Identification of Anticancer Targets in Ovarian Cancer Using Genomic Drug Sensitivity Data

利用基因组药物敏感性数据鉴定卵巢癌抗癌靶点

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Abstract

PARP inhibitors exploit synthetic lethality in BRCA1/2-mutated ovarian cancers but are limited by emerging therapeutic resistance. Therefore, novel biomarkers predicting PARP inhibitor response are urgently needed. In this study, we performed integrative analysis using drug sensitivity, patient survival, gene dependency, and expression data to identify biomarkers associated with PARP inhibitor response in ovarian cancer. Mutations in BRCA1, MLL2, NF1, and SMARCA4 were associated with increased sensitivity to PARP inhibitors, suggesting potential synthetic lethality with PARP1. In contrast, SMAD4 mutations were linked to PARP inhibitor resistance, and low SMAD4 expression was associated with poor overall survival in patients with ovarian cancer. Further gene dependency score (GDS)-based screening revealed 51 candidate genes potentially involved in SMAD4-mediated resistance. Functional enrichment revealed associations with stress response, tumor-associated signaling pathways, and additional processes. Subsequent correlation and survival analyses nominated ACACA, PRPF4B, and TUBD1 as potential therapeutic targets. Notably, low ACACA expression in patients with low SMAD4 expression was associated with improved survival, indicating its relevance in overcoming PARP inhibitor resistance. This study contributes to predicting clinical outcomes in ovarian cancer and developing personalized treatment strategies.

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