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Pan-cancer transcriptional regulatory network analysis reveals key drivers and epigenetic modulators in tumorigenesis
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Abstract
Cancer remains a leading cause of mortality worldwide, largely due to the complexity of its transcriptional and epigenetic dysregulation. However, integrating multi-omics data to construct context-specific transcriptional regulatory networks (TRNs) and dissecting their pan-cancer relevance remain challenging. Here, we developed a framework integrating gene expression, chromatin accessibility, and DNA methylation data to reconstruct TRNs across 16 cancer types from The Cancer Genome Atlas. Using the PECA model, we identified TF-RE-TG (transcription factor-regulatory element - target gene) regulatory relationships and refined networks using protein-protein interaction or methylation-aware filtering. Our analysis revealed cancer-specific and pan-cancer dysregulated TFs and TGs. Notably, hub TFs like TBP and SP2 orchestrated pan-cancer modules linked to DNA repair. Survival analysis identified prognostic TGs (e.g., TAS2R14, ANLN), while enhancer and methylation analyses highlighted epigenetic-related regulatory axes (e.g., NFIB-RPS6KB2, MYB-BTK) in tumorigenesis. Our study provides a comprehensive resource of cancer TRNs, unveiling conserved regulatory mechanisms and epigenetic vulnerabilities, with implications for precision oncology.
- organism: human
- assay: bulk RNA-seq
- assay: DNA methylation
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
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