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Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
Published on: March 1, 2024
A ferroptosis-related risk model for non-coding RNA AC002331.1 in colon cancer: construction via competing endogenous
Jiahui Liu1, Chenning Zhang1, Bao Ma1
1Department of Clinical Research Center, Central Hospital, Shandong First Medical University, No. 105, Jiefang Road, Lixia District, Jinan City, 250013, Shandong Province, China.
Background:
Colon cancer, a globally prevalent malignancy with high mortality, involves lncRNA regulation, ferroptosis pathway abnormalities, and gut microbiota dysbiosis. Ferroptosis-related gene models may aid prognostic evaluation, while microbiota metabolites modulate ferroptosis in contexts like ulcerative colitis.
Methods:
Using the GEO dataset (GSE97300), we screened differentially expressed lncRNAs (e.g., AC002331.1). Competing endogenous RNA networks were predicted via miRcode and miRTarBase, followed by integration with FerrDb to establish ferroptosis regulatory relationships. GutMGene analyzed microbiota metabolite-gene interactions. A 12-gene prognostic model (e.g., HMGB1, VEGFA) was constructed using TCGA data and WEKA 3.8, validated by Kaplan-Meier analysis and ROC curves (10-fold cross-validation).
Results:
LncRNA AC002331.1 was upregulated in colon cancer and positively associated with improved OS/DFS (log-rank test, p < 0.05). Its ceRNA network regulated 29 ferroptosis-related genes. The prognostic model showed discriminative power (ROC AUC = 0.653-0.683). Model genes were co-regulated by microbiota metabolites (e.g.,succinate).
Conclusions:
This study establishes the first lncRNA AC002331.1-centered ceRNA-ferroptosis prognostic model for colon cancer, revealing microbiota-metabolite interactions in disease progression. It provides novel mechanistic insights for therapeutic targeting.
