Genetic profile of DNA repair genes in Triple Negative Breast Cancer

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University of Pisa

BIOS

Research Doctorate School in BIOmolecular Sciences

SSD BIO/11

Doctorate Course in

Experimental and Molecular Oncology

2012-2014

Title of the Thesis:

Genetic profile of DNA repair genes

in Triple Negative Breast Cancer

President of the Doctorate Course

Prof. Generoso Bevilacqua

Candidate

Tutor

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Summary

Abstract

... 1

Introduction

... 3

1. BREAST CANCER ... 4

1.1. Histopathological features of Breast Cancer ... 6

1.2. Gene expression profile define new classes of breast cancer ... 7

1.3. Genomic landscape of breast cancer ... 9

2. HEREDITARY BREAST CANCER ... 11

2.1. BRCA genes ... 11

2.2. Other breast cancer susceptibility genes ... 14

2.2.1. High penetrant genes (low frequency) ... 14

2.2.2. Moderate penetrant genes ... 16

3. TRIPLE NEGATIVE BREAST CANCER ... 20

3.1. Molecular characterization of TNBC ... 21

3.2. Genomic features of TNBC ... 24

3.3. TN and basal like: one doesn’t fit to another ... 27

4. BRCA1 AND TNBC: THE BRCAness PHENOTYPE ... 30

4.1. Other Susceptibility loci for TNBC ... 32

5. DNA REPAIR AND BREAST CANCER ... 34

5.1. DNA Repair Mechanisms ... 37

5.1.1. Mismatch repair (MMR) ... 37

5.1.2. Nucleotide Excision Repair (NER) ... 38

5.1.3. Base excision repair (BER) ... 39

5.1.4. Homologous recombination (HR) ... 39

5.1.5. Non Homologous End Joining (NHEJ) ... 40

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5.1.7. DNA-damage checkpoints ... 41

5.2. Targeting DNA repair ... 42

5.3. Biomarkers for DNA repair deficiency ... 46

5.4. TNBC and DNA repair ... 48

6. TNBC AND THERAPY ... 49

6.1. Standard therapies for TNBC ... 50

6.1.1. Anthracyclines ... 51

6.1.2. Taxanes ... 51

6.1.3. Platinum compounds ... 52

6.1.4. Alkylating agents ... 53

6.2. Target therapy: PARP1 inhibitors ... 54

6.3. Neoadjuvant therapy as a tool to develop predictive biomarkers ... 55

7. AIM OF THE STUDY ... 59

Materials and Methods

... 61

1. Germline screening: patients ... 62

2. Tumor Tissues Screening: patients ... 62

3. DNA extraction ... 63

4. MLPA Analysis ... 63

5. Libraries preparation and ION PGM sequencing : the ION torrent protocol ... 64

6. Data processing and analysis ... 67

7. Sanger sequencing ... 69

8. High Resolution Melting (HRM) in healthy controls ... 69

9. Loss Of Heterozygosity (LOH) analysis in tumour tissues ... 70

10. Statistical Analysis ... 71

Results

... 72

1. GERMLINE MUTATIONAL ANALYSIS IN TNBC NEOADJUVANT PATIENTS ... 73

1.1. Neoadjuvant patients histopathological features ... 73

1.2. Mutational screening in neadiuvant patients and selection of variants ... 74

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1.4. Neoadjuvant germine screening: mutation overview ... 76

1.5. Characterization of novel variants ... 85

1.6. Pathogenetic variants carriers tend to have better clinical outcome ... 86

2. MUTATIONAL SCREENING IN TNBC TISSUES ... 88

2.1. TNBC features ... 88

2.2. Selection of interesting variants in tumor tissues ... 90

2.3. Overview of the rare and predicted pathogenetic variants in TNBC tissues ... 91

2.4. Pathways and genes mutated in TNBC ... 108

2.4.1. Homologous recombination genes ... 108

2.4.2. Mismatch Repair genes ... 109

2.4.3. Non Homologous End Joining genes ... 110

2.4.4. Other pathways ... 110

2.5. TNBC are enriched in genomic rearrangement involving DNA repair genes ... 112

2.6. Correlation of genomic status of tumor tissue and disease free survival ... 114

Discussion

... 118

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Genetic profile of DNA repair genes in TNBC Abstract

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Abstract

Triple Negative Breast Cancer (TNBC), negative for estrogen, progesterone and Her2 receptor, constitutes 10–20% of all breast cancers and more frequently affect young patients. TNBC tumors are generally large in size, higher grade cancers with lymph node involvement at diagnosis, and are biologically more aggressive than other subtypes. Treatment of TNBC patients has been challenging due to the heterogeneity of the disease and the absence of well-defined molecular targets. TNBCs share many phenotypic features with BRCA1-related and basal-like tumors, such as receptors negativity, expression of basal cytokeratins CK5/6, and a similar gene expression profile. This similarity is defined BRCAness and suggests that TNBC and BRCA-related cancer may also share molecular and genetic features and a common deficiency in DNA repair genes. In addition to BRCA1 and BRCA2, mutations in other genes involved in DNA repair may predispose to breast and ovarian cancer and the therapy response can be determined by germline or somatic alterations in these genes. So, the aim of this thesis is to investigate which genes involved in DNA repair are mutated in TNBC and to correlate a genetic signature with the response to neoadjuvant or adjuvant therapy.

The entire coding sequences and intron-exon junctions of 24 genes involved in the main DNA repair pathways (BRCA1, BRCA2, CDH1, MRE11A, MSH2, PARP1, CHEK2, MSH6, RAD52, PTEN, STK11, ERCC1, TP53, PMS1, PMS2, NBN, RAD50, BRIP1, BARD1, MLH1, MUTYH, RAD51C, TP53BP1 and PALB2) were screened using PGM Ion Torrent platform. Some of these are considered breast and ovarian cancer susceptibility genes, while others are associated with breast tumorigenesis. Moreover a set of genes was analyzed for the presence of large rearrangements by MLPA. Two cohort of patients diagnosed of TNBC have been analyzed: 19 patients, with and without family history of breast cancer, treated with neoadjuvant chemotherapy including taxane and anthracycline for germline mutations and 37 unselected TNBC patients with a follow up >5 years for somatic and germline mutations.

The mutational screening in the neoadjuvant setting, have identified 5 patients with clearly pathogenetic mutation in BRCA1, RAD51c and PALB2 accounting for a 20% of the total. Other 15 predicted pathogenetic variants in DNA repair genes were found. Data suggest a potential correlation between the presence of germline pathogenetic mutations, indicative of DNA repair defects, and a positive outcome after neoadjuvant therapy. Furthermore, this approach allowed the identification of 4 novel mutations predicted deleterious by in silico analysis and never reported in literature. In the second set of patients, BRCA1 and BRCA2 mutations were found in 7 patients and one patient, respectively. Also germline

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Genetic profile of DNA repair genes in TNBC Abstract

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mutation in BRIP1 and CDH1 were found. Overall in 56 TNBC patients screened, this gene panel has evidenced that around 25% of them harbour a germline mutation in DNA repair genes. In addition to that, many interesting somatic variants were found in 8 genes (BRCA2, BRIP1, CDH1, MLH1, MSH2, NBN, PMS1, TP53) in this set of TNBC tissues. In particular TP53 was mutated in 68% of patients, and this condition was associated with a worse outcome. The large rearrangement analysis confirmed that PTEN and TP53 loss, along with EGFR gain, are frequent events in TNBC.

