Risk Factors as Biomarkers of Susceptibility in Breast Cancer

C H A P T E R

46 Risk Factors as Biomarkers of Susceptibility in Breast Cancer Carolina Negrei1, Bianca Galateanu2 1

Departament of Toxicology, Faculty of Pharmacy, “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania; 2Department of Biochemistry and Molecular Biology, University of Bucharest, Bucharest, Romania

INTRODUCTION Epidemiology Over the entire span of their lives women, and postmenopausal women especially, have an 11% risk of developing breast cancer, making this the most widespread malignancy among women. The current worldwide trend in incidence rate is higher in developed countries, but changes in lifestyle may lead to increases in less developed countries as well (Tao et al., 2015).

Pathology Adenocarcinomas are the most type of common cancer, almost excluding lymphoma and sarcoma pathology. Both noninvasive and invasive breast tumors usually originate in the lobules and ducts, and their specific morphology becomes evident via microscopic examination, which provides decisive histological data to distinguish lobular from ductal carcinomas. According to present evidence, the site of origin for both types is considered to be the terminal duct lobuloalveolar unit (Russo and Russo, 1999). Usually determined by mammography (Ernster et al., 2002), atypical ductal hyperplasia leading to in situ breast carcinomas do not pervade the basement membrane but may be considered as early precursors of invasive types (Kuerer et al., 2009). This has been successfully shown in a number of progression models for normal breast tissue. Between ductal and lobular invasive types, the histological category most commonly diagnosed (approximately 80% of all cases) is ductal carcinoma. Invasive lobular carcinoma occurs much less often (Li et al., 2003), mostly in elderly women and, despite a specific Biomarkers in Toxicology, Second Edition https://doi.org/10.1016/B978-0-12-814655-2.00046-3

metastatic pattern, it has a similar prognosis for other ages (Arpino et al., 2004). Other well-defined morphologic but more infrequent subtypes providing better prognosis may include Paget and adenoid cystic, papillary, medullary, tubular, and mucinous carcinomas.

Risk Factors Among the most significant risk factors for developing breast cancer, inherent predisposing factors have to be taken into account. Factors such as gender, age, and history of benign or malignant breast disease in both patients and their family (more significantly in a first-degree relative) may be broad predictors. Although gender would seem irrelevant as a breast cancer risk factor, because of the difference between males and females in exposure to hormones, male breast cancer cases used to be very rare, but they are becoming more frequent of late. The risk of developing breast cancer is mainly age dependent as a consequence of genetic and epigenetic changes (Fraga et al., 2007). Thus, there is low risk but more aggressive progression before the age of 25, and the risk increases significantly in the third decade. Diagnosis is largely established prior to menopause, possibly indicative of a hormonal status association (Tao et al., 2015). Several more specific predisposing factors stand out, the most important of which are hormonal and reproductive particulars related to estrogen exposure (age at first period, first pregnancy and menopause, high levels of endogenous sex steroid hormone, lifetime use of hormonal drugs), breast density, and genetic and epigenetic alterations. Breast density relates to the amount of mammary gland stromal and epithelial cells, and higher density arises from more extensive fibrous and glandular

841

Copyright © 2019 Elsevier Inc. All rights reserved.

842

46. BREAST CANCER BIOMARKERS

tissue as opposed to adipose tissue. This is a significant (four times higher than average) risk for both breast cancer occurrence and more aggressive tumors. Further factors of individual risk are proliferative breast lesions with an excessive number of cells, some of which display morphological abnormalities. At the same time, behavioral and lifestyle factors (weight, diet, exercise, and use of alcohol) should not be overlooked (Veronesi et al., 2005). Risk factors have a cumulative effect on overall risk. Life StageeRelated Risks In addition to genetic and environmental risks, there is a certain increased vulnerability to cancer depending on the person’s development of life phase, when the tissue is more susceptible to the occurrence of alterations under the influence of epigenetic factors. These factors are likely to trigger changes in the underlying body structure and functions as well as cellular modifications. For breast development, important stages include the fetal stage, puberty with its marked growth, and late pregnancy with its precipitated preparation for breastfeeding. In the fetal phase, the more pronounced vulnerability is the result of the immaturity of most protection fostering mechanisms such as DNA repair, functioning of the immune system, enzymes and liver metabolism, and incomplete formation of the bloodebrain barrier (BBB) to ensure protection against external aggression (Fenton et al., 2012). Developmental stageerelated susceptibility may be determined by biomarkers as well, and recent research has focused on rodent models to offer evidence of potential epigenetic or underlying genetic risk factors. Thus, the following have been deemed of significance and they have been presented in order of relevant life stage importance. Gestation and Development of the Fetus Summarized in the theory of “fetal basis of adult disease,” the first 3 months of pregnancy in particular and the entire pre-birth period are characterized by quick cellular division and growth, susceptible to the influence of environmental toxicity or modified hormone (such as estrogen) action (Birnbaum and Fenton, 2003), which can alter underlying tissue structure, function, and programming (Fenton et al., 2012). The risk of cancer later in life has been suggested to be influenced by endogenous factors, such as altered hormonal exposure as indicated by weight at birth, gestational age, birth order, twins and maternal age, and preeclampsia (Park et al., 2008). The influence of elevated estrogen levels during pregnancy on cancer risk later on is also apparent from exposure during pregnancy to exogenous agents capable of endocrinal disruption (such as diethylstilbestrol or phytoestrogens) (Hoover et al., 2011).

Puberty As a period of rapid and substantial growth, puberty is the second life stage with an increased susceptibility to breast cancer. On an intrinsic level, puberty is normally governed by two endocrine processes: first, development of the hypothalamicepituitaryegonadal axis (gonadarche) and secondly, maturation of the hypothalamicepituitaryeadrenal axis and the ability to produce and secrete androgens (adrenarche) (Fenton et al., 2012; Wan et al., 2012). This accounts for the capacity of disturbances in either or both axes to determine modified pubertal timing. The onset of puberty is indicated by physical markers such as breast development, the so-called “growth spurt,” growth of pubic hair, and the first menstrual cycle and its development towards regularity (Fenton et al., 2012). Breast, bone, and brain development are under the control of estrogens (reviewed in Fenton et al., 2012). However, early onset of puberty may be the result of disruptions with major effects on cancer risk. Precocious puberty may be determined by hormonal profiling and the appearance of sudden breast development or pubic hair growth (Carel et al., 2004), together with an assessment of bone age and performance of pelvic ultrasound checks. This is usually identified in girls under 8 years of age. Elevated breast density is a very relevant risk factor for breast cancer (higher breast tissue density means five times more likely to develop cancer) (IBCERCC, 2013). Early breast development and increased numbers of terminal duct lobular units increase vulnerability to exposure to carcinogenic factors (Fenton, 2006; Biro et al., 2010). Precocious onset of menarche is also a risk factor for breast cancer (D’Aloisio et al., 2013), so much so that a woman’s risk is approximately 10% lower for each year of menarche delay (Biro et al., 2010). According to recent studies, an association has been established between early onset of menarche and vitamin D deficiency [defined as 25-hydroxyvitamin D [25(OH)D] blood level<20 ng/mL (IOM, 2011)], which makes vitamin D deficiency an important factor in breast cancer risk. Other intrinsic factors include height and obesity. In a pubertal pattern of growth, height is in direct relation to estrogen as well as a sex steroide dependent increase in growth hormone and production of insulin-like growth factor-I (Carel et al., 2004), making it a definite risk factor for breast cancer. Obesity, on the other hand, as indicated by body mass index (BMI) is a risk factor for breast cancer in young girls, as associated with precocious breast development (Biro et al., 2003; Wan et al., 2012) triggered by increased body fat (Biro et al., 2003), and women after menopause. Exogenous agents, such as exposure to radiation and environmental compounds, directly determine DNA mutation, subsequently altered mammary gland

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

INTRODUCTION

environment, and deregulation of the mammary stem cell (IBCERCC, 2013). Susceptible stages in adulthood are pregnancy and lactation because hormonal developments and changes in the morphology of terminal duct lobular units (Kobayashi et al., 2012; Faupel-Badger et al., 2013) may also increase cancer risk. Pregnancy In epidemiological studies, pregnancy has been shown to generally lower the breast cancer risk for the longer term, despite its transitory short-term effect of increasing post-birth risk due to the stimulation of malignant cell transformation. Thus, multiple births are a strong protective factor for breast cancer risk (FaupelBadger et al., 2013). Lactation and Breastfeeding Milk secretion and breastfeeding involve all developments turning the mammary epithelium into a mature milk-producing gland (Faupel-Badger et al., 2013) after birth (Neville et al., 2001). According to research, breastfeeding and particularly sustained lactation can be a protective factor as far as breast cancer is concerned (Bernier et al., 2000; Kobayashi et al., 2012), possibly due to a decrease in estrogen exposure resulting from fewer menstrual cycles. Family History A family history of breast cancer is a predictor of likely disease, even though if present in first- or second-degree relatives. When diagnosis of the relative in question occurs at age 50 or in case of multiple relatives affected by the disease (Pharoah et al., 1997). Genetic Modifications Despite the fact that testing for different genetic biomarkers is comparatively easy to perform, the challenge lies in the ability to consider these biomarkers in their context, making efforts toward predictive genetic testing while not overlooking the medical, social, and psychological implications of results, whether positive, negative, or pending (Walsh et al., 2016). History of Benign Conditions A personal history of nonproliferative benign conditions such as fibroadenomas and cysts is not a marker of high breast cancer risk (Page et al., 2003; Dupont et al., 1993). However, the risk rises by 1.5e1.9 with proliferative benign conditions, such as papilloma, hyperplasia, or radial scar, and 4e6 times for atypical lobular or ductal hyperplasia.

