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Prognostic role of genetic biomarkers in clinical progression of prostate cancer.

ABSTRACT: The aim of this study was to analyze the use of 12 single-nucleotide polymorphisms in genes ELAC2, RNASEL and MSR1 as biomarkers for prostate cancer (PCa) detection and progression, as well as perform a genetic classification of high-risk patients. A cohort of 451 men (235 patients and 216 controls) was studied. We calculated means of regression analysis using clinical values (stage, prostate-specific antigen, Gleason score and progression) in patients and controls at the basal stage and after a follow-up of 72 months. Significantly different allele frequencies between patients and controls were observed for rs1904577 and rs918 (MSR1 gene) and for rs17552022 and rs5030739 (ELAC2). We found evidence of increased risk for PCa in rs486907 and rs2127565 in variants AA and CC, respectively. In addition, rs627928 (TT-GT), rs486907 (AG) and rs3747531 (CG-CC) were associated with low tumor aggressiveness. Some had a weak linkage, such as rs1904577 and rs2127565, rs4792311 and rs17552022, and rs1904577 and rs918. Our study provides the proof-of-principle that some of the genetic variants (such as rs486907, rs627928 and rs2127565) in genes RNASEL, MSR1 and ELAC2 can be used as predictors of aggressiveness and progression of PCa. In the future, clinical use of these biomarkers, in combination with current ones, could potentially reduce the rate of unnecessary biopsies and specific treatments.

SUBMITTER: Alvarez-Cubero MJ

PROVIDER: S-EPMC4558485 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Prognostic role of genetic biomarkers in clinical progression of prostate cancer.

Alvarez-Cubero Maria Jesus MJ Martinez-Gonzalez Luis Javier LJ Saiz Maria M Carmona-Saez Pedro P Alvarez Juan Carlos JC Pascual-Geler Manrique M Lorente Jose Antonio JA Cozar Jose Manuel JM

Experimental & molecular medicine 20150807

The aim of this study was to analyze the use of 12 single-nucleotide polymorphisms in genes ELAC2, RNASEL and MSR1 as biomarkers for prostate cancer (PCa) detection and progression, as well as perform a genetic classification of high-risk patients. A cohort of 451 men (235 patients and 216 controls) was studied. We calculated means of regression analysis using clinical values (stage, prostate-specific antigen, Gleason score and progression) in patients and controls at the basal stage and after a ...[more]

PMID: 26251261

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Project description:BackgroundEven though emerging studies supplied evidence that Adhesion Molecule with Ig Like Domain family 2 (AMIGO2) plays a critical role in numerous cancers, comprehensive analysis of the prognostic value and significant role of AMIGO2 in prostate cancer (PCa) have not been described.MethodsDifferentially expressed analysis, survival analysis and univariate cox regression analysis were first performed to explore the diagnostic and prognostic role of AMIGO2 in various cancers, especially in PCa. Tissue microarray were used to examined the association between AMGIO2 and clinical features. Multivariate cox regression analysis, concordance index, nomogram construction, the receiver operator characteristic curve and calibration curves were further used to discover the effects of AMIGO2 on recurrence-free survival (RFS) and clinicopathological characteristics, including age, Gleason score (GS) and tumor stage. Genetic and Epigenetic Alterations analysis were further conducted to explore the potential effect of AMIGO2 in PCa and examined by biological function analysis and in vitro experiments.ResultsAMIGO2 was associated with poor RFS (P<0.05) and differentially expressed (P<0.05) in multiple cancer type, especially in PCa. Besides, decreasing the expression of AMIGO2 inhibited PCa cell proliferation and colony formation in vitro. In addition, AMIGO2 was a reliable prognostic marker providing additional information (C-index: 0.7) that supplement the currently used prognosis evaluation system, e.g., T stage (C-index: 0.62) and GS (C-index: 0.65). A novel nomogram was established based on AMIGO2, tumor stage and GS with accuracies (areas under curve) of 0.70, 0.78 and 0.82 for predicting 3-, 5- and 7-year RFS, respectively. Bioinformatic analysis and in vitro examination also suggested that AMIGO2 might involve in the progression of PCa tumors inducing epithelial mesenchymal transition (EMT).ConclusionsWe identified AMIGO2 as a pan-cancer gene that could not only be a prognostic biomarker in various cancers, especially in PCa, but may functionally promoting PCa progression via EMT and mediating docetaxel resistance, suggesting AMIGO2 as a potential target for future treatment of PCa.

Project description:The identification and validation of biomarkers for clinical applications remains an important issue for improving diagnostics and therapy in many diseases, including prostate cancer. Gene expression profiles are routinely applied to identify diagnostic and predictive biomarkers or novel targets for cancer. However, only few predictive markers identified in silico have also been validated for clinical, functional or mechanistic relevance in disease progression. In this study, we have used a broad, bioinformatics-based approach to identify such biomarkers across a spectrum of progression stages, including normal and tumor-adjacent, premalignant, primary and late stage lesions. Bioinformatics data mining combined with clinical validation of biomarkers by sensitive, quantitative reverse-transcription PCR (qRT-PCR), followed by functional evaluation of candidate genes in disease-relevant processes, such as cancer cell proliferation, motility and invasion. From 300 initial candidates, eight genes were selected for validation by several layers of data mining and filtering. For clinical validation, differential mRNA expression of selected genes was measured by qRT-PCR in 197 clinical prostate tissue samples including normal prostate, compared against histologically benign and cancerous tissues. Based on the qRT-PCR results, significantly different mRNA expression was confirmed in normal prostate versus malignant PCa samples (for all eight genes), but also in cancer-adjacent tissues, even in the absence of detectable cancer cells, thus pointing to the possibility of pronounced field effects in prostate lesions. For the validation of the functional properties of these genes, and to demonstrate their putative relevance for disease-relevant processes, siRNA knock-down studies were performed in both 2D and 3D organotypic cell culture models. Silencing of three genes (DLX1, PLA2G7 and RHOU) in the prostate cancer cell lines PC3 and VCaP by siRNA resulted in marked growth arrest and cytotoxicity, particularly in 3D organotypic cell culture conditions. In addition, silencing of PLA2G7, RHOU, ACSM1, LAMB1 and CACNA1D also resulted in reduced tumor cell invasion in PC3 organoid cultures. For PLA2G7 and RHOU, the effects of siRNA silencing on proliferation and cell-motility could also be confirmed in 2D monolayer cultures. In conclusion, DLX1 and RHOU showed the strongest potential as useful clinical biomarkers for PCa diagnosis, further validated by their functional roles in PCa progression. These candidates may be useful for more reliable identification of relapses or therapy failures prior to the recurrence local or distant metastases.

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Prognostic role of genetic biomarkers in clinical progression of prostate cancer.

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Prognostic role of genetic biomarkers in clinical progression of prostate cancer.

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