<em>RAD51</em> and Breast Cancer Susceptibility: No Evidence for Rare Variant Association in the Breast Cancer Family Registry Study

<div><h3>Background</h3><p>Although inherited breast cancer has been associated with germline mutations in genes that are functionally involved in the DNA homologous recombination repair (HRR) pathway, including <em>BRCA1</em>, <em>BRCA2</em>, <em>TP53</em>, <em>ATM</em>, <em>BRIP1</em>, <em>CHEK2</em> and <em>PALB2,</em> about 70% of breast cancer heritability remains unexplained. Because of their critical functions in maintaining genome integrity and already well-established associations with breast cancer susceptibility, it is likely that additional genes involved in the HRR pathway harbor sequence variants associated with increased risk of breast cancer. <em>RAD51</em> plays a central biological function in DNA repair and despite the fact that rare, likely dysfunctional variants in three of its five paralogs, <em>RAD51C, RAD51D,</em> and <em>XRCC2,</em> have been associated with breast and/or ovarian cancer risk, no population-based case-control mutation screening data are available for the <em>RAD51</em> gene. We thus postulated that <em>RAD51</em> could harbor rare germline mutations that confer increased risk of breast cancer.</p> <h3>Methodology/Principal Findings</h3><p>We screened the coding exons and proximal splice junction regions of the gene for germline sequence variation in 1,330 early-onset breast cancer cases and 1,123 controls from the Breast Cancer Family Registry, using the same population-based sampling and analytical strategy that we developed for assessment of rare sequence variants in <em>ATM</em> and <em>CHEK2.</em> In total, 12 distinct very rare or private variants were characterized in <em>RAD51</em>, with 10 cases (0.75%) and 9 controls (0.80%) carrying such a variant. Variants were either likely neutral missense substitutions (3), silent substitutions (4) or non-coding substitutions (5) that were predicted to have little effect on efficiency of the splicing machinery.</p> <h3>Conclusion</h3><p>Altogether, our data suggest that <em>RAD51</em> tolerates so little dysfunctional sequence variation that rare variants in the gene contribute little, if anything, to breast cancer susceptibility.</p> </div

Rare genetic variants of <i>RAD51</i> identified in the BCFR.

*<p>A protein multiple sequence alignment (PMSA) including 15 sequences from Human to Drosophila (Dmel) was used to obtain scores for Align-GVGD and for SIFT (Median sequence conservation of 4.32 substitutions per position).</p><p>NA, not applicable.</p

Stratified analyses of the <i>RAD51</i> −135G/C SNP on breast cancer risk in the BCFR.

a<p>Test for the difference in C allele frequency between cases and controls.</p>b<p>Results of the logistic regression assuming a log-additive model with study center and age included in the regression model as covariates in the combined analysis, and with race/ethnicity, study center and age as covariates in the stratified analysis.</p

Revealing the Molecular Portrait of Triple Negative Breast Tumors in an Understudied Population through Omics Analysis of Formalin-Fixed and Paraffin-Embedded Tissues

<div><p>Triple negative breast cancer (TNBC), defined by the lack of expression of the estrogen receptor, progesterone receptor and human epidermal receptor 2, is an aggressive form of breast cancer that is more prevalent in certain populations, in particular in low- and middle-income regions. The detailed molecular features of TNBC in these regions remain unexplored as samples are mostly accessible as formalin-fixed paraffin embedded (FFPE) archived tissues, a challenging material for advanced genomic and transcriptomic studies. Using dedicated reagents and analysis pipelines, we performed whole exome sequencing and miRNA and mRNA profiling of 12 FFPE tumor tissues collected from pathological archives in Mexico. Sequencing analyses of the tumor tissues and their blood pairs identified <i>TP53</i> and <i>RB1</i> genes as the most frequently mutated genes, with a somatic mutation load of 1.7 mutations/exome Mb on average. Transcriptional analyses revealed an overexpression of growth-promoting signals (EGFR, PDGFR, VEGF, PIK3CA, FOXM1), a repression of cell cycle control pathways (TP53, RB1), a deregulation of DNA-repair pathways, and alterations in epigenetic modifiers through miRNA:mRNA network de-regulation. The molecular programs identified were typical of those described in basal-like tumors in other populations. This work demonstrates the feasibility of using archived clinical samples for advanced integrated genomics analyses. It thus opens up opportunities for investigating molecular features of tumors from regions where only FFPE tissues are available, allowing retrospective studies on the search for treatment strategies or on the exploration of the geographic diversity of breast cancer.</p></div

PAM50 classification of TNBC samples.

<p>The hierarchically-clustered normalized expression values of the PAM50 classifier genes is shown for the 12 triple negative breast cancers (TNBCs) analyzed and the five centroids. The samples were classified according to their correlation with the PAM50 centroids. Red and blue boxes represent overexpressed and down-regulated genes, respectively.</p

Whole exome sequencing summary statistics.

<p>Whole exome sequencing summary statistics.</p

Summary results of whole exome sequencing for all matched samples (n = 12).

<p>Top panel, details of mutations found in tumors in each specific samples (blue squares are single-nucleotide variants (SNVs) and red squares are insertions and deletions (Indels). Right panel shows the mutations per exome, the amount of mutations in driving and DNA repair genes and total number of mutations per tumor. Lower panel shows gene annotations derived from present results and other studies: Recurrent gene mutated in more than one sample in present series; Mutated in triple negative breast cancer (TNBC) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref007" target="_blank">7</a>], significantly mutated in TNBC from TCGA [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref049" target="_blank">49</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref050" target="_blank">50</a>]; Oncogenes and tumor suppressors class derived from references [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref021" target="_blank">21</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref051" target="_blank">51</a>]; Epigenetic modifiers class derived from references [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref052" target="_blank">52</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126762#pone.0126762.ref053" target="_blank">53</a>]; Clinical target, genes that are targets of drugs in clinical trials or approved by FDA. (<a href="http://www.fda.gov/Drugs/InformationOnDrugs/ApprovedDrugs/default.htm" target="_blank">http://www.fda.gov/Drugs/InformationOnDrugs/ApprovedDrugs/default.htm</a>).</p

Networks of connectivity between miRNA and mRNA.

<p>(A) Networks of (A) up-regulated miRNAs and down-regulated mRNAs, (B) down-regulated miRNAs and up-regulated mRNAs, identified in the TNBC samples (only high confident interactions and genes involved in cancer were selected).</p