Identification of a distinct luminal subgroup diagnosing and stratifying early stage prostate cancer by tissue-based single-cell RNA sequencing

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Mol Cancer. 2020 Oct 8;19(1):147. doi: 10.1186/s12943-020-01264-9.

ABSTRACT

BACKGROUND: The highly intra-tumoral heterogeneity and complex cell origination of prostate cancer greatly limits the utility of traditional bulk RNA sequencing in finding better biomarker for disease diagnosis and stratification. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel biomarkers. However, this technique has yet been used in the study of prostate cancer heterogeneity.

METHODS: Cell types and the corresponding marker genes were identified by single-cell RNA sequencing. Malignant states of different clusters were evaluated by copy number variation analysis and differentially expressed genes of pseudo-bulks sequencing. Diagnosis and stratification of prostate cancer was estimated by receiver operating characteristic curves of marker genes. Expression characteristics of marker genes were verified by immunostaining.

RESULTS: Fifteen cell groups including three luminal clusters with different expression profiles were identified in prostate cancer tissues. The luminal cluster with the highest copy number variation level and marker genes enriched in prostate cancer-related metabolic processes was considered the malignant cluster. This cluster contained a distinct subgroup with high expression level of prostate cancer biomarkers and a strong distinguishing ability of normal and cancerous prostates across different pathology grading. In addition, we identified another marker gene, Hepsin (HPN), with a 0.930 area under the curve score distinguishing normal tissue from prostate cancer lesion. This finding was further validated by immunostaining of HPN in prostate cancer tissue array.

CONCLUSION: Our findings provide a valuable resource for interpreting tumor heterogeneity in prostate cancer, and a novel candidate marker for prostate cancer management.

PMID:33032611 | DOI:10.1186/s12943-020-01264-9