Only few years after their first pioneering study, Hedenfalk et al analyzed the gene-expression patterns of 15 primary tumors and 1 metastatic tumor from eight hereditary breast cancer families where no BRCA1/2mutations could be detected (non-BRCA1/2).98 Based on class discovery analysis, the authors were able to identify 2 distinct and homogenous subgroups among the 16 tumors. Sixty genes were found to be differentially expressed between the two subgroups. Of these, ribosomal-related genes were overrepresented. Notably, all families in which multiple family members were examined remained intact when divided into subgroups. The authors noted that these subgroupings could reflect different underlying genetic predispositions; however, they never validated their observation.


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Molecular subtypes of hereditary breast cancer

A pioneering study in 2000 by Perou and colleagues was the first to show that breast cancers can be divided into subtypes distinguished by differences in their gene-expression profiles.99 In subsequent studies, these observations have been repeated in larger sample series, and it is now established that at least four intrinsic molecular subtypes exist, designated basal-like, luminal A (lumA), luminal B (lumB), and HER2-enriched. These subtypes correspond broadly to histopathological characteristics and correlate to clinical outcome. Basal-like cancers are mostly high-grade and TN tumors (ER-negative, PR-negative, and HER2-negative), while HER2-enriched cancers often show amplification and high expression of the HER2 (ERBB2) gene and a series of genes located in the ERBB2 amplicon. Cancers of the luminal subtypes are ER-positive. In addition, lumA is low-grade and PR-positive tumor, while lumB is often high-grade cancer and to some extent PR-negative. The intrinsic subtypes are found to be highly conserved across different microarray platforms and across tumors from distinct ethnic populations.100–104

The first study to investigate molecular breast cancer subtypes in association with hereditary breast cancers was conducted by Waddell et al in 2010.105 Their study group comprised BRCA1 (n = 19), BRCA2 (n = 30), and non-BRCA1/2 (n = 25) hereditary breast cancers. Subtype prediction by the PAM50 classifier revealed that 74% BRCA1 tumors were basal-like, 73% of BRCA2 tumors were luminal (equally distributed among lumA and lumB), and 52% of non-BRCA1/2 tumors were lumA. These observations has subsequently been confirmed, first by Jönsson and colleagues in a large cohort comprising BRCA1 (n = 34), BRCA2 (n = 39), and non-BRCA1/2 (n = 195) and more recently by our group in a sample series of 33 BRCA1, 22 BRCA2, and 70 non-BRCA1/2 samples.106,107 Strong associations between basal-like andBRCA1-associated breast cancers (85% and 61%), as well as lumB and BRCA2-associated cancers (56% and 73%) were observed in both studies. Fernández-Ramires et al analyzed 14 tumors from BRCA1 mutation carriers of which 9 were ER-negative.108 In the study, they were able to substratify the ER-negative tumors into two groups with slight differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors. These subgroups showed some association with the BRCA1 mutation type (protein truncating versus missense).

In a recent study, we analyzed 70 non-BRCA1/2 cancers and found that the distribution of subtypes was markedly different from the distribution found among BRCA1/2 mutation carriers.34 All five molecular subtypes were found within the non-BRCA1/2 tumor class. The majority of non-BRCA1/2 tumors were mainly classified as lumA (47%) or lumB (26%), while fewer were basal-like (13%), HER2-enriched (10%), and normal-like (4%). The distribution of molecular subtypes among the non-BRCA1/2 tumors was found to be similar to the distribution of sporadic tumors; although a tendency toward more non-BRCA1/2 tumors was basal-like while fewer were classified as lumB. These numbers were highly concordant with the previous studies.105,106 From 11 families, tumor material from more than one affected individual was included in the study. Surprisingly, we found that members of the same family shared the same tumor subtype in 8 of the 11 families. Three of the families were characterized by lumA tumors only (including the three-case family), three families had lumB tumors, one had HER2-enriched tumors, and one had only basal-like tumors. To confirm our observations, we subtyped the samples of Hedenfalk et al98 consisting of tumors from a total of five high-risk families. The patterns of aggregation of molecular subtypes within families were confirmed in four of the families. These findings could indicate an underlying common genetic basis in these families. The family members may carry an inherited susceptibility not just to breast cancer but to a particular subtype of breast cancer. In support of the “same gene—same subtype” hypothesis, in another study by Waddell et al, the authors noticed that all tumor biopsies from ATMmutation carriers included in their study were classified as luminal (four lumB and two lumA).109 Within a large non-BRCA1/2 family, four out of five family members were classified as lumA. Furthermore, a study by Nagel et al included a group of 26 breast tumors from CHEK2*1100delC carriers; all were classified as luminal tumors (8 lumA and 18 lumB).110 The cancer-risk and tumor subtype may either be a result of private mutations in high-penetrance genes or be a result of multiple low/moderate-penetrant genes acting in concert. In light of these findings, future genetic analysis may benefit from subgrouping families into molecularly homogeneous subtypes in order to search for new high-penetrance susceptibility genes.