843

Prognostic Factors Although not thoroughly clarified and therefore not formally endorsed for overall clinical use, criteria such as the stage (extent) of the disease, tumor grade, expression of estrogen receptors, expression of progesterone receptors, and human epidermal receptor-2/neu are among the prognostic factors used to determine the likely progression of the disease (Harris et al., 2007; Bast et al., 2001). Given its importance among prognostic factors, staging is currently achieved based on the TNM system (Singletary et al., 2002), as it focuses on indicators of clinical importance such as the size of the tumor (T), involvement level of lymph nodes (N), and presence of distant metastases (M). Although not predictive of response to therapy, the above characteristics are strong individual predictors of future progress of the disease, with tumor size indicating death independently from the other criteria. Generally, poorer prognosis is evidenced by larger tumor size, greater number of affected lymph nodes (Cianfrocca and Goldstein, 2004), and presence of distant metastasis (with 2 years median overall survival time) (Giordano et al., 2004). Another prognosis factor, tumor grade, is established as high, moderate, or low, with high-grade disease characterized by faster progression and extreme potential for spreading. Currently, grading is mainly achieved using the Nottingham histological grade system (Elston and Ellis, 1991), based on criteria referring to glandular formation and cell-related aspects such as size, shape, proliferation rate, and pattern. As far as disease markers are concerned, the most important to examine as far as prognosis are the expressions of the estrogen and progesterone receptors, both belonging to the steroid hormone receptor group. Generally, expression of the estrogen and/or the progesterone receptors is predictive of improved response to hormonal therapy and better survival. Expression of both receptor types indicates up to 80% effective response. Expression of the estrogen receptor only predicts 30% responsiveness, whereas absence of either receptor expressions indicates nonresponsiveness to estrogen receptor modulator therapy (Lapidus et al., 1998). An additional marker to examine is the human epidermal growth factor receptor 2 (HER2/neu) of the HER receptor tyrosine kinases. This is overexpressed in 30% of breast cancers, which are more aggressive and show poor prognosis. The drug of choice for the treatment of HER2/neu overexpressing breast cancer cases is trastuzumab (Menard et al., 2003). Other gene expression profiles have recently been researched to help predict responsiveness to therapy and the likelihood of recurrence and response to

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

844

46. BREAST CANCER BIOMARKERS

treatment (e.g., assays such as Oncotype DX, the MammaPrint test, the Rotterdam Signature, and the Breast Cancer Gene Expression Ratio) (Harris et al., 2007).

Detection and Screening The current means used for breast cancer detection and screening are physical examination combined with imaging tools such as ultrasonography, mammography, magnetic resonance imaging (MRI), and positron emission tomography, as well as analysis of tumor markers. Tumor Marker Analysis The term “tumor marker” refers to features distinguishing the tumor from normal tissue, which are measurable and/or visible outcomes of tumourigenesis (Levenson, 2007). Biomarkers’ efficacy depends directly on the degree of their clinical sensitivity (the ratio of subjects with confirmed disease with positive test results) and specificity (the ratio of healthy control subjects with negative test results) (Pepe et al., 2001). The main characteristics of effective detection biomarkers include: (1) none or minimal invasive, (2) use of only small specimen amounts, (3) site-specificity expressed in the ability to discern between nonmalignant and malignant events at the level of the same tissue/organ, (4) enhanced specificity allowing for limitation of false-positive results, (5) ease of performance, (6) cost-effectiveness, and (7) independence from the observer (Levenson, 2007). In relation to breast cancer, researchers have examined a range of analytes of biological molecules with the potential to act as biomarkers for the disease. Therefore, various carbohydrates, lipids, polyamines, proteins, DNA, and RNA have been studied in breast tissue, plasma, serum, and ductal lavage fluid or nipple aspirate fluid (Levenson, 2007). The study of proteins as biomarkers (proteomics) applies biochemical analysis to proteins and focuses on the function of expressed genes. Thus, proteomics is able to render an accurate and dynamic account not only of the cell intrinsic genetic program but also of the impact of its proximal environment. This ability of proteomics to relate gene sequence to cellular physiology suggests the usefulness of biomarker discovery for complementing the genome with the proteome. In addition, with the aid of recent techniques such as matrix-assisted laser desorption/ionization time-offlight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser desorption/ionization (SELDITOF MS), high-throughput analysis of the proteome has become feasible. However, the tumor marker value of proteins remains to be clarified through comprehensive prospective clinical studies, and the only cancer

biomarker with proven effectiveness is the prostatespecific antigen screening for prostate cancer (Lane et al., 2010). Among proteins with a substantial value for breast cancer diagnosis, prognosis, or prediction, one should mention CA27-29 and CA15-3 (Gast et al., 2009; Duffy, 2006) or the extracellular mucin 1 (MUC1) protein (antigens for MUC1). MUC1 overexpression and aberrant glycosylation are markers for several cancer types. Recent studies have focused on the capacity of autoantibodies to aberrant O-glycoforms of MUC1 to operate as diagnostic biomarkers. Further sensitive biomarkers for effective early detection of breast cancer have been found in cancer-associated immunoglobulin G autoantibodies in breast cancer patients’ serum against various aberrant O-glycopeptide epitopes derived from MUC1 (Wandall et al., 2010). The technique of measuring gene expression from available sequence information (genomics) allows for determination of an expression profile representing cell function and phenotype (transcriptome). Such molecular signatures of potential biomarker value for early detection have recently come within reach by means of such technologies as multiplex polymerase chain reaction (PCR) (Srinivas et al., 2001) and cDNA oligonucleotide arrays. In addition, according to certain studies, it seems that plasma mRNA may be used as a highly sensitive tumor marker thus allowing earlier cancer detection (Silva et al., 2002). However, research needs to be continued to resolve the problem of RNA stability in the bloodstream, more so in the presence of high serum ribonuclease levels found in cancer patients (Levenson, 2007). Testing for Genetic and Molecular Changes Genetic testing for mutations in breast cancer susceptibility genes such as BRCA1, BRCA2 (conducted so far in over one million individuals), and other genes is one prototype for the incorporation of genomics into personalized medicine practice. It has proved effective for both improvement of specific strategies for screening and prevention and use as a marker in targeted therapy. However, close compliance with the principles of genetic counseling has become even more important with the increasingly rapid development of molecular sequencing for the purposes of successful targeting of therapies. At the same time, it is key to establish whether genomic analysis is conducted to determine inherited susceptibilities or whether its primary purpose is genomic analysis of the tumor. Approximately 30% of high-risk breast cancer families and around 15% of breast cancer familial relative risk (i.e., the disease risk for an affected individual’s relative/the disease risk for the general population) may be attributed to pathogenic mutations (King, 2014;

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

INTRODUCTION

Bahcall, 2013; Antoniou et al., 2008; Rebbeck et al., 2011). However, the difficulty arises to contextualize the risk of disease of inherited mutations and sequence variants in BRCA1/BRCA2.

