The Methylome-Genome Interactions in Localized Prostate Cancer Define Disease Aggression
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE107298 | GEO | 2019/06/30
REPOSITORIES: GEO
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Project description:Prostate cancer is a leading cause of cancer death amongst males. The main clinical dilemma in treating prostate cancer is the high number of indolent cases that confer a significant risk of over diagnosis and over treatment. In this study we have performed a genome expression profiling of tumor tissue specimens from 36 patients with prostate cancer to identify transcripts that delineate aggressive and indolent cancer. We included normal prostate biopsies from 14 patients in our analysis. Unsupervised hierarchical cluster analysis separated the cancer samples into two groups with a significant overrepresentation of tumors from patients with biochemical recurrence in one of the groups (Chi2, p=0.02). The samples were separated by basically three clusters of genes that showed differential expression between the two sample clusters - totaling 371 transcripts. Ingenuity Pathway Analysis revealed that one cluster contained genes associated with invasive properties of the tumor, another genes associated with the cell cycle, and the last cluster genes involved in several biological functions. We successfully validated the transcripts association with recurrence using two publicly available patient datasets totaling 669 patients. Twelve genes were found to be independent predictors of recurrence in multivariate logistical regression analysis. In this study we have performed a genome expression profiling of tumor tissue specimens from 36 patients with prostate cancer to identify transcripts that delineate aggressive and indolent cancer. We included normal prostate biopsies from 14 patients in our analysis.
2015-07-01 | E-GEOD-46602 | biostudies-arrayexpress
Project description:Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.
2017-01-10 | GSE84042 | GEO
Project description:Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.
2017-01-10 | GSE83917 | GEO
Project description:Developing an effective predictor of tumour recurrence is an important challenge in the management of localized prostate cancer. Accurate prediction of disease-free survival is essential for decision-making before or after definitive local therapy, and would allow identification of patients who may derive benefit from adjuvant therapy. Today these decisions are largely based on the clinic-pathologic prognostic factors of tumour size, extent and grade along with serum PSA abundance. MicroRNAs (miRNAs) are promising class of biomarkers to improve patient risk-stratification: they show differential abundance across prostate cancer sub-types and have both oncogenic and tumour-suppressive roles. Here, we report the miRNA abundance profiling of 319 prostate tumours with matching detailed clinical annotation, long-term follow-up and accompanying genetic and epigenetic data including mRNA abundance, copy number alterations, point mutations and methylation. We built a cancer driver-miRNA-target regulatory network to characterize the extent to which genomic, transcriptional and post-transcriptional events contribute to the miRNA abundance architecture. By linking this network with machine-learning we created a multi-modal biomarker that accurately predicts biochemical recurrence after definitive local therapy. We find that combining miRNA information with genetic and epigenetic drivers and clinicopathological parameters improves biomarker accuracy, and quantifies the value of multi-modal biomarkers that exploit the regulatory architecture of gene expression in their development.
2024-04-05 | GSE135535 | GEO
Project description:Prostate cancer is a leading cause of cancer death amongst males. The main clinical dilemma in treating prostate cancer is the high number of indolent cases that confer a significant risk of over diagnosis and over treatment. In this study we have performed a genome expression profiling of tumor tissue specimens from 36 patients with prostate cancer to identify transcripts that delineate aggressive and indolent cancer. We included normal prostate biopsies from 14 patients in our analysis. Unsupervised hierarchical cluster analysis separated the cancer samples into two groups with a significant overrepresentation of tumors from patients with biochemical recurrence in one of the groups (Chi2, p=0.02). The samples were separated by basically three clusters of genes that showed differential expression between the two sample clusters - totaling 371 transcripts. Ingenuity Pathway Analysis revealed that one cluster contained genes associated with invasive properties of the tumor, another genes associated with the cell cycle, and the last cluster genes involved in several biological functions. We successfully validated the transcripts association with recurrence using two publicly available patient datasets totaling 669 patients. Twelve genes were found to be independent predictors of recurrence in multivariate logistical regression analysis.
2015-07-01 | GSE46602 | GEO
Project description:Current prostate cancer prognostic models are based on pre-treatment prostate-specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict clinical disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. We analyzed a Swedish Watchful Waiting cohort (1977â1999) with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Thus the determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses preventing the development of molecular biomarkers for prostate cancer progression. 281 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); Training set: first 186 samples; Validation cohort: remaining 95 cases from the same population.
