Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence
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ABSTRACT:
PROVIDER: PRJNA1023930 | ENA |
REPOSITORIES: ENA
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Project description:The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for high-risk prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence status and the CAPRA-S to identify genes related to high-risk disease
2024-10-03 | GSE244631 | GEO
Project description:Prognostic classifier for predicting biochemical recurrence in localized prostate cancer patients after radical prostatectomy
| PRJNA627697 | ENA
Project description:The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for intermediate prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence (BCR) status and the CAPRA-S to identify genes related to high-risk disease. Two public cohort (TCGA-PRAD and GSE54460) were used to validate the results. Expression profiling of our cohort uncovered associations between PIP and INHBA with BCR and high CAPRA-S score, as well as associations between VCAN, SFRP2, and THBS4 and BCR. Despite low levels of the ESR1 gene compared to AR, we found strong expression of the ER signaling signature, suggesting that BCR may be driven by ER-mediated pathways. Kaplan-Meier and univariate Cox proportional hazards regression analysis indicated the expression of ESR1, PGR, VCAN, and SFRP2 could predict the occurrence of relapse events. This is in keeping with the pathways represented by these genes which contribute to angiogenesis and the epithelial-mesenchymal transition. It is likely that VCAN works by activating the stroma and remodeling the tumor microenvironment. Additionally, SFRP2 overexpression has been associated with increased tumor size and reduced survival rates in breast cancer and among prostate cancer patients who experienced BCR. ESR1 influences disease progression by activating stroma, stimulating stem/progenitor prostate cancer, and inducing TGF-β. Estrogen signaling may therefore serve as a surrogate to AR signaling during progression and in hormone-refractory disease, particularly in prostate cancer patients with stromal-rich tumors. Collectively, the use of agnostic biomarkers developed for breast cancer stratification has facilitated a precise clinical classification of patients undergoing radical prostatectomy and highlighted the therapeutic potential of targeting estrogen signaling in prostate cancer.
| S-EPMC10641020 | biostudies-literature
Project description:BACKGROUND: Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR. METHODS: The study population included 85 clinically high-risk patients who developed BCR after RP. Time-dependent receiver operating characteristic (ROC) curves, weighted Cox proportional hazard models, and decision curves were used to compare GC scores to Gleason score (GS), PSA doubling time (PSAdT), time to BCR (ttBCR), the Stephenson nomogram, and CAPRA-S for predicting metastatic disease progression. All tests were two-sided with a type I error probability of 5%. RESULTS: GC scores stratified men with BCR into those who would or would not develop metastasis (8% of patients with low versus 40% with high scores developed metastasis, p<0.001). The area under the curve for predicting metastasis after BCR was 0.82 (95% CI, 0.76-0.86) for GC, compared to GS 0.64 (0.58-0.70), PSAdT 0.69 (0.61-0.77) and ttBCR 0.52 (0.46-0.59). Decision curve analysis showed that GC scores had a higher overall net benefit compared to models based solely on clinicopathologic features. In multivariable modeling with clinicopathologic variables, GC score was the only significant predictor of metastasis (p=0.003). CONCLUSIONS: When compared to clinicopathologic variables, GC better predicted metastatic progression among this cohort of men with BCR following RP. While confirmatory studies are needed, these results suggest that use of GC may allow for better selection of men requiring earlier initiation of treatment at the time of BCR.
2016-09-19 | GSE51066 | GEO
Project description:The risk of locoregional or distant failure in advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) patients is high. However, no suitable markers for stratification are clinically available. Thus, we aimed to identify a microRNA(miRNA)-signature predicting disease recurrence. For this purpose the miRNA profiles from 162 HNSCC samples were analysed with regard to identification of a low-complex porgnostic signature. The data set consists of a discovery dataset (n=85) and a validation dataset (n=77). The study resulted in a prognostic 5-miRNA signature significantly predicting the relevant clinical endpoint freedom from recurrence.
2018-09-06 | E-MTAB-5793 | 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:Accurate estimation of recurrence risk is needed for optimal treatment of clinically localized prostate cancer (PCa) patients. We combined classical clinicopathological predictors of biochemical recurrence (BCR) and molecular markers into a new risk score for predicting BCR after radical prostatectomy (RP). A retrospective study which included 122 PCa patients who attended our department between 2000 and 2007 was conducted. Total RNA was isolated from formalin-fixed paraffin embedded PCa tissue. Gene expression patterns were analyzed in 21 selected samples from 7 localized, 6 locally advanced, and 8 metastatic PCa patients using Illumina microarrays. Expression levels of 41 genes were validated by quantitative PCR in an independent retrospective series of 101 patients with ≥ 10 years follow-up who underwent RP for clinically localized PCa. Univariate and multivariate logistic regression analysis were used to identify individual predictors of BCR. A risk score (RS) for predicting BCR including clinicopathological and gene expression data was developed and Kaplan-Meier curves were generated. Interaction networks between the genes of the model were built by GeneMANIA Cytoscape plugin. In a median follow-up of 120 months (range 3-190), 37 patients developed BCR (36.6%). Expression levels of 7,930 transcripts differed between clinically localized and locally advanced-metastatic PCa groups (FDR<0.1). A set of 41 genes were validated by quantitative PCR. Regression analysis showed that expression of ASF1B and MCL1 as well as Gleason score, extracapsular extension, seminal vesicle invasion and positive margins were independent prognostic factors of BCR. A RS generated using these gene expression and clinicopathological variables was able to discriminate between two groups of patients with a significantly different probability of BCR (HR 6.24; CI 3.23-12.4, p<0.01), improving the individual discriminative performance of each of these variables on their own. Direct interactions between the two genes of the model were not found. In conclusion, identification of new gene expression patterns associated with a high probability of BCR in clinically localized PCa patients treated with RP, and their combination with clinicopathological variables in a robust, easy-to-use and reliable classifier may contribute to improve PCa risk stratification and, consequently, to tailor treatment and surveillance strategies in these patients.
2024-04-23 | GSE149226 | 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.
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