Syndromes Predisposing to Breast Cancer Hereditary Breast and Ovarian Syndrome Given the numerous cases of worldwide breast cancer obviously developed as the result of an inherited predisposition, the identification of mutated genes as genetic risk biomarkers markedly increases in relevance. Thus, genetic testing becomes all the more important and worthwhile, so much so as early detection results in a more than 90% cure rate. In that respect, as highlighted above, BRCA1 and BRCA2 predominate among breast cancer susceptibility genes. BRCA1 is a large gene, consisting of 24 exons, out of which 22 are coding; the remaining two are noncoding. The location of BRCA1 is chromosome 17. BRCA2 consists of 27 exons and is located on chromosome 13 (genenames.org). Both genes are involved in DNA response to damage and in homologous recombination (Venkitaraman, 220). Families with a history of both male and female breast cancers show higher pretest probability for BRCA2 testing, whereas families with both ovarian and breast cancers present higher pretest probability for BRCA1 testing (Frank et al., 2002). According to epidemiologic studies, mutations in BRCA1 determine a 70% lifetime breast cancer risk by age 70 (Whittemore et al., 1997; Claus et al., 1991, 1993, 1996) and even 90% for certain families with frequent early onset of ovarian or breast cancers (Ford et al., 1994).

High Penetrance Genes Predisposing to Breast Cancer Actual development of cancer depends on the contribution of factors such as the particular type of constitutional aberration in BRCA1 or BRCA2, occurrence of modifying genomic alterations, and influence of the environment. Susceptibility, however, exists mostly as the result of genomic aberrations consisting of premature truncations of the BRCA1 and BRCA2 proteins by frameshift or nonsense mutations. Among the more than 2000 distinct rare variants of BRCA1 and BRCA2, there are missense mutations, intronic changes, and small in-frame deletions and insertions that have been reported (Breast Cancer Information Core; www.research.nhgri.nih.gov/bic). BRCA1 main domains are located in the RING finger, and BRCT domains and their involvement are key for DNA repair function.

845

The location of pathogenic, highly penetrant missense mutations in BRCA2 involves the DNA binding domain in particular (Guidugli et al., 2013, 2014). In BRCA1 and BRCA2 there occur extensive genomic structural variations or rearrangements, representing 14% of mutations and 2.6% of mutations, respectively. The difference in the volume of structural variations between BRCA1 and BRCA2 may be attributed to the numerous Alu repeats characterizing the genomic region of BRCA1 gene location (Judkins et al., 2012). In relation to BRCA1 and BRCA2, “founder” (population specific) mutations have been identified, among which the mutations occurring in the eastern European Jewish population have been well studied and documented. Thus, BRCA1 is the site of two mutations (5382insC and 185delG) and BRCA2 undergoes one mutation (6174delT) and up to 3% of this population are carriers of such a founder mutation (Offit et al., 1996; Szabo and King, 1997; Thorlacius et al., 1997). Given that 5% of all mutations in BRCA1 and BRCA2 in breast cancer patients belonging to this population group display nonfounder mutations, reflex full gene sequencing may be necessary in the case of negative results (Szabo and King, 1997; Thorlacius et al., 1997). Carriers identified from population studies show a lower degree of disease penetrance as compared with carriers evidenced by means of kindred-based studies. Because of an almost 60% breast cancer risk and a 40% ovarian cancer likelihood by age 70, identified BRCA1 mutation carriers are encouraged to be regularly screened. On the other hand, the likelihood of developing the disease by the same age in carriers of the BRCA2 mutation is 49% for breast cancer and 18% for ovarian cancer (Chen and Parmigiani, 2007). However, a certain degree of risk variability has been observed between the two types of cancer, explained in part, in respect to the risk for ovarian cancer, of genotypee phenotype correlations suggested by statistical data, highlighting a connection between specific phenotypes and the location of BRCA1/BRCA2 mutations. This has prompted the assumption that frameshift- and nonsense-type mutations occurring in each distal and proximal genomic region associate with lower ovarian cancer risk compared to analogous mutations by the center of either coding sequence (also known as “ovarian cancer cluster regions”) (Gayther et al., 1996, 1997). From the perspective of the mutation location, statistic cohort data gathered from BRCA1/BRCA2 mutation carriers in the records of the CIMBA group (Consortium of Investigators of Modifiers of BRCA1/ BRCA2) highlight relative decreases in breast cancer risk and increases in ovarian cancer risk concerning mutations in each gene central region. At the same time, there seems to be a higher breast cancer risk concerning mutations in the 30 and 50 regions in each gene.

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

846

46. BREAST CANCER BIOMARKERS

An additional clarification for this risk variability comes from genome-wide association studies, which have prompted for the action of common genetic modifiers of ovarian and breast cancer risks in BRCA1/ BRCA2 mutation carriers (Antoniou et al., 2010; Gaudet et al., 2010; Rebbeck et al., 2011; Wang et al., 2010). The risk derived from the genomic location of BRCA1/BRCA2 mutations combined with that triggered by modifier genes differentiates between BRCA1 mutation carriers and BRCA2 mutation carriers at highest risk; thus, by age 80, the likelihood in the former carrier group to develop breast cancer is >81% and for ovarian cancer it is >63% (Gaudet et al., 2013). If considered in the context of further risk-modifying variables observed in carriers of the BRCA1/BRCA2 mutation, mutation location and modifier genes are currently emerging as significant genomic biomarkers, whose worth may reside in their prospective capacity to better estimate the risk itself and to provide improved prognosis of disease behavior. An additional value may lie in profiling the phenotype of hereditary disease (such as the estrogen receptor status). This has been suggested by the observed tendency of tumors in BRCA1 mutation carrier breast cancer patients toward more aggressive disease features (Bignon et al., 1995; Jacquemier et al., 1995; Johannsson et al., 1997; Robson et al., 1998). However, accurate interpretation of genetic biomarkers for inherited risk needs to also take note of variants of unknown significance (e.g., small in-frame deletion/insertion variants, as well as intronic and missense ones). Classification of these variants in all genes as neutral/ low effect (Lindor et al., 2012) or pathogenic is a difficult task in clinical genetic testing. In the absence of an established database, such classification used animal or in silico models in an attempt to as nearly as possible infer the behavior of the disease in humans from patterns of development profiled in animals is difficult. It is also challenging to predict the functional influence of encountered variants on the foundation of the structure and/or conservation of amino acids. More recently, efforts have converged toward initiation of a database, which is designed for organization and oversight of clinical information on such variants (Clinvardwww.ncbi. nlm.nih.gov/clinvar). Consistent work by the International EvidenceBased Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Consortium has focused on BRCA1 and BRCA2, furthered by the Global Alliance for Genomics and with the aim of establishing an international database of BRCA1/BRCA2 variants. In addition to the database of variants of unknown significance as a tool for more accurate interpretation of genetic biomarkers, research has also endeavored to design quantitative risk prediction methods as necessary algorithms for assessment of such variants’

likelihood for pathogenicity. Thus, for each variant envisaged, work involves measurement of family disease history, conservation, the pathology of the tumor and RNA splicing effects (Guidugli et al., 2013; Spurdle et al., 2012; Iversen et al., 2011; Lindor et al., 2012), and combined evolutionary sequence conservation (Guidugli et al., 2013, 2014; Lindor et al., 2012, Tavtigian et al., 2008, Goldgar et al., 2004). However, the need to compensate for the lack of statistical power concerning individual or rare variants has prompted development and use of high-throughput quantitative cell-based in vitro assays, aimed at providing a reliable estimate of their outcome in relation to BRCA1 and BRCA2 protein functions. Specificity and sensitivity for the variant specific biomarker VUS (Guidugli et al., 2013) or variants of unknown significance are assessed with acknowledged controls of normal versus pathogenic mutations. Hypomorphic mutations preserve protein activity to some extent, but they also present particular difficulties in gene variant interpretation. Identification and clinical validation of variants or biomarkers in genes predisposing to breast cancer, which feature more moderate risk, allow for the design of increasingly personalized strategies for surveillance and prevention of disease.

Therapeutic Implications of Genetic Biomarkers Clinical management of individuals with BRCA1 and BRCA2 mutation has been adjusted from the perspective of genetic testing. Genetic testing is a valuable source of information for evidence-based medical decisions. Identification of BRCA mutations requires constant surveillance of the breast, achieved by means of the carrier’s self-examination, accompanied by clinical examination, and sustained and validated by mammography, sonography, or MRI (Burke et al., 1997; Kriege et al., 2004; Morris et al., 2003), which should be performed annually as early as the age of 25 in women at hereditary risk (Mettler et al., 1996). Mammography and MRI, however, show different levels of sensitivity in the case of BRCA mutation carriers, with the former missing as many as 29% of new tumors thus making MRI the standard one. Breast cancer risk for BRCA1 and BRCA 2 mutation carriers may also be significantly (>90%) decreased by mastectomy, but this is comparatively infrequent. Chemoprevention is a further means of breast cancer risk reduction in BRCA1 and BRCA2 mutation carriers as well, and studies are underway to develop more advanced options than tamoxifen. The standard current means to reduce risk in such mutation carriers is salpingo-oophorectomy, with effectiveness rates between 80% and 96% for ovarian cancer (Kauff et al., 2002; Rebbeck et al., 2002; Finch et al.,

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

INTRODUCTION

2006) and approximately 50% for breast cancer. This is most likely due to its capacity to induce menopause (Kauff et al., 2002; Rebbeck et al., 2002; Eisen et al., 2005), resulting in a 60% reduction of overall mortality in these patients (Domchek et al., 2010). Several drugs have proven effectiveness against BRCA1 and BRCA2 cancers, such as platinum chemotherapy and poly(ADP-ribose) polymerase inhibitors.

