Evidence map›Paper›PMID 40395892›Full record

ArticleArchives of medical science : AMS2025

Investigation of potential prognostic biomarkers for colorectal cancer.

Hui Li, Jie Liu, WenHui Liu, Liang Zheng, JuHui Chen

Abstract read
In one paragraph

Article in Archives of medical science : AMS, 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

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

5 authors.

Hui LiDepartment of Abdominal Radiotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, China.
Jie LiuDepartment of Abdominal Radiotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, China.
WenHui LiuDepartment of Radiation Oncology, Mengchao Hepatobiliary Hospital of Fujian Medical University, China.
Liang ZhengDepartment of Abdominal Radiotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, China.
JuHui ChenDepartment of Abdominal Radiotherapy, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Colorectal cancer (CRC) is the third leading cause of cancer-related death. Since CRC is largely asymptomatic until the alert features develop to an advanced stage, implementation of a screening program is important to reduce cancer morbidity and mortality. Current screening methods have significant limitations. Material and methods: CRC-related microarray datasets were collected from the GEO database and differentially expressed genes (DEGs) were identified. Next, Venn analysis, functional enrichment analysis, protein interaction network (PPI) analysis, and survival analysis were performed. Results: A total of 5267 and 4233 DEGs were identified in two datasets (GSE20916, GSE33133). The intersection of up-regulated genes in the two datasets was obtained by Venn Analysis as 1058 DEGs. Among the 1058 genes, 992 genes with survival and clinical information in TCGA were screened. Eleven DEGs were identified as potential prognostic markers. Model results show that the time period with the most obvious prognostic effect is 5 years, and the AUC value is the highest. ROC curve results are consistent with the model results of the survival analysis. The survival curve showed that LRRC8A, PCAT6, PLA2G15, SRD5A1, T1GD1 may be oncogenes, and DSN1, ERI1, EIT1, GLMN, MAPKAPK, NOP14 may be tumor suppressor genes. Conclusions: This study discovers novel prognostic markers through Cox regression and survival analysis, and provides a theoretical basis for the treatment of CRC.

Indexed as

colorectal cancerprognostic biomarkertreatment

Identifiers

PMID40395892
PMCPMC12087331

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