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

PARP inhibitors exploit synthetic lethality in <i>BRCA1/2</i>-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 <i>BRCA1</i>, <i>MLL2</i>, <i>NF1</i>, and <i>SMARCA4</i> were associated with increased sensitivity to PARP inhibitors, suggesting potential synthetic lethality with PARP1. In contrast, <i>SMAD4</i> mutations were linked to PARP inhibitor resistance, and low <i>SMAD4</i> 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 <i>SMAD4</i>-mediated resistance. Functional enrichment revealed associations with stress response, tumor-associated signaling pathways, and additional processes. Subsequent correlation and survival analyses nominated <i>ACACA</i>, <i>PRPF4B</i>, and <i>TUBD1</i> as potential therapeutic targets. Notably, low <i>ACACA</i> expression in patients with low <i>SMAD4</i> 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.