Familial non-BRCA1/2 breast cancers have been shown to comprise a very heterogeneous group of cancers with respect to histopathological characteristics. It has been established that these cancers are often of lower grade compared to sporadic cancers, but with IHC profiles similar to sporadic cancers.33,67 Results from studies on breast cancers from CHEK2 mutation carriers have been inconsistent. Two studies found tumors from CHEK2 carriers to be more frequently ER-positive, while one study reported no difference between carriers and non-carriers.68–70

Clinical Implications of Hereditary Breast Cancer

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Genetic counseling and risk assessment

Familial breast cancer cases are today identified by evaluation of a family pedigree showing breast and ovarian cancer cases. Presymptomatic testing for pathogenic mutations in BRCA1 and BRCA2 has become widespread during the last decade and is now used in the counseling of families with a strong history of breast and ovarian cancers and for estimating the cancer-risk of healthy family members.71,72 Mutation carriers are recommended intensive surveillance programs of breast and ovaries and offered prophylactic surgery. Prophylactic mastectomy has been shown to lower the risk of breast cancer among mutation carriers. Furthermore, the women are offered prophylactic bilateral salpingo-oophorectomy (BSO) after child-bearing age to lower their risk of developing both breast and ovarian cancers, even further.73–76 Just as important is the fact that if no mutation is detected in a family member of a known BRCA mutation-carrying family, the individual’s risk of cancer is equal to that of the general population. Genetic testing of BRCA1 and BRCA2 is often laborious and complex because of the size of the genes. Though newer methods such as targeted NGS have improved the sensitivity, it is likely that a fraction of the mutations remains undetected. In addition, a recent Polish study has demonstrated that up to half of BRCA1 and BRCA2 mutation carriers lack an obvious family history and will therefore not be identified by current selection criteria.77 As described above, in >70% of families with aggregation of breast and ovarian cancers, pathogenic mutation in BRCA1 or BRCA2 cannot be identified. Consequently, the cancer-risk assessment becomes less accurate because of lack of presymptomatic testing options. In addition, unclassified sequence variants are often detected in the coding or non-coding regions of BRCA1 and BRCA2. The clinical significance of such variants is often uncertain and therefore remains a challenge in counseling and clinical management. Confident classification of these variants as well as identification of more high-risk alleles would provide a more accurate risk assessment and improve genetic counseling dramatically for this group of families.

Novel targeted treatment strategies for hereditary breast cancer

As inactivation of BRCA1 and BRCA2 leads to impaired HR DNA repair, it has been investigated whether mutation carriers would be sensitive to DNA cross-lining agents such as platinum salts, as they introduce double-strand DNA breaks. Very encouraging, high response rates to cisplatin have recently been demonstrated in patients with BRCA1 germline mutations.78,79

A novel potential targeted treatment strategy for breast cancer patients with BRCA1 or BRCA2 germline mutations that recently has emerged is the use of poly(ADP-ribose) polymerase (PARP) inhibitors. PARP1 is involved in base excision repair (BER) mechanisms, and inhibition of PARP1 leads to spontaneous single-strand DNA lesions. During DNA replication, these DNA nicks can degenerate to form double-strand breaks during DNA replication because of collapsed replication forks, which activate HR repair. As described previously, inactivation of BRCA1 or BRCA2 leads to impairment of the HR DNA repair pathway, sensitizing the cancer cells to PARP1 inhibition. Disabling both pathways results in chromosomal instability, cell cycle arrest, and apoptosis. Cell survival assays have showed that cells with BRCA1 or BRCA2 inactivation were highly sensitive to PARP-inhibitors.80–82 Early clinical trials demonstrated significant efficiency of PARP-inhibitors in BRCA-deficient breast and ovarian cancers.83–85 Because of the phenotypic similarities between BRCA1-associated and TN cancers, a phase 2 study has been conducted to test the efficiency of iniparib (in addition to standard chemotherapy) in metastatic TN cancers, with promising results.86 However, the clinical phase 3 trial failed to show significant improvements. BRCA1 and BRCA2 statuses were not assessed; it is therefore not possible to conclude whether a subgroup of BRCA1– and BRCA2-deficient tumors would have benefited from the treatment. This emphasizes the need for more refined methods of selecting patients who will respond to PARP-inhibitors.87 If targeted therapies against BRCA1– and BRCA2-deficient tumors such as cisplatin or PARP-inhibitors enter clinical practice, genetic testing becomes increasingly important to identify patients with BRCA-deficient tumors.

Molecular Profiling of Hereditary Breast Cancer

During the last decades, the microarray technology has been used extensively to study breast cancer biology. Numerous studies have used the platform for transcriptome and genomic profiling analyses, and recently, studies of genome-wide microRNA and methylations profiling have emerged.88–93 Microarray-based molecular profiling studies have uncovered the complexity and heterogeneity of breast cancer and established that breast cancer is not a single disease entity but rather a group of distinct disorders.

