Novel Metabolic Reprogramming and Circadian Rhythm Related Molecular Subtyping and Prognostic Signature for Ovarian Cancer

📖 Top 30% JournalJan 26, 2026Current medicinal chemistry

New Metabolic and Body Clock Molecular Types Linked to Outlook in Ovarian Cancer

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Circadian Biology on OpenScience ↗PubMed ↗DOI ↗

Abstract

A total of 138 metabolic reprogramming and circadian rhythm-related genes were identified in ovarian cancer.

The expression of metabolic reprogramming and circadian rhythm-related genes differs significantly between ovarian cancer and healthy controls.
A Cox regression model based on four genes was developed to predict patient survival outcomes.
Two distinct ovarian cancer subtypes were identified, showing significant differences in overall survival.
Analysis of immune cell types revealed significant expression differences across 26 immune cell categories.
A six-gene predictive model demonstrated moderate accuracy in assessing ovarian cancer outcomes.
Gene Set Enrichment Analysis highlighted significant pathways, particularly those related to IL-10 synthesis.

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INTRODUCTION: Ovarian cancer (OC), characterized by high mortality and lacking early diagnostic markers, poses a significant health threat. This study investigated the expression of metabolic reprogramming and circadian rhythm-related genes (MRCRRGs) in OC and their association with clinical features.

METHODS: OC datasets and MRCRRG lists were sourced from TCGA, GEO, and Gene- Cards. Comprehensive bioinformatics analyses included calculating Metabolic Reprogramming and Circadian Rhythm Scores (MRCR.Score), identifying MRCR score-related genes (MRCRSRGs), building a Cox regression model, performing clustering for subtype identification, analyzing immune cell infiltration and immune checkpoint gene expression, conducting differential expression analysis, and performing Gene Set Enrichment Analysis (GSEA).

RESULTS: We identified 138 MRCRRGs. MRCR. Score differed significantly between OC and controls. Thirty-four MRCRSRGs were identified, and a Cox model based on four genes was developed. Clustering revealed two distinct OC subtypes with significant overall survival differences. Immune infiltration analysis showed significant expression differences in 26 immune cell types, and immune checkpoint genes differed between subtypes. Differential expression identified 89 genes (88 upregulated, 1 downregulated). A six-gene predictive model demonstrated moderate accuracy. GSEA revealed significant enrichment of key pathways, notably Fcgr3a-mediated IL-10 synthesis.

DISCUSSION: Findings demonstrate strong links between MRCRRGs, OC subtypes, patient survival, and the tumor immune microenvironment. Enrichment of pathways like Fcgr3a-mediated IL10 synthesis suggests novel OC mechanisms. Reliant on bioinformatics, the study provides insights into OC heterogeneity.

CONCLUSION: This study establishes a foundation for understanding MRCRRG molecular mechanisms in OC. The identified subtypes, prognostic model, immune landscape alterations, and enriched pathways offer valuable insights for future experimental validation and potential diagnostic/therapeutic strategies.

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