In a study by Fernández-Ramires et al of 14 non-BRCA1/2 hereditary breast cancers, 2 subgroups very similar to the intrinsic lumA and lumB subtypes were identified.111 By comparing the lumA non-BRCA1/2with sporadic tumors of the same subtype, they identified a set of 157 deregulated genes of which 21 could be linked to DNA damage response canonical pathway. No differences between lumB non-BRCA1/2 and its sporadic counterpart were detected.

BRCA1/2 classification within tumor subgroups

Because of the strong association between BRCA1/2mutation status and molecular subtypes, we choose to stratify tumor samples according to molecular subtype prior to classification in order to avoid potential confounding effects.107 By conducting BRCA1-versus-sporadic classification within only basal-like samples using support vector machine (SVM)-based LOOCV, we found that basal-like BRCA1 tumors could successfully be distinguished from sporadic tumors of the basal-like subtype with high accuracy (balanced accuracy: 83%, sensitivity: 85%, specificity: 80%). Likewise, BRCA2 classification was performed among lumB tumors, as the vast majority of BRCA2tumors were of the lumB subtype. This resulted in a balanced accuracy of 89% (sensitivity: 88%, specificity: 90%). We sought to validate our subtype-specific BRCA1/2 signatures in a set of independent samples. Using the data sets of van’tVeer and Jönsson studies,96,112 we validated our BRCA1/2 signatures. Using the two independent data sets, we were able to successfully validate both the BRCA1 consisting of 100 genes and BRCA2 signature of 110 genes with high accuracies (82–87%). Our results support the hypothesis that BRCA1-associated tumors represent a distinct biological subgroup among basal-like tumors, which has been a topic of debate. Likewise, BRCA2-associated tumors pose a distinct subgroup among lumB tumors. Next, we applied the subtype-specific signatures to predict BRCA1 and BRCA2associations among non-BRCA1/2 tumors, respectively.34 We found that seven out of nine basal non-BRCA1/2 samples were BRCA1-like. In a similar approach using our lumB BRCA2 signature, we identified 7 out of 18 (39%) lumB non-BRCA1/2 tumors to be BRCA2-like. This could indicate BRCA1/2 deficiencies in these tumors, either caused by an inactivating mutation not detected by current methods or epigenetic silencing such as promoter hypermethylation of the BRCA1/2 genes or other susceptibility genes in the same pathway. In three of the BRCA1-like tumors, we provided evidence for epigenetic inactivation ofBRCA1 by promoter methylation.

Although additional validation studies are required, indication of BRCA1/2 involvement (BRCAness), using subtype-specific BRCA1/2 signatures in combination with subtype classification, RNA profiling could potentially be valuable as a tool for distinguishing pathogenic mutations from benign variants, for identifying undetected mutation carriers, and for selecting patients sensitive to new therapeutics such as PARP-inhibitors.

