Unravelling the molecular landscape of endometrial cancer subtypes: insights from multi-omics analysis.

Abstract

Endometrial cancer (EC) as one of the most common gynecologic malignancies is increasing in incidence during the past 10 years. Genome-Wide Association Studies (GWAS) extended to metabolic and protein phenotypes inspired us to employ multi-omics methods to analyze the causal relationships of plasma metabolites and proteins with EC to advance our understanding of EC biology and pave the way for more targeted approaches to its diagnosis and treatment by comparing the molecular profiles of different EC subtypes. Two-sample Mendelian randomization (MR) was performed to investigate the effects of plasma metabolites and proteins on risks of different subtypes of EC (endometrioid and non-endometrioid). Pathway analysis, transcriptomic analysis, and network analysis were further employed to illustrate gene-protein-metabolites interactions underlying the pathogenesis of distinct EC histological types. We identified 66 causal relationships between plasma metabolites and endometrioid EC, and 132 causal relationships between plasma proteins and endometrioid EC. Additionally, 40 causal relationships between plasma metabolites and non-endometrioid EC, and 125 causal relationships between plasma proteins and non-endometrioid EC were observed. Substantial differences were observed between endometrioid and non-endometrioid histological types of EC at both the metabolite and protein levels. We identified 7 overlapping proteins (RGMA, NRXN2, EVA1C, SLC14A1, SLC6A14, SCUBE1, FGF8) in endometrioid subtype and 6 overlapping proteins (IL32, GRB7, L1CAM, CCL25, GGT2, PSG5) in non-endometrioid subtype and network analysis of above proteins and metabolites to identify coregulated nodes. Our findings observed substantial differences between endometrioid and non-endometrioid EC at the metabolite and protein levels, providing novel insights into gene-protein-metabolites interactions that could influence future EC treatments.