and prevalence,
Table 1. Breast cancer risk factors
Risk Factor Breast Cancer Risk
Ratio (95% CI) ≥2 fold increased risk
First-degree relatives with breast cancer
1 2.14 (1.92-2.38)
2 3.84 (2.37-6.22)
Any 1.86 (1.69-2.06)
Age of first-degree relatives with breast cancer
<40 years 3.0 (1.8-4.9)
<50 years 2.17 (1.86-2.53)
Breast Density BI-RADS category 4 2.04 (1.84-2.26) 1.5 to 2.0-fold increased risk
Prior benign breast biopsy result 1.87 (1.64-2.13) 2nd degree relative with breast cancer 1.7 (1.4-2.0) Breast Density BI-RADS category 3 1.62 (1.51-1.75) 1.0 to 1.5-fold increased risk
Current oral contraceptive use 1.30 (1.12-1.49)
Nulliparity 1.25 (1.08-1.46)
have been identified, namely high-, intermediate-, and low-risk alleles (78). So far, almost 50 % of the genetic variance of breast cancer risk can be explained by known loci. The remaining proportion could be explained by a combination of intermediate- and low-risk alleles.
2.1.2 Candidate genes:
Breast cancer candidate genes are thought to be one of the likely causes for breast cancer development. The most studied candidate genes are those involved in different pathways related to cancer etiology such as DNA repair, proteins interacting and/or modulating BRCA1/2 cellular functions, homologous recombination (HR), interstrand DNA crosslinking, sex steroid action or metabolism, cell cycle control, tumor suppressors, centrosome amplification, telomere elongation, AURKA interacting proteins, mitotic and other kinases, apoptosis, ubiquitination and gene products influencing mammographic density. In addition, a breast cancer candidate gene may be selected due to its particular chromosomal location, suspected of being involved in the disease. Many breast cancer candidate genes have been revealed by microarray-based assays (79).
2.1.3 Susceptibility genes:
Extensive research has been published over the last two decades since the discovery of the first breast cancer susceptibility gene regarding the causes of hereditary and familial breast cancer. Three classes of breast cancer susceptibility alleles are now recognized (80, 81). Alleles of genes such as BRCA1, BRCA2, PTEN and TP53 that confer high lifetime risks of the disease (RR> 8 folds) but are relatively rare (82). On the other hand, mutations in intermediate-risk alleles (e.g CHEK2, ATM, BRIP1, PALB2, XRCC2,
etc.) confer average risks of 2-4 folds for each allele, and explain a further ~5% of the
familial risk (83). Finally, common low-risk alleles (frequency ≥ 5% with a RR <1.5) can be identified systematically through genome wide association studies (GWAS). Indeed, previous genome-wide and large-scale association studies have identified multiple common susceptibility loci that explain ~9% of the overall inherited susceptibility to breast cancer (84).
A further ~14% of the familial risk has now been explained via the Collaborative Oncological Gene-Environment Study project (COGS) due to the identification of 107
new breast cancer low-penetrance loci (85-86). Therefore, approximatly 50% of the overall breast cancer genetic component is now currently explained by known genetic variants.
It is important to mention that the FRR of breast cancer susceptibility alleles is inversely related to their frequencies. Indeed, high and moderate breast cancer susceptibility loci are rare in the general population but are associated with a high risk of developing the disease, whereas low-penetrance polymorphisms are common and associated with a relatively modest risk (87). This goes in agreement with the evolutionary theory predicting that most variants affecting risk for a given disease should be found at only low frequency in the overall population (Figure 4).
2.3.2.1 High penetrance:
High penetrance alleles such as BRCA1, BRCA2 (FANCD2), TP53, STK11, PTEN and CDH1 explain approximately 20% of breast cancer inherited susceptibility (Table 2). These high-risk alleles have also been identified as part of inherited cancer syndromes. Indeed, germline TP53 mutations are found in Li-Fraumeni cancer syndrome (LFS) (88-89), PTEN germline mutations in Cowden syndrome (90) and STK11/LKB1 mutations in Peutz-Jegher syndrome (91).
