A novel DNA methylation signature is associated with androgen receptor activity and patient prognosis in bone metastatic prostate cancer

Abstract

Background Patients with metastatic prostate cancer (PC) are treated with androgen deprivation therapy (ADT) that initially reduces metastasis growth, but after some time lethal castration-resistant PC (CRPC) develops. A better understanding of the tumor biology in bone metastases is needed to guide further treatment developments. Subgroups of PC bone metastases based on transcriptome profiling have been previously identified by our research team, and specifically, heterogeneities related to androgen receptor (AR) activity have been described. Epigenetic alterations during PC progression remain elusive and this study aims to explore promoter gene methylation signatures in relation to gene expression and tumor AR activity. Materials and methods Genome-wide promoter-associated CpG methylation signatures of a total of 94 tumor samples, including paired non-malignant and malignant primary tumor areas originating from radical prostatectomy samples (n = 12), and bone metastasis samples of separate patients with hormone-naive (n = 14), short-term castrated (n = 4) or CRPC (n = 52) disease were analyzed using the Infinium Methylation EPIC arrays, along with gene expression analysis by Illumina Bead Chip arrays (n = 90). AR activity was defined from expression levels of genes associated with canonical AR activity. Results Integrated epigenome and transcriptome analysis identified pronounced hypermethylation in malignant compared to non-malignant areas of localized prostate tumors. Metastases showed an overall hypomethylation in relation to primary PC, including CpGs in the AR promoter accompanied with induction of AR mRNA levels. We identified a Methylation Classifier for Androgen receptor activity (MCA) signature, which separated metastases into two clusters (MCA positive/negative) related to tumor characteristics and patient prognosis. The MCA positive metastases showed low methylation levels of genes associated with canonical AR signaling and patients had a more favorable prognosis after ADT. In contrast, MCA negative patients had low AR activity associated with hypermethylation of AR-associated genes, and a worse prognosis after ADT. Conclusions A promoter methylation signature classifies PC bone metastases into two groups and predicts tumor AR activity and patient prognosis after ADT. The explanation for the methylation diversities observed during PC progression and their biological and clinical relevance need further exploration.

Establishment of a Novel Combined Nomogram for Predicting the Risk of Progression Related to Castration Resistance in Patients With Prostate Cancer

“…With the rapid development of genomics, a large number of genomic data were obtained from the microarray chip and high-throughput sequencing, which helped us to better understand the tumor heterogeneity and guide future clinical decision-making ( Miyamoto et al, 2018 ; Labrecque et al, 2019 ; Puhr et al, 2021 ; Ylitalo et al, 2021 ). For example, the SPP1 gene was identified as an extracellular matrix signature, which was remarkably up-regulated in mCRPC and may be a novel therapeutic target for mCRPC patients ( Pang et al, 2019 ).…”

Epithelial and Stromal Characteristics of Primary Tumors Predict the Bone Metastatic Subtype of Prostate Cancer and Patient Survival after Androgen-Deprivation Therapy

“…The duration of the initially favorable response is highly variable between patients. We have shown that human PC bone metastases can be separated into different subgroups with different transcriptome, proteome, metabolome, genetics, epigenetics, immune phenotypes, clinical behavior, and response to standard treatments [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Or in other words, there are different types of aggressive PC.…”

Feature Selection of OMIC Data by Ensemble Swarm Intelligence Based Approaches

“…The dataset GSE173330 supplied DNA methylation data from several tissues in toothed whales ( N = 254) and dolphin ( N = 291) ( Robeck et al, 2021 ). The last dataset GSE174613 analyzed samples of non-malignancy obtained from prostatectomy specimens ( n = 12) and of bone metastasis tissue samples obtained from separate prostate cancer patients ( n = 70) ( Ylitalo et al, 2021 ).…”