Tumor microenvironment deconvolution identifies cell-type-independent aberrant DNA methylation and gene expression in prostate cancer.

BACKGROUND: Among men, prostate cancer (PCa) is the second most common cancer and the second leading cause of cancer death. Etiologic factors associated with both prostate carcinogenesis and somatic alterations in tumors are incompletely understood. While genetic variants associated with PCa have been identified, epigenetic alterations in PCa are relatively understudied. To date, DNA methylation (DNAm) and gene expression (GE) in PCa have been investigated; however, these studies did not correct for cell-type proportions of the tumor microenvironment (TME), which could confound results. METHODS: The data (GSE183040) consisted of DNAm and GE data from both tumor and adjacent non-tumor prostate tissue of 56 patients who underwent radical prostatectomies prior to any treatment. This study builds upon previous studies that examined methylation patterns and GE in PCa patients by using a novel tumor deconvolution approach to identify and correct for cell-type proportions of the TME in its epigenome-wide association study (EWAS) and differential expression analysis (DEA). RESULTS: The inclusion of cell-type proportions in EWASs and DEAs reduced the scope of significant alterations associated with PCa. We identified 2,093 significantly differentially methylated CpGs (DMC), and 51 genes associated with PCa, including PCA3, SPINK1, and AMACR. CONCLUSIONS: This work illustrates the importance of correcting for cell types of the TME when performing EWASs and DEAs on PCa samples, and establishes a more confounding-adverse methodology. We identified a more tumor-cell-specific set of altered genes and epigenetic marks that can be further investigated as potential biomarkers of disease or potential therapeutic targets.

Detailed immune profiling in pediatric Crohn's disease using methylation cytometry.

DNA methylation has been extensively utilized to study epigenetic patterns across many diseases as well as to deconvolve blood cell type proportions. This study builds upon previous studies examining methylation patterns in paediatric patients with varying stages of Crohn's disease to extend the immune profiling of these patients using a novel deconvolution approach. Compared with control subjects, we observed significantly decreased levels of CD4 memory and naive, CD8 naive, and natural killer cells and elevated neutrophil levels in Crohn's disease. In addition, Crohn's patients had a significantly elevated neutrophil-to-lymphocyte ratio. Using an epigenome-wide association approach and adjusting for potential confounders, including cell type, we observed 397 differentially methylated CpG (DMC) sites associated with Crohn's disease. The top genetic pathway associated with the DMCs was the regulation of arginine metabolic processes which are involved in the regulation of T cells.

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks.

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.