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A TMEFF2-regulated cell cycle derived gene signature is prognostic of recurrence risk in prostate cancer.

ABSTRACT: BACKGROUND:The clinical behavior of prostate cancer (PCa) is variable, and while the majority of cases remain indolent, 10% of patients progress to deadly forms of the disease. Current clinical predictors used at the time of diagnosis have limitations to accurately establish progression risk. Here we describe the development of a tumor suppressor regulated, cell-cycle gene expression based prognostic signature for PCa, and validate its independent contribution to risk stratification in several radical prostatectomy (RP) patient cohorts. METHODS:We used RNA interference experiments in PCa cell lines to identify a gene expression based gene signature associated with Tmeff2, an androgen regulated, tumor suppressor gene whose expression shows remarkable heterogeneity in PCa. Gene expression was confirmed by qRT-PCR. Correlation of the signature with disease outcome (time to recurrence) was retrospectively evaluated in four geographically different cohorts of patients that underwent RP (834 samples), using multivariate logistical regression analysis. Multivariate analyses were adjusted for standard clinicopathological variables. Performance of the signature was compared to previously described gene expression based signatures using the SigCheck software. RESULTS:Low levels of TMEFF2 mRNA significantly (p

SUBMITTER: Georgescu C

PROVIDER: S-EPMC6503380 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A TMEFF2-regulated cell cycle derived gene signature is prognostic of recurrence risk in prostate cancer.

Georgescu Constantin C Corbin Joshua M JM Thibivilliers Sandra S Webb Zachary D ZD Zhao Yan D YD Koster Jan J Fung Kar-Ming KM Asch Adam S AS Wren Jonathan D JD Ruiz-Echevarría Maria J MJ

BMC cancer 20190506 1

<h4>Background</h4>The clinical behavior of prostate cancer (PCa) is variable, and while the majority of cases remain indolent, 10% of patients progress to deadly forms of the disease. Current clinical predictors used at the time of diagnosis have limitations to accurately establish progression risk. Here we describe the development of a tumor suppressor regulated, cell-cycle gene expression based prognostic signature for PCa, and validate its independent contribution to risk stratification in s ...[more]

PMID: 31060542

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Project description:Optimum management of clinically localised prostate cancer presents unique challenges because of the highly variable and often indolent natural history of the disease. To predict disease aggressiveness, clinicians combine clinical variables to create prognostic models, but the models have limited accuracy. We assessed the prognostic value of a predefined cell cycle progression (CCP) score in two cohorts of patients with prostate cancer.We measured the expression of 31 genes involved in CCP with quantitative RT-PCR on RNA extracted from formalin-fixed paraffin-embedded tumour samples, and created a predefined score and assessed its usefulness in the prediction of disease outcome. The signature was assessed retrospectively in a cohort of patients from the USA who had undergone radical prostatectomy, and in a cohort of randomly selected men with clinically localised prostate cancer diagnosed by use of a transurethral resection of the prostate (TURP) in the UK who were managed conservatively. The primary endpoint was time to biochemical recurrence for the cohort of patients who had radical prostatectomy, and time to death from prostate cancer for the TURP cohort.After prostatectomy, the CCP score was useful for predicting biochemical recurrence in the univariate analysis (hazard ratio for a 1-unit change [doubling] in CCP 1·89; 95% CI 1·54-2·31; p=5·6×10(-9)) and the best multivariate analysis (1·77, 1·40-2·22; p=4·3×10(-6)). In the best predictive model (final multivariate analysis), the CCP score and prostate-specific antigen (PSA) concentration were the most important variables and were more significant than any other clinical variable. In the TURP cohort, the CCP score was the most important variable for prediction of time to death from prostate cancer in both univariate analysis (2·92, 2·38-3·57, p=6·1×10(-22)) and the final multivariate analysis (2·57, 1·93-3·43; p=8·2×10(-11)), and was stronger than all other prognostic factors, although PSA concentration also added useful information. Heterogeneity in the hazard ratio for the CCP score was not noted in any case for any clinical variables.The results of this study provide strong evidence that the CCP score is a robust prognostic marker, which, after additional validation, could have an essential role in determining the appropriate treatment for patients with prostate cancer.Cancer Research UK, Queen Mary University of London, Orchid Appeal, US National Institutes of Health, and Koch Foundation.