Genomic aberration in hereditary breast cancer

With the implementation of microarray-based comparative genomic hybridization (array-CGH), high resolution analysis of chromosomal aberrations in tumor samples became easy accessible. The first study utilizing array-CGH for analysis of hereditary breast cancers was in 2005 by Jönsson et al.113 The investigators obtained genomic profiles from BRCA1 (n = 14), BRCA2 (n = 12), and sporadic (n = 26) breast cancer patients. Using SVMs classification, 11 of 12 samples with BRCA1 mutations were correctly identified in the BRCA1 classification, while 4 non-BRCA1 samples were misclassified. BRCA2classification resulted in 9 of 12 samples correctly classified and 4 misclassified. In addition, they identified 4p, 4q, and 5q as frequently lost in BRCA1 tumors relative to sporadic tumors. 7p and 17q24 were found to be frequently gained in BRCA2 compared to sporadic tumors. The study observed highest frequencies of copy number alternations in BRCA1 tumors. The regions described as discriminative by Jönsson et al were further evaluated in an array-CGH study by Melchor et al in a series composed ofBRCA1 (n = 19), BRCA2 (n = 24), non-BRCA1/2 (n = 31), and sporadic tumors (n = 19).114 The authors observed that the regions mainly differentiated ER-positive tumors from ER-negative tumors rather thanBRCA mutation status, caused by the fact that in the Jönsson study, all BRCA1 tumors were ER-negative and all BRCA2 tumors were ER-positive. On this background, it was suggested that ER-status should be considered in future study designs. Five years after their first study, Jönsson and colleagues reported in 2010 a study of a set of 346 primary tumor samples (plus 13 metastases), including BRCA1 (n = 17),BRCA2 (n = 31), non-BRCA1/2 familiar (n = 126), and sporadic (n = 172) tumors.112 The study identified genomic subtypes by unsupervised clustering of the copy number profiles designated basal-complex, 17q12, luminal-complex, luminal-simple, amplifier, and mixed. The genomic subtypes were highly concordant to the intrinsic subtypes determined by gene-expression. The majority of BRCA1 tumors (77%) had the basal-complex subtype (comparable to basal-like), while the majority of BRCA2 (78%) were luminal-complex (comparable to lumB). The familial non-BRCA1/2 samples were distributed across the different genomic subtypes similar to the sporadic cancers. Luminal-complex BRCA2 tumors were characterized by losses on 3p21.31, 3p14.1, 6q16.2, 13q14.2, 14q24.3, and 22q13.31 and gains on 17q25.3 compared with non-BRCA2 tumors in the same genomic subtype, whereas the sporadic tumors showed more-frequent gain of 11q13.3. No region was found to differ significantly between BRCA1 and non-BRCA1 tumors in the basal-complex subtype.

From these array-CGH studies, among others, it also became clear that patterns of genomic aberrations are highly influenced by the ER/HER2 status and the molecular subtype of the tumors. To construct subtype-independent BRCA1 and BRCA2 classifiers, Joosse and colleagues used ER-matched tumor samples for feature selection and training of the classifiers. In Joosse et al,115 18 BRCA1 and 32 sporadic tumors were used as training set for construction of a BRCA1 classifier, while 16 BRCA1 and 16 sporadic tumors made up the test set. Using this approach, a sensitivity of 88% and a specificity of 94% when applied to the test set were obtained. The classifier was also used to identify BRCA1-like tumor profiles among 48 non-BRCA1/2 tumors from HBOC families. The results showed that 2 of the 48 non-BRCA1/2 breast tumors exhibited chromosomal aberrations similar to those found in BRCA1-mutated tumors. Further analysis demonstrated LOH of BRCA1 in both cases and hypermethylation of BRCA1 gene promoter in one case. The most abundant genomic abbreviations that differed between BRCA1 and sporadic tumors were 3q22-27 (gain), 5q12-14 (loss), 6p23-22 (gain), 12p13 (gain), 12q21-23 (loss), and 13q31-34 (gain). A similar approach was used by Joosse et al for construction of a BRCA2 classifier, using a training set of 28 BRCA2and 28 sporadic tumors.116 From a validation set of 19 BRCA2 and 19 sporadic tumors, they achieved a sensitivity of 89% and a specificity of 84%. Testing a set of 89 cases from non-BRCA1/2 high-risk families, 12 were found to exhibit a high level of similarity with true BRCA2-mutated breast tumors. In three cases, additional indications of dysfunctional BRCA2 were found by determining allele-specific mRNA expression. Nine other cases demonstrated LOH/allelic imbalance of the BRCA2 locus, indicating possible loss of BRCA2 not detected by standard diagnostic procedures. Chromosomal aberrations specific for BRCA2-mutated tumors were loss of 13q and 14q and gain of 17q.

