ArticleBMC cancer2025
Integrative multi-omics analysis identifies key genes and colocalized signals associated with colorectal cancer risk.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Integrative Transcriptomic and Genetic Analysis PrioritizesClinical, cosmetic and investigational dermatology · 2026Article
- Identify MTDH as a Key Gene of Radio-Resistance in Colorectal Cancer Based on Multi-Omics and Experimental Validation.Oncology research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundColorectal cancer (CRC) affects approximately 1.9 million people globally each year. While CRC development involves complex genetic and environmental interactions, the underlying molecular mechanisms remain incompletely understood. This study integrated multi-omics data to investigate gene-CRC associations across methylation, expression, and protein levels.
methodsWe obtained summary statistics from methylation QTL (mQTL), expression QTL (eQTL), and protein QTL (pQTL) studies. CRC genetic associations were derived from a meta-analysis of 31 GWAS datasets (100,204 cases, 154,587 controls). Summary data-based Mendelian randomization (SMR) analysis assessed associations between molecular features and CRC risk, followed by colocalization analysis to identify shared causal variants. Functional enrichment analysis was performed using Gene Ontology (GO) and KEGG pathway databases.
resultsSMR analysis identified 2,387 methylation associations (837 genes) and 707 expression associations with CRC. Integration revealed 158 overlapping genes, with six proteins (CCM2, FTCD, ICAM1, LTA, PCSK7, TNFSF14) validated for CRC association. Four genes—CCM2, FTCD, ICAM1, and TNFSF14—showed consistent effects across expression and protein levels. Higher CCM2 and TNFSF14 levels were protective, while higher FTCD and ICAM1 levels increased CRC risk. Colocalization analysis confirmed that CCM2 (PPH4 = 0.857) and ICAM1 (PPH4 = 0.812) share genetic variants with CRC. Functional enrichment analysis revealed significant involvement in immune-related processes, including interferon-gamma signaling, antigen presentation, and NF-kappa B pathway, as well as cell adhesion and endoplasmic reticulum functions.
conclusionsOur multi-omics integration identified CCM2 and ICAM1 as genes causally associated with CRC risk through shared genetic architecture. Functional analysis highlighted their roles in immune regulation and cell adhesion processes. These findings enhance understanding of CRC pathogenesis and highlight potential therapeutic targets.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.