Although an exhaustible number of microarray profiling studies of breast cancers have been published, few studies analyzing hereditary breast cancers exist. Small sample sizes are a common denominator of most of the early studies that have been published. High-quality RNA and DNA are a prerequisite for conducting microarray analysis, wherefore access to frozen tumor tissue is necessary. The small study numbers can be explained by the fact that hereditary breast cancers account for only a minor fraction of breast cancer cases and access to frozen tumor tissue is often limited. Recently, several studies on larger cohorts using newer generations of microarray platforms have been published. In the following, the early and the more recent studies will be discussed. Tables 1 and ​and22 represent overviews of the published transcriptome profiling studies and genomic profiling studies of hereditary breast cancers, respectively.

Table 1. Published microarray RNA profiling studies of hereditary breast cancers. Numbers refer to number of BRCA1, BRCA2, non-BRCA1/2, and sporadic breast cancers primary tumors analyzed. Studies with sample overlap are listed together

Hedenfalk et al (2001) 7 8 7 22 cDNA arrays (6,512 clones)   94
van’tVeer et al (2002) 18 2 78 98 Oligo-array (Rosetta) (24,479 probes)   96
Hedenfalk et al (2003) 16 16 cDNA arrays (6,512 clones)   98
Bane et al (2009) 7 6 13 UHN human 19K cDNA arrays (19,008 clones)   117
Waddell et al (2010) 19 20 25 75 Illumina Human-6 v. 2 BeadChips (46,000 probes)   105
Waddell et al (2010) 18 19 29 76 Illumina Whole Genome-DASL (24,000 trans.) 6 ATM V2424G 109
Jönsson et al (2010)
Jönsson et al (2012)
34 39 195 309 577 Operon Oligo-arrays (26,819 probes)   106,112
Fernández-Ramires et al (2009)
Fernández-Ramires et al (2011)
13 14 22 49 CNIO human cDNA Oncochip v2 (7,237 clones)   108,111
Dudaladava et al (2006)
Lisowska et al (2011)
12 1 8 14 35 Affymetrix HG U133 Plus 2.0 Chip (47,000 trans.)   189,97
Nagel et al (2011) 47 6 76 129 Affymetrix HG U133 Plus 2.0 Chip (47,000 trans.) 26 CHEK2 1100delC 110
Larsen et al (2013)
Larsen et al (2014)
33 22 70 128 253 Agilent SurePrint G3 (60,000 probes)   34,107

Table 2. Published array-CGH studies of hereditary breast cancers. Numbers refer to number of BRCA1, BRCA2, non-BRCA1/2, and sporadic breast cancers primary tumors analyzed. Studies with sample overlap are listed together

Hedenfalk et al (2003) 8 8 cDNA arrays (11,367 clones) 98
Jönsson et al (2005) 14 12 26 52 BAC array (5,000 clones) 113
Waddell et al (2010a) 11 9 14 34 Illumina CNV370 duo beadarrays (370,000 SNPs) 105
Jönsson et al (2010) 17 31 126 172 344 BAC array (32,000 clones) 112
Melchor et al (2007)
Melchor et al (2008)
19 24 31 19 93 BAC array (4,134 clones) 114
Joosse et al (2009)
Joosse et al (2012)
32 57 89 48 226 BAC/PAC array (3,500 clones) 115

Gene-expression profiling of hereditary breast cancer

The early studies

The first microarray-based study of hereditary breast cancers was published by Hedenfalk et al in 2001.94 With an underlying hypothesis that germline BRCA1/2 mutations have a profound impact on the gene-expression pattern, they analyzed tumors from BRCA1 (n = 7) and BRCA2 (n = 8) mutation carriers and sporadic tumors (n = 7). The authors identified 51 genes whose variation in expression best differentiated the three groups of cancers. Two different classification schemes were used for classification of BRCA1 and BRCA2, one for separating BRCA1 tumors from non-BRCA1 tumors and another for separating BRCA2 from non-BRCA2 tumors. All seven BRCA1 tumors were correctly classified, while one non-BRCA1 tumor was misclassified as a BRCA1 tumor. Further investigations revealed hypermethylation of the BRCA1 promoter in the single misclassified tumors. Distinguishing BRCA2 tumors from non-BRCA2 tumors were less successful, predicting 5 out of 8 BRCA2 tumors correctly and 13 out of 14 tumors withoutBRCA2 mutations correctly. Furthermore, they identified 176 genes with distinct expression betweenBRCA1 and BRCA2 tumors with genes involved in DNA repair and apoptosis pathways to be higher expressed in BRCA1 relative to BRCA2 tumors. The study served as a proof-of-concept study; however, concerns have been raised because of the small sample size and a lack of appropriate matching according to clinical parameters such as ER-status, known to have profound impact on the gene-expression pattern.95 In later BRCA1 classification studies by van’tVeer et al and Lisowska et al, samples were matched according to ER-status prior to BRCA1 classification.96,97 Lisowska obtained only near-random classification while van’t Veer achieved high accuracy (95%) when classifying 17 ER- BRCA1 tumors and 21 ER-sporadic tumors. Based on absolute correlation coefficients they identified 100 optimal marker genes for use in a leave-out one cross validation (LOOCV) classification algorithm. Again, promoter hypermethylation was demonstrated in a sporadic tumor classified as BRCA1-like. The main concern has been that the genes used for classification were identified using all samples, including also the left-out ones, wherefore the classification performance may be biased because of possible information leakage. Notably, no gene overlap was seen between the gene signatures identified by van’tVeer et al and Hedenfalk et al.