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Article Abstract
Background: Cervical 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.
Methods: We 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.
Results: Single-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.
Conclusion: PTK6 emerges as a critical immune infiltration-related prognostic biomarker through single-cell transcriptomic analysis.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357816 | PMC |
| http://dx.doi.org/10.1007/s12672-025-03365-7 | DOI Listing |
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