Evidence map›Paper›PMID 40667555›Full record

ArticleAmerican journal of cancer research2025

Identification of CDK2 as a key apoptotic gene for predicting cervical cancer prognosis using bioinformatics and machine learning.

Miao-Miao Li, Min Song, Shu-Xia Wu, Xing-Ye Ren

Abstract read
In one paragraph

Article in American journal of cancer research, 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
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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Miao-Miao LiSchool of Clinical Medicine, Shandong Second Medical University Weifang 261053, Shandong, China.
Min SongDepartment of Obsteric, Jinan Maternal and Child Care Hospital Jinan 250001, Shandong, China.
Shu-Xia WuDepartment of Gynecology and Obstetrics, The Fifth People's Hospital of Jinan Jinan 250022, Shandong, China.
Xing-Ye RenDepartment of Gynecology, The Forth Peoples' Hospital of Jinan Jinan 250031, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to identify apoptosis - related genes with diagnostic and prognostic value in cervical cancer (CC) using integrated bioinformatics and machine learning approaches.

methodsGene expression datasets were obtained from the National Center for Biotechnology Information Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA), with GSE192897 used as the training set. A total of 451 differentially expressed genes (DEGs) were identified, including 221 upregulated and 230 downregulated genes. Eleven apoptosis - related upregulated DEGs were selected for further analysis using three machine learning algorithms: random forest, logistic regression, and support vector machine. Validation was performed using GSE192897, GSE166466, and TCGA-CESC datasets.

resultsAmong the evaluated genes, cyclin-dependent kinase 2 (CDK2) consistently achieved an AUC > 0.8 in all three validation datasets and had a weighted sum rank > 10, meeting stringent selection criteria. In a CC mouse model, CDK2 expression was significantly elevated and positively correlated with squamous cell carcinoma antigen, carcinoembryonic antigen, vascular endothelial growth factor, and heparanase. siRNA-mediated knockdown of CDK2 reduced cell proliferation and migration while promoting apoptosis. Mice with high CDK2 expression showed significantly lower 4-week survival rates, indicating poor prognosis.

conclusionsThis study identified CDK2 as a key apoptosis - related gene with strong diagnostic and prognostic value in cervical cancer. CDK2 promotes tumor progression and is associated with poor survival, suggesting its potential as a biomarker and therapeutic target for personalized treatment strategies in CC.

Indexed as

apoptosisbioinformaticsCDK2Cervical cancerdiagnosismachine learning

Identifiers

PMID40667555
PMCPMC12256406

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