Other Highly Penetrant Breast Cancer Predisposing Genes One important outcome of the development of sequencing technologies is the discovery of further predisposing genes, such as TP53 and CDH1. Although rare, genomic alterations in the TP53 gene encoding the tumor suppressor protein p. TP53 is involved in Li-Fraumeni syndrome and a comparatively increased risk of breast cancer (Hisada et al., 1998). Negative/ Indeterminate results in tests for BRCA1 and BRCA2 mutations testing and a marked history of cancer in the family require testing for TP53 mutation. In addition to the diffuse gastric cancer risk, CDH1 mutation carriers also face a 40%e50% risk of lobular breast cancer (http://www.nccn.org/professionals/physician_gls/ pdf/genetics_screening.pdf). Further, highly penetrant breast cancer predisposing genes PTEN and STK11 determine overt phenotypes such as PTEN hamartoma tumor syndromes and the Peutz-Jeghers syndrome in respective patients of marked breast cancer risk (Amos et al., 2004; Boardman et al., 1998, 2000a; b).

Moderate Penetrance Breast Cancer Genes Carriers of moderately penetrant breast cancer predisposing genes such as CHEK2, ATM, PALB2, BRIP1, RAD51C, RAD51D, BARD1 should be subjected to screening in line with the patient’s family and personal histories.

Low Penetrance Breast Cancer Polygenes Breast cancer risk may also be weakly increased by common genetic variants (e.g., TGFBR2, MYC, TET2) identified in genome-wide association studies in 76 loci (Couch et al., 2014; Michailidou et al., 2013; Maxwell and Nathanson, 2013). Although still unclear for the most part, one of their mechanisms of action is via gene transcription. Among relevant signatures, single nucleotide polymorphisms, microsatellite instability, and epigenetic changes (e.g., changes in DNA methylation) should be mentioned. Epigenetic changes such as DNA methylation involve markers regulating gene expression, but these do not

847

modify the original DNA sequence. Such markers may undergo modifications themselves and may be inherited. As a gene expression regulator, DNA methylation can silence genes for tumor suppression and thus bear significant influence on tumorigenesis. The value of biomarkers for DNA methylation relies on the similarity of primary tumor and blood plasma methylation patterns (Hoque et al., 2006) in the very incipient stages of breast tumor progression (van Hoesel et al., 2013; Radpour et al., 2011; Fabian et al., 2005; Wong et al., 2011; Yan et al., 2006). The proven high sensitivity (>90%) of plasma measurement of DNA methylation of certain genes renders it an effective prospective means for screening.

DNA Methylation, Definitions, and Measurement Methods Altered gene expression is mainly triggered by microRNA expression, DNA methylation levels, and histone modifications. Epigenetic phenomena for which DNA methylation is key are cell development and differentiation, genomic imprinting and silencing of transposable elements, and inactivation of the X-chromosome. As representative of DNA methylation, methylated cytosine 5-methylcytosine (5mC), found in approximately 4% of cytosines, is an outcome of adding a methyl group to the 50 position of cytosine mainly in CpG sequences. As a result of hypomethylation, total 5mC levels are known to be lower in tumors compared with neighboring tissues (reviewed in Robertson, 2005). This DNA loss of methylation occurs mainly in repetitive DNA elements, resulting in their reactivation and enhanced aberrant recombination, rendering them genomically unstable. Gene-specific hypomethylation is also possible and leads to repeated expression of affected genes. Hypomethylation is a modification occurring early in cancer. The opposite phenomenon, gene-specific increase in epigenetic methylation (hypermethylation), more commonly occurs in the CpG island promoters. Its capacity to lead to gene inactivation is relevant for cancer as it also affects tumor suppressor genes, as well as mutation. Numerous genes feature hypermethylated CpG island promoters in breast cancer, which are involved in regulation of the cell cycle, in DNA repair, in the remodeling of chromatin, in cell signaling, and in transcription and tumor cell invasion and apoptosis. An additional important type of methylated cytosine is 5-hydroxymethylcytosine (5hmC), even if at significantly lower levels. The 5hmC cytosine results from oxidation of 5mC by Tet enzymes (Kohli and Zhang, 2013). This pathway of oxidation can continue, rendering 5-carboxylcytosine and 5-formylcytosine, as substrates for the DNA repair enzyme thymidineeDNA

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

848

46. BREAST CANCER BIOMARKERS

glycosylase, emerging as one mechanism for methyl group removal from cytosine.

IMPACT OF METHYLATION BIOMARKERS DNA Methylation Markers and Primary Prevention In the context of increasing research efforts for cancer prevention, studies have also been directed toward assessment of the potential of DNA methylation as a biomarker for cancer risk evaluation. From the various studies conducted, some have aimed to examine the correlation between breast cancer risk and DNA methylation, both gene specific and global (reviewed in Terry et al., 2011; Brennan and Flanagan, 2012). For instance, risk assessment studies were performed on white blood cell DNA, concluding on significant association of both hyper- and hypo-global methylation with breast cancer, highlighting the potential as a biomarker for breast cancer risk global DNA methylation. However, there are certain limitations at this time to the approach of DNA methylation as cancer risk predictor, such as a certain degree of uncertainty derived from the potential for resulting data to be in fact an outcome of differences in cell populations or a response to underlying disease. In addition, DNA methylation can be influenced by other factors as well, such as genetics and age, to which lifestyle and environmental factors may be added (e.g., diet, smoking, air pollution, heavy metals, stress) (Terry et al., 2011; Bakulski and Fallin, 2014). Therefore, evaluation of the value of DNA methylation as a predictor for cancer requires larger population studies, allowing for extended follow-up, as well as serial blood collections (Pepe et al., 2001).

DNA Methylation Markers for Secondary Prevention and Early Detection Screening tools for diagnosis and to determine treatment and prognosis are proposed as secondary preventive means. Despite its proven practical usefulness in effectively reducing breast cancer mortality for women at medium risk, regular screening by mammography (Mandelblatt et al., 2009; Webb et al., 2014) is generally not entirely satisfactory in specificity and sensitivity and even more limited in the case of younger females or those with dense breasts (Elmore et al., 1998; Alagaratnam and Wong, 1985; Moss, 2004; Qaseem et al., 2007). Such limitations as well as the complexity of the disease make a single-marker approach insufficient

for effective early detection. The basic principle underlying the current general strategy in the management of cancer is to improve screening sensitivity and specificity by actively promoting the use of multiple various markers combined with different risk factors, adjusted for by reliable and validated statistical models (Wald et al., 1999). Therefore, more effective early detection requires both discovery of additional markers and more precise assessment and stratification of risk. In that respect, biomarkers as additional screening means for early detection are useful for high-risk groups, as they have the ability to identify the disease in the absence of symptoms as well as in cases with normal results by mammography and breast examination (Evron et al., 2001). One such tool consists of plasma/serum cancer screening biomarkers such as the CA-125 for ovarian cancer. A screening tool not used very often for secondary prevention is the category of blood biomarkers such as circulating cell-free DNA in the plasma, released from apoptotic and necrotic cells in the tumor. A number of studies have concluded that circulating DNA levels are higher in the presence of cancer. The potential usefulness of this blood-based biomarker has been further supported by the fact that, though initially examined for mutations, methylation patterns were discovered in circulating DNA that were similar to those of primary tumor ones (Gormally et al., 2007; Wang et al., 2010; Van De Voorde et al., 2012; Suijkerbuijk et al., 2011). Methylation of plasma DNA has been found to possess early detection marker potential (van Hoesel et al., 2013) resulting from studies showing DNA hypermethylation of certain biomarkers (e.g., RARb2, RASSF1A) in early breast cancer stages. Several specific characteristics support the biomarker potential of DNA methylation. Thus, promoter hypermethylation is more frequent than mutations and occurs early in breast tumorigenesis (Hoque et al., 2009; Lewis et al., 2005; Pasquali et al., 2007). In addition, aberrant DNA methylation in malignant cells also occurs in the immediate tissue. There are also technical aspects contributing to the usefulness of DNA methylation as a biomarker. Given its stability and as such the possibility for PCR amplification, analysis of aberrations only requires small amounts of DNA in comparison to gene expression profiling (Sidransky, 1997). Moreover, hypermethylated sequences are easier to detect compared to genetic alterations due to the positive signal they form against an unmethylated background. Furthermore, current research is being conducted on multiple genes such as RASSF1A, CDH1, BRCA1, APC, GSTP1, RARb (reviewed in Ma et al., 2013, Van De Voorde et al., 2012, Suijkerbuijk et al., 2011).