This gene panel approach has proved useful to identify a large number of germline mutations in TNBC patients. In the next future, the genetic screening of TNBC patients, even without family history of breast cancer, may be a real option in order to design personalized therapy for individuals with a BRCAness phenotype. Moreover, these results may provide new insights into TNBC pathogenesis and may help to further improve the accuracy of treatments.

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Genetic profile of DNA repair genes in TNBC Introduction

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1. BREAST CANCER

Breast cancer is the most common cancer worldwide for females, and the 2nd most common cancer overall, with more than 1,676,000 new cases diagnosed in 2012 (25% of female cases and 13% of the total) (Ferlay et al. (2013)).

The major risk factors for the development of breast cancer are hormonal and genetic (family history). Breast carcinomas can, therefore, be divided into sporadic cases, possibly related to hormonal exposure, and hereditary cases, associated with family history or germ-line mutations.

The development of sporadic breast cancer is mainly related to hormone exposure: gender, age at menarche and menopause, reproductive history, breast-feeding, and exogenous estrogens. The majority of these cancers occur in postmenopausal women and overexpress estrogen receptor (ER). Estrogen itself has at least two major roles in the development of breast cancer. Metabolites of estrogen can cause mutations or generate DNA-damaging free radicals (Miller, 2003). Via its hormonal actions, estrogens drive the proliferation of premalignant lesions.

However, other mechanisms play a role, as a significant subset of breast carcinomas are ER-negative or occur in women without increased estrogen exposure.

Pathways to carcinogenesis are complex and variable. Indeed, not one common genetic or functional change can be found in every breast cancer. Most reported changes occur in only a subset of carcinomas and usually in highly variable combinations with other changes.

A general model for carcinogenesis postulates that a normal cell must achieve seven new capabilities, including genetic instability, to become malignant (Hahn & Weinberg, 2002). In hereditary carcinoma, one or more of these alterations is facilitated by the inheritance of germ-line mutations. Each of the new capabilities can be achieved by a change in one of many genes. For example, changes in ER, EGF-R, RAS, or HER2/neu may result in self-sufficiency in growth signals. On the other hand, one cellular alteration (e.g., a change in a genes such as p53 that has a central role in controlling the cell cycle, DNA repair, and apoptosis) can affect more than one of these capabilities.

Population of cells that harbour mutations give rise to morphologically recognizable breast lesions and are associated with an increased risk of progression to cancer. Loss of heterozygosity is a rare event in proliferative lesions but becomes frequent in atypical hyperplasia and is almost universally present in carcinoma in situ. During the progression, also due to increased genomic instability, the malignant cells become immortalized and acquire the ability to drive neo angiogenesis.

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The majority of breast malignant lesions are adenocarcinomas, which are divided in in situ carcinoma and invasive carcinomas. Carcinoma in situ describes a neoplastic proliferation that is limited to ducts and lobules by the basement membrane. Invasive carcinoma has penetrated through the basement membrane into stroma: here the cells have the potential to invade the vasculature and reach lymph nodes or distant sites. By current convention, “lobular” refers to carcinoma of a specific type (not expressing E-cadherine), and “ductal” is used more generally for carcinomas with no other designation.

The morphologic and biologic features of carcinomas are usually established at the in situ stage, since in the majority of cases the in situ lesion closely resembles the subsequent invasive carcinoma. Finding the cell of origin of breast cancers is a field of great interest: the cancer stem cell hypothesis proposes that malignant changes occur in a stem cell population and that only the malignant stem cells would contribute to tumor progression or recurrence (Campbell & Polyak, 2014),(Stingl & Caldas, 2007).

The most likely cell type of origin of carcinomas is the ER-expressing luminal cell, since the majority of breast cancer are ER positive. negative tumors may arise from ER-negative myoephielial cells or from a ER positive precursor that loses ER expression (Gauthier et al., 2007).

Even this view of oncogenesis is focused on the malignant epithelial cell, is important to take into account the other tissue components. The structure and function of the normal breast require complex interactions between luminal cells, myoepithelial cells, and stromal cells. The same functions that allow for normal formation of new ductal branch points and lobules during puberty and pregnancy—abrogation of the basement membrane, increased proliferation, escape from growth inhibition, angiogenesis, and invasion of stroma—can be co-opted during carcinogenesis by abnormal epithelial cells, stromal cells, or both (Wiseman & Werb, 2002). While the changes described above are accumulating in the luminal cells or myoepithelial cells, parallel changes also occur due to mutation or epigenetic changes (e.g. DNA methylation) or via abnormal signaling pathways in these other cell types, resulting in the loss of normal cellular interactions and tissue structure. Loss of these normal functions also occurs with age, and this loss might contribute to the increased risk of breast cancer in older women.

The final step of carcinogenesis, the transition of carcinoma limited by the basement membrane to ducts and lobules (carcinoma in situ) to invasive carcinoma, is the most important and unfortunately the least understood (Fig 1). There are many path that can lead to the development of breast cancer, this recognition had led to the introduction of molecular classification systems.

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Fig 1. Tumor initiation and progression events (from Robbins, VIII edition)

1.1. Histopathological features of Breast Cancer

Breast cancer is a heterogeneous disease, and therefore, no golden standard therapy exists suitable for all tumours. For many years, tumours of the breast were characterized by tumour size only. Later on, a histological classification system was developed, dividing breast cancer into subgroups distinguished by the histological appearance of the tumour but even this subdivision failed to form homogeneous breast cancer subgroups (Weigelt et al., 2008), (Page, 2003).

Currently, the most widely used classification system of breast cancer combines histo-morphological information (such as histological subtype and grading) as well as TNM staging information, i.e. tumour size (T) together with lymph node (N) and distant metastasis occurrence (M) (Elston & Ellis, 1991) (Sobin & Compton, 2010).

The outcome for women with breast cancer varies widely and is determined by many genetic, molecular and histopathological factors. From a clinical point of view the major prognostic factors are incorporated into the American Joint Committee on Cancer (AJCC) staging system, which divided patient into five stages (0 to IV) that are correlated with survival:

- Invasive carcinoma (infiltrating the stroma tissue) versus in situ disease (confined to the ductal system)

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- Lymph node metastases: axillary lymph node involvement is the most important prognostic factor, as with no nodal involvement, the 10-year disease free survival (DFS)is close to 80% and decrease to 10% when more than 10 nodes are positive. - Tumor size: this feature is the second most important prognostic factor

- Locally advanced disease (carcinomas invading into skin or skeletal muscle at diagnosis)

- Inflammatory carcinoma

Many other minor prognostic factors are very important to define therapy strategy such as histological subtype, histological grade, estrogen and progesterone receptor, Her2 expression, lymphovascular invasion, proliferative rate, DNA content and gene expression profile.

1.2. Gene expression profile define new classes of breast cancer

Recognition of the importance of the hormone receptors and the human epidermal growth factor receptor 2 in breast cancer, and the large scale use of immunohistochemistry (IHC), enabled almost every cancer center in the world to differentiate breast cancer patients into three major groups: the hormone receptor positive group (which expresses ER and/or PgR), the HER2-positive group, and the ‘‘triple negative’’ group (which is negative for ER, PgR, and HER2).

