Evidence map›Paper›PMID 40818002›Full record

ArticleDiscover oncology2025

PTK6 mediated immune signatures revealed by single cell transcriptomic and multi omics big data analysis in cervical cancer.

Fen Zhao, Huanxin Zhong, Lifang You, Yi Du, Changchang Huang

Abstract read
In one paragraph

Article in Discover oncology, 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

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2 · The registry

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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

5 authors.

Fen ZhaoDepartment of Gynecology, First People's Hospital of Linping District, No. 369 Yingbin Road, Nanyuan Subdistrict, Linping District, Hangzhou, Zhejiang, China.
Huanxin ZhongDepartment of Gynecology, First People's Hospital of Linping District, No. 369 Yingbin Road, Nanyuan Subdistrict, Linping District, Hangzhou, Zhejiang, China.
Lifang YouDepartment of Gynecology, First People's Hospital of Linping District, No. 369 Yingbin Road, Nanyuan Subdistrict, Linping District, Hangzhou, Zhejiang, China.
Yi DuDepartment of Gynecology, First People's Hospital of Linping District, No. 369 Yingbin Road, Nanyuan Subdistrict, Linping District, Hangzhou, Zhejiang, China.
Changchang HuangDepartment of Gynecology, First People's Hospital of Linping District, No. 369 Yingbin Road, Nanyuan Subdistrict, Linping District, Hangzhou, Zhejiang, China. huangcc1028@163.com.

Funding

This work was supported by Medical Science and Technology Project of Zhejiang Province No.2025KY196
6 · The paper itself

Abstract

backgroundCervical cancer exhibits heterogeneous clinical outcomes, requiring improved prognostic tools. Single-cell RNA sequencing enables high-resolution analysis of tumor microenvironment cellular heterogeneity. This study developed a prognostic model for cervical cancer through single-cell transcriptomic analysis and immune infiltration characterization, focusing on PTK6 as a key biomarker.

methodsWe analyzed TCGA and GEO transcriptomic data with single-cell RNA sequencing datasets. Fifteen machine learning algorithms constructed prognostic models using immune infiltration-related genes. Single-cell analysis employed Seurat for cell clustering and annotation. PTK6 expression was validated in H8 and HeLa cell lines via RT-qPCR and siRNA knockdown experiments.

resultsSingle-cell sequencing revealed distinct cellular populations including CD8T cells, CD4Tconv cells, and fibroblasts. The prognostic model achieved excellent performance with AUC values of 0.737-0.757 across 1-5 years. PTK6 showed significantly elevated expression in tumors and strong correlations with immune infiltration. Single-cell analysis confirmed PTK6 expression across multiple cell types. Functional validation demonstrated that PTK6 knockdown reduced HeLa cell proliferation, confirming its oncogenic role.

conclusionPTK6 emerges as a critical immune infiltration-related prognostic biomarker through single-cell transcriptomic analysis.

Indexed as

Cervical cancerImmune infiltrationMachine learningPrognostic biomarkerPTK6Single-cell RNA sequencing

Identifiers

PMID40818002
PMCPMC12357816

What Socratic holds

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Registered trials

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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 Socratic graph.