Potential Transcriptomic Biomarkers for Predicting Platinum-based Chemotherapy Resistance in Patients With High-grade Serous Ovarian Cancer.

Abstract

Background/aim: Due to the absence of screening protocols, high-grade serous ovarian cancer (HGSOC) patients are frequently diagnosed at an advanced stage, which significantly reduces the survival rate. Moreover, relapse occurs in approximately 70% of HGSOC patients after primary treatment. Predicting resistance to primary chemotherapy remains a challenge. In the research setting, transcriptomic analyses have emerged as powerful tools for predicting which HGSOC patients are likely to benefit from primary treatment. The aim of this review was to investigate the literature demonstrating the potential of transcriptomic signatures as biomarkers for assessing the risk of resistance to platinum-based chemotherapy.

Materials and methods: We conducted a three-step search process on PubMed to systematically review English-language articles published between 2020 and 2024. From the 123 articles retrieved, we included 11 articles that investigated transcriptomic signatures by RNA sequencing in tissues from chemo-sensitive and -resistant HGSOC patients.

Results: We report the clinicopathological data of 727 patients in the experimental cohorts, transcriptomic signatures, and technical aspects. Finally, the review lists 15 publicly available datasets used in the included studies. Furthermore, we investigated the overlap of 167 differentially expressed genes retrieved across the various articles.

Conclusion: We believe this review might offer valuable insights for further studies focusing on predicting platinum resistance and personalized treatments. In addition to discussing the latest findings and potential candidates, we highlight the challenges of validating biomarkers across studies and publicly available datasets. Transcriptomic signatures represent a potential tool for patient stratification, prognosis, and the potential adoption of long-term therapies, such as poly (ADP-ribose) polymerase inhibitors (PARPis).