CD45⁺ hybrid circulating cells may reflect tumor-immune interactions and serve as transcriptomic indicators of metastatic potential in prostate cancer

<b>Rationale:</b> 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 <i>KRT18</i> (pan-cytokeratin) and <i>PTPRC</i> (CD45), termed KP_Pos, in metastatic prostate cancer (mPCa), and to assess their molecular features, tumor microenvironmental (TME) origins, and clinical relevance. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> 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.

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Publication Details

Journal
Theranostics
Published
2025-11-20
DOI
https://doi.org/10.7150/thno.122226
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81

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article

CD45⁺ hybrid circulating cells may reflect tumor-immune interactions and serve as transcriptomic indicators of metastatic potential in prostate cancer

Minseok S. Kim, Jungchan Jung, Jihee Jung, Yeonsue Jang et al.
1 citations
Theranostics
Single-cell and spatial transcriptomics
0.81
article

CD45⁺ hybrid circulating cells may reflect tumor-immune interactions and serve as transcriptomic indicators of metastatic potential in prostate cancer

Minseok S. Kim, Jungchan Jung, Jihee Jung, Yeonsue Jang, Baek Gil Kim, Hyeong Jung Woo, Jae Young Joung, Woon‐Hae Kim, D. Song, Hyun Ho Han, Min Kim, Jong Soo Lee, Nam Hoon Cho, Hyun Young Shin, Ayoung Yoo
article en
1 citations

Abstract

<b>Rationale:</b> 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 <i>KRT18</i> (pan-cytokeratin) and <i>PTPRC</i> (CD45), termed KP_Pos, in metastatic prostate cancer (mPCa), and to assess their molecular features, tumor microenvironmental (TME) origins, and clinical relevance. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> 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.

TheranosticsVol. 16(3)
Daegu Gyeongbuk Institute of Science and Technology (KR), Yonsei University (KR), National Cancer Center (US), National Cancer Center (KR)
National Research Foundation, Ministry of Education, Korea Health Industry Development Institute, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
0.81
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