Dataset Information

Prostate-specific antigen glycoprofiling as diagnostic and prognostic biomarker of prostate cancer.

ABSTRACT: The initial part of this review details the controversy behind the use of a serological level of prostate-specific antigen (PSA) for the diagnostics of prostate cancer (PCa). Novel biomarkers are in demand for PCa diagnostics, outperforming traditional PSA tests. The review provides a detailed and comprehensive summary that PSA glycoprofiling can effectively solve this problem, thereby considerably reducing the number of unnecessary biopsies. In addition, PSA glycoprofiling can serve as a prognostic PCa biomarker to identify PCa patients with an aggressive form of PCa, avoiding unnecessary further treatments which are significantly life altering (incontinence or impotence).

SUBMITTER: Tkac J

PROVIDER: S-EPMC6388024 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prostate-specific antigen glycoprofiling as diagnostic and prognostic biomarker of prostate cancer.

Tkac Jan J Gajdosova Veronika V Hroncekova Stefania S Bertok Tomas T Hires Michal M Jane Eduard E Lorencova Lenka L Kasak Peter P

Interface focus 20190215 2

The initial part of this review details the controversy behind the use of a serological level of prostate-specific antigen (PSA) for the diagnostics of prostate cancer (PCa). Novel biomarkers are in demand for PCa diagnostics, outperforming traditional PSA tests. The review provides a detailed and comprehensive summary that PSA glycoprofiling can effectively solve this problem, thereby considerably reducing the number of unnecessary biopsies. In addition, PSA glycoprofiling can serve as a progno ...[more]

PMID: 30842876

Similar Datasets

Project description:BACKGROUND:The identification of appropriate biomarkers is essential to support important clinical decisions in patients with prostate cancer. The aim of our study was a systematic bioinformatical analysis of the mRNA expression of all genes available for the prostate adenocarcinoma cohort of The Cancer Genome Atlas (TCGA), regarding their potential prognostic and diagnostic role. METHODS:The study cohort comprises 499 patients (TCGA prostate cancer cohort). mRNA expression data were available for approx. 20,000 genes. The bioinformatical statistical pipeline addressed gene expression differences in tumor vs. benign prostate tissue (including gene set enrichment analysis, GSEA) in samples from tumors with different aggressivenesses (Gleason score), as well as prognostic values in multistep survival analyses. RESULTS:Among all genes analyzed, 1754 were significantly downregulated and 1553 genes were significantly upregulated in tumor tissue. In GSEA, 16 of 30 top enriched biological processes were alterations of epigenetic regulation at different levels. Significant correlation with Gleason Score was evident for 8724 genes (range of Pearson r-values 0.09-0.43; all p < 0.05). In univariate Cox regression analyses, mRNA expression of 3571 genes showed statistically significant association with biochemical recurrence-free survival with a range of hazard ratios 0.3-3.8 (p-value 7.4e- 07 to 0.05). Among these, 571 genes were independently associated with biochemical recurrence in multivariate analysis. Access to the full database including results is provided as supplement. CONCLUSIONS:In our systematic analysis we found a big number of genes of potential diagnostic and prognostic value, many of which have not been studied in prostate cancer to date. Due to the comprehensive nature of this analysis and free access to the results, this study represents a reference database for prostate cancer researchers which can be used as a powerful tool for validation purposes and planning of new studies.

Project description:Objective: To investigate the role of PSMA in the differential diagnosis of adrenocortical carcinoma samples (ACCs) and adrenocortical adenoma samples (ACAs), to validate the prognostic role of PSMA in patients with ACCs, and to explore the possibility that this marker can differentiate localized ACCs from adrenal metastases from other sites. Methods: PSMA protein expression in tissue samples from 50 ACCs, 90 ACAs (including 20 from patients who presented with Cushing's syndrome, 20 aldosterone-producing adenomas and 50 non-functional tumors) and 10 tissues that were metastases from other primary sites was assessed by immunohistochemistry. The clinical and pathological characteristics were compared, the intensity and density were analyzed, and the prognostic role was evaluated. Results: The analysis of clinical and pathological features revealed that the size of ACCs was greater than that of benign tissues and the ACC patients were older than the ACA patients (p < 0.01). The percentage of PSMA-positive vessels, the mean intensity and the degree of staining density were found to be significantly lower in ACAs than in ACCs (p < 0.01). In these 140 samples, 60% of the ACCs were grouped in the positive category. The samples were negative for metastases that were from other primary sites. The ENSAT stage and Ki-67 were correlated with PSMA expression. The survival distribution revealed that high PSMA expression did not show any prognostic relevance in the current ACCs series. Those samples with a score of > 3.5 were 75 times more likely to be malignant (OR = 75). We established a cut-off score of 3.5 (p < 0.05), which had 46% sensitivity and 99% specificity. Paralleling PSMA and Ki-67 maximized the area under the curve, with 72% sensitivity and 100% specificity. Conclusions: Our results strongly confirm that PSMA is helpful for distinguishing benign from malignant tumors and that its high expression levels correlate with a high ENSAT stage and high proliferation. The combination of PSMA and Ki-67 can be particularly useful. Furthermore, PSMA might be a useful tool for the identification of localized adrenal carcinoma and metastatic carcinoma.

Dataset Information

Prostate-specific antigen glycoprofiling as diagnostic and prognostic biomarker of prostate cancer.

Publications

Prostate-specific antigen glycoprofiling as diagnostic and prognostic biomarker of prostate cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets