Epigenome analysis of prostatectomy specimens and samples of prostate cancer bone metastases
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE174613 | GEO | 2021/07/01
REPOSITORIES: GEO
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Project description:Androgens are a prequisite for the development of human prostate and prostate cancer. Androgen action is mediated via androgen receptor. Androgen ablation therapy is used for the treatment of metastasized prostate cancer. The aim of the study was to identify genes differentially expressed in benign human prostate, prostate cancer and in prostate tissue three days after castration. These genes are potential diagnostic and therapeutic targets for prostate cancer and benign prostatic hyperplasia. We used microarrays to examine the gene expression profiles in benign prostate adjacent to prostate cancer and prostate cancer in radical prostatectomy specimens and in prostate tissue samples taken 3 days after surgical castration performed for treatment of prostate cancer. Human prostate tissue was obtained from radical prostatectomy samples and from prostate biopsy samples (castrated samples). Benign and malignant tissues samples were microdissected from prostatectomy samples. Tissues were used for RNA isolation and were further processed as samples for microarray. Three prostatectomy samples were used as replicates (benign and malignant prostate). All prostate cancers were Gleason 3+3 pattern. Castrated tissue samples were taken from patients three days after surgical castration for the treatment of advanced or metastasized prostate cancer. Six biopsies were taken from each subject and individual subject samples were used as three replicates in microarray.
2012-06-19 | E-GEOD-32982 | biostudies-arrayexpress
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:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
2013-07-01 | E-GEOD-46691 | biostudies-arrayexpress
Project description:Transcriptomic profiling of metastasis tissue samples obtained from prostate cancer patients was performed using Clariom D human arrays.
2021-11-23 | GSE189343 | GEO
Project description:Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Method:A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 235 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance. Patients treated with RP between 2000 and 2006 were identified from the Mayo Clinic tumor registry for a case-cohort study design. This involved identification of all patients with metastasis and a representative of the full cohort .Thus, men at high risk of recurrence post-RP (open/robotic) with no prior neoadjuvant/prostate cancer treatment were selected based on any of preoperative PSA >20 ng/mL, pathological Gleason score (GS) â¥8, SVI, or GPSM (GS; preoperative PSA; SVI; margins) score â¥10.The cohort of 1,010 men included 73 cases with metastasis as evidenced by CT or bone scan. A 20% random sample (n=202) was drawn from the cohort. This included 19 of 73 metastatic cases. To increase sampling of metastasis, the remaining 54 metastatic cases were added, resulting in a final study set of 256 patients. 21 samples did not pass QC and were eliminated from this study. Patients not experiencing metastasis regardless of BCR (defined as follow-up PSA â¥0.4 ng/mL >30 days post-RP) were censored at last follow-up. The study was approved by Mayo Clinic Institutional Review Board.
2014-11-13 | E-GEOD-62116 | biostudies-arrayexpress
Project description:To identify molecular singnal alterations between androgen dependent prostate cancer and castration resistant prostate cancer, we performed interspecies comparative microarray analyses using RNAs prepared from uncastrasion and castration tumor from LNCAP Orhotopic xenograft models of prostate cancer. microarray data from uncastrasion and castration tumor revealed that the gene expression profile is most significantly altered in between androgen dependent prostate cancer and castration resistant prostate cancer. Comparative analyses of LNCAP Orhotopic xenograft models of prostate cancer showed that genes involved in androgen dependent and androgen independent tumor were significantly altered. We prepared RNA samples from 4 samples uncastrasion and 4 samples castration tumors from LNCAP Orhotopic xenograft models of prostate cancer . High-quality RNA samples were subjected to microarray analysis using the Affymetrix Human Gene 2.0 ST platform, and only those results that passed examinations for quality assurance and quality control of the Human Gene 2.0 ST arrays were retrieved. In total, we obtained gene expression profiles from the following samples: 4 samples uncastrasion and 4 samples castration tumors
2013-04-20 | E-GEOD-46218 | biostudies-arrayexpress
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
2013-07-01 | GSE46691 | GEO
Project description:Proteome characterization of gland confined prostate tumors and non-malignant prostate tissue. Whole cell protein extracts were purified from FFPE radical prostatectomy specimens for a total of 28 tumor samples and 8 adjacent non-malignant prostate tissues. Associated ProteomeXchange identifiers: PXD003430, PXD003452, PXD003515, PXD004132, PXD003615, PXD003636. Quantitative proteomic analysis of adjacent non-malignant prostate tissue (n=8) and gland confined prostate tumors (n=28) obtained from radical prostatectomy procedures; and bone metastatic prostate tumors (n=22) obtained from patients operated to relief spinal cord compression. At the time of surgery, most metastatic patients had relapsed after androgen-deprivation therapy, while 5 were previously untreated.
2018-08-21 | PXD009868 | Pride
Project description:Purpose: Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population. Method:A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 235 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance.
2014-11-13 | GSE62116 | GEO
Project description:We analyzed the global gene expression pattern of Tregs between healthy donors and prostate cancer patients. We found that genes related to cell cycle, cellular proliferation, immune responses, hematological system development and function were differentially expressed in Tregs from prostate cancer patients. Total RNA samples of Tregs, isolated from peripheral blood, were obtained from three separate healthy donors and three metastatic castration-resistant prostate cancer patients. Global gene expression pattern was examined by performing GeneChip microarray hybridization. Genes differentially expressed between the two groups of donors were sorted and categorized based on their biological functions.
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