ArticleDiscover oncology2025
Integrative eQTL and Mendelian randomization analysis reveals key genes in colorectal cancer.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Telmisartan Repurposing Targets Novel Biomarkers for Precision Colorectal Cancer Therapy.Pharmaceutics · 2026Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer (CRC) represents a crucial global public health concern, yet its molecular mechanisms underlying CRC are not completely comprehended. This study utilizes Mendelian randomization (MR) in conjunction with comprehensive transcriptome profiling to discover crucial genetic markers associated with CRC.
methodUsing CRC datasets from The Cancer Genome Atlas (TCGA), R software analyzed differentially expressed (DEGs). eQTLs served as instrumental variables (IVs) to identify CRC genes by means of two-sample MR methods. Key CRC genes were found by intersecting DEGs with genome-wide association study (GWAS) data. The causal impacts of these intersecting genes were analyzed using Summary-data-based Mendelian Randomization (SMR). In order to validate the gene-disease associations, the GSE39582 dataset was employed, along with polymerase chain reaction (PCR) techniques. Subsequent studies defined the roles of these genes in the CRC pathophysiology, incorporating functional enrichment, Gene Set Enrichment Analysis (GSEA), TISCH, and immune cell infiltration analyses.
resultsMR, TCGA and SMR identified three key genes-MCM6, RAB6B, and CDC25B-that are closely linked to CRC. These genes play vital roles in activities like mitotic DNA replication and cell cycle regulation. Moreover, findings from CIBERSORT analysis showed a unique immune cell pattern in CRC, underscoring the importance of immune mechanisms in the development of this disease. MR results are confirmed by a cohort and polymerase chain reaction (PCR) assessments.
conclusionThree critical CRC-affecting genes were identified, offering new molecular insights and potential research and treatment directions.
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