2010-05-07 | E-GEOD-16560 | biostudies-arrayexpress
Project description:Detection of DNA hypermethylation has emerged as a novel molecular biomarker for the evaluation of prostate cancer diagnosis and prognosis, but the use of single gene hypermethylation could produce unspecific results. Defining the specific gene hypermethylation profile for prostate cancer could provide groups of genes that specifically discriminate the patients with indolent and aggressive tumors. To compare the methylation profile of normal and malignant prostate we performed Genome-wide methylation analysis on 83 tumor samples, that included all clinical stages of the disease, 10 normal prostate samples and LNCaP, DU145 and PC3 prostate cancer cell lines using the GoldenGate Methylation Cancer Panel I (Illumina, Inc.) that interrogate for 1505 CpGs. We found 41 genes significantly hypermethylated in more than 20% of the tumors analyzed (p<0.01). Of these we identified GSTM2 and PENK as novel hypermethylated genes in prostate cancer that were simultaneously methylated in 40.9% of the tumors analyzed. We also identified panels of genes more frequently methylated in tumor samples with clinico-pathological indicators of poor prognosis: high Gleason score, elevated Ki-67 or advanced disease. Of these, we found that simultaneous hypermethylation of CFTR and HTR1B is common in patients with high Gleason score and high ki-67 levels and might signal the population at higher risk of therapeutic failure. DNA hypermethylation profile was associated with cancer-specific mortality (log-rank, p=0.007) and biochemical recurrence-free survival (log-rank, p=0.0008). In conclusion, our data strongly indicate that epigenetic silencing of GSTM2 and PENK is a common event in prostate cancer that could be used as a molecular marker for prostate cancer diagnosis. In addition, simultaneous HTR1B and CFTR hypermethylation could help discriminate aggressive from indolent prostate tumors.A DNA hypermethylation profile associated with cancer-specific mortality and biochemical recurrence in patients receiving radical prostatectomy is presented. GST2 and PENK are new hipermethylated genes identified. Simultaneous hypermethylation of CFTR and HTR1B could help discriminate aggressive disease.
2014-12-31 | GSE46177 | GEO
Project description:This is a case control study designed to identify microRNA sequences associated with metastasis following radical prostatectomy for clinically localized prostate cancer. Samples were obtained from patients with clinical evidence of metastatic disease following surgery (cases) and patients who showed no evidence of metastasis or biochemical recurrence at least 5 years following surgery (controls). Cases and controls were matched for tumor grade and duration of follow-up.
2019-07-25 | GSE117674 | GEO
Project description:Genome wide DNA methylation profiling of normal and tumor prostate samples, as well as cultured primary prostate cells overexpressing DNA Methyltransferases (DNMTs) and EZH2 Candidate gene based studies have identified a handful of aberrant CpG DNA methylation events in prostate cancer. However, DNA methylation profiles have not been compared on a large scale between prostate tumor and normal prostate, and the mechanisms behind these alterations are unknown. In this study, we quantitatively profiled 95 primary prostate tumors and 86 healthy prostate tissue samples for their DNA methylation levels at 26,333 CpGs representing 14,104 gene promoters by using the Illumina HumanMethylation27 platform. A 2-class Significance Analysis of this dataset revealed 5,912 CpG sites with increased DNA methylation and 2,151 CpG sites with decreased DNA methylation in tumors (FDR < 0.8%). Prediction Analysis of this dataset identified 87 CpGs that are the most predictive diagnostic methylation biomarkers of prostate cancer. By integrating available clinical follow-up data, we also identified 69 prognostic DNA methylation alterations that correlate with biochemical recurrence of the tumor. To identify the mechanisms responsible for these genome-wide DNA methylation alterations, we measured the gene expression levels of several DNA methyltransferases (DNMTs) and their interacting proteins by TaqMan qPCR and observed increased expression of DNMT3A2, DNMT3B, and EZH2 in tumors. Subsequent transient transfection assays in cultured primary prostate cells revealed that DNMT3B1 and DNMT3B2 overexpression resulted in increased methylation of a substantial subset of CpG sites that also showed tumor-specific increased methylation. Bisulfite converted DNA from 193 samples were hybridized to the Illumina Infinium 27k Human Methylation Beadchip v1.2. The tissue samples (first 181) and the cultured cell samples (last 12) were normalized independently.
2011-04-19 | E-GEOD-26126 | biostudies-arrayexpress
Project description:Genomic hallmarks of localized, non-indolent prostate cancer
| PRJNA327861 | ENA