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2022-RA-1446-ESGO Comprehensive assessment of gene mutations revealed overlapping dependencies for PARPi and chemotherapy response in ovarian cancer
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  1. Alessandra Tozzi1,
  2. Muriel Disler2,
  3. Ricardo Coelho2,
  4. Flavio Lombardo2,
  5. Andre Fedier2,
  6. Monica Nunez Lopez2,
  7. Florian Freuler2,
  8. Francis Jacob2 and
  9. Viola Heinzelmann-Schwarz1
  1. 1Hospital for Women, University Hospital of Basel, Basel, Switzerland
  2. 2Ovarian Cancer Research, Department of Biomedicine, Basel, Switzerland

Abstract

Introduction/Background PARP inhibitors (PARPi) have revolutionized the therapeutic landscape of epithelial ovarian cancer (EOC) prolonging the progression-free survival, especially in BRCA1/2 mutations carriers or in patients with defects in homologous recombination (HR) repair. However, it remains uncertain which PARPi to apply and how to select responders using clinical and molecular characteristics, especially in forefront therapy when platinum sensitivity is still unknown.

Methodology We selected 33 promising genes that showed a prediction of enhanced PARPi sensitivity after a systematic literature review and the exploration of publicly available CRISPR-Cas9 library screens and Genomics of Drug Sensitivity in Cancer data. We performed functional assessment in six constitutively Cas9 expressing OC cell lines and subsequent examined our set of genes using a CRISPR-Cas9 mutagenesis assay with various PARPi and carboplatin.

Results Our functional screen identified ten novel potential PARPi response biomarkers, with different impact on cell fitness and drug response.ATM was the only gene that produced an enhanced olaparib sensitivity in all the cell lines.Acquired olaparib sensitivity was also observed for MUS81, NBN, RAD51B/C, RNASEH2A, PALB2, XRCC1, and XRCC3 in at least 3 cell lines.CDK12 was identified as an essential gene in all the cell lines tested without altering the response to Olaparib.Since the best clinical biomarker of PARPi sensitivity remains the sensitivity to chemotherapy, we next compared dropout rates of top candidate genes under different PARPi (olaparib, niraparib, talazoparib) and carboplatin. Interestingly, we observed almost identical results, independently of tested gene and drug compound. This confirming the strong correlation of cancer cell response to DNA damaging drugs.

Conclusion Our data show various overlapping gene dependencies suggesting a general mechanism-of-action of PARPi and chemotherapy. Genetic screen of the identified set of genes correlated with PARPi sensitivity may allow a better stratification of patients with increase benefit to this treatment.

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