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

MALE BREAST CANCER SUSCEPTIBILITY FACTORS

For adequate sensitivity and specificity in the detection of breast cancer, a range of epigenetic markers should be used (Van De Voorde et al., 2012). Results from research showing the presence of aberrant promoter hypermethylation in serum or plasma DNA in high-risk cases for a substantial amount of time prior to diagnosis further suggest its usefulness as a screening tool of plasma DNA methylation markers. In fact, there is increasing evidence that plasma DNA methylation of certain genes allows for over 90% sensitivity for breast cancer detection. One important benefit of blood markers for more effective screening is its use as an alternative or additional option to MRI and mammography, especially in cases where these screening tools have shown less sensitivity, and to reduce cumulative radiation.

DNA Methylation Markers and Tertiary Prevention and Role in Prognosis Despite abundant information on DNA methylation in tissue samples at diagnosis, research of the correlation between DNA methylation patterns on diagnosis and subsequent prognosis and overall survival is scarce. Results of all recent studies that initiated on correlations between DNA methylation and breast cancer have converged toward cumulatively demonstrating the importance of methylation biomarkers present in tissue, plasma, and serum samples for secondary and tertiary prevention, as well as for prognosis of disease behavior and therapy outcome for the patient. Further studies, especially cohort studies, are needed to accurately clarify the prognostic contribution of DNA methylation biomarkers, particularly in samples harvested at baseline. Continued extensive research is a necessary means to demonstrate the usefulness for screening and prognosis in general practice of complementing standard clinical markers measured at diagnosis (stage, grade, tumor size, molecular subtype) with assessment of methylation biomarkers. To conclude, growing information on all aspects of the correlation between incidence of breast cancer and DNA methylation markers has not been fully clarified. Prospective research is required to eliminate temporality-related uncertainties resulting from the retrospective character of most studies thus far, which has made it difficult to determine whether aberrant methylation is a cause of or a consequence of cancer or its treatment. Future research also needs to ascertain, by repeated measurement, the potential for environmental factors to alter levels of DNA methylation markers, as well as the capacity of such modifications to influence the risk itself. Finally, the panel of studied gene targets should be diversified.

849

MALE BREAST CANCER SUSCEPTIBILITY FACTORS Epidemiology Male breast cancer accounts for less than 1% of all breast cancers and only 0.2% of all cancers in males (ACS, 2013).

Pathology Although rare, the glandular and adipose tissues of the breast in adult males can grow and proliferate as a result of a process similar to that occurring in females subject to high estrogen and progesterone levels, ending in disruption of the estrogen-to-androgen ratio (Johnson and Murad, 2009; Dickson, 2012). Growth of adipose tissue and a decrease of testosterone production thus inclining the estrogen:androgen ratio toward estrogen is the primary cause of breast cancer in men of age >65 (Niewoehner and Schorer, 2008). In approximately 85% of cases, male breast cancer appears as a subareolar, unilateral thickening of the breast and is usually painless and may involve nipple retraction, ulceration, or discharge (Johansen Taber et al., 2010; Zygogianni et al., 2012).

Risk Factors Major risk factors for male breast cancer include excess estrogen:androgen ratio, family disease history, inclusion in a particular ethnic group, occurrence of specific gene mutations, and environmental factors (Niewoehner and Schorer, 2008; Johansen Taber et al., 2010; Zygogianni et al., 2012; Ruddy and Winer, 2013). One of the most important causes of higher estrogen: androgen ratio underlying male breast cancer is the Klinefelter syndrome (XXY sex chromosomes), which is also characterized by more estrogen and progesterone receptors in the breast tissue (Aksglaede et al., 2013). Both of these features pose a very significant breast cancer risk (20e30 times normal) (Brinton, 2011). Among other causes of excess estrogen:androgen ratio potentially leading to male breast cancer are low levels of androgen determined by such testicular anomalies as orchitis or cryptorchidism, elevated estrogen and androgen caused by congenital adrenal hyperplasia or Leydig cell tumor, therapy with exogenous estrogen, increased estradiol levels triggered by abnormal aromatase function or Sertoli cell tumor, abnormal levels of sex hormone binding globulin, hyperthyroidism, liver or renal disease, obesity, environmental antiandrogenic and proestrogenic factors (e.g., excessive heat), and carcinogenic compounds and radiation (Niewoehner and Schorer, 2008; Johansen Taber et al., 2010;

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

850

46. BREAST CANCER BIOMARKERS

Zygogianni et al., 2012; Ruddy and Winer, 2013). Given their shared risk factors, gynecomastia may be considered a marker of breast cancer risk. Recently, a new cause of gynecomastia has been added to the established one (high effect of estrogens or the low effect of androgens, i.e., use of estrogen receptor binding drugs e.g., digitalis, diazepam, and ketoconazole) and exogenous compounds (marijuana) (Niewoehner and Schorer, 2008; Swerdloff and Ng, 2011). Another important risk factor for male breast cancer is mutation in the BRCA2 gene (accounting for 5%e10% likelihood) and, to a lesser extent, the BRCA1 gene (Ruddy and Winer, 2013). Because of a current lack of awareness of this disease in men, screening and breast examination for males is infrequent, which sharply diminishes the possibility for early detection. In over 50% of cases, tumors of the male breast are diagnosed at stage II or more, whereas this only happens in about 35% of cases in women (Johansen Taber et al., 2010; Zygogianni et al., 2012).

Cancer Aggressiveness Risk Factors Accumulating evidence from clinical and epidemiological studies increasingly demonstrating the diversity of risk factors for cancer occurrence and for lifethreatening cancer, as well as the complexity of their interplay, suggests a potential difference between prediagnostic risk factors for cancer occurrence and those for cancer death (Autier, 2012; Barnett et al., 2008), even in the same organ. This renders the significance of finding the so-called “cancer aggressiveness risk factor,” consisting of individual-specific genetic, lifestyle, and/or environmental features or of measuring nontumor biomarkers to determine individuals who are more likely to develop aggressive, life-threatening cancers. From this perspective, it has been determined that even if highly instrumental in breast cancer risk, reproductive factors are weak for breast cancer mortality (Barnett et al., 2008). Though modest as breast cancer risk triggers in post-menopausal women, adiposity increases the risk for breast cancer death in women before menopause (Loi et al., 2005). The example of fertility may be added to these, which is generally a weak risk for breast cancer but an aggravating one for cancer death in women aged 40 and above and in those who give birth (Daling et al., 2002).

Impact of Cancer Aggressiveness Risk Factors for Patient Management and Health Policies The identification of cancer aggressiveness risk factors is a most important tool for risk stratification and therefore proves useful for medical practice and health

policies. Primary prevention would acquire the necessary base to target efforts in high-risk individuals by providing personalized counseling. Furthermore, given the basic purpose of screening to detect cancer early and thus prevent lethal disease outcomes, application of cancer aggressiveness risk factors would decrease harm from unnecessary screening in less aggressive cancer risk cases. By differentiating between subjects at higher risk of cancer death and those at mere higher risk of cancer occurrence, screening would thus become more cost-effective and improve participation due to better patient awareness. At the same time, use of such tools would improve cancer patient stratification and referral, distinguishing between absence of life-threatening risk, where active surveillance is the adequate approach, and presence of life-threatening risk, requiring immediate treatment. A further benefit would impact decisions for therapeutic options, warning against cancer aggressiveness risk factors leading to likelihood of relapse despite an ostensibly favorable prognosis and endorsing more resolute management of such patients. Lastly, discovery of such risk factors would greatly assist in clarification of biological mechanisms leading to poor prognosis for progression, relapse, and lethal cancer outcome. In the context of cancer overdiagnosis and resulting overtreatment with unnecessarily aggressive therapy, relevance of cancer aggressiveness risk factors for medical practice lies in their potential to prioritize referral to diagnosis and specialized care. By eliminating pseudocancers and borderline or in situ cancers from therapy, their use can increase costeffectiveness of both screening and therapy and reduce associated harm. Further research in this respect would prove highly beneficial for the design of screening policies, chemoprevention strategies, and making better-informed decisions on treatment options based on more accurate evaluation of relapse risks and would avoid unnecessary treatment.