A more recent approach to classify breast cancer subgroups is gene expression profiling, which allows simultaneous assessment of the contribution of thousands of genes in a single tumor sample. This approach revealed a biological diversity in breast cancer that mirrors the clinical diversity in outcomes (Perou et al., 2000).

In the first years of 2000, many studies have identified several subtypes of breast cancer that differ from one another and that may be considered as individual diseases, under the general term of “breast cancer disease”.

Initial evidence for molecular subtypes of breast cancer came from a cDNA-microarray study of gene expression among a small number of tumor samples and several benign controls.

In 2000, Perou and colleagues compared gene expression among 42 subjects of a group of over 8000 genes: a subset of 1753 was selected based on expression levels that differed by at least four-fold across all samples. Based on these genes, computer-assisted hierarchical clustering was performed to group samples with similar patterns of expression obtaining 4 main subgroups.

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Two of the subgroups had expression patterns similar to normal breast epithelium, specifically basal and luminal epithelial cells. These two groups correspond to tumors that had previously been clinically classified as ER-positive or ER-negative.

The third group was characterized by strong HER2 expression and low expression of ER and its related genes. The other group displayed a genetic expression profile most similar to normal breast tissue and remains enigmatic. Based on these findings, Perou proposed a novel molecular classification of breast cancer into basal-like, luminal, HER2-positive, and normal breast subgroups. In subsequent work by the same group, this classification was refined and expanded to distinguish between luminal A and luminal B tumor subtypes on the basis of their proliferation rate (Sorlie et al., 2001). The five molecular subtypes identified by Perou and Sorlie have been confirmed in independent data sets from other investigators (Sorlie et al., 2003) and among different ethnic groups of patients (Yu, Lee, Tan, & Tan, 2004):

Luminal A (40-55%): this is the largest group and consists of cancers that are ER and

PgR positive and HER2/neu negative. The gene signature is dominated by genes under control of ER and characteristic of normal luminal cells. The majority are well differentiated and most occur in postmenopausal women. They are usually slowly growing and well respond to hormone therapy.

Luminal B (15-20%) This group also express ER but is generally of higher grade, has a

higher proliferative rate and often express HER2. They more likely have lymph node metastases and may respond to therapy.

Normal breast like (6-10%): this is a small group of well-differentiated ER positive HER2

negative cancers and display no specific tumor expression pattern.

Basal like (13-25%): These cancers are notable for the absence of ER, PgR and HER2

and the expression markers of myoepithelial cells (basal keratins, P-cadherin, p65, laminin), progenitor cells or putative stem cells (cytokeratins 5-6). This group include also medullary carcinoma, a subtype with a good prognosis, and metaplastic carcinoma, that instead show worse prognosis.

Basal like cancers are of particular interest because of their distinct genetic and epidemiologic features. They generally have high grade and high proliferation rate, are associated with visceral metastasis and brain metastases. However 15-20% of tumors have a pathological complete response to chemotherapy.

HER2/neu positive (7-12%): This group comprise ER negative carcinomas that

overexpress HER2/neu protein. In 90% of cases overexpression is due to amplification of HER2 genomic locus, which includes also other genes. These cancers are poorly differentiated, have high proliferation rate and are associated with poor prognosis.

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After these two pilot studies, the molecular classification has been enriched with larger studies. In 2009, Parker et al. derived a minimal gene set (PAM50) for classifying “intrinsic” subtypes of breast cancer (Parker et al., 2009). The PAM50 gene set has high agreement in classification with larger “intrinsic” gene sets previously used for subtyping, and is now commonly employed (Ellis et al., 2011), (Esserman et al., 2012), (Gonzalez-Angulo et al., 2012). The intrinsic subtypes are found to be highly conserved across different microarray platforms and across tumors from distinct ethnic populations (Sorlie et al., 2003), (Yu et al., 2004);(Parker et al., 2009).

In a study of high-throughput protein expression analysis (Abd El-Rehim et al., 2005) immunohistochemical markers were assessed for 1076 tumor samples of invasive breast cancer and hierarchical clustering analysis was conducted to group tumors based on IHC characteristics. Six clusters of tumors were identified, roughly corresponding to the five subtypes previously identified, and one small new group consisting of only four tumor samples. Key histological markers that differed significantly between tumor types included androgen receptor, HER2, cytokeratin 18, MUC1, Cytokeratin 5/6, p53, nuclear BRCA1, ER, and E-cadherin. This large study gives additional support to the identification of luminal A, luminal B, normal-like, HER2-positive, and basal-like cancers as discrete biological entities.

1.3. Genomic landscape of breast cancer

The latest level at which breast cancer complexity has been dissected is the genomic level. In the last few years, have been published pivotal studies in which breast cancer tumours were clustered on the basis of their mutation profiles or the presence of other genomic aberrations (Curtis et al., 2012); (Cancer Genome Atlas, 2012b).

Importantly, a study of The Cancer Genome Atlas (2011) revealed that breast and ovarian cancers are dominated by genomic alterations more than by somatic mutations in a list of selected genes. Using the largest sample collection with extensive genomic, transcriptomic and clinical annotation in existence, in 2012 Curtis and colleagues described a scheme for classifying breast tumors into 10 subtypes based on the pattern of copy number alterations (CNA). This classification was named IntClust since the clustering of tumors is based on the integration of genomic and transcriptomic data to find probable driver events.

Around 1000 genes, whose alterations was correlated with a differential expression level, were considered to divide 2000 breast cancer specimen in different clusters.

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An ER-positive subgroup composed by luminal tumours with alterations in chr 11 (IntClust2) was described. One subgroup (IntClust3) with low genomic instability was composed predominantly of luminal A cases, and was enriched for histotypes that typically have good prognosis, including invasive lobular and tubular carcinomas.

Another subgroup (IntClust 4) was also composed of favorable outcome cases, but included both ER-positive and ER-negative cases and varied intrinsic subtypes, and had an essentially flat copy number landscape. A significant proportion of cases within this subgroup exhibit extensive lymphocytic infiltration. Several intermediate prognosis groups of predominantly ER-positive cancers were identified (Clusters 1, 6, 9).

They also noted that the majority of basal-like tumours formed a stable, mostly high-genomic instability subgroup (IntClust10, n = 96). This subgroup had relatively good long-term outcomes after 5 years, and characteristic cis-acting alterations (5 loss/8q gain/10p gain/12p gain). The ERBB2-amplified cancers composed of HER2-enriched (ER-negative) cases and luminal (ER-positive) cases appear as IntClust 5.

In 2012, another integrative and collaborative huge study leaded by The Cancer Genome Atlas Network was performed. Different sets of primary breast cancers were analyzed by genomic DNA copy number arrays, DNA methylation, exome sequencing, mRNA arrays, microRNA sequencing and reverse phase protein arrays. This study demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity (luminal, basal-like, Her2 enriched, normal-like).

To a great extent, the four major integrated clustering subdivisions correlated well with the previously-published mRNA-subtypes.

