Integrative GWAS and RNA-Seq analysis for target identification and virtual drug screening in colorectal cancer
Qinghui Liu, Yiyang Lei, Zixuan Liu, Jiale Han, Zhengrui Li, Zhengrui Li, Zhengrui Li, Zhengrui Li
TL;DR
This study combines genetic and RNA data to identify key genes in colorectal cancer and finds potential drug targets, including PYGL, for new therapies.
Contribution
The novel integration of GWAS and RNA-seq data identifies CRC-associated genes and prioritizes PYGL as a druggable target through virtual screening.
Findings
24 CRC-associated genes, including PYGL, SMAD7, and TCF7L2, are involved in tumor metabolism and Wnt/TCF signaling.
Five genes (CDKN2B, BOC, METRNL, etc.) are significantly correlated with survival outcomes in CRC patients.
Ten small-molecule candidates targeting PYGL show high binding affinity, suggesting therapeutic potential.
Abstract
Colorectal cancer (CRC) is a leading cause of global cancer-related mortality, necessitating the identification of novel therapeutic targets. Integrating genetic and transcriptomic data may reveal key molecular drivers of CRC progression and treatment opportunities. We performed a multiomics analysis combining genome-wide association study (GWAS) data (p < 1e-6) and RNA-seq data from the TCGA. Differential expression analysis (Limma) identified 24 consistently dysregulated genes (17 mRNAs, 7 lncRNAs) in CRC. Survival analysis was used to evaluate their prognostic impact on overall survival (OS), relapse-free survival (RFS), and post progression survival (PPS). Drug‒gene interactions were explored via Enrichr, and virtual screening (PubChem) prioritized high-affinity compounds that target PYGL, a metabolic regulator. Integration of GWAS and RNA-seq revealed that 24 CRC-associated…
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Taxonomy
TopicsBioinformatics and Genomic Networks · RNA modifications and cancer · Computational Drug Discovery Methods