Evidence map›Paper›PMID 41612047›Full record

ArticleHuman cell2026

Construction of a risk model based on exosome-related genes predict clinical prognosis and therapeutic response and revealing TIMP1 as a promising target in colorectal cancer.

Xinyu Gao, Te Zhang, Tianhao Li, Yongdan Zhang, Xipeng Zhang, Haoren Jing

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Article in Human cell, 2026. 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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5 · Who and what money

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6 authors.

Xinyu GaoDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China.
Te ZhangDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China.
Tianhao LiDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China.
Yongdan ZhangDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China.
Xipeng ZhangDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China.
Haoren JingDepartment of Colorectal Surgery, Tianjin Union Medical Center, The First Affiliated Hospital of Nankai University, Tianjin, China. jinghaoren@mail.nankai.edu.cn.

Funding

Tianjin Key Medical Discipline(Specialty) Construction Project NO:TJYXZDXK-044A
6 · The paper itself

Abstract

Various exosome-derived proteins have been reported to play essential roles in regulating colorectal cancer progression and affecting the prognosis of cancer patients. It is necessary to explore the critical exosome-related genes in colorectal cancer. In this study, 23 differentially expressed exosome-related genes associated with prognosis in colorectal cancer (CRC) were identified based on two datasets, The Cancer Genome Atlas (TCGA) and exoRbase. Based on machine learning-Boruta and lasso-Cox regression-nine essential genes were finally identified, and a risk model was constructed. The risk model was able to predict the prognosis of the patients well. Specifically, the prognosis of high-risk patients was worse, and the prognosis of low-risk patients was better. Multivariate Cox regression revealed that the risk model was an independent prognostic factor. Mechanism studies showed that pathways such as MYOGENESIS, APICAL JUNCTION, Epithelial-Mesenchymal Transition (EMT), ANGIOGENESIS, and KRAS SIGNALING DN were highly enriched in the high-risk group. In addition, tumor-promoting immune cells, such as Treg cells and macrophages, exhibited increased activity in the high-risk group, suggesting that high-risk patients may be less responsive to immunotherapy. Furthermore, in multiple external immunotherapeutic and chemotherapeutic datasets, we found that high-risk patients are less sensitive to therapy than low-risk patients, suggesting that this risk score may predict immune and chemotherapy response. Scoring the importance of nine genes, we found that TIMP1 was the most critical exosome-related gene in colorectal cancer patients. Knockdown of TIMP1 in colorectal cancer cells significantly inhibited the proliferation and migration of colorectal cancer cells. In conclusion, we identified several crucial colorectal cancer exosome-associated genes using public datasets and machine learning, and constructed risk models to predict prognosis and response to immunotherapy. TIMP1 was further identified as a critical oncogene in patients with colorectal cancer. Our results provide a theoretical basis for subsequent exosome-based preclinical trials.

Indexed as

Colorectal NeoplasmsExosomesGene ExpressionMolecular Targeted TherapyTissue Inhibitor of Metalloproteinase-1Epithelial-Mesenchymal TransitionHumansImmunotherapyPrognosisRiskTIMP1 protein, humanTissue Inhibitor of Metalloproteinase-1Clinical prognosis modelColorectal cancerExosomesTIMP1

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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.