Evidence map›Paper›PMID 40595026›Full record

ArticleScientific reports2025

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Zhaohui Wu, Liuliu Cao, Jie Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Zhaohui WuDigestive System Department, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Liuliu CaoDepartment of Emergency, The Affiliated Hospital of North China University of Science and Technology, Tangshan, Hebei, China.
Jie ZhaoDigestive System Department, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China. zhaojie1710@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular mechanisms and prognostic biomarkers remain poorly characterized. This study aimed to identify novel biomarkers linking CRC and T2DM pathogenesis and evaluate their clinical utility in predicting therapeutic responses and survival outcomes. By integrating multi-omics data from public repositories and applying machine learning-driven feature selection, we identified three core biomarkers-FABP4,CDR2L,and FSTL3 that independently predicted overall survival in CRC patients with diabetes. A prognostic nomogram combining these biomarkers with clinicopathological variables (tumor stage, grade, and age) achieved high accuracy for 1-, 3-, and 5-year survival prediction. Functional characterization revealed strong associations between biomarker overexpression and tumor microenvironment remodeling, particularly through fibroblast-mediated immune cell recruitment and cross-talk with lymphocytes. Critically, low expression of these genes correlated with improved anti-PD-1 immunotherapy responses in an independent clinical cohort. Our findings establish FABP4, CDR2L, and FSTL3 as pivotal regulators at the CRC-diabetes interface, with dual utility as prognostic indicators and predictors of immunotherapy efficacy.

Indexed as

Colorectal NeoplasmsDiabetes Mellitus, Type 2TranscriptomeTumor MicroenvironmentAgedBiomarkers, TumorFatty Acid-Binding ProteinsFemaleFollistatin-Related ProteinsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, TumorFABP4 protein, humanFatty Acid-Binding ProteinsFollistatin-Related ProteinsColorectal cancerMachine learningSingle-cellType 2 diabetes mellitus

Identifiers

PMID40595026
PMCPMC12215021

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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.