GrantR03CA
Dissecting clonal determinants of platinum/PARP inhibitor cross-resistance in ovarian cancer
- Activity
- R03
- Institute
- CA
- Fiscal years
- 2025–2025
- Amount counted
- $164,000
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Abstract public domain (NIH RePORTER)
ABSTRACT The recalcitrance of high-grade serous ovarian cancer (HGSOC) to available therapies is largely enabled by the disease’s ability to fast disseminate into the peritoneal cavity and its intrinsic molecular heterogeneity. A first-line platinum-taxane regimen, in combination with PARP inhibitors (PARPi) as maintenance therapy has improved patients’ survival and revolutionized HGSOC management, especially for those carrying mutations in BRCA1/2 genes. Recently, the sensitivity to PARPi has been associated not only with BRCA1/2 mutations, but with a broader homologous recombination deficiency (HRD) signature, which accounts for nearly 50% of HGSOCs. Surprisingly, PARPi sensitivity has also been observed in homologous recombination-proficient (HRP) tumors. Despite successful, the emergence of cross-resistance to platinum/PARPi treatment strongly hindered the long- term clinical benefit, posing a significant clinical challenge. The genetic and epigenetic instability of HGSOCs strongly contributes to the development of cross-resistant clones, which undergo lineage expansion, leading to treatment failure and disease relapse. Furthermore, the mechanisms driving the selection of Platinum/PARPi cross-resistant clones, and their evolution remain poorly understood. A critical question is whether recurrent disease is driven by pre-existing resistant clonal populations or by de novo (acquired) molecular scars selected during the treatment. Addressing this question is crucial for understanding HGSOC progression and developing more effective therapies. To investigate these issues, we have developed a novel somatic mosaic genetically-engineered mouse model (smGEMM) of HGSOC combined with a molecular barcoding technology. This approach allows for the high-throughput isolation and detailed characterization of specific cell lineages, including therapy cross-resistant clones, enabling us to track clonal dynamics and to identify molecular drivers of resistance. To assess this hypothesis, we will pursue specific aims that 1) generate longitudinal lineage-traced models of HRP and HRD HGSOCs using smGEMM models, 2) functionally characterize the clonal dynamics of platinum/PARPi resistance and 3) perform cross-species validation of molecular dependencies driving platinum/PARPi resistance. Our findings will be significant because they will 1) uncover the transcriptomic and genomic mechanisms behind platinum/PARPi cross-resistance in HRP and HRD tumors, 2) reconstruct the evolutionary pathways of aggressive HGSOCs, 3) identify the cross-species molecular signatures of platinum/PARPi resistance. Importantly, this research has the potential to extend beyond HGSOC, as Platinum/PARPi combinaiton is used in other HRD cancers, such as breast and pancreatic cancer. Furthermore, our CRT and sm-GEMM platforms are adaptable to other gynecological cancers, hence benefiting the broader scientific community. Ultimately, this study will address urgent clinical needs by identifying molecular signatures of platinum/PARPi resistance and discovering biomarkers for patient stratification and therapeutic targeting.
Public health relevance public domain (NIH RePORTER)
NARRATIVE While the introduction of PARP inhibitors has improved survival rates of high grade serous ovarian cancer (HGSOC) patients, recurrence remains frequent, often accompanied by cross-resistance to platinum-based chemotherapy. The proposed research will use an innovative genetically-engineered mouse model coupled with molecular barcoding to deeply investigate the clonal architecture and dynamics of HGSOC in response to platinum/PARPi treatment and to identifying molecular determinants and mechanisms of cross-resistance in vivo. This work has the potential to significantly improve outcomes for patients with HGSOC by guiding the development of precision therapies and enhancing patient stratification for treatment.