Single‐cell spatial transcriptomic sequencing and machine learning models uncover molecular mechanisms and diagnostic biomarkers of Peyronie's disease formation in rats

Abstract Peyronie's disease (PD), commonly known as penile induration, is a prevalent male reproductive system disorder with complex etiology. It is characterized by fibrosis of the tunica albuginea (TA), which may be accompanied by pain, deformity, erectile dysfunction, discomfort, and/or dissatisfaction with self‐image. This study aimed to investigate molecular and cellular changes in PD using single‐cell spatial transcriptomics. In this study, we induced PD by injecting adenovirus transforming growth factor‐β1 (TGF‐β1) into the TA of rats. The model was successfully induced after 45 days. We conducted single‐cell spatial transcriptomics sequencing and analysis on penile tissues from three PD‐induced rats and three sham‐operated control rats. Unbiased clustering of 28,779 cell nuclei from PD‐induced and sham‐operated control rats revealed 11 cell lineages and 29 clusters. Comparative analysis identified lineage‐specific alterations in gene expression, clusters composition, and intercellular communication in PD. Combining spatial transcriptomics data, we localized 17 cell clusters on rat penile tissue sections and confirmed the spatial activity patterns of these clusters, potential disease‐related differential genes, and signaling pathways. Differential regulatory network analysis of fibroblast cluster enriched for the unfolded protein response, ribosome pathway, and Egfr smrte pathway. Through single‐cell machine learning, we constructed diagnostic evaluation models for PD and found that LOC106360841 (Rpl37‐ps5), LOC102555453, Klf9, RT1‐A1, and Oasl2 have potential as biomarkers. By integrating differential gene expression and enriched pathways, we propose a potential PD mechanism. Dysfunctions in ribosomal proteins (e.g., LOC106360841/Rpl37‐ps5 and LOC102555453), the ribosome pathway, and unfolded protein response stress response induce endoplasmic reticulum stress in rat penile tissue. This activates fibroblasts, driving extracellular matrix production and deposition, and causing penile fibrosis. Additionally, Lum may promote this process via TGF‐β pathway activation. These findings enhance our understanding of PD's molecular mechanisms and diagnostic biomarkers, with potential clinical implications for prediction and management.

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Journal
Open Research (University of Surrey)
Published
2025-05-01
DOI
https://doi.org/10.1002/viw.20250011
Primary Topic
Reproductive System and Pregnancy
Type
article
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article

Single‐cell spatial transcriptomic sequencing and machine learning models uncover molecular mechanisms and diagnostic biomarkers of Peyronie's disease formation in rats

Keyuan Lou, Qiancheng Mao, Hao Guo, Yuanshan Cui et al.
Open Research (University of Surrey)
Reproductive System and Pregnancy
article

Single‐cell spatial transcriptomic sequencing and machine learning models uncover molecular mechanisms and diagnostic biomarkers of Peyronie's disease formation in rats

Keyuan Lou, Qiancheng Mao, Hao Guo, Yuanshan Cui, Junpeng Chi, Jiankun Zhang, Jitao Wu
article en

Abstract

Abstract Peyronie's disease (PD), commonly known as penile induration, is a prevalent male reproductive system disorder with complex etiology. It is characterized by fibrosis of the tunica albuginea (TA), which may be accompanied by pain, deformity, erectile dysfunction, discomfort, and/or dissatisfaction with self‐image. This study aimed to investigate molecular and cellular changes in PD using single‐cell spatial transcriptomics. In this study, we induced PD by injecting adenovirus transforming growth factor‐β1 (TGF‐β1) into the TA of rats. The model was successfully induced after 45 days. We conducted single‐cell spatial transcriptomics sequencing and analysis on penile tissues from three PD‐induced rats and three sham‐operated control rats. Unbiased clustering of 28,779 cell nuclei from PD‐induced and sham‐operated control rats revealed 11 cell lineages and 29 clusters. Comparative analysis identified lineage‐specific alterations in gene expression, clusters composition, and intercellular communication in PD. Combining spatial transcriptomics data, we localized 17 cell clusters on rat penile tissue sections and confirmed the spatial activity patterns of these clusters, potential disease‐related differential genes, and signaling pathways. Differential regulatory network analysis of fibroblast cluster enriched for the unfolded protein response, ribosome pathway, and Egfr smrte pathway. Through single‐cell machine learning, we constructed diagnostic evaluation models for PD and found that LOC106360841 (Rpl37‐ps5), LOC102555453, Klf9, RT1‐A1, and Oasl2 have potential as biomarkers. By integrating differential gene expression and enriched pathways, we propose a potential PD mechanism. Dysfunctions in ribosomal proteins (e.g., LOC106360841/Rpl37‐ps5 and LOC102555453), the ribosome pathway, and unfolded protein response stress response induce endoplasmic reticulum stress in rat penile tissue. This activates fibroblasts, driving extracellular matrix production and deposition, and causing penile fibrosis. Additionally, Lum may promote this process via TGF‐β pathway activation. These findings enhance our understanding of PD's molecular mechanisms and diagnostic biomarkers, with potential clinical implications for prediction and management.

Open Research (University of Surrey)Vol. 6(4)
Qingdao University (CN), Yuhuangding Hospital (CN), Weifang People's Hospital (CN)
Openalex Percentile: Top 90%
Reproductive System and Pregnancy
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