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

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.

The Role of Somatic Mutations on the Immune Response of the Tumor Microenvironment in Prostate Cancer

“…Importantly, scRNA-seq can assess the mutational heterogenicity and transcriptional pathways in cell populations present in the bulk tumor and the TME in an unbiased fashion at the level of individual cells. There are a number of recent examples of scRNA-seq analysis of PCa, which have investigated the heterogeneity of tumors at the single-cell level [42,105,106].…”

Single-Cell Transcriptome Profiling Reveals Neutrophil Heterogeneity and Functional Multiplicity in the Early Stage of Severe Burn Patients

“…Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing subsets of immune cells and their corresponding functions ( 14 , 15 ). To explore the heterogeneity and functional changes in PMNs in severely burned patients, we used single-cell sequencing to detect circulating PMNs in healthy and burned groups.…”

SCReadCounts: Estimation of cell-level SNVs from scRNA-seq data

“…We have explored a variety of SCReadCounts applications on over 300,000 single cells from 6 different studies on normal and tumor human samples, including adipose tissue, adrenal neuroblastoma, acute myeloid leukemia, non-small lung cancer, prostate carcinoma, and the MCF7 cell line derived from breast adenocarcinoma [12,[24][25][26][27][28][29][30]. Here we demonstrate three different SCReadCounts applications on 59,884 cells derived from seven neuroblastoma samples [26]: (1) estimation of cell level expression of known somatic mutations and RNA-editing sites, (2) estimation of cell level allele expression from biallelic positions as called in the pooled scRNA-seq data, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest.…”