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Genome scale analysis of DNA methylation patterns in prostate cancer patient derived xenograft models [EPIC Set 1]

ABSTRACT: DNA methylation alterations are a universal feature of cancer. In prostate cancer, site specific DNA methylation changes have been suggested as driver in disease initial and progression. Here we provide a comprehensive assessment of DNA methylation changes in prostate cancer patient derived xenograft (PDX) models. We delineate patterns of both site specific and global methylation changes and nominate novel candidates for biomarker development. Genome wide DNA methylation profiling of prostate cancer patient derived xenograft and cell line models using Infinium EPIC arrays

ORGANISM(S): Homo sapiens

PROVIDER: GSE227814 | GEO | 2023/12/31

REPOSITORIES: GEO

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Project description:Prostate cancer incidence and related mortality are disproportionately higher in African American (AA) men than European American (EA) men, but the molecular mechanisms contributing to racial disparities are not fully elucidated. To identify molecular factors that can contribute to disease biology in prostate cancer from AA and EA men, we utilized a multi-omics approach to measure and integrate DNA methylation with gene expression changes. We compared and contrasted results from adjacent non-tumor and tumor tissues from AA and EA men. We found that hypermethylated regions are enriched for PRC2 and H3K27me3 pathways and EZH2/SUZ12 cofactors in a race-independent manner. On the other hand, hypomethylated regions in prostate tumors from AA men were enriched for olfactory/ribosomal pathways as well as distinct cofactors such as CTCF and KMT2A. DNA methylation at transcription start sites and 5’-UTR at GATA3, an androgen receptor (AR) coregulator, is associated with decreased gene expression in prostate tumors of AA men. Our analysis also showed an inverse correlation between DNA methylation and RNA expression of AR transcriptional targets, such as TRIM63, in prostate tumors of AA men. Our observations suggest a dysregulation of the AR signaling pathway in prostate cancer from AA men. To determine whether targeting AR results in race-specific gene expression changes, we utilized a prostate-cancer-specific Boolean network. Our simulation revealed that prolonged AR inhibition results in significant dysregulation in TGF-β, IDH1, and cell cycle pathways in prostate cancer of AA men. We expanded our observation of gene expression changes in the Boolean network and investigated RNA-sequencing data to better understand overall transcriptional alterations occurring in prostate tumors from AA and EA men. We found that gene expression changes related to microtubules, a subset of immune-related, and TMPRSS2-fusion pathways were dysregulated in prostate tumors of AA men and corresponded with progression-free survival of AA men. Altogether, the current study dissects complex signaling networks that are clinically actionable in prostate cancer from AA and EA men.

Dataset Information

Genome scale analysis of DNA methylation patterns in prostate cancer patient derived xenograft models [EPIC Set 1]

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