CD45⁺ hybrid circulating cells may reflect tumor-immune interactions and serve as transcriptomic indicators of...

Rationale: Circulating hybrid cells expressing both epithelial and immune markers have emerged as indicators of dynamic tumor-immune interactions. This study aimed to characterize circulating hybrid cells co-expressing KRT18 (pan-cytokeratin) and PTPRC (CD45), termed KP_Pos, in metastatic prostate cancer (mPCa), and to assess their molecular features, tumor microenvironmental (TME) origins, and clinical relevance. Methods: Imaging mass cytometry (IMC) was used to examine spatial relationships between CK⁺ tumor and CD45⁺ immune cells in metastatic prostate tissues. Single-cell RNA sequencing (scRNA-seq) datasets from mPCa were analyzed to identify KP_Pos cells and characterize their transcriptional heterogeneity across epithelial and immune lineages. Differentially expressed genes (DEGs) between KP_Pos and other cells were used to generate predictive gene signatures. Random forest (RF) and extreme gradient boosting (XGB) models were applied to evaluate metastatic classification performance, and high-performing signatures were validated in bulk RNA-seq datasets and correlated with clinical parameters. Results: IMC revealed frequent spatial proximity between tumor and immune compartments, supporting a TME-derived hybrid phenotype. KP_Pos cells were detected across multiple immune and epithelial clusters, showing heterogeneity and enrichment of immune response and epithelial-mesenchymal transition (EMT)-related genes. Machine learning-based classifiers using KP_Pos-derived DEGs achieved high predictive accuracy (AUC ≥ 0.7) for metastasis, and selected combinations further improved performance in internal validation sets. Signature scores significantly correlated with PSA and Gleason grade, and CD45⁺ hybrid circulating cells were more abundant in patients with advanced disease burden. Conclusions: CD45⁺ KRT18⁺ hybrid circulating cells (KP_Pos) represent biologically distinct populations shaped by tumor-immune interactions within the TME. Their transcriptomic features and derived gene signatures may serve as biomarkers of metastatic potential and indicators of disease progression in prostate cancer. However, their causal role in metastasis and impact on survival remain to be determined.