Evidence map›Paper›PMID 41511578›Full record

ArticleInternational journal of colorectal disease2026

The subtype identification of colorectal cancer and construction of the risk model based on cholesterol synthesis-related genes to predict prognosis and guide immunotherapy.

Qing Sun, Ruolin Sun, Bokun He, Hongjie Meng, Jie Jin

Abstract read
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Article in International journal of colorectal disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Qing Sun *Department of Gastroentero-Anorectal Surgery, Zhuji People's Hospital of Zhejiang Province, 9 Jianmin Road, Taozhu Street, Zhuji City, Shaoxing City, Zhejiang Province, 311800, China.
Ruolin Sun *Hangzhou Medical College, Hangzhou City, Zhejiang Province, 310000, China.
Bokun HeDepartment of General Surgery, Zhuji People's Hospital of Zhejiang Province, Zhuji City, Shaoxing City, Zhejiang Province, 311800, China.
Hongjie MengDepartment of Gastroentero-Anorectal Surgery, Zhuji People's Hospital of Zhejiang Province, 9 Jianmin Road, Taozhu Street, Zhuji City, Shaoxing City, Zhejiang Province, 311800, China.
Jie JinDepartment of Gastroentero-Anorectal Surgery, Zhuji People's Hospital of Zhejiang Province, 9 Jianmin Road, Taozhu Street, Zhuji City, Shaoxing City, Zhejiang Province, 311800, China. Jie_Jinn@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColorectal cancer (CRC) is a common malignant tumor worldwide. The cholesterol synthesis (CS) pathway is crucial in the occurrence and development of cancer. This study aims to predict the prognosis of CRC patients based on the cholesterol synthesis-related genes (CSRGs).

methodsThe patient data of CRC were downloaded from the TCGA and GEO databases, and the CSRGs were downloaded from Genecards. In the TCGA-CRC training set, univariate Cox regression analysis was conducted on the CSRGs, and subtype classification was performed through consensus clustering. Combined with the PPI network and regression analysis, key CSRGs were identified to establish a prognostic model. ROC curves and Kaplan-Meier survival analysis were used to evaluate the model and validate it in the GSE17538 validation set. At the same time, immune analysis and drug sensitivity analysis were conducted. Finally, the functions of these characteristic genes were investigated in an in vitro cell model.

resultsThe TCGA-CRC was divided into two subtypes. A 10-gene Cholesterol Synthesis-related Risk Signature (CSRS) was constructed. The patients were grouped according to the median value of the CSRS. The high-CSRS group had a poorer prognosis, and the abundance of macrophages, neutrophils, and TIL was higher in this group. The drug sensitivity prediction indicated that several candidate drugs (such as Linsitinib) might affect the progression of CRC through unique mechanisms. In vitro experiments demonstrated that EEF1A2 could promote the malignant progression of tumors.

conclusionThe results of this project provide some guidance for elucidating potential CS-related biomarkers for predicting prognosis in CRC patients.

Indexed as

CholesterolColorectal NeoplasmsImmunotherapyBiomarkers, TumorCell Line, TumorGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimatePrognosisBiomarkers, TumorCholesterolCholesterol synthesisColorectal cancerImmunotherapyPrognosisSubtype

Identifiers

PMID41511578
PMCPMC12789220

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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.