The mutational screening by exome sequencing of 510 breast tumours identified 30,626 somatic mutations. The MuSiC package (Dees et al., 2012), which determines the significance of the observed mutation rate of each gene based on the background mutation rate, identified 35 Significantly Mutated Genes. In addition to identifying nearly all genes previously implicated in breast cancer (PIK3CA, PTEN, AKT1, TP53, GATA3, CDH1, RB1, MLL3, MAP3K1 and CDKN1B), a number of novel genes were identified including TBX3, RUNX1, CBFB, AFF2, PIK3R1, PTPN22, PTPRD, NF1, SF3B1, and CCND3.

Unsupervised hierarchical clustering analysis of 525 tumors and 22 tumor adjacent normal tissues using the top 3,662 variably expressed genes identified 12 classes. MicroRNA expression levels were assayed via Illumina sequencing, using 1222 miRBase27 v16 mature and star strands as the reference database of microRNA transcripts/genes. Seven subtypes were identified. These subtypes correlated with mRNA-subtypes, ER, PR and HER2 clinical status but not with mutation status. Methylation profiling for a common set of

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574 probes used in an unsupervised clustering analysis, identified five distinct DNA methylation groups. Group 3 showed a hyper-methylated phenotype and was significantly enriched for Luminal B mRNA-subtype and under-represented for PIK3CA and MAP3K1/MAP2K4 mutations. Group 5 showed the lowest levels of DNA methylation, overlapped with the Basal-like mRNA-subtype, and showed a high frequency of TP53 mutations.

Quantified expression of 171 cancer-related proteins and phospho-proteins by RPPA (Reverse Phase Protein Array) was performed on 403 breast tumors. Unsupervised hierarchical clustering analyses identified seven subtypes. These protein subtypes were highly concordant with the mRNA-subtypes, particularly with Basal-like and HER2E mRNA subtypes.

This study also performed analysis on a selected set of genes (Walsh et al., 2010) using the normal tissue DNA data and detected a number of germline predisposing variants. These analysis identified 47/507 patients with deleterious germline variants, representing nine different genes (ATM, BRCA1, BRCA2, BRIP1, CHEK2, NBN, PTEN, RAD51C, and TP53) supporting the hypothesis that ~10% of sporadic breast cancers may have a strong germline contribution. These data confirmed the association between the presence of germline BRCA1 mutations and Basal-like breast cancers (Sorlie et al., 2003); (Foulkes, 2003).

The landscape of somatic alterations in breast cancer is complex and heterogeneous. This variety is reflected in the diverse clinical behavior of breast tumors and provides critical insight for the development of rational therapies.

2. HEREDITARY BREAST CANCER

In the middle of the 19th century, first reports described familial aggregation of breast cancers. Today, positive family history is one of the most important risk factors for developing breast cancer. It is currently estimated that approximately 5–10% of all breast cancers have a hereditary background. These families show an apparently dominant inheritance pattern and are often characterized by an early age of onset, overrepresentation of ovarian cancers, bilateral breast cancers, and male breast cancers (Honrado, Benitez, & Palacios, 2004).

2.1. BRCA genes

Many reports suggested that germline mutations in the BRCA1 and BRCA2 genes were responsible for the majority of hereditary breast cancers, although more recent studies

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have demonstrated that mutations in the two genes only account for 25–28% of the family risk (Melchor & Benitez, 2013). However, it is expected that additional BRCA1/2 mutations remain undetected by the screening methods used today or the hereditary may be due to mutations in other genes. Women carrying a BRCA1 or BRCA2 germline mutation also have increased risk of developing ovarian cancer and fallopian tube cancer. In addition, BRCA2 mutation carriers also have increased risk of other cancer types such as male breast cancer, prostate cancer, pancreas cancer, gastrointestinal cancers and melanoma (Breast Cancer Linkage, 1999);(Thompson & Easton, 2004). In a large study by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), the median age of diagnosis was found be to be 40 years among BRCA1 and 43 years among BRCA2 mutation carriers (Mavaddat et al., 2012). Even though germline mutations in BRCA1 and BRCA2 confer high risk of breast and ovarian cancers, the penetrance of these genes is incomplete. The risk in BRCA1 and BRCA2 mutation carriers of developing breast cancer by the age of 70 is 45–87%. For ovarian cancer, the risk is 45–60% among BRCA1 mutation carriers and 11–35% among BRCA2 mutation carriers (A. Antoniou et al., 2003); (S. Chen & Parmigiani, 2007). However, the penetrance depends on several different factors, including the type of mutation and exogenous factors. Lifestyle factors such as physical exercise and lack of obesity in adolescence have been associated with significant delay in breast cancer onset (King, Marks, Mandell, & New York Breast Cancer Study, 2003).

BRCA1 and BRCA2 function as tumor suppressor genes and are important in maintenance of genomic stability through their role in DNA damage signaling and DNA repair. Both BRCA1 and BRCA2 are implicated in mediating repair of double strand breaks by homologous recombination (HR) by interactions with RAD51. Upon DNA damage, BRCA1 will associate with RAD51 and localize to the damaged region by which BRCA1 becomes phosphorylated. BRCA2 functions downstream of BRCA1 by complex-formation with RAD51. The primary function of BRCA2 is to facilitate HR (Roy, Chun, & Powell, 2012). Cells deficient for BRCA1 or BRCA2 are unable to repair double strand breaks by the error-free HR, resulting in repair by the error-prone non-homologous end-joining (NHEJ) pathway introducing chromosomal instability. During S-phase, the expression levels of BRCA1 and BRCA2 increase, indicating a function in maintaining genomic stability during the DNA replication process. Besides its role in HR, BRCA1 appears to have additional functions in DNA repair. BRCA1 is also part of the BRCA1-associated genome-surveillance complex (BASC), which includes ATM, RAD50, MRE11, and NBS1 and the mismatch repair proteins MLH1, PMS2, MSH2, and MSH6. BRCA1 has also been demonstrated to be involved in transcription-coupled excision repair,

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chromatin remodeling, and together with BARD1 in the ubiquitination process, by which proteins are tagged for degradation by the proteasome (Narod & Foulkes, 2004).

In all, 1,790 distinct mutations, polymorphisms, and variants in the BRCA1 gene and 2,000 in BRCA2 have been reported to the Breast Cancer Information Core (BIC) database, respectively (July 2014, research.nhgri.nih.gov/bic). Approximately 53–55% of these are private mutations, are only detected in single families. Mutations are distributed across the entire coding sequences. The most common types of pathogenic mutations are small deletions or insertions or nonsense mutations resulting in protein truncation leading to non-functional protein. Mutations affecting splice-sites as well as large genomic rearrangements are also observed in both genes (Thomassen, Gerdes, Cruger, Jensen, & Kruse, 2006). Missense mutations, silent mutations, and polymorphisms are also frequently identified; however, the clinical interpretation of their pathogenic potential is often difficult. Also, variants such as small in-frame insertions and deletions and possible splice-site alterations are problematic for precise cancer-risk estimation. Almost 1,800 distinct sequence variants found in BRCA1 and BRCA2 are classified as having unknown clinical significance (variants of unknown significance, VUS). To assess the clinical significance of individually rare sequence variants is challenging, as existing methods require a high number of occurrences of the specific variant. In 2009, the ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium was established with the purpose of evaluating the clinical significance of rare sequence variants by pooling genetic and associated clinical and histopathological information from a world-wide network of laboratories to gather sufficient data and resources to facilitate the classification of UVs (Spurdle et al., 2012). Recently, ENIGMA group have reported a useful tool to facilitate VUS analysis (Jhuraney et al., 2015).

