Identification of candidate mediators of chemoresponse in breast cancer through therapy-driven selection of somatic variants.

PURPOSE: More than a third of primary breast cancer patients are treated with cytotoxic chemotherapy, typically without guidance from predictive markers. Increased use of neoadjuvant chemotherapy provides opportunities for identification of molecules associated with treatment response, by comparing matched tumour samples before and after therapy. Our hypothesis was that somatic variants of increased prevalence after therapy promote resistance, while variants with reduced prevalence cause sensitivity. METHODS: We performed systematic analyses of matched pairs of cancer exomes from primary oestrogen receptor-positive/HER2-negative breast cancers (n = 6) treated with neoadjuvant epirubicin/cyclophosphamide. We identified candidate genes as mediators of chemotherapy response by consistent subclonal changes in somatic variant prevalence through therapy, predicted variant impact on gene function, and enrichment of specific functional pathways. Influence of candidate genes on breast cancer outcome was tested using publicly available breast cancer expression data (n = 1903). RESULTS: We identified 14 genes as the strongest candidate mediators of chemoresponse: TCHH, MUC17, ARAP2, FLG2, ABL1, CENPF, COL6A3, DMBT1, ITGA7, PLXNA1, S100PBP, SYNE1, ZFHX4, and CACNA1C. Genes contained somatic variants showing prevalence changes in up to 4 patients, with up to 3 being predicted as damaging. Genes coding for extra-cellular matrix components or related signalling pathways were significantly over-represented among variants showing prevalence changes. Expression of 5 genes (TCHH, ABL1, CENPF, S100PBP, and ZFHX4) was significantly associated with patient survival. CONCLUSIONS: Genomic analysis of paired pre- and post-therapy samples resulting from neoadjuvant therapy provides a powerful method for identification of mediators of response. Genes we identified should be assessed as predictive markers or targets in chemo-sensitization.

MiR-195 and Its Target SEMA6D Regulate Chemoresponse in Breast Cancer.

BACKGROUND: poor prognosis primary breast cancers are typically treated with cytotoxic chemotherapy. However, recurrences remain relatively common even after this aggressive therapy. Comparison of matched tumours pre- and post-chemotherapy can allow identification of molecular characteristics of therapy resistance and thereby potentially aid discovery of novel predictive markers or targets for chemosensitisation. Through this comparison, we aimed to identify microRNAs associated with chemoresistance, define microRNA target genes, and assess targets as predictors of chemotherapy response. METHODS: cancer cells were laser microdissected from matched breast cancer tissues pre- and post-chemotherapy from estrogen receptor positive/HER2 negative breast cancers showing partial responses to epirubicin/cyclophosphamide chemotherapy (n = 5). MicroRNA expression was profiled using qPCR arrays. MicroRNA/mRNA expression was manipulated in estrogen receptor positive/HER2 negative breast cancer cell lines (MCF7 and MDA-MB-175 cells) with mimics, inhibitors or siRNAs, and chemoresponse was assessed using MTT and colony forming survival assays. MicroRNA targets were identified by RNA-sequencing of microRNA mimic pull-downs, and comparison of these with mRNAs containing predicted microRNA binding sites. Survival correlations were tested using the METABRIC expression dataset (n = 1979). RESULTS: miR-195 and miR-26b were consistently up-regulated after therapy, and changes in their expression in cell lines caused significant differences in chemotherapy sensitivity, in accordance with up-regulation driving resistance. SEMA6D was defined and confirmed as a target of the microRNAs. Reduced SEMA6D expression was significantly associated with chemoresistance, in accordance with SEMA6D being a down-stream effector of the microRNAs. Finally, low SEMA6D expression in breast cancers was significantly associated with poor survival after chemotherapy, but not after other therapies. CONCLUSIONS: microRNAs and their targets influence chemoresponse, allowing the identification of SEMA6D as a predictive marker for chemotherapy response that could be used to direct therapy or as a target in chemosensitisation strategies.

Genomic and Expression Analyses Define MUC17 and PCNX1 as Predictors of Chemotherapy Response in Breast Cancer.

Poor-prognosis breast cancers are treated with cytotoxic chemotherapy, but often without any guidance from therapy predictive markers because universally accepted markers are not currently available. Treatment failure, in the form of recurrences, is relatively common. We aimed to identify chemotherapy predictive markers and resistance pathways in breast cancer. Our hypothesis was that tumor cells remaining after neoadjuvant chemotherapy (NAC) contain somatic variants causing therapy resistance, while variants present pre-NAC but lost post-NAC cause sensitivity. Whole-exome sequencing was performed on matched pre- and post-NAC cancer cells, which were isolated by laser microdissection, from 6 cancer cases, and somatic variants selected for or against by NAC were identified. Somatic variant diversity was significantly reduced after therapy (P < 0.05). MUC17 variants were identified in 3 tumors and were selected against by NAC in each case, while PCNX1 variants were identified in 2 tumors and were selected for in both cases, implicating the function of these genes in defining chemoresponse. In vitro knockdown of MUC17 or PCNX1 was associated with significantly increased or decreased chemotherapy sensitivity, respectively (P < 0.05), further supporting their roles in chemotherapy response. Expression was tested for predictive value in two independent cohorts of chemotherapy-treated breast cancers (n = 53, n = 303). Kaplan-Meier analyses revealed that low MUC17 expression was significantly associated with longer survival after chemotherapy, whereas low PCNX1 was significantly associated with reduced survival. We concluded that therapy-driven selection of somatic variants allows identification of chemotherapy response genes. With respect to MUC17 and PCNX1, therapy-driven selection acting on somatic variants, in vitro knockdown data concerning drug sensitivity, and survival analysis of expression levels in patient cohorts all define the genes as mediators of and predictive markers for chemotherapy response in breast cancer.