Systematic Multi-Omics Investigation of Androgen Receptor Driven Gene Expression and Epigenetics changes in Prostate Cancer.
Lin LiKyung Hyun ChoXiuping YuSiyuan ChengPublished in: bioRxiv : the preprint server for biology (2024)
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.
Keyphrases
- prostate cancer
- transcription factor
- gene expression
- radical prostatectomy
- genome wide
- genome wide identification
- data analysis
- dna methylation
- single cell
- electronic health record
- dna binding
- dna damage
- big data
- mental health
- induced apoptosis
- cell adhesion
- machine learning
- stem cells
- signaling pathway
- rna seq
- copy number
- social media
- drug induced
- cell death
- replacement therapy
- stress induced
- bone marrow
- endothelial cells