Evidence map›Paper›PMID 40987803›Full record

ArticleScientific reports2025

Comprehensive characterization of the molecular feature of acetylation in colorectal cancer using integrated single-cell and bulk RNA sequencing.

Kai Li, Wei Song, Yuefeng Zhang, Jianfei Luo

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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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Kai Li *Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, No. 238, Jiefang Road, Wuhan, 430060, Hubei, China.
Wei Song *Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, No. 238, Jiefang Road, Wuhan, 430060, Hubei, China.
Yuefeng Zhang *Department of Hepatobiliary Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.
Jianfei LuoDepartment of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, No. 238, Jiefang Road, Wuhan, 430060, Hubei, China. luojianfei@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) remains a major global health burden with high mortality rates, underscoring the need for effective therapies. This study explores the acetylation characteristics in CRC using single-cell RNA sequencing (scRNA-seq) and weighted gene co-expression network analysis (WGCNA), assessing their relationship with prognosis and the immune microenvironment. We analyzed two scRNA-seq datasets from the GEO database to identify distinct cell subtypes. Acetylation activity scores were calculated using the ssGSEA method. A WGCNA was constructed to identify gene modules associated with acetylation. An acetylation-related prognostic signature (ARPS) was developed, and its clinical significance was evaluated through survival analysis and immune landscape characterization. Acetylation activity was significantly elevated in epithelial, endothelial, and stromal cells. Based on the results of scRNA-seq, WGCNA identified 169 acetylation-related genes. Intersection with 1,691 acetylation-related differentially expressed genes (DEGs) yielded 131 common genes. Combining clinical data with the expression profiles of these genes, we employed 101 machine learning algorithms to develop an ARPS that accurately predicts the prognosis of CRC patients. Low-risk patients showed increased infiltration of immune cells, enhanced immune function, and better responses to immunotherapy. These findings underscore the clinical significance of acetylation features in CRC prognosis and immune response, highlighting their potential as biomarkers and therapeutic targets.

Indexed as

Colorectal NeoplasmsSingle-Cell AnalysisAcetylationBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisSequence Analysis, RNATumor MicroenvironmentBiomarkers, TumorAcetylationColorectal cancerImmunotherapyPrognostic modelTumor microenvironment

Identifiers

PMID40987803
PMCPMC12457583

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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.