References Aksglaede, L., Link, K., Giwercman, A., 2013. 47,XXY Klinefelter syndrome: clinical characteristics and age-specific recommendations for medical management. Am. J. Med. Genet. C. Semin. Med. Genet. 163, 55e63. Alagaratnam, T.T., Wong, J., 1985. Limitations of mammography in Chinese females. Clin. Radiol. 36 (2), 175e177. American Cancer Society (ACS), 2013. Breast Cancer. Available at: www.cancer.org/cancer/breastcancer/index. Amos, C.I., Keitheri-Cheteri, M.B., Sabripour, M., et al., 2004. Genotype-phenotype correlations in Peutz-Jeghers syndrome. J. Med. Genet. 41 (5), 327e333. Antoniou, A.C., Beesley, J., McGuffog, L., et al., 2010. Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers: implications for risk prediction. Cancer Res. 70 (23), 9742e9754.

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

REFERENCES

Antoniou, A.C., Cunningham, A.P., Peto, J., et al., 2008. The BOADICEA model of genetic susceptibility to breast and ovarian cancers: updates and extensions. Br. J. Cancer 98 (8), 1457e1466. Arpino, G., Bardou, V.J., Clark, G.M., Elledge, R.M., 2004. Infiltrating lobular carcinoma of the breast: tumor characteristics and clinical outcome. Breast Cancer Res. 6 (3), R149eR156. Autier, P., 2012. Risk factors for breast cancer for women aged 40 to 49 years. Ann. Intern. Med. 157 (7), 529. Bahcall, O.G., 2013. iCOGS collection provides a collaborative model. Foreword. Nat. Genet. 45, 343. Bakulski, K.M., Fallin, M.D., 2014. Epigenetic epidemiology: promises for public health research. Environ. Mol. Mutagen. 55 (3), 171e183. Barnett, G.C., Shah, M., Redman, K., et al., 2008. Risk factors for the incidence of breast cancer: do they affect survival from the disease? J. Clin. Oncol. 26 (20), 3310e3316. Bast Jr., R.C., Ravdin, P., Hayes, D.F., et al., 2001. 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J. Clin. Oncol. 19 (6), 1865e1878. Bernier, M.O., Plu-Bureau, G., Bossard, N., et al., 2000. Breastfeeding and risk of breast cancer: a metaanalysis of published studies. Hum. Reprod. Update 6, 374e386. Bignon, Y.J., Fonck, Y., Chassagne, M.C., 1995. Histoprognostic grade in tumours from families with hereditary predisposition to breast cancer. Lancet 346 (8969), 258. Birnbaum, L.S., Fenton, S.E., 2003. Cancer and developmental exposure to endocrine disruptors. Environ. Health Perspect. 111, 389e394. Biro, F.M., Galvez, M.P., Greenspan, L.C., 2010. Pubertal assessment method and baseline characteristics in a mixed longitudinal study of girls. Pediatrics 126, e583ee590. Biro, F.M., Lucky, A.W., Simbartl, L.A., 2003. Pubertal maturation in girls and the relationship to anthropometric changes: pathways through puberty. J. Pediatr. 142, 643e646. Boardman, L.A., Thibodeau, S.N., Schaid, D.J., et al., 1998. Increased risk for cancer in patients with the Peutz-Jeghers syndrome. Ann. Intern. Med. 128 (11), 896e899. Boardman, L.A., Couch, F.J., Burgart, L.J., et al., 2000a. Genetic heterogeneity in Peutz-Jeghers syndrome. Hum. Mutat. 16 (1), 23e30. Boardman, L.A., Pittelkow, M.R., Couch, F.J., et al., 2000b. Association of Peutz-Jeghers-like mucocutaneous pigmentation with breast and gynecologic carcinomas in women. Medicine 79 (5), 293e298. Brennan, K., Flanagan, J.M., 2012. Is there a link between genome-wide hypomethylation in blood and cancer risk? Cancer Prev. Res. 5 (12), 1345e1357. Brinton, L.A., 2011. Breast cancer risk among patients with Klinefelter syndrome. Acta Paediatr. 100, 814e818. Burke, W., Petersen, G., Lynch, P., et al., 1997. Recommendations for follow-up care of individuals with an inherited predisposition to cancer. I. Hereditary nonpolyposis colon cancer. Cancer Genetics Studies Consortium. J. Am. Med. Assoc. 277 (11), 915e919. Carel, J.C., Lahlou, N., Roger, M., Chaussain, J.L., 2004. Precocious puberty and statural growth. Hum. Reprod. Update 10, 135e147. Chen, S., Parmigiani, G., 2007. Meta-analysis of BRCA1 and BRCA2 penetrance. J. Clin. Oncol. 25 (11), 1329e1333. Cianfrocca, M., Goldstein, L.J., 2004. Prognostic and predictive factors in early-stage breast cancer. Oncol. 9 (6), 606e616. Claus, E.B., Risch, N., Thompson, W.D., 1991. Genetic analysis of breast cancer in the cancer and steroid hormone study. Am. J. Hum. Genet. 48 (2), 232e242. Claus, E.B., Risch, N., Thompson, W.D., 1993. The calculation of breast cancer risk for women with a first degree family history of ovarian cancer. Breast Cancer Res. Treat. 28 (2), 115e120.

851

Claus, E.B., Schildkraut, J.M., Thompson, W.D., Risch, N.J., 1996. The genetic attributable risk of breast and ovarian cancer. Cancer 77 (11), 2318e2324. Couch, F.J., Nathanson, K.L., Offit, K., 2014. Two decades after BRCA: setting paradigms in personalized cancer care and prevention. Science 343 (6178), 1466e1470. D’Aloisio, A.A., Deroo, L.A., Baird, D.D., Weinberg, C.R., Sandler, D.R., 2013. Prenatal and infant exposures and age at menarche. Epidemiology 24, 277e284. Daling, J.R., Malone, K.E., Doody, D.R., et al., 2002. The relation of reproductive factors to mortality from breast cancer. Cancer Epidemiol. Biomarkers Prev. 11 (3), 235e241. Dickson, G., 2012. Gynecomastia. Am. Fam. Physician 85, 716e722. Domchek, S.M., Friebel, T.M., Singer, C.F., et al., 2010. Association of risk-reducing surgery in BRCA1 or BRCA2 mutation carriers with cancer risk and mortality. J. Am. Med. Assoc. 304 (9), 967e975. Duffy, M.J., 2006. Serum tumor markers in breast cancer: are they of clinical value? Clin. Chem. 52 (3), 345e351. Dupont, W.D., Parl, F.F., Hartmann, W.H., et al., 1993. Breast cancer risk associated with proliferative breast disease and atypical hyperplasia. Cancer 71 (4), 1258e1265. Eisen, A., Lubinski, J., Klijn, J., et al., 2005. Breast cancer risk following bilateral oophorectomy in BRCA1 and BRCA2 mutation carriers: an international case-control study. J. Clin. Oncol. 23 (30), 7491e7496. Elmore, J.G., Barton, M.B., Moceri, V.M., et al., 1998. Ten-year risk of false positive screening mammograms and clinical breast examinations. N. Engl. J. Med. 338 (16), 1089e1096. Elston, C.W., Ellis, I.O., 1991. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19 (5), 403e410. Ernster, V.L., Ballard-Barbash, R., Barlow, W.E., et al., 2002. Detection of ductal carcinoma in situ in women undergoing screening mammography. J. Natl. Cancer Inst. 94 (20), 1546e1554. Evron, E., Dooley, W.C., Umbricht, C.B., et al., 2001. Detection of breast cancer cells in ductal lavage fluid by methylation-specific PCR. Lancet 357 (9265), 1335e1336. Fabian, C.J., Kimler, B.F., Mayo, M.S., Khan, S.A., 2005. Breast-tissue sampling for risk assessment and prevention. Endocr. Relat. Canc. 12 (2), 185e213. Faupel-Badger, J.M., Arcaro, K.F., Balkam, J.J., 2013. Postpartum remodeling, lactation, and breast cancer risk: summary of a National Cancer Institute-sponsored workshop. J. Natl. Cancer Inst. 105, 166e174. Fenton, S.E., Reed, C., Newbold, R.R., 2012. Perinatal environmental exposures affect mammary development, function, and cancer risk in adulthood. Annu. Rev. Pharmacol. Toxicol. 52, 455e479. Fenton, S.E., 2006. Endocrine-disrupting compounds and mammary gland development: early exposure and later life consequences. Endocrinology 147, S18eS24. Finch, A., Beiner, M., Lubinski, J., et al., 2006. Salpingo-oophorectomy and the risk of ovarian, fallopian tube, and peritoneal cancers in women with a BRCA1 or BRCA2 mutation. J. Am. Med. Assoc. 296 (2), 185e192. Ford, D., Easton, D.F., Bishop, D.T., et al., 1994. Risks of cancer in BRCA1-mutation carriers. Breast Cancer Linkage Consortium. Lancet 343 (8899), 692e695. Fraga, M.F., Agrelo, R., Esteller, M., 2007. Cross-talk between aging and cancer: the epigenetic language. Ann. N. Y. Acad. Sci. 1100, 60e74. Frank, T.S., Deffenbaugh, A.M., Reid, J.E., et al., 2002. Clinical characteristics of individuals with germline mutations in BRCA1 and BRCA2: analysis of 10,000 individuals. J. Clin. Oncol. 20 (6), 1480e1490.

