Dataset Information

Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome.

ABSTRACT: BACKGROUND:The development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids. METHODS:We measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stable miRNAs in an independent training cohort (n?=?99) and created a biomarker predictive of Gleason grade using machine-learning techniques. Finally, we validated this biomarker in an independent validation cohort (n?=?40). RESULTS:We found that each individual has a specific urine miRNA fingerprint. These fingerprints are temporally stable and associated with specific biological functions. We identified seven miRNAs that were stable over time within individual patients and integrated them with machine-learning techniques to create a novel biomarker for prostate cancer that overcomes interindividual variability. Our urine biomarker robustly identified high-risk patients and achieved similar accuracy as tissue-based prognostic markers (area under the receiver operating characteristic = 0.72, 95% confidence interval = 0.69 to 0.76 in the training cohort, and area under the receiver operating characteristic curve = 0.74, 95% confidence interval = 0.55 to 0.92 in the validation cohort). CONCLUSIONS:These data highlight the importance of quantifying intra- and intertumoral heterogeneity in biomarker development. This noninvasive biomarker may usefully supplement invasive or expensive radiologic- and tissue-based assays.

SUBMITTER: Jeon J

PROVIDER: S-EPMC7073919 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome.

Jeon Jouhyun J Olkhov-Mitsel Ekaterina E Xie Honglei H Yao Cindy Q CQ Zhao Fang F Jahangiri Sahar S Cuizon Carmelle C Scarcello Seville S Jeyapala Renu R Watson John D JD Fraser Michael M Ray Jessica J Commisso Kristina K Loblaw Andrew A Fleshner Neil E NE Bristow Robert G RG Downes Michelle M Vesprini Danny D Liu Stanley S Bapat Bharati B Boutros Paul C PC

Journal of the National Cancer Institute 20200301 3

<h4>Background</h4>The development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids.<h4>Methods</h4>We measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stabl ...[more]

PMID: 31161221

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Project description:BackgroundProstate cancer (PCa) is one of the most lethal cancers in male individuals. The synaptosome associated protein 25 (SNAP25) gene is a key mediator of multiple biological functions in tumors. However, its significant impact on the prognosis in PCa remains to be elucidated.MethodsWe performed a comprehensive analysis of the Cancer Genome Atlas dataset (TCGA) to identify the differentially expressed genes between PCa and normal prostate tissue. We subjected the differentially expressed genes to gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes functional analysis, and constructed a protein-protein interaction network. We then screened for pivotal genes to identify the hub genes of prognostic significance by performing Cox regression analysis. We identified SNAP25 as one such gene and analyzed the relationship between its expression in PCa to poor prognosis using GEPIA interactive web server.ResultsTCGA database demonstrated that SNAP25 was significantly downregulated in PCa. The progressive decrease in SNAP25 expression with the increase in the clinical staging and grading of PCa demonstrates that reduced SNAP25 expression considerably exacerbates the clinical presentation. Our findings confirm that SNAP25 expression strongly correlates with overall survival, which was determined using the Gleason score. We also validated the role of SNAP25 expression in the prognosis of patients with PCa. We used Gene Set Enrichment and Gene Ontology analyses to evaluate the function of SNAP25 and further explored the association between SNAP25 expression and tumor-infiltrating immune cells using the Tumor Immune Assessment Resource database. We found for the first time that SNAP25 is involved in the activation, differentiation, and migration of immune cells in PCa. Its expression was positively correlated with immune