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

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 pathogen...

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Main Authors: Zhaohui Wu, Liuliu Cao, Jie Zhao
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-07015-4
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author Zhaohui Wu
Liuliu Cao
Jie Zhao
author_facet Zhaohui Wu
Liuliu Cao
Jie Zhao
author_sort Zhaohui Wu
collection DOAJ
description 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.
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spelling doaj-art-d82b70a51b9e49f8a56298b00e08a2ff2025-08-20T04:01:23ZengNature PortfolioScientific Reports2045-23222025-07-0115111710.1038/s41598-025-07015-4Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancerZhaohui Wu0Liuliu Cao1Jie Zhao2Digestive System Department, Second Hospital of Shanxi Medical UniversityDepartment of Emergency, The Affiliated Hospital of North China University of Science and TechnologyDigestive System Department, Second Hospital of Shanxi Medical UniversityAbstract 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.https://doi.org/10.1038/s41598-025-07015-4Colorectal cancerType 2 diabetes mellitusMachine learningSingle-cell
spellingShingle Zhaohui Wu
Liuliu Cao
Jie Zhao
Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
Scientific Reports
Colorectal cancer
Type 2 diabetes mellitus
Machine learning
Single-cell
title Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
title_full Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
title_fullStr Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
title_full_unstemmed Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
title_short Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
title_sort integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer
topic Colorectal cancer
Type 2 diabetes mellitus
Machine learning
Single-cell
url https://doi.org/10.1038/s41598-025-07015-4
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AT liuliucao integratedanalysisofsharedgeneexpressionsignaturesandimmunemicroenvironmentheterogeneityintype2diabetesmellitusandcolorectalcancer
AT jiezhao integratedanalysisofsharedgeneexpressionsignaturesandimmunemicroenvironmentheterogeneityintype2diabetesmellitusandcolorectalcancer