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

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. 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. 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. PTK6 emerges as a critical immune infiltration-related prognostic biomarker through single-cell transcriptomic analysis.