ABSTRACT
Prostate cancer (PCa) is the most frequently diagnosed among men malignant disease that remains poorly characterized at the molecular level. Advanced PCa is not curable, and the current treatment methods can only increase the life expectancy by several months. Identification of the genetic aberrations in tumor cells provides clues to understanding the mechanisms of PCa pathogenesis and the basis for developing new therapeutic approaches. Here we present data on somatic mutations, namely single nucleotide variations (SNVs), small insertions and deletions, detected in prostate tumor tissue obtained from Russian patients with PCa. Moreover, we provide a raw dataset on the whole exome and targeted DNA sequencing of tumor and non-tumor prostate tissue obtained from Russian patients with PCa and benign prostatic hyperplasia (BPH). This data is available at NCBI Sequence Read Archive under Accession No. PRJNA506922.
ABSTRACT
There is a clear need in molecular markers for prostate cancer (PC) risk stratification. Alteration of DNA methylation is one of processes that occur during ÐÑ progression. Methylation-sensitive PCR with high resolution melting curve analysis (MS-HRM) can be used for gene methylation analysis in routine laboratory practice. This method requires very small amounts of DNA for analysis. Numerous results have been accumulated on DNA methylation in PC samples analyzed by the Infinium HumanMethylation450 BeadChip (HM450). However, the consistency of MS-HRM results with chip hybridization results has not been examined yet. The aim of this study was to assess the consistency of results of GSTP1, APC and RASSF1 gene methylation analysis in ÐÑ biopsy samples obtained by MS-HRM and chip hybridization. The methylation levels of each gene determined by MS-HRM were statistically different in the group of PC tissue samples and the samples without signs of tumor growth. Chip hybridization data analysis confirmed the results obtained with the MS-HRM. Differences in methylation levels between tumor tissue and histologically intact tissue of each sample determined by MS-HRM and chip hybridization, were consistent with each other. Thus, we showed that the assessment of GSTP1, APC and RASSF1 gene methylation analysis using MS-HRM is suitable for the design of laboratory assays that will differentiate the PC tissue from the tissue without signs of tumor growth.
Subject(s)
Adenomatous Polyposis Coli Protein , DNA Methylation , DNA, Neoplasm , Glutathione S-Transferase pi , Oligonucleotide Array Sequence Analysis/methods , Prostatic Neoplasms , Tumor Suppressor Proteins , Adenomatous Polyposis Coli Protein/genetics , Adenomatous Polyposis Coli Protein/metabolism , Adult , Aged , DNA, Neoplasm/genetics , DNA, Neoplasm/metabolism , Glutathione S-Transferase pi/genetics , Glutathione S-Transferase pi/metabolism , Humans , Male , Middle Aged , Oligonucleotide Array Sequence Analysis/instrumentation , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/genetics , Prostatic Neoplasms/metabolism , Tumor Suppressor Proteins/genetics , Tumor Suppressor Proteins/metabolismABSTRACT
Using the technology of DNA chips Infinium HumanMethylation 450 BeadChip it was analyzed quantitative DNA methylation status in 12 paired samples of prostate adenocarcinoma, and morphologically altered tissues. Analysis of differentially methylated regions of the genome showed an association with abnormal status for 21610 and 3852 hypomethylated hyper-methylated CpG sites. Dominance in the cancer genome hypermethylated sites and their predominant localization in the regulatory regions of genes indicate their possible role in the implementation of mechanisms of gene suppression in the pathogenesis of prostate cancer (PCa). For 14 genes studied were characterized array maximum values hypermethylation in promoter region (> 50% CpG sites) in combination with a high level of methylation differences between treatment groups (> 40%). Role of hypermethylation in some of them: AOX1, KLF8, ZNF154, TMEM106A in the pathogenesis of prostate cancer has been showed previously. Hypermethylation of genes ACSS3, TAC1, TUBA4B, ZSCAN12 not previously been shown for prostate cancer, but is characterized by the association with other cancers. In turn, the differences in the levels of methylation in genes GPRASP1, NKX2-6, ARX, CYBA, EPSTI1, RHCG been documented as a result of a number of genome-research oncology, but has not been studied in detail. To assess the diagnostic potential of epigenetic markers of prostate cancer there was carried out unbiased selection of individual CpG sites most reliably discriminate against tumor samples from a group of no tumor samples. In selected diagnostic model based on logistic regression included 9 CpG sites. Validation of the model was carried out on an independent dataset of methylation of 40 paired samples from the prostate cancer project Atlas of Cancer Genome (TCGA) analyzed on the same version of the DNA chip. Summarized rates of diagnostic informativeness of a model (specificity 95%, sensitivity of 97%, the area under the curve of the diagnostic test (ROC) - 0,96), obtained after validation, allow us to consider these CpG Sites as potential markers for molecular diagnosis of prostate cancer.
Subject(s)
Biomarkers, Tumor/genetics , DNA Methylation , DNA, Neoplasm/genetics , Genome-Wide Association Study , Neoplasm Proteins/genetics , Oligonucleotide Array Sequence Analysis/methods , Prostatic Neoplasms/genetics , Adult , Biomarkers, Tumor/metabolism , CpG Islands , DNA, Neoplasm/metabolism , Humans , Male , Middle Aged , Neoplasm Proteins/metabolism , Prostatic Neoplasms/metabolismABSTRACT
The RNA-seq approach for prostate cancer candidate RNA biomarkers screening in plasma and urine obtained by minimally invasive or noninvasive methods is proved to be feasible. Significant amount of RNA biomarkers associated with prostate cancer according to the literature were found in plasma and urine samples obtained from patients with benign prostatic hyperplasia (BPH). The number of detected markers was shown to vary in accordance with method of library preparation used for transcriptome profiling. The detection of known RNA biomarkers for prostate cancer in urine and plasma samples shows the feasibility of such method for minimally invasive diagnostics. The fact of presence of the same RNA biomarkers in samples from patients with BPH suggests their possible lack of specificity and confirms the need for further research in this area.