The BRCA1 circos is a visualization resource that compiles and displays functional data on all documented BRCA1 missense variants (http://research.nhgri.nih.gov/bic/circos/). It aggregates data from all published BRCA1 missense variants for functional studies, from yeast assay to Embryonic Stem cells in vitro assays, offering various functionalities to search and interpret individual-level functional information for each BRCA1 missense variant.

A germline mutation in BRCA1 or BRCA2 only represents the first hit in the classical Knudson’s two-hit hypothesis; the second inactivating somatic mutation often involves deletion of the wild-type allele, known as loss of heterozygosity (LOH). LOH has been reported to be present in the majority (80%) of tumors arising from mutation carriers (N. Collins et al., 1995). Another somatic inactivation mechanism, epigenetic silencing by promoter methylation of BRCA1, has been reported in 9–13% of sporadic breast tumors, an up to 42% in non-BRCA1/2 hereditary breast tumors leading to reduced BRCA1

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expression (Tapia et al., 2008);(Larsen et al., 2014). In contrast, BRCA1 promoter methylations are rare in tumors from BRCA1 and BRCA2 mutation carriers, and BRCA2 promoter methylation in general is seldom observed in both sporadic and hereditary breast cancers (Dworkin, Spearman, Tseng, Sweet, & Toland, 2009); (N. Collins, Wooster, & Stratton, 1997).

2.2. Other breast cancer susceptibility genes

Several rare gene variants have been described to confer an increased risk of breast cancer, involving high-penetrance such as TP53, CDH1, PTEN, STK11, RAD51C, and RAD51D and the low/moderate-penetrance genes such as ATM, CHEK2, BRIP1, and PALB2, among others.

In general, most of these genes are involved in the maintenance of genomic integrity and DNA repair mechanisms, and many are associated with multiple cancer syndromes such as Li–Fraumeni syndrome (TP53), Cowden syndrome (PTEN), and Peutz–Jeghers syndrome (STK11/ LKB1) (Turnbull & Rahman, 2008);(Walsh & King, 2007). Furthermore, a number of common low-penetrance breast cancer alleles have recently been identified by genome-wide association studies (GWAS), including 10q26, 16q12, 2q35, 8q24, 5p12, 11p15, 5q11, and 2q33 (Easton et al., 2007).

2.2.1. High penetrant genes (low frequency)

TP53: TP53 is a tumor suppressor gene located on chromosome 17p13.1 that plays a major role in the regulation of cell growth (Menendez, Inga, & Resnick, 2009). TP53 germline mutations give rise to Li–Fraumeni syndrome (LFS), a rare predisposition cancer syndrome associated with approximately 1% of breast cancer cases. This gene predisposes for a wide spectrum of malignancies and patients with LFS, are mutated in TP53 in approximately 70%. Mutations are most commonly missense and small deletions (Varley, 2003). BC is the most frequent malignancy among femaleTP53 mutation carriers and represents up to 1/3 of all cancers in LFS families. Overall, although LFS is responsible for a small fraction of breast cancer cases, a woman with LFS has a breast cancer risk of 56% by the age of 45 and greater than 90% by the age of 60 (Olivier et al., 2003). Furthermore, recent studies have shown the majority of LFS-associated breast cancer cases are HER2/neu positive and nodes positive (Melhem-Bertrandt et al., 2012). Moreover it is suggested that the likelihood of the mutation in women <30 years of age and no family history is approximately 5–8% (Masciari et al., 2012).

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The latest NCCN guidelines issued in 2014 recommends testing of TP53 in all women with BC <35 years of age regardless of family history “either concurrently with BRCA1/2 testing or as a follow up test after negative BRCA1/2 testing”.

PTEN: PTEN is a phosphatase tensin homolog located on chromosome 10q23.3. PTEN is a major break for carcinogenesis due to its phosphatidylinositol-3-kinase (PI3K) phosphatase activity. PTEN precise function is not clear; however, dysfunctional PTEN leads to inability to activate cell cycle arrest and apoptosis, leading to abnormal cell survival (Shen et al., 2007). Germline mutations in PTEN are the cause of Cowden syndrome (CS) an autosomal dominant disorder with incomplete penetrance, which is characterized by increased risk of malignant transformation. Approximately 80% of affected individuals will have a detectable PTEN mutation that may include a missense, point, deletion, insertion, frame shift or nonsense mutation. Among the 20% of patients with no identifiable PTEN mutation, half may bear a mutation in PTEN promoter (Zhou et al., 2003). BC is the most common malignancy associated with CS. Although CS is responsible for <1% of BC cases, affected females have a lifetime risk of BC that reaches 50%, with an average age at diagnosis much younger than in sporadic BC (36–46 years old) (Liaw et al., 1997).

STK11: The SKT-11 gene is located on chromosome 19p13.3 and encodes for serine– threonine protein kinase11. It is designated as a tumor suppressor gene, participating in membrane bonding and apoptosis (S. P. Collins, Reoma, Gamm, & Uhler, 2000). Furthermore, it is a negative regulator of the mTOR pathway. Germline mutations in SKT-11 gene are the cause of Peutz–Jeghers syndrome (PJS), a rare autosomal dominant disorder characterized by multiple gastrointestinal polyps and mucocutaneous pigmentations of the lips, buccal mucosa and digits. Affected individuals are at increased risk for colorectal, breast, small bowel, pancreatic, gastric and ovarian cancer. Mutations of SKT-11 are detected in approximately 70–80% of patients with PJS, with 15% of them being deletions (Volikos et al., 2006). Women with PJS present with an increased risk for BC that reaches 50%. BC incidence has been shown to rise up to 32% by the age of 60, whereas it was only 8% by the age of 40 and a 20% risk for ovarian cancer (Lim et al., 2004).

CDH1: The E-Cadherin gene is a calcium dependent cell–cell adhesion molecule expressed in junctions between epithelial cells (Graziano, Humar, & Guilford, 2003). CDH1 germline mutations have been associated with hereditary diffuse gastric cancer (HDGC). Approximately 30% of families with HDGC due to CDH1 mutations also

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include women with lobular breast cancer (LBC). However, women with LBC without a family history of HDGC rarely harbor a CDH1 mutation. It has been estimated that the cumulative risk of LBC in female CDH1 mutation carriers from HDGC families reaches 39% at 80 years old (Pharoah, Guilford, Caldas, & International Gastric Cancer Linkage, 2001). In contrast to HDGC, missense mutations are the most frequent alterations, accounting for 60% of the cases described so far. Truncating mutations account for the remaining 40% (Kluijt et al., 2012); (Schrader et al., 2008).

Theoretically, women with LBC diagnosed before the age of 45 or those who have a family history of LBC and lack BRCA1/2 mutations, are eligible for CDH1 testing. However, family history of HDGC appears to be an important component. In a recent study it has been reported that among 408 cases of LBC without history of HDGC screened for CDH1 mutations, only three germline CDH1 mutations have been described (Schrader et al., 2011).

