Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA203690 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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
Project description:Prostate tumors with the gene fusion TMPRSS2:ERG have been reported to have a significantly higher risk of recurrence compared with tumors lacking the fusion. Tumors from 139 patients who underwent radical prostatectomy were analyzed for the expression of 502 cancer-related genes to identify genes differentially regulated in TMPRSS2:ERG fusion tumors as well as identify biomarkers of biochemical recurrence. 139 prostate fresh-frozen tumors from radical prostatectomy surgery where profiled on the Illumina Human Cancer DASL Panel. 69 tumors were positive for the gene fusion TMPRSS2:ERG while 70 where not. 33 of the 139 patients experienced biochemical recurrence. Data was analyzed for differential genes in TMPRSS2:ERG fusion positive tumors as well as clinical and molecular biomarkers of recurrence.
2009-10-22 | E-GEOD-18655 | biostudies-arrayexpress
Project description:Comparison of circulating miRNA levels in patients who experienced rapid biochemical recurrence or no recurrence following radical prostatectomy
2013-05-22 | GSE47125 | GEO
Project description:Comparison of circulating miRNA levels in patients who experienced rapid biochemical recurrence or no recurrence following radical prostatectomy qRT-PCR miRNA expression profiling of patient serum
2013-05-22 | E-GEOD-47125 | biostudies-arrayexpress
Project description:The aim of this study is to construct an inflammatory response-related genes (IRRGs) signature to monitor biochemical recurrence (BCR) and treatment effects in prostate cancer patients (PCa)
2022-08-04 | GSE210205 | GEO
Project description:Adjuvant tamoxifen is a valid treatment option for women with estrogen receptor (ER)-positive breast cancer. However, up to 40% of patients experience distant or local recurrence or die. MicroRNAs have been suggested to be important prognosticators in breast cancer. This study aims to identify microRNAs with the potential to predict tamoxifen response. We performed a global microRNA screen in primary tumours of six matched pairs of postmenopausal, ER-positive breast cancer patients treated with tamoxifen, who were either recurrence free or had developed a recurrence. Patients were treated at the Robert Bosch Hospital, Stuttgart, Germany, between 1986 and 2005. Total RNA from FFPE tissue from 12 postmenopausal patients with ER-positive breast cancer (6 patients with and 6 patients without recurrence) was extracted. Hybridisation of biotin-labelled RNA was performed on Affymetrix GeneChip miRNA_2.0 Arrays.
2014-07-01 | E-GEOD-46823 | biostudies-arrayexpress
Project description:This study aimed to uncover new circulating microRNAs (miRNAs) that would distinguish patients with pancreatic cancer (PanC) from healthy subjects (HS), and predict patients’ clinical phenotypes and outcomes.
2020-06-19 | E-MTAB-8378 | biostudies-arrayexpress