Abstract

Abstract Identification of mutation-specific targeted therapies is a critical challenge in precision medicine, in part because many cancer mutations are loss-of-function and are not druggable. Even when a mutation-specific targeted therapy exists, resistance invariably develops necessitating alterative therapeutic options. Synthetic lethality can help identify new therapeutic targets for these mutations. In synthetic lethal (SL) interactions, an alteration in one gene leads to dependency on a second gene. Neither alteration by itself is essential for survival, but together these alterations lead to cancer cell death. We have recently developed a new computational method (Mining Synthetic Lethals, MiSL) that mines SL interactions from pan-cancer primary tumor data (such as TCGA). The underlying assumption of MiSL is that SL partners of a mutation will be selectively amplified or never deleted and overexpressed in primary tumor samples harbouring the mutation. Since MiSL mines relationships from primary human tumor data, it enables the identification of SL interactions in the native context of human tumors and is more likely to find relationships relevant to in vivo tumor biology than shRNA screens. Here, we applied MiSL to identify SL partners of the BRCA1 mutation in triple-negative breast cancer (TNBC). BRCA1 is mutated in 15-20% of TNBC and is a known cancer susceptibility gene in breast cancer. MiSL identified 22 SL partners of the BRCA1 mutation in TNBC: these were enriched for DNA repair genes consistent with the known SL relationship between BRCA1 and the DNA repair gene PARP. Notably, XRCC6, a gene involved in non-homologous end joining, was predicted to be a SL partner of the BRCA1 mutation in TNBC. MiSL selected XRCC6 because XRCC6 deletions (which were associated with lowered expression of XRCC6) were mutually exclusive with BRCA1 mutations in pan-cancer analysis (p = 0.01), and XRCC6 was upregulated in BRCA1-mutated TNBC compared to BRCA1-WT TNBC (p = 0.02). To test the prediction, we examined the effect of XRCC6 knockdown (KD) in the BRCA1-mutated TNBC cell line SUM149. Consistent with our prediction, we found that XRCC6 KD significantly increased apoptosis (37.3%) and reduced viability (50% reduction, p < 0.0001) in SUM149 cells compared to controls. XRCC6 KD in a BRCA1-WT breast cancer cell line, T47D, resulted in significantly lower reduction in cell viability compared to the BRCA1-mutated cell line (p<0.0001). These data indicated that XRCC6 KD more effectively induced cell death in the presence of BRCA1 mutation than in cells WT for the gene. We are currently testing XRCC6 KD effects in TNBC cell lines harbouring germline BRCA1 mutations. Thus, we have identified a novel SL partner of the BRCA1 mutation in TNBC that can lead to the development of new therapeutic options for BRCA1-mutated breast cancers and to new chemoprevention strategies for individuals carrying germline BRCA1 mutations. Citation Format: Yihui Shi, Xiaohe Liu, Jia Li, Lidia Sambucetti, Subarna Sinha. Primary tumor data mining identifies a novel synthetic lethal partner of the BRCA1 mutation in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2974.

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