2.2.2. Moderate penetrant genes

CHEK2: CHEK2 gene encodes for a serine threonine kinase, which is activated in response to DNA double strand breaks (DSBs), contributing to signal transduction to downstream repair proteins. It has been also found to phosphorylate BRCA1, facilitating its role in DNA repair (Stracker, Usui, & Petrini, 2009). Certain CHEK2 mutations have been associated with BC. Mutation 110delC has been shown to increase BC risk by 2–3-fold. This mutation is particularly frequent in Northern European population, where it carries a lifetime risk of BC as high as 37%. Homozygotes have a 6-fold increased risk of BC (Adank et al., 2011). Carriers of CHEK2 mutations have an increased risk of bilateral or recurrent BC and tend to have a worse outcome (Mellemkjaer et al., 2008). This mutation is also associated with male BC. Although it is responsible for less than 1% of hereditary breast cancer syndromes, CHEK2 is an important gene, since its mutations are detected in approximately 5% of BC patients of non-BRCA families. The majority of CHEK2-associated BC is ER positive and therefore, might be subjective to chemoprevention with tamoxifen.

ATM: ATM is a multifunctional gene that plays a pivotal role in DSB repair and in cell cycle progression. Homozygous ATM mutation carriers suffer from ataxia telangiectasia (AT), a disorder characterized by cerebral ataxia, immunodeficiency and increased risk of certain malignancies, including BC (Ahmed & Rahman, 2006).

On the other hand, heterozygous carriers of ATM mutations have a 2-fold increased BC risk (Thompson et al., 2005) compared to general population. In women under the age of

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50, this risk reaches 5-fold. However, clinical utility of ATM genetic testing in heterozygotes is difficult to assess and there are no specific guidelines. Of note, decreased expression of ATM protein has been associated with aggressive features in sporadic BC (Bueno et al., 2014).

PALB2: PALB2 has emerged a new BC susceptibility gene. It is often described as a “binding partner and localizer of BRCA2”, contributing to DNA repair mechanism homologous recombination and tumor suppression (Xia et al., 2006). Classification of PALB2 as a BC susceptibility gene was based on data showing that 1.08% of individuals with hereditary BC negative for BRCA1/2harbor a monoallelic mutation in PALB2, which confers a 2-fold high risk (Rahman et al., 2007). In a recent study by Fernandes et al. that included approximately 1500 patients with familial BC, the prevalence of PALB2 mutations was 0.8%, with the majority occurring in high risk patients (Fernandes et al., 2014). Although, based on the above studies, PALB2 is characterized as a rare, intermediate-risk gene with regards to inherited genetic susceptibility to BC, a recent study that included 154 families who had mutations in the gene demonstrated a breast cancer risk of approximately 35% (A. C. Antoniou et al., 2014).

BRIP1: BRIP1 encodes a protein that was identified as the binding partner of BRCA1. Similar to PALB2, truncating mutations of the gene have been detected in BRCA1/2 negative BC families and the relative BC risk has been estimated to be approximately 2-fold (Seal et al., 2006). Interestingly, BRIP1 missense mutations have been found in high risk Jewish women who are BRCA1/2 negative (Catucci et al., 2012).

RAD51c: RAD51C is an integral component of FA/BRCA pathway and plays an important role in DSB repair through Homologous Recombination (HR). Homozygous mutations in RAD51C are associated with a FA phenotype, whereas heterozygous mutations have been identified in breast and ovarian cancer (OC) families. Initially, RAD51C was studied as a possible BC/OC susceptibility gene in 1100 high risk BRCA1/2 negative German families. In this study, six monoallelic RAD51C mutations were found in 1.3% of families with BC and OC. Interestingly, no pathogenic mutations were identified in high risk families with BC only (Meindl et al., 2010). Subsequently, several studies confirmed the occurrence of RAD51C predominantly in BC and/or OC families (Blanco et al., 2014), (Osorio et al., 2012). The inclusion of RAD51C gene in routine clinical testing is a matter of debate. In a recent study, no RAD51C mutation was found in 410 patients from BRCA1/2 negative families with at least one case of OC who were referred for genetic testing (De Leeneer et al., 2012). It is therefore suggested that mutations

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in RAD51C gene occur in a low frequency, with an exception of some founder populations. On the other hand, RAD51C carcinomas are HR deficient and might benefit from new targeted therapies, such as PARP inhibitors. In this context, further genome-wide studies in high-risk families are warranted for the identification of RAD51C mutation carriers.

RAD51d: RAD51D is also an important co-factor of DSB repair mechanism. RAD51D protein forms a complex with RAD51C, RAD51B and XXRC2, which binds to single-stranded DNA and plays an important role in response to DNA damage.

RAD51D has emerged mainly as an OC susceptibility gene (Osher et al., 2012). Recently, a study that analyzed 841 BRCA negative patients either from BC/OC families or with early onset BC/OC identified three RAD51D mutations in four BC/OC families with only one OC case (Gutierrez-Enriquez et al., 2014).

NBS, MRE11, RAD50: The MRN complex, consisting of MRE11, RAD50 and NBS1 proteins plays multiple key roles in DSB repair and maintenance of genomic integrity. Germline homozygous mutations in NBS1 and MRE11 cause the rare autosomal disorders Nijmegen Breakage Syndrome (NBS) and Ataxia Telangiectasia-like disorder (A-TLD), respectively (Rupnik, Grenon, & Lowndes, 2008).

Pathogenic mutations have been found in all MRN genes. In a recent meta-analysis that included 9 case control studies, NBS1 mutation 657del5 has been associated with significant BC risk. There is less supporting evidence that RAD50 and MRE11might act as BC susceptibility genes. (Heikkinen, Karppinen, Soini, Makinen, & Winqvist, 2003); (Bartkova et al., 2008). In an attempt to assess the role of rare MRN variants as intermediate-risk BC susceptibility alleles, a recent study has performed a mutation analysis of MRN genes in a large number of early-onset BC cases. Interestingly, this study confirmed that rare missense substitutions and less frequently, protein-truncating variants of MRN genes confer a 2–3-fold increased risk of BC. However, this study has limitations, mainly because the three genes have been evaluated as if they constitute a single gene (Damiola et al., 2014).

BARD1: BARD1 (BRCA1-associated RING domain 1) encodes a protein that shares structural and functional similarities with BRCA1. It was initially identified as a protein interacting with BRCA1 in DSB repair and apoptosis initiation. Initially, only a small number of missense mutations and variants with unclear biological effect were identified.

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Subsequently, several studies have found deleterious mutations in high risk BRCA negative BC families.

On the other hand, as a BRCA1 interactor, BARD1 has been implicated in modification of BRCA1/2 associated BC risk. Although a number of studies have been controversial, a recent study that included a large number of BRCA1/2 mutation carriers has failed to support a role for BARD1 variation as a modifier of BC risk in this particular population.

FANCM: As previously noted, FA is a rare recessive genetic disorder, characterized by a high incidence of leukemias and solid tumors. To date, there are 13 FA genes identified, each one corresponding to one complementation group. Several FA genes are well known high or intermediate risk BC susceptibility genes (BRCA2, PALB2, BRIP1), which makes all members of the FA pathway attractive BC candidate genes. FANCM is a FA gene that plays a crucial role in DNA repair process (Wang, 2007).

