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Updated: Jun 18, 2025
Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients
Published on: November 19, 2019
Systematic Multi-Omics Investigation of Androgen Receptor Driven Gene Expression and Epigenetics changes in Prostate
Lin Li1,2, Kyung Hyun Cho1, Xiuping Yu1,2,3
1Department of Biochemistry and Molecular biology, LSU Health Shreveport, Shreveport, LA.
Background:
Prostate cancer, a common malignancy, is driven by androgen receptor (AR) signaling. Understanding the function of AR signaling is critical for prostate cancer research.
Methods:
We performed multi-omics data analysis for the AR+, androgen-sensitive LNCaP cell line, focusing on gene expression (RNAseq), chromatin accessibility (ATACseq), and transcription factor binding (ChIPseq). High-quality datasets were curated from public repositories and processed using state-of-the-art bioinformatics tools.
Results:
Our analysis identified 1004 up-regulated and 707 down-regulated genes in response to androgen deprivation therapy (ADT) which diminished AR signaling activity. Gene-set enrichment analysis revealed that AR signaling influences pathways related to neuron differentiation, cell adhesion, P53 signaling, and inflammation. ATACseq and ChIPseq data demonstrated that as a transcription factor, AR primarily binds to distal enhancers, influencing chromatin modifications without affecting proximal promoter regions. In addition, the AR-induced genes maintained higher active chromatin states than AR-inhibited genes, even under ADT conditions. Furthermore, ADT did not directly induce neuroendocrine differentiation in LNCaP cells, suggesting a complex mechanism behind neuroendocrine prostate cancer development. In addition, a publicly available online application LNCaP-ADT (https://pcatools.shinyapps.io/shinyADT/) was launched for users to visualize and browse data generated by this study.
Conclusion:
This study provides a comprehensive multi-omics dataset, elucidating the role of AR signaling in prostate cancer at the transcriptomic and epigenomic levels. The reprocessed data is publicly available, offering a valuable resource for future prostate cancer research.
