Evidence map›Paper›PMID 40165100›Full record

ArticleBMC gastroenterology2025

Deciphering the integrated immunogenomic landscape of colorectal cancer: insights from Mendelian randomization and immune-stratified molecular subtyping.

Ke-Jie He, Guoyu Gong

Abstract read
In one paragraph

Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ke-Jie HeThe Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou city, Zhejiang Province, China. hekejie@stu.xmu.edu.cn.
Guoyu GongSchool of Medicine, Xiamen University, Xiamen, China.

Funding

Quzhou Municipal Science and Technology Bureau 2023K117
6 · The paper itself

Abstract

purposeThis study aimed to decipher the intricate interplay between the immune landscape and CRC pathogenesis, elucidating how distinct immunophenotypes causally influence disease susceptibility and stratify patient outcomes.

methodsWe obtained the immunocyte phenotypes and CRC data from their respective genome-wide association studies. The primary analysis used the inverse variance weighting (IVW) method. We also simultaneously employed MR-Egger, weighted mode, simple mode, and weighted median approaches to strengthen the findings. Consensus clustering stratified 619 TCGA CRC patients by immunome expression. Functional assays examined the tumor suppressor GPD1L.

resultsThe IVW MR analysis identified 17 immunocyte phenotypes positively potentially associated with increased CRC risk (P < 0.05, OR > 1), and 18 phenotypes negatively potentially associated with decreased CRC risk (P < 0.05, OR < 1). These associations were not confounded by heterogeneity or horizontal pleiotropy (P > 0.05). Reverse MR analysis further revealed 4 additional immunocyte phenotypes positively potentially associated with CRC (P < 0.05, OR > 1). Clustering resolved prognostic C1/C2 subtypes dependent on coordinated immunophenotypic programs. GPD1L knockdown promoted CRC cell proliferation.

conclusionsGenetic interrogation delineated causal immunome-CRC relationships at single-cell resolution. Immune-stratified CRC subtyping stratified patient outcomes. GPD1L exhibited tumor-suppressive functions. Our findings establish an integrated immunogenomic framework elucidating CRC pathogenesis with implications for precision immunotherapies.

Indexed as

Colorectal NeoplasmsGenome-Wide Association StudyHumansImmunophenotypingMendelian Randomization AnalysisPhenotypeColorectal cancerGPD1LImmune-stratified molecular subtypesImmunophenotypesMendelian randomizationTumor suppressor

Identifiers

PMID40165100
PMCPMC11959972

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.