Genome-wide linkage studies of familial breast cancer have failed to map other highly penetrant breast cancer susceptibility genes, strongly suggesting that no further genes with an important relative risk comparable to these known high penetrance genes exist (92-93).
BRCA1 and BRCA2:
Linkage studies conducted in the 1990s led to the discovery of mutations in BRCA1 and BRCA2 genes that confer a high risk for breast cancer (94-95-96).
Indeed, in families with multiple cases of breast cancer, the disease was associated with
BRCA1 in 52% and with BRCA2 in 32% of all families. In normal cells, these genes
prevent cancer by directing the synthesis of the corresponding tumor suppressor proteins (97).
Although BRCA1 and BRCA2 mutations are rare in most populations (occurring in approximately 1 out of 400 persons), it may be mentioned that they are much more
common in the Ashkenazi Jewish population, in which 1 out of 40 persons carries one of the three main disease-associated mutations (BRCA1 185delAG, BRCA1 5382insC, and
BRCA2 6174delT) (98-99).
Women bearing these inherited mutations also have an increased risk for developing cancers other than breast cancer, more particularly ovarian, prostate and pancreatic cancers (100).
Although the major susceptibility loci for the genes BRCA1 and BRCA2 have been identified as high-penetrance alleles, these alleles only account for approximately 15–20% of the familial component of breast cancer (101, 102,103). Jacques Simard and colleagues have demonstrated that among French-Canadians, about one third of the high-risk families are carrying mutations in the BRCA1 and BRCA2 genes, which suggests the existence of multiple other breast cancer associated alleles of moderate to low penetrance (104). Moreover, Mary Claire King’s team has conducted a study of 300 probands belonging to families with more than four cases of breast or ovarian cancer and screened them with multiple DNA-based and RNA-based methods for detecting genomic rearrangements in
BRCA1 and BRCA2 as well as germline mutations in CHEK2, TP53 and PTEN in all cases.
Results from this study predict that among patients with breast cancer and severe family histories of cancer that test negative for BRCA1 and BRCA2 mutations, approximately 12% can be expected to carry a large genomic deletion or duplication in either BRCA1 or
BRCA2, and approximately 5% can be expected to carry a mutation in either CHEK2 or TP53 (105).
Variants of uncertain significance:
While thousands of BRCA1 and BRCA2 truncating mutations have been associated with an increased risk for cancer among carriers, the contribution of other BRCA1 and BRCA2 variants to cancer risk remains largely undefined (Figure 5). Variants of uncertain significance (VUSs) are mainly missense mutations, but they also include a number of intronic variants and in-frame deletions and insertions (106). The uncertainty in establishing the relevance of BRCA1 and BRCA2 variants to disease is an important
Risk allele frequency
Figure 4: Breast cancer susceptibility loci: relative risk and minor allele frequency connected with these loci All known breast cancer susceptibility loci are associated with one of three classes of breast cancer susceptibility loci, namely: high-, moderate- and low-penetrance loci. Rare genetic variants confer a high to moderate (RR>2 folds), whereas the relative risk of breast cancer conferred by common variants is comparatively modest (RR<2).
R el at ive r is k
obstacle to identify individuals at risk for cancer and to provide appropriate health care options and counseling. Such non-informative results can be a source of anxiety to individuals and their offspring, because they will not be able to use the information from genetic testing to modify their behavior or lifestyle, or to make important clinical decisions that may, in many cases, involve prophylactic surgery (107). In addition, all first-degree relatives including non-carriers are considered at risk as long as the contribution of the variant to disease cannot be assessed.
