Identification of a novel microRNA panel associated with metastasis following radical prostatectomy for prostate cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE117674 | GEO | 2019/07/25
REPOSITORIES: GEO
Similar Datasets
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:This SuperSeries is composed of the following subset Series: GSE26022: [Gene Expression Training Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26242: [Gene Expression Validation Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26245: [miRNA Training Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26247: [miRNA Validation Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy Refer to individual Series
2011-06-01 | E-GEOD-26367 | biostudies-arrayexpress
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 biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens. Total RNA prepared from FFPE cores from prostatectomy samples of 70 patients were used for the training phase (29 with biochemical recurrence and 41 controls). All samples were analyzed by both custom Prostate DASL of 522 genes and by Illumina miRNA microarray. Subsequently in the validation phase, samples from 40 patients were used on the same platforms (13 with biochemical recurrence and 27 controls). For the training set, 45 cases were from Sunnybrook Health Science Center (Toronto, ON), and 25 patients from Emory University. For the validation set, all samples were from Emory University. Relevant clinical metadata included are PSA, T-stage, and Gleason Score.
2011-06-01 | E-GEOD-26245 | biostudies-arrayexpress
Project description:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens. Total RNA prepared from FFPE cores from prostatectomy samples of 70 patients were used for the training phase (29 with biochemical recurrence and 41 controls). All samples were analyzed by both custom Prostate DASL of 522 genes and by Illumina miRNA microarray. Subsequently in the validation phase, samples from 40 patients were used on the same platforms (13 with biochemical recurrence and 27 controls). For the training set, 45 cases were from Sunnybrook Health Science Center (Toronto, ON), and 25 patients from Emory University. For the validation set, all samples were from Emory University. Relevant clinical metadata included are PSA, T-stage, and Gleason Score.
2011-06-01 | E-GEOD-26247 | biostudies-arrayexpress
Project description:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens. Total RNA prepared from FFPE cores from prostatectomy samples of 70 patients were used for the training phase (29 with biochemical recurrence and 41 controls). All samples were analyzed by both custom Prostate DASL of 522 genes and by Illumina miRNA microarray. Subsequently in the validation phase, samples from 40 patients were used on the same platforms (13 with biochemical recurrence and 27 controls). For the training set, 45 cases were from Sunnybrook Health Science Center (Toronto, ON), and 25 patients from Emory University. For the validation set, all samples were from Emory University. Relevant clinical metadata included are PSA, T-stage, and Gleason Score.
2011-06-01 | E-GEOD-26242 | 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. 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:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens.
2011-06-01 | GSE26247 | GEO
Project description:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens.
2011-06-01 | GSE26245 | GEO
Project description:To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed paraffin-embedded (FFPE) radical prostatectomy specimens with known long term outcome to perform DASL expression profiling with a custom-designed panel of 522 prostate cancer relevant genes that we designed. We identified a panel of ten protein-coding genes and two miRNA genes that could be used to separate patients with and without biochemical recurrence (p < 0.001), as well as for the subset of 42 Gleason score 7 patients (p < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of recurrence for all cases (p = 0.013) and for a subset of 19 Gleason score 7 cases (p = 0.010), both of which were adjusted for relevant clinical information including T-stage, PSA and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens. Total RNA prepared from FFPE cores from prostatectomy samples of 70 patients were used for the training phase (29 with biochemical recurrence and 41 controls). All samples were analyzed by both custom Prostate DASL of 522 genes and by Illumina miRNA microarray. Subsequently in the validation phase, samples from 40 patients were used on the same platforms (13 with biochemical recurrence and 27 controls). For the training set, 45 cases were from Sunnybrook Health Science Center (Toronto, ON), and 25 patients from Emory University. For the validation set, all samples were from Emory University. Relevant clinical metadata included are PSA, T-stage, and Gleason Score. ***This submission represents the mRNA component of the study
2011-06-01 | E-GEOD-26022 | biostudies-arrayexpress