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

852

46. BREAST CANCER BIOMARKERS

Gast, M.C., Schellens, J.H., Beijnen, J.H., 2009. Clinical proteomics in breast cancer: a review. Breast Cancer Res. Treat. 116 (1), 17e29. Gaudet, M.M., Kirchhoff, T., Green, T., et al., 2010. Common genetic variants and modification of penetrance of BRCA2-associated breast cancer. PLoS Genet. 6 (10), e1001183. Gaudet, M.M., Kuchenbaecker, K.B., Vijai, J., et al., 2013. Identification of a BRCA2-specific modifier locus at 6p24 related to breast cancer risk. PLoS Genet. 9 (3), e1003173. Gayther, S.A., Harrington, P., Russell, P., et al., 1996. Rapid detection of regionally clustered germ-line BRCA1 mutations by multiplex heteroduplex analysis. UKCCCR Familial Ovarian Cancer Study Group. Am. J. Hum. Genet. 58 (3), 451e456. Gayther, S.A., Harrington, P., Russell, P., et al., 1997. Frequently occurring germ-line mutations of the BRCA1 gene in ovarian cancer families from Russia. Am. J. Hum. Genet. 60 (5), 1239e1242. Giordano, S.H., Buzdar, A.U., Smith, T.L., et al., 2004. Is breast cancer survival improving? Cancer 100 (1), 44e52. Goldgar, D.E., Easton, D.F., Deffenbaugh, A.M., et al., 2004. Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2. Am. J. Hum. Genet. 75 (4), 535e544. Gormally, E., Caboux, E., Vineis, P., Hainaut, P., 2007. Circulating free DNA in plasma or serum as biomarker of carcinogenesis: practical aspects and biological significance. Mutat. Res. 635, 105e117. Guidugli, L., Carreira, A., Caputo, S.M., et al., 2014. Functional assays for analysis of variants of uncertain significance in BRCA2. Hum. Mutat. 35 (2), 151e164. Guidugli, L., Pankratz, V.S., Singh, N., et al., 2013. A classification model for BRCA2 DNA binding domain missense variants based on homology-directed repair activity. Cancer Res. 73 (1), 265e275. Harris, L., Fritsche, H., Mennel, R., et al., 2007. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J. Clin. Oncol. 25 (33), 5287e5312. Hisada, M., Garber, J.E., Fung, C.Y., et al., 1998. Multiple primary cancers in families with Li-Fraumeni syndrome. J. Natl. Cancer Inst. 90 (8), 606e611. Hoover, R.N., Hyer, M., Pfeiffer, R.M., 2011. Adverse health outcomes in women exposed in utero to diethylstilbestrol. N. Engl. J. Med. 365, 1304e1314. Hoque, M.O., Feng, Q., Toure, P., et al., 2006. Detection of aberrant methylation of four genes in plasma DNA for the Wdetection of breast cancer. J. Clin. Oncol. 24 (26), 4262e4269. Hoque, M.O., Prencipe, M., Poeta, M.L., et al., 2009. Changes in CpG islands promoter methylation patterns during ductal breast carcinoma progression. Cancer Epidemiol. Biomark. Prev. 18 (10), 2694e2700. Interagency Breast Cancer and Environmental Research Coordinating Committee (IBCERCC), 2013. Breast Cancer and the Environment: Prioritizing Prevention. Available at: www.niehs.nih.gov/about/ assets/docs/ibcercc_full_508.pdf. IOM (Institute of Medicine), 2011. Dietary Reference Intakes for Calcium and Vitamin D. Committee to Review Dietary Reference Intakes for Calcium and Vitamin D. The National Academies Press, Washington, DC. Iversen Jr., E.S., Couch, F.J., Goldgar, D.E., et al., 2011. A computational method to classify variants of uncertain significance using functional assay data with application to BRCA1. Cancer Epidemiol. Biomark. Prev. 20 (6), 1078e1088. Jacquemier, J., Eisinger, F., Birnbaum, D., Sobol, H., 1995. Histoprognostic grade in BRCA1-associated breast cancer. Lancet 345 (8963), 1503.

Johannsson, O.T., Idvall, I., Anderson, C., et al., 1997. Tumour biological features of BRCA1-induced breast and ovarian cancer. Eur. J. Cancer 33 (3), 362e371. Johansen Taber, K.A., Morisy, L.R., Osbahr, A.J., Dickinson, B.D., 2010. Male breast cancer: risk factors, diagnosis, and management. Oncol. Rep. 24, 1115e1120. Johnson, R.E., Murad, M.H., 2009. Gynecomastia: pathophysiology, evaluation, and management. Mayo Clin. Proc. 84, 1010e1015. Judkins, T., Rosenthal, E., Arnell, C., et al., 2012. Clinical significance of large rearrangements in BRCA1 and BRCA2. Cancer 118 (21), 5210e5216. Kauff, N.D., Satagopan, J.M., Robson, M.E., et al., 2002. Risk-reducing salpingooophorectomy in women with a BRCA1 or BRCA2 mutation. N. Engl. J. Med. 346 (21), 1609e1615. King, M.-C., 2014. The race’ to clone BRCA1. Science 343, 1462e1465. Kobayashi, S., Sugiura, H., Ando, Y., 2012. Reproductive history and breast cancer risk. Breast Canc. 19, 302e308. Kohli, R.M., Zhang, Y., 2013. TET enzymes, TDG and the dynamics of DNA demethylation. Nature 502 (7472), 472e479. Kriege, M., Brekelmans, C.T., Boetes, C., et al., 2004. Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. N. Engl. J. Med. 351 (5), 427e437. Kuerer, H.M., Albarracin, C.T., Yang, W.T., et al., 2009. Ductal carcinoma in situ: state of the science and roadmap to advance the field. J. Clin. Oncol. 27 (2), 279e288. Lane, J.A., Hamdy, F.C., Martin, R.M., et al., 2010. Latest results from the UK trials evaluating prostate cancer screening and treatment: the CAP and ProtecT studies. Eur. J. Cancer 46 (17), 3095e3101. Lapidus, R.G., Nass, S.J., Davidson, N.E., 1998. The loss of estrogen and progesterone receptor gene expression in human breast cancer. J. Mammary Gland Biol. Neoplasia 3 (1), 85e94. Levenson, V.V., 2007. Biomarkers for early detection of breast cancer: what, when, and where? Biochim. Biophys. Acta 1770 (6), 847e856. Lewis, C.M., Cler, L.R., Bu, D.-W., et al., 2005. Promoter hypermethylation in benign breast epithelium in relation to predicted breast cancer risk. Clin. Cancer Res. 11 (1), 166e172. Li, C.I., Anderson, B.O., Daling, J.R., Moe, R.E., 2003. Trends in incidence rates of invasive lobular and ductal breast carcinoma. JAMA 289 (11), 1421e1424. Lindor, N.M., Guidugli, L., Wang, X., et al., 2012. A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS). Hum. Mutat. 33 (1), 8e21. Loi, S., Milne, R.L., Friedlander, M.L., et al., 2005. Obesity and outcomes in premenopausal and postmenopausal breast cancer. Cancer Epidemiol. Biomarkers Prev. 14 (7), 1686e1691. Ma, Y., Wang, X., Jin, H., 2013. Methylated DNA and microRNA in body fluids as biomarkers for cancer detection. Int. J. Mol. Sci. 14 (5), 10307e10331. Mandelblatt, J.S., Cronin, K.A., Bailey, S., et al., 2009. Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann. Intern. Med. 151 (10), 738e747. Maxwell, K.N., Nathanson, K.L., 2013. Common breast cancer risk variants in the post-COGS era: a comprehensive review. Breast Cancer Res. 15 (6), 212. Menard, S., Pupa, S.M., Campiglio, M., Tagliabue, E., 2003. Biologic and therapeutic role of HER2 in cancer. Oncogene 22 (42), 6570e6578. Mettler, F.A., Upton, A.C., Kelsey, C.A., et al., 1996. Benefits versus risks from mammography: a critical reassessment. Cancer 77 (5), 903e909.