At present, the clinical relevance of relatively few of these variants has been established (108). This includes common variants that were classified as of neutral or of no clinical significance (109) and a small number of variants at evolutionarily conserved residues (110) or splicing consensus sites that were classified as deleterious using a statistical genetic combined likelihood model (111) or in vivo splicing/exon skipping analysis (112). Classification of other BRCA1 and BRCA2 variants as cancer-predisposing or -neutral has proven problematic because it is not known whether the subtle changes caused by these variants sufficiently alter protein function to favor the development of cancer.
STK11: The STK11/LKB1 gene was mapped to 19p13.3 following the
demonstration of chromosome 19p allele loss in intestinal hematomas and linkage analysis from Peutz-Jegher syndrome (PJS) patients. A five folds increased risk of an early onset breast cancer appears to be associated with PJS. Some data suggest that mutations in exon 6 of STK11 are associated with a higher cancer risk than mutations within other regions of the gene (113).
Like BRCA1 and BRCA2, STK11 germline mutations may cause ovarian tumors (114).
PTEN: The PTEN tumor suppressor gene, located on 10q23.3, encodes a
dual-specificity phosphatase that can dephosphorylate both protein and phospholipid substrates. Many studies showed the association of this gene with diverse phenotypic features affecting multiple cancers such as breast cancer. Indeed, breast cancer risk estimates (67–85 %) for women with germline PTEN mutations are similar to those quoted for patients with germline mutations in the BRCA1/2 genes. Germline mutations in PTEN are also associated with colorectal cancer and the cowden syndrome, another
autosomal dominant cancer syndrome associated with hereditary forms of breast cancer (115). Variants in the promoter region and within the transcription start site (TSS) of
PTEN have been found to be associated with these breast and colorectal cancers. However,
a study undertaken by Francine Durocher’s group showed that PTEN germline mutations are rare and are unlikely to account for a significant proportion of familial breast cancer cases in the French-Canadian population (116).
TP53: The p53 protein is expressed at low levels in virtually all normal cells.
Wild-type p53 functions as a suppressor of neoplastic growth, and mutation or deletion of both normal alleles of the gene eliminates this suppression (117). The protein product of the
TP53 gene has an important biological function as a cell cycle checkpoint. To date, the TP53 gene is the most commonly altered gene identified in human tumors. In 1990, Li et
al. identified germline TP53 mutations at the 17q13.1 locus in a series of families with LFS (118). This study features diverse childhood cancers as well as early onset breast cancer cases (119-120). The absolute risk of breast cancer in a TP53 mutation carrier reaches ~50% by the age of 50 (121).
2.3.2.1 Moderate penetrance:
Another group of genetic variants associated with breast cancer risk are uncommon variants with a minor allele frequency (MAF) from 0.005 to 0.01 and moderate effects on risk. In fact, their contribution to FRR is estimated at less than 5% (Table 2). These variants have been identified in candidate gene by family-based association studies.
They include protein-truncating variants in CHEK2, (122, 123), PALB2 (124),
BRIP1 (125), and ATM (126). Other candidate breast cancer genes have been proposed,
such as MRE11 that encodes a component of the MRE11-RAD50-NBS1 complex, which is critical for the maintenance of genomic integrity and for tumor suppression (127).
Recently, Park et al. identified RINT1 as a new moderate-penetrance breast cancer-associated gene (128). It is remarkable that almost all genes belonging to this category are involved in DNA repair pathway. Since few genes have been studied using a mechanism- or function-based gene candidate approach, it is likely that additional susceptibility variants of this class exist. However, re-sequencing and whole-exome studies of large numbers of cases and controls will be required to uncover such novel markers.
Figure 5. Variants of uncertain significance diagrams of human BRCA1 and BRCA2 genes with the location and frequency of all missense variants in these two genes ad listed in the Breast Cancer Information Core database.
This figure shows the small number of variants that have been definitively classified as either pathogenic (in red) or neutral (in blue). The diagram clearly shows that the majority of these missense mutations are of uncertain significance (shown in black). (Adapted from: Couch FJ et al. Hum Mutat. 2008).
