Evidence map›Paper›PMID 41523911›Full record

ArticleHuman mutation2026

Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.

Tingting Zhang, Jianchao Meng, Qingyun Wang, Peng Zhang, Hui Li, Hailang Wei, Denggang Chen, Chen Bai, Sujit Nair

Abstract read
In one paragraph

Article in Human mutation, 2026. 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Corrections and comments

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

9 authors.

Tingting ZhangDepartment of Clinical Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.
Jianchao MengDepartment of Clinical Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.
Qingyun WangOtorhinolaryngology Department, Taihe Hospital, Hubei University of Medicine, Shiyan City, China, hbmu.edu.cn.
Peng ZhangDepartment of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.ORCID https://orcid.org/0009-0008-3696-7973
Hui LiDepartment of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.
Hailang WeiDepartment of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.ORCID https://orcid.org/0000-0002-6661-4019
Denggang ChenDepartment of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.ORCID https://orcid.org/0000-0003-1262-2029
Chen BaiDepartment of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.ORCID https://orcid.org/0000-0001-7964-2353
Sujit NairDepartment of Clinical Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan, China, hbmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colon cancer is one of the most prevalent malignant tumors. Accurate evaluation of patient prognosis and optimization of treatment strategies continue to be major research focuses in colon cancer. Based on The Cancer Genome Atlas (TCGA) database, this study is the first to comprehensively analyze the expression, biological roles, and prognosis of itaconate and Hallmark pathway-related genes in colon cancer using bulk transcriptomics, single-cell transcriptomics, and spatial transcriptomics data. Through strict screening in 448 colon cancer patients from TCGA database (training set) and 7 colon cancer prognostic models from the Gene Expression Omnibus (GEO) database (including 1473 cases in the validation set), 10 prognosis-related genes (TIMP1, FJX1, CD36, CXCL1, ETS2, CDKN2A, INHBB, PLEC, TUBB2, and P4HA1) were selected. The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C-index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years. ScRNAseq (GSE225857) and spatial transcriptomics analyses clarified the cell-specific expression and spatial distribution characteristics of these genes in the tumor microenvironment (TME), with high functional scores mainly enriched in epithelial and stromal cells. Tissue microarray (TMA) showed that the high-risk group had higher tumor mutation burden (TMB) and higher expression of immune checkpoint genes, suggesting higher sensitivity to immunotherapy. Drug sensitivity analysis identified four potentially effective drugs, such as sepantronium bromide, which had better effects on high-risk patients. This study provides a theoretical basis and new targets for precise prognosis and stratified treatment of colon cancer.

Indexed as

Biomarkers, TumorColonic NeoplasmsSuccinatesTranscriptomeComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisSpatial AnalysisSpatial TranscriptomicsBiomarkers, TumorSuccinatescolon cancerHallmark pathwayitaconateprognostic modelsingle-cell transcriptomicsspatial transcriptomics

Identifiers

PMID41523911
PMCPMC12790287

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.