Project description:Background: Biochemical recurrence (BCR) is an indicator of prostate cancer (PCa)-specific recurrence and mortality. However, there is a lack of an effective prediction model that can be used to predict prognosis and to determine the optimal method of treatment for patients with BCR. Hence, the aim of this study was to construct a protein-based nomogram that could predict BCR in PCa. Methods: Protein expression data of PCa patients was obtained from The Cancer Proteome Atlas (TCPA) database. Clinical data on the patients was downloaded from The Cancer Genome Atlas (TCGA) database. Lasso and Cox regression analyses were conducted to select the most significant prognostic proteins and formulate a protein signature that could predict BCR. Subsequently, Kaplan-Meier survival analysis and Cox regression analyses were conducted to evaluate the performance of the prognostic protein-based signature. Additionally, a nomogram was constructed using multivariate Cox regression analysis. Results: We constructed a 5-protein-based prognostic prediction signature that could be used to identify high-risk and low-risk groups of PCa patients. The survival analysis demonstrated that patients with a higher BCR showed significantly worse survival than those with a lower BCR (p < 0.0001). The time-dependent receiver operating characteristic curve showed that the signature had an excellent prognostic efficiency for 1, 3, and 5-year BCR (area under curve in training set: 0.691, 0.797, 0.808 and 0.74, 0.739, 0.82 in the test set). Univariate and multivariate analyses indicated that this 5-protein signature could be used as independent prognosis marker for PCa patients. Moreover, the concordance index (C-index) confirmed the predictive value of this 5-protein signature in 3, 5, and 10-year BCR overall survival (C-index: 0.764, 95% confidence interval: 0.701-0.827). Finally, we constructed a nomogram to predict BCR of PCa. Conclusions: Our study identified a 5-protein-based signature and constructed a nomogram that could reliably predict BCR. The findings might be of paramount importance for the prediction of PCa prognosis and medical decision-making. Subjects: Bioinformatics, oncology, urology.

Project description:Dexamethasone is reported to induce both tumor-suppressive and tumor-promoting effects. The purpose of this study was to identify the genomic impact of dexamethasone in glioblastoma stem cell (GSC) lines and its prognostic value; furthermore, to identify drugs that can counter these side effects of dexamethasone exposure.We utilized 3 independent GSC lines with tumorigenic potential for this study. Whole-genome expression profiling and pathway analyses were done with dexamethasone-exposed and control cells. GSCs were also co-exposed to dexamethasone and temozolomide. Risk scores were calculated for most affected genes, and their associations with survival in The Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data databases. In silico Connectivity Map analysis identified camptothecin as antagonist to dexamethasone-induced negative effects.Pathway analyses predicted an activation of dexamethasone network (z-score: 2.908). Top activated canonical pathways included "role of breast cancer 1 in DNA damage response" (P=1.07E-04). GSCs were protected against temozolomide-induced apoptosis when coincubated with dexamethasone. Altered cellular functions included cell movement, cell survival, and apoptosis with z-scores of 2.815, 5.137, and -3.122, respectively. CCAAT/enhancer binding protein beta (CEBPB) was activated in a dose dependent manner specifically in slow-dividing "stem-like" cells. CEBPB was activated in dexamethasone-treated orthotopic tumors. Patients with high risk scores had significantly shorter survival. Camptothecin was validated as potential partial neutralizer of dexamethasone-induced oncogenic effects.Dexamethasone exposure induces a genetic program and CEBPB expression in GSCs that adversely affects key cellular functions and response to therapeutics. High risk scores associated with these genes have negative prognostic value in patients. Our findings further suggest camptothecin as a potential neutralizer of adverse dexamethasone-mediated effects.

Dataset Information

A TMEFF2-regulated cell cycle derived gene signature is prognostic of recurrence risk in prostate cancer.

Publications

A TMEFF2-regulated cell cycle derived gene signature is prognostic of recurrence risk in prostate cancer.

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