Conclusion and Future Perspectives

The results from the last decade of pathological and molecular characterization of hereditary breast cancer have unquestionably contributed with important insights into the biological mechanism underlying hereditary breast cancers. It is now well established that tumors of hereditary breast cancers are not phenotypically distinct groups of cancers, instead they are associated with the intrinsic molecular subtypes. BRCA1 tumors are mainly TN/basal-like, BRCA2 tumors are ER+/lumB cancers, and non-BRCA1/2 tumors are more phenotypically heterogeneous but most often of the ER+/luminal subtypes. The described studies also stress the importance of careful study design. Because of the strong association to the molecular subtypes, proper sample matching is important to avoid bias in order to detect genomic features unique for hereditary breast cancers. By stratifying for ER-status or molecular subtypes, recent RNA- and DNA-based classification studies have demonstrated that tumors from BRCA1 and BRCA2 mutation carriers represent distinct biological entities among ER−/basal-like and ER+/lumB tumors, respectively. Signatures based on transcriptome as well as genome profiling have proven suitable for prediction of BRCA1/2 status with high accuracies and have been shown to have the capacity to identify tumors with BRCA1/2-like molecular phenotypes among tumors with no recognized BRCA1/2 mutation. Although more research on larger cohorts is required, molecular signatures could have the potential to improve diagnostics by facilitating the clinical interpretation of the large number of sequence variants of unknown clinical significance found in the BRCA1/2 genes by distinguishing pathogenic mutations from benign variants. Such signatures could also be used as a tool for preselecting patients for mutation screening, as a significant proportion of BRCA1and BRCA2 germline mutation carriers do not have a family history of breast cancers. New targeted therapies such as PARP-inhibitors have been demonstrated to be effective treatments for BRCA1/2mutation carriers because of dysfunctional HR DNA repair. In addition to germline mutations, other mechanisms, such as somatic and epigenetic inactivation of BRCA1/2, can lead to BRCA-deficiency and impaired HR DNA repair. Molecular signatures could potentially prove to provide a general method for detecting BRCA-deficient tumors sensitive to new target therapies making it applicable for optimal treatment decisions. Molecular profiling may also be valuable to future genetic analysis by stratifying tumor/families into molecularly homogenous subgroups to aid the search for new breast cancer susceptibility genes. The landscape of hereditary breast cancer is starting to emerge; however, studies of non-coding RNA expression (such as microRNA and lncRNA), NGS, as well as epigenetic studies will undoubtedly add important details to the description of the complex genetic architecture underlying hereditary breast cancer.

Author Contributions

Martin J. Larsen,1,2 Mads Thomassen,1,2 Anne-Marie Gerdes,3 and Torben A. Kruse1,2

Wrote the first draft of the manuscript: MJL. Contributed to the writing of the manuscript: MJL, MT, AMG, TK. Agree with manuscript results and conclusions: MJL, MT, AMG, TK. Jointly developed the structure and arguments for the paper: MJL, MT, AMG, TK. Made critical revisions and approved final version: MJL, MT, AMG, TK. All authors reviewed and approved of the final manuscript.

ACADEMIC EDITOR: Goberdhan P. Dimri, Editor in Chief

FUNDING: The work was supported by Danish Cancer Society, Dansk Kræftforsknings Fond, Savværksejer Jeppe Juhls og hustru Ovita Juhls Mindelegat, Raimond og Dagmar Ringgård Bohns Fond, Kong Christian IX og Dronning Louises Jubilæumslegat, Ingeniør K. A. Rohde og hustrus Legat, Snedkermester Sophus Jacobsens og hustru Astrid Jacobsens Fond, Fru Astrid Thaysens Legat for Lægevidenskabelig Grundforskning, Aase og Ejnar Danielsens Fond, and Grosserer M. Brogaard og Hustrus Mindefonde. The authors confirm that the funder had no influence over the study design, content of the article, or selection of this journal.

COMPETING INTERESTS: Authors disclose no potential conflicts of interest.

Paper subject to independent expert blind peer review by minimum of two reviewers. All editorial decisions made by independent academic editor. Prior to publication all authors have given signed confirmation of agreement to article publication and compliance with all applicable ethical and legal requirements, including the accuracy of author and contributor information, disclosure of competing interests and funding sources, compliance with ethical requirements relating to human and animal study participants, and compliance with any copyright requirements of third parties.

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Source: Breast Cancer: Basic and Clinical Research.
This article was originally published on October 15, 2014