Deciphering the Dysregulated Pathways and Candidate Therapeutic Compounds for Primary Ovarian Cancer Using Whole Transcriptomics Data and Next Generation Knowledge Discovery Strategies

Abstract

Ovarian cancer (OC) is a type of gynaecological cancer with a higher mortality rate due to diagnosis at an advanced stage and limited treatment options. This study aimed to leverage transcriptomic data to identify cellular and molecular pathways and potential anti-cancer compounds that specifically target primary invasive epithelial ovarian cancer (EOC). By employing next-generation knowledge discovery (NGKD) methodologies, we sought to unravel the intricate molecular landscape of primary invasive EOC using RNA sequencing (RNA-seq) data and decipher potential therapeutics for this debilitating disease. We performed NGKD analysis of the Gene Expression Omnibus (GEO) dataset GSE1295399 obtained from whole RNA-seq experiments. Using the raw counts and filtered metadata from GEO, we identified 2123 differentially expressed genes (DEGs) based on a Log₂ fold change (≤ ±0.6) and a p-value cutoff of < 0.05, between primary invasive EOC and benign EOC using the ExpressAnalyst platform. The DEGs were further analysed using both ExpressAnalyst and WebGestalt tools for differentially regulated cellular and molecular pathways and gene ontology (GOs), including biological process (GO-BP), molecular function (GO-MF) and cellular components (GO-CC). Both L1000 Fire Works Display (L1000FWD) and L1000 Characteristic Direction Signature Search Engine (L1000CDS2) tools were used to decipher synthetic or natural chemical compounds with the potential to reverse OC-associated gene signatures. DEGs implicated in key cellular and molecular pathways, such as oxidative phosphorylation, cell cycle, proteasome, programmed cell death protein-1 (PD-1) signalling, nuclear factor kappa B (NF-kB) signalling, cytokine and chemokine signalling, natural killer cell-mediated cytotoxicity and microRNAs in cancer, were positively enriched. The ribosome, translation, translational initiation and elongation and transforming growth factor-beta (TGF-β) signalling were negatively enriched in primary invasive EOC. Based on NGKD analysis, we identified approximately 50 synthetic or natural compounds, including naproxol, palbociclib, etoposide, wortmannin, PP-110, AZD-8055, amsacrine and BRD-K6595526. The results of this study could aid in the development of personalized treatment plans based on the unique profile of each tumour type, thus facilitating the development of personalized or precision treatment plans and improving diagnostic and prognostic capabilities in the clinic. In conclusion, the combination of RNA-seq and cutting-edge NGKD methodologies holds significant promise for identifying key cellular and molecular pathways and OC therapeutics.