Evidence mapPaperPMID 40438869Full record

ArticleOncology letters2025

Comprehensive analysis of a palmitoylation-related prognostic signature in colorectal cancer: Implications for immune therapy and personalized treatment.

Xiaokang Wang, Jian Li, Zi Wang, Qingyun Wu

Abstract read
In one paragraph

Article in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

1 citing paper in PubMed.

  1. Article
4 · The record

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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

4 authors.

Xiaokang WangDepartment of Medical Oncology, Xianning Central Hospital, The First Affiliated Hospital of Hubei Institute of Science and Technology, Xianning, Hubei 437000, P.R. China.
Jian LiDepartment of Gastroenterology, Xianning Central Hospital, The First Affiliated Hospital of Hubei Institute of Science and Technology, Xianning, Hubei 437000, P.R. China.
Zi WangCollege of Medicine, Hubei Three Gorges Polytechnic, Yichang, Hubei 443000, P.R. China.
Qingyun WuDepartment of Gastrointestinal Surgery, Xianning Central Hospital, The First Affiliated Hospital of Hubei Institute of Science and Technology, Xianning, Hubei 437000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) remains one of the leading causes of cancer-associated mortality worldwide. While immune checkpoint inhibitors have shown promise in treatment, there is a need for reliable biomarkers to predict patient prognosis and guide personalized therapies. Palmitoylation, a post-translational modification, has been implicated in various cancer processes, yet its role in CRC prognosis remains unclear. Transcriptome, survival, somatic mutation and copy number variation data were retrieved from The Cancer Genome Atlas, and the GSE17538 dataset was used for external validation. A palmitoylation-related risk signature was developed using univariate Cox regression, Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analyses. Patients were stratified into high- and low-risk groups based on the median risk score. Prognostic accuracy was assessed using receiver operating characteristic curves and Kaplan-Meier overall survival (OS) analysis with validation in an independent cohort. Functional enrichment, immune cell infiltration and drug sensitivity analyses were performed to explore underlying mechanisms and therapeutic implications. Subsequently, keratin 8 pseudogene 12 (KRT8P12) overexpression was evaluated in HT29 cells, and knockdown HT29 cell lines were generated using lentivirus. Cell proliferation was assessed using Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays, cell migration was evaluated by Transwell assay and cell apoptosis was assessed using Annexin-V/propidium iodide staining. A palmitoylation-related risk signature consisting of six genes (KRT8P12, ZDHHC3, PCOLCE2, MPP2, LARS2 and MMAA) was identified. High-risk patients exhibited significantly worse OS (HR=3.19; P<0.001) compared with low-risk patients. Immune cell infiltration analysis revealed enhanced immune activity in the low-risk group, which was associated with higher expression of immune checkpoint genes. Immunotherapy prediction models indicated that low-risk patients might benefit more from immune checkpoint inhibitors. Drug sensitivity analysis identified distinct drug response profiles between the high- and low-risk groups. Furthermore,

Indexed as

CRCimmune cell infiltrationimmunotherapypalmitoylationprognostic signature

Identifiers

PMID40438869
PMCPMC12117421

What Socratic holds

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