ArticleJournal of clinical practice and research2026
Adenosine Pathway-Based Prognostic Signature for Predicting Clinical Outcomes and Immune Microenvironment Characteristics in Epithelial Ovarian Cancer.
Article in Journal of clinical practice and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This study aimed to develop and validate an adenosynergic prognostic signature for stratifying clinical outcomes and characterizing the tumor immune microenvironment in patients with EOC. Materials and Methods: A retrospective bioinformatics analysis, complemented by experimental validation, was conducted. Adenosine signaling activity was quantified using ssGSEA, and key adenosynergic modules were identified using WGCNA. Prognostically significant adenosine-related genes (ARGs) were selected through LASSO Cox regression to construct a composite signature, which was then validated across multiple datasets. Functional enrichment analysis, immune infiltration estimation, and somatic alteration mapping were performed. Results: The blue module showed the strongest correlation with adenosine pathway activity. Nine independent prognostic ARGs were identified: 5 risk-associated genes (PIK3CG, VSIG4, MATK, PIEZO1, and RARRES1) and 4 protective genes (SELL, S1PR4, IL18BP, and CD40LG). The signature demonstrated robust time-dependent predictive accuracy for overall survival, with AUCs ranging from 0.62 at 1 year to 0.71 at 5 years (95% CI: 0.58-0.75 for 1 year, 0.63-0.71 for 3 years, and 0.67-0.75 for 5 years). High-risk patients exhibited significantly worse survival and inversely correlated CD8 Conclusion: This study establishes a novel prognostic signature for stratifying OC outcomes. The model quantifies immunosuppressive microenvironmental features and identifies clinically actionable targets, particularly VSIG4, to guide treatment in EOC.
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