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Identifying cancer drivers and actionable mutations is critical for precision oncology. In epithelial ovarian cancer (EOC) the majority of mutations lack biological or clinical validation. We fully characterized 43 lines of Patient-Derived Xenografts (PDXs) and performed copy number analysis and whole exome sequencing of 12 lines derived from na&#239;ve, high grade EOCs. Pyrosequencing allowed quantifying mutations in the source tumours. Drug response was assayed on PDX Derived Tumour Cells (PDTCs) and in vivo on PDXs. We identified a <i>PIK3R1</i>^W624R variant in PDXs from a high grade serous EOC. Allele frequencies of <i>PIK3R1</i>^W624R in all the passaged PDXs and in samples of the source tumour suggested that it was truncal and thus possibly a driver mutation. After inconclusive results in silico analyses, PDTCs and PDXs allowed the showing actionability of <i>PIK3R1</i>^W624R and addiction of <i>PIK3R1</i>^W624R carrying cells to inhibitors of the PI3K/AKT/mTOR pathway. It is noteworthy that <i>PIK3R1</i> encodes the p85&#945; regulatory subunit of PI3K, that is very rarely mutated in EOC. The <i>PIK3R1</i>^W624R mutation is located in the cSH2 domain of the p85&#945; that has never been involved in oncogenesis. These data show that patient-derived models are irreplaceable in their role of unveiling unpredicted driver and actionable variants in advanced ovarian cancer.