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS

REFERENCES

Michailidou, K., Hall, P., Gonzalez-Neira, A., et al., 2013. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat. Genet. 45 (4), 353e361, 361e351e352. Morris, E.A., Liberman, L., Ballon, D.J., et al., 2003. MRI of occult breast carcinoma in a high-risk population. Am. J. Roentgenol. 181 (3), 619e626. Moss, S., 2004. Should women under 50 be screened for breast cancer? Br. J. Cancer 91 (3), 413e417. Neville, M.C., Morton, J., Umemura, S., 2001. Lactogenesis: the transition from pregnancy to lactation. Pediatr. Clin. North Am. 48, 35e52. Niewoehner, C.B., Schorer, A.E., 2008. Gynaecomastia and breast cancer in men. BMJ 336, 709e713. Offit, K., Gilewski, T., McGuire, P., et al., 1996. Germline BRCA1 185delAG mutations in Jewish women with breast cancer. Lancet 347 (9016), 1643e1645. Page, D.L., Schuyler, P.A., Dupont, W.D., et al., 2003. Atypical lobular hyperplasia as a unilateral predictor of breast cancer risk: a retrospective cohort study. Lancet 361 (9352), 125e129. Park, S.K., Kang, D., McGlynn, K.A., 2008. Intrauterine environments and breast cancer risk: meta-analysis and systematic review. Breast Cancer Res. 10, R8. Pasquali, L., Bedeir, A., Ringquist, S., et al., 2007. Quantification of CpG island methylation in progressive breast lesions from normal to invasive carcinoma. Cancer Lett. 257 (1), 136e144. Pepe, M.S., Etzioni, R., Feng, Z., et al., 2001. Phases of biomarker development for early detection of cancer. J. Natl. Cancer Inst. 93 (14), 1054e1061. Pharoah, P.D., Day, N.E., Duffy, S., et al., 1997. Family history and the risk of breast cancer: a systematic review and meta-analysis. Int. J. Cancer 71 (5), 800e809. Qaseem, A., Snow, V., Sherif, K., et al., 2007. Screening mammography for women 40 to 49 years of age: a clinical practice guideline from the American College of Physicians. Ann. Intern. Med. 146 (7), 511e515. Radpour, R., Barekati, Z., Kohler, C., et al., 2011. Hypermethylation of tumor suppressor genes involved in critical regulatory pathways for developing a blood-based test in breast cancer. PLoS One 6 (1), e16080. Rebbeck, T.R., Lynch, H.T., Neuhausen, S.L., et al., 2002. Prophylactic oophorectomy in carriers of BRCA1 or BRCA2 mutations. N. Engl. J. Med. 346 (21), 1616e1622. Rebbeck, T.R., Mitra, N., Domchek, S.M., et al., 2011. Modification of BRCA1-associated breast and ovarian cancer risk by BRCA1interacting genes. Cancer Res. 71 (17), 5792e5805. Robertson, K.D., 2005. DNA methylation and human disease. Nat. Rev. Genet. 6 (8), 597e610. Robson, M., Rajan, P., Rosen, P.P., et al., 1998. BRCA-associated breast cancer: absence of a characteristic immunophenotype. Cancer Res. 58 (9), 1839e1842. Ruddy, K.J., Winer, E.P., 2013. Male breast cancer: risk factors, biology, diagnosis, treatment and survivorship. Ann. Oncol. 24, 1434e1443. Russo, J., Russo, I.H., 1999. Cellular basis of breast cancer susceptibility. Oncol. Res. 11 (4), 169e178. Sidransky, D., 1997. Nucleic acid-based methods for the detection of cancer. Science 278 (5340), 1054e1058. Silva, J., Silva, J.M., Garcia, V., et al., 2002. RNA is more sensitive than DNA in identification of breast cancer patients bearing tumor nucleic acids in plasma. Genes Chromosomes Cancer 35 (4), 375e376. Singletary, S.E., Allred, C., Ashley, P., et al., 2002. Revision of the American Joint Committee on Cancer staging system for breast cancer. J. Clin. Oncol. 20 (17), 3628e3636.

853

Spurdle, A.B., Whiley, P.J., Thompson, B., et al., 2012. BRCA1 R1699Q variant displaying ambiguous functional abrogation confers intermediate breast and ovarian cancer risk. J. Med. Genet. 49 (8), 525e532. Srinivas, P.R., Kramer, B.S., Srivastava, S., 2001. Trends in biomarker research for cancer detection. Lancet Oncol. 2 (11), 698e704. Suijkerbuijk, K.P.M., van Diest, P.J., van der Wall, E., 2011. Improving early breast cancer detection: focus on methylation. Ann. Oncol. 22 (1), 24e29. Swerdloff, R.S., Ng, J.C.M., 2011. Gynecomastia: Etiology, Diagnosis, and Treatment. Available at: www.endotext.org/male/male14/ male14.html. Szabo, C.I., King, M.C., 1997. Population genetics of BRCA1 and BRCA2. Am. J. Hum. Genet. 60 (5), 1013e1020. Tao, Z., Shi, A., Lu, C., et al., 2015. Breast Cancer: epidemiology and etiology. Cell Biochem. Biophys. 72 (2), 333e338. Tavtigian, S.V., Byrnes, G.B., Goldgar, D.E., Thomas, A., 2008. Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications. Hum. Mutat. 29 (11), 1342e1354. Terry, M.B., Delgado-Cruzata, L., Vin-Raviv, N., et al., 2011. DNA methylation in white blood cells: association with risk factors in epidemiologic studies. Epigenetics 6 (7), 828e837. Thorlacius, S., Sigurdsson, S., Bjarnadottir, H., et al., 1997. Study of a single BRCA2 mutation with high Carrier frequency in a small population. Am. J. Hum. Genet. 60 (5), 1079e1084. Van De Voorde, L., Speeckaert, R., Van Gestel, D., et al., 2012. DNA methylation-based biomarkers in serum of patients with breast cancer. Mutat. Res. 751 (2), 304e325. van Hoesel, A.Q., Sato, Y., Elashoff, D.A., et al., 2013. Assessment of DNA methylation status in early stages of breast cancer development. Br. J. Cancer 108 (10), 2033e2038. Veronesi, U., Boyle, P., Goldhirsch, A., et al., 2005. Breast cancer. Lancet 365 (9472), 1727e1741. Wald, N.J., Hackshaw, A.K., Frost, C.D., 1999. When can a risk factor be used as a worthwhile screening test? BMJ 319 (7224), 1562e1565. Walsh, M.F., Nathanson, K.L., Couch, F.J., Offit, K., 2016. Genomic biomarkers for breast cancer risk. Adv. Exp. Med. Biol. 882, 1e32. Wan, W., Deng, X., Archer, K.J., Sun, S.S., 2012. Pubertal pathways and the relationship to anthropometric changes in childhood: the Fels longitudinal study. Open J. Pediatr. 2, 9. Wandall, H.H., Blixt, O., Tarp, M.A., et al., 2010. Cancer biomarkers defined by autoantibody signatures to aberrant Oglycopeptide epitopes. Cancer Res. 70 (4), 1306e1313. Wang, X., Pankratz, V.S., Fredericksen, Z., et al., 2010. Common variants associated with breast cancer in genomewide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers. Hum. Mol. Genet. 19 (14), 2886e2897. Webb, M.L., Cady, B., Michaelson, J.S., et al., 2014. A failure analysis of invasive breast cancer. Cancer 120 (18), 2839e2846. Whittemore, A.S., Gong, G., Itnyre, J., 1997. Prevalence and contribution of BRCA1 mutations in breast cancer and ovarian cancer: results from three U.S. population-based case-control studies of ovarian cancer. Am. J. Hum. Genet. 60 (3), 496e504. Wong, E.M., Southey, M.C., Fox, S.B., et al., 2011. Constitutional methylation of the BRCA1 promoter is specifically associated with BRCA1 mutation-associated pathology in early-onset breast cancer. Cancer Prev. Res. 4 (1), 23e33. Yan, P.S., Venkataramu, C., Ibrahim, A., et al., 2006. Mapping geographic zones of cancer risk with epigenetic biomarkers in normal breast tissue. Clin. Cancer Res. 12 (22), 6626e6636. Zygogianni, A.G., Kyrgias, G., Gennatas, C., 2012. Male breast carcinoma: epidemiology, risk factors and current therapeutic approaches. Asian Pac. J. Cancer Prev 13, 15e19.

VII. CARCINOGENS BIOMONITORING AND CANCER BIOMARKERS