Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing

Nowadays, chronic benign and malignant prostatic diseases are prevalent, costly, and impose a significant burden. Benign prostatic hyperplasia (BPH), a common condition in the aging population, often coexists with localized prostate cancer (PCa). These diseases likely share underlying molecular mechanisms, which remain poorly understood. The exploration of novel cell subpopulations and specific biomarkers for accurate diagnosis and treatment of prostatic diseases is ongoing and holds great clinical promise. Prostate cell proliferation and immune inflammation are key contributors to the progression of BPH and PCa, involving various prostate and immune cell subpopulations. This raises important questions about how specific cell types drive phenotypic heterogeneity. Advanced single-cell RNA sequencing (scRNA-seq), a cutting-edge technology, offers unparalleled insights at the single-cell level. Similar to a microscope that identifies cell types within tissue samples, scRNA-seq elucidates cellular heterogeneity and diversity within single cell populations, positioning itself as a future-leading sequencing technology. Considering that BPH and PCa share androgen-dependent growth, chronic inflammation and specific microenvironmental changes, this review discusses recent discoveries of novel cell subpopulations and molecular signatures in BPH and PCa that can be dissected by scRNA-seq. It aims to help researchers better understand the molecular pathogenesis of these conditions while offering new therapeutic possibilities for clinical management of benign and malignant prostatic disorders.

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Publication Details

Journal
Frontiers in Immunology
Published
2026-01-09
DOI
https://doi.org/10.3389/fimmu.2025.1684895
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing

He Ma, Bingjie Lai, Yu Pan
Frontiers in Immunology
Single-cell and spatial transcriptomics
article

Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing

He Ma, Bingjie Lai, Yu Pan
article en

Abstract

Nowadays, chronic benign and malignant prostatic diseases are prevalent, costly, and impose a significant burden. Benign prostatic hyperplasia (BPH), a common condition in the aging population, often coexists with localized prostate cancer (PCa). These diseases likely share underlying molecular mechanisms, which remain poorly understood. The exploration of novel cell subpopulations and specific biomarkers for accurate diagnosis and treatment of prostatic diseases is ongoing and holds great clinical promise. Prostate cell proliferation and immune inflammation are key contributors to the progression of BPH and PCa, involving various prostate and immune cell subpopulations. This raises important questions about how specific cell types drive phenotypic heterogeneity. Advanced single-cell RNA sequencing (scRNA-seq), a cutting-edge technology, offers unparalleled insights at the single-cell level. Similar to a microscope that identifies cell types within tissue samples, scRNA-seq elucidates cellular heterogeneity and diversity within single cell populations, positioning itself as a future-leading sequencing technology. Considering that BPH and PCa share androgen-dependent growth, chronic inflammation and specific microenvironmental changes, this review discusses recent discoveries of novel cell subpopulations and molecular signatures in BPH and PCa that can be dissected by scRNA-seq. It aims to help researchers better understand the molecular pathogenesis of these conditions while offering new therapeutic possibilities for clinical management of benign and malignant prostatic disorders.

Frontiers in ImmunologyVol. 16
Second Affiliated Hospital of Jilin University (CN)
Good health and well-being
Openalex Percentile: Top 93%
Single-cell and spatial transcriptomics
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