In a recent study, the c.5101C > T FANCM nonsense mutation has been associated with BC risk in a Finnish population. Importantly, the highest frequency of the mutation was observed in triple-negative BC patients. Apparently, further studies in different populations are essential for the evaluation of BC risk associated with the mutation (Kiiski et al., 2014).

Low and moderate penetrant genes/loci can only explain a minor fraction of the remaining non-BRCA1/2 families that show high incidence of breast cancer. Despite intensive research, genetic linkage analysis, and most recently, next-generation sequencing (NGS) exome studies have failed to identify other common high-penetrance breast cancer sus-ceptibility genes, such as BRCA1 and BRCA2. A Genome-wide association studies (GWAS) and the recent international collaborative analyses have confirmed 77 common polymorphisms individually associated with breast cancer risk, which add a further 14% (Melchor & Benitez, 2013), (Michailidou et al., 2013). Evidence from an Illumina collaborative oncological gene environment study (iCOGS) experiment suggests that further single nucleotide polymorphisms (SNPs) may contribute at least 14% to the heritability, leaving only approximately 50% of hereditary cases as unexplained. No single high-penetrance gene is likely to account for a larger fraction of the remaining familial aggregation (Snape et al., 2012);(Smith et al., 2006). Instead, the remaining predisposition is expected to be a mixture of rare high-risk variants and polygenic mecha-nisms involving more common and/or rare low-penetrance alleles or rare moderate-penetrance genes, acting in concert to confer a high breast cancer-risk (Turnbull & Rahman, 2008).

Patients with breast cancer should be offered genetic testing, according to consensus guidelines, when they present with a suspicious family history, specific high-risk disease

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features (triple negative or bilateral breast cancer) or at a young age (Khatcheressian et al., 2013). However, the implementation of multigene panel testing has originated new issues regarding patient eligibility for gene testing beyond BRCA. According to National Comprehensive Cancer Network (NCCN) guidelines, gene panels are aimed at individuals who are tested negative for BRCA1/2 and for those whose family pedigree is suggestive of more than one hereditary syndrome.

3. TRIPLE NEGATIVE BREAST CANCER

Despite of the molecular ad expression efforts to better characterize the heterogeneity of breast tumors, the hormone evaluation is still the major feature considered for the immediate classification of a breast tumours and guide clinical management.

Triple-negative breast cancer (TNBC) is defined by a lack of significant expression of the estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) (L. Carey, Winer, Viale, Cameron, & Gianni, 2010) and accounts for 15% to 20% of newly diagnosed breast cancer cases (Metzger-Filho et al., 2012). Patients with TNBC are generally younger than the overall population of breast cancer patients (K. R. Bauer, Brown, Cress, Parise, & Caggiano, 2007), and they more frequently have larger and higher-grade tumors (Rakha et al., 2007).

Different population-based studies have demonstrated a higher prevalence of TNBC among women of African American or black ethnicity (Morris et al., 2007),(Lund et al., 2009). A clear correlation has been made between young age at diagnosis and TNBC. In a large population-based study involving 6,370 patients, women with TNBC were significantly more likely to be under the age of 40 years (K. R. Bauer et al., 2007).

TNBC is known to have an early peak of recurrence between the first and third year after diagnosis followed by a marked decrease in the recurrence rate in subsequent years and less frequent relapse after 8 years (Dent et al., 2007). Worse survival outcomes have been reported for TNBC tumors when compared with hormone receptor–positive tumors in several studies (Dent et al., 2009). Moreover, TNBCs have a site-specific distribution of recurrence. In a retrospective analysis of 1,608 patients, a greater proportion of TNBCs had visceral metastasis as first site of disease recurrence when compared with other types of BC (Dent et al., 2009). Despite these common features recognized in TNBC, there is notable diversity within the group.

Histologic variability provides one example of such, with invasive ductal, metaplastic and medullary breast cancers coexisting in this patient population (Reis-Filho & Tutt, 2008).

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Furthermore, the TNBC subtype does not directly correspond to a single molecular breast cancer subgroup (Rakha et al., 2009). Though most fit into the category of basal-like cancers, these groups are overlapping rather than synonymous.

Defining TNBC through the absence of predictive biologic markers is limitating and could explain the heterogeneity of behavior and clinical outcome of TN patients. Subclassifications of TNBC based on the presence of biomarkers, gene signatures, and BRCA dysfunction have been proposed.

3.1. Molecular characterization of TNBC

In 2011 Lehmann group (Lehmann et al., 2011) performed a comprehensive and fundamental molecular analysis to better understand the basis of TBNC and to explore the true heterogeneity of this subgroup. To identify global differences in gene expression (GE) between TNBC subtypes, they compared 14 publicly available breast cancer microarray datasets, all generated on Affimetrix microarray. After the selection of set of 2188 genes significantly enriched in expression to determine the top canonical pathways associated, 337 TNBC were classified in 6 stable clusters: basal-like1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M),mesenchymal stem–like (MSL); luminal androgen receptor (LAR). Other 49 tumours were classified into an “unstable” group. BL1 subtype are heavily enriched in cell cycle and cell division components and pathways (cell cycle, DNA replication reactome, G2 cell-cycle pathway, RNA polymerase, and G1 to S cell cycle). The annotations are supported by the expression of genes associated with proliferation, such as AURKA, AURKB, CENPA, CENPF, BUB1, TTK, CCNA2, PRC1, MYC, NRAS, PLK1, and BIRC5. Elevated DNA damage response (ATR/BRCA) pathways accompany the proliferation pathways in the BL1 subtype. Increased proliferation and cell-cycle checkpoint loss are consistent with the elevated expression of the DNA damage response genes observed (CHEK1, FANCA, FANCG, RAD54BP, RAD51, NBN, EXO1, MSH2, MCM10, RAD21, and MDC1).

Moreover the proliferative nature of this subtype is supported by the finding of high Ki-67 mRNA expression and nuclear Ki-67 staining as assessed by IHC analysis. The basal like tumours are Ki67 positive for 70% of the cases, while other subtypes in around 40%. Enrichment of proliferation genes and increased Ki-67 expression in basal-like TNBC tumors suggest that this subtype would preferentially respond to antimitotic agents such as taxanes (paclitaxel or docetaxel) (J. A. Bauer et al., 2010).

This is notable when comparing the percentage of patients achieving a pathologic complete response (pCR) in 42 TNBC patients treated with neoadjuvant taxane in 2 studies (J. A. Bauer et al., 2010; Juul et al., 2010). In these combined studies, TNBC

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patients whose tumors correlated to the basal-like (BL1 and BL2) subtype had a significantly higher pCR (63%; P = 0.042) when treated with taxane-based therapies as compared with mesenchymal-like (31%) or LAR (14%) subtypes.

The BL2 subtype displays unique gene ontologies involving growth factor signaling (EGF pathway, NGF pathway, MET pathway, Wnt/β-catenin, and IGF1R pathway) as well as glycolysis and gluconeogenesis. Likewise, the BL2 subtype is uniquely enriched in growth factor receptor such as EGFR, MET, and EPHA2. This subtype has features suggestive of basal/myoepithelial origin as demonstrated by higher expression levels of TP63 and MME (CD10).

