Evidence map›Paper›PMID 40406253›Full record

ArticleFrontiers in oncology2025

Comprehensive analysis of potential biomarkers for the diagnosis and prognosis of Cervical squamous cell carcinoma - based on GEO and TCGA databases.

Yufen Chen, Qinghua Deng, Tengyue Fu, Yuxiang Huang, Houlin Li, Jingmu Xie, Feng Liao, Feimiao Zeng, Xinyi Fang, Ruiman Li and 1 more

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In one paragraph

Article in Frontiers in oncology, 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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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Yufen Chen *Department of Obstetrics and Gynecology, The First Affiliate Hospital of Jinan University, Guangzhou, Guangdong, China.
Qinghua Deng *Department of Gynaecology, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Tengyue Fu *Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Yuxiang HuangGuangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, China.
Houlin LiGuangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, China.
Jingmu XieGuangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, China.
Feng LiaoGuangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, China.
Feimiao ZengDepartment of Gynaecology, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Xinyi FangReproductive Medical Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Ruiman LiDepartment of Obstetrics and Gynecology, The First Affiliate Hospital of Jinan University, Guangzhou, Guangdong, China.
Zhuming ChenGuangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cervical squamous cell carcinoma (CESC) constitutes a substantial global health burden, especially in resource-limited regions. The identification of reliable biomarkers is critical for developing a clinically applicable nomogram to predict survival outcomes and evaluate immune infiltration in CESC patients. Methods: This study integrated RNA-seq data from GEO and TCGA databases to identify key genes associated with CESC through differential expression analysis and machine learning techniques. Prognostic models were constructed and validated, with additional analyses exploring immune cell infiltration and gene function via GSEA and clinical correlation. Finally, key genes were validated via qRT-PCR in CESC tissues. Results: A total of 112 differentially expressed genes (DEGs) were identified through differential analysis of the GEO and TCGA datasets. Conclusion:

Indexed as

biomarkercervical squamous cell carcinoma (CESC)diagnosisimmune infiltrationsurvival prognosis

Identifiers

PMID40406253
PMCPMC12094959

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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.