The IM subtype is enriched of immune cell processes gene expression. These processes include immune cell signaling (TH1/TH2 pathway, NK cell pathway, B cell receptor signaling pathway, DC pathway, and T cell receptor signaling), cytokine signaling (cytokine pathway, IL-12 pathway, and IL-7 pathway), antigen processing and presentation, and signaling through core immune signal transduction pathways (NFKB, TNF, and JAK/STAT signaling).

Immune signaling genes within the IM subtype substantially overlap with a gene signature for medullary breast cancer, a rare, histologically distinct form of TNBC that despite its high-grade histology is associated with a favorable prognosis (Bertucci et al., 2006). The Mesenchymal (M) subtype is enriched in components and pathways involved in cell motility (regulation of actin by Rho), ECM receptor interaction, and cell differentiation pathways (Wnt pathway, anaplastic lymphoma kinase (ALK) pathway, and TGF-β signaling).

The MSL subtype shares similar profile of the M subtype, but differ for enhanced processes linked to growth factor signaling pathways that include inositol phosphate metabolism, EGFR, PDGF, calcium signaling, G-protein coupled receptor, and ERK1/2 signaling as well as ABC transporter and adipocytokine signaling.

The prevalence of cell differentiation and growth factor signaling pathways is illustrated by expression of TGF-β signaling pathway components, epithelial-mesenchymal transition– associated (EMT-associated) genes and decreased E-cadherin (CDH1) expression. The MSL subtype is also enriched in genes involved in angiogenesis, including VEGFR2. Moreover in part overlap with IM subtype for the implication of immune signaling.

One interesting difference between the M and MSL subtypes is that the MSL subtype expresses low levels of proliferation genes and higher levels of stem cells genes (ABCA8, PROCR, ENG, ALDHA1, PER1, ABCB1, TERF2IP BCL2, BMP2, and THY1), numerous HOX genes (HOXA5, HOXA10, MEIS1, MEIS2, MEOX1, MEOX2, and MSX1), and mesenchymal stem cell–specific markers (BMP2, ENG, ITGAV, KDR, NGFR, NT5E, PDGFRB, THY1, and VCAM1).

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The M and MSL groups share similar features with a highly dedifferentiated type of breast cancer called metaplastic breast cancer, which is characterized by mesenchymal/sarcomatoid or squamous features and is chemoresistant (Gibson, Qian, Ku, & Lai, 2005).

The MSL subtype also displays low expression of claudins 3, 4, and 7, consistent with a recently identified claudin-low subtype of breast cancer (Prat et al., 2010).

Finally, the gene expression in the LAR group is the most differential among TNBC subtypes. This subtype is ER negative, but gene ontologies are heavily enriched in hormonally regulated pathways including steroid synthesis, porphyrin metabolism, and androgen/estrogen metabolism. AR (androgen receptor) mRNA was highly expressed together with numerous downstream AR targets and coactivators. This subtype showed high IHC staining for AR also. Tumors in the LAR subtype display luminal GE patterns, with FOXA1, KRT18, and XBP1 among the most highly expressed genes.

Breast cancers can be classified as luminal or basal-like, dependent on their expression of different cytokeratins. TNBC tumor subtypes display differential expression of both basal-like cytokeratins (KRT5, KRT6A, KRT6B, KRT14, KRT16, KRT17, KRT23, and KRT81) and luminal cytokeratins (KRT7, KRT8, KRT18, and KRT19) across the subtypes. Only the tumors within the LAR subtype lacked basal cytokeratin expression and expressed high levels of luminal cytokeratins and other luminal markers.

In the same work, a TNBC cell line panel was used to assess differential response to several agents targeting different pathway; PARP, AR, Src, and PI3K/mTOR signaling (Neve et al., 2006). BL1/BL2 cell lines, when treated with agents targeting DNA repair, especially platinum compounds, have in general a good response. PARP inhibitors treatment (olaparib and veliparib) showed instead more variability in response among cell lines. Cell lines expressing high levels of AR mRNA and protein, are sensitive to the AR antagonist bicalutamide and to an Hsp90 inhibitor, since this chaperonine is essential for AR protein folding. Importantly, AR status in TNBC patients may represent a molecular marker for preselection of patients for antiandrogen therapy.

GE analysis of the mesenchymal-like subtypes demonstrated enrichment in the expression of genes in EMT and cell motility pathways. Since the non-receptor tyrosine kinase Src plays critical roles in cell migration, the authors investigated the effect of the Src inhibitor dasatinib on the panel of TNBC lines. Cell lines belonging to the mesenchymal-like subtypes (M and MSL) were more sensitive to dasatinib.

Activating mutations in PIK3CA are the most frequent genetic event in breast cancer (Samuels et al., 2004): when TNBC cell lines were treated with the dual PI3K/mTOR inhibitor NVP-BEZ235, mesenchymal-like and LAR TNBC cell lines were more sensitive to

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NVP-BEZ235 compared with basal like cell lines suggesting that deregulation of the PI3K pathway is important for these subtype.

3.2. Genomic features of TNBC

In the most comprehensive integrated genomic study by the Cancer Genome Atlas Network, basal-like tumors showed a high frequency of TP53 mutations (80%) which, when combined with inferred TP53 pathway activity, suggests that loss of TP53 function occurs within most, if not all, basal-like cancers. In addition to loss of TP53, loss of RB1 and BRCA1 are Basal-like features (Herschkowitz, He, Fan, & Perou, 2008).

PIK3CA was the next most commonly mutated gene (~9%); however, defective PI3K pathway activity, whether from gene (Saal et al., 2008), protein (Stemke-Hale et al., 2008) or high PI3K/AKT pathway activities, was highest in Basal-like cancers. Alternative means of activating the PI3K pathway in Basal-like cancers likely includes loss of PTEN and INPP4B and/or amplification of PIK3CA.

A recent paper from Shah (Shah et al., 2012) and collaborators described exome sequencing of 102 TNBC, and analyzed the clonal spectrum of somatic mutations in this group.

The author searched for mutation enrichment patterns in three ways; by single gene mutation frequency over multiple cases; by the mutation frequency over multiple members of a gene family and by correlating mutation status with expression networks. First, similar to other studies (Langerod et al., 2007) p53 is the most frequently mutated gene 62% of basal TNBC and 43% of non-basal TNBC cases harboring a validated somatic mutation. Frequent mutations in PIK3CA at 10.2%, USH2A (Ushers syndrome gene, implicated in actin cytoskeletal functions) at 9.2%, MYO3A at 9.2%, PTEN and RB1 at 7.7%, SYNE1/2 at 9% and BRCA2 (3%) were observed. Considering background mutation rates, TP53, PIK3CA, RB1, PTEN, MYO3A and GH1 showed evidence of single gene selection. Several other well-known oncogenes (BRAF, NRAS, ERBB2, and ERBB3) have rare mutations.

Moreover, the impact of gene family involvement through sparse mutation patterns in functionally connected genes was evaluated. TP53 related pathways along with chromatin remodeling, PIK3 signaling, ERBB2 signaling, integrin signaling and focal adhesion, WNT/cadherin signaling, growth hormone and nuclear receptor co-activators, ATM/Rb related pathways were the most affected. Also MYO3A, a cytoskeleton motor protein involved in cell shape/ motility, was related to several pathways upstream and downstream of integrin signaling. The mutated genes stretch from extracellular matrix interactions (ECM) (laminins, collagens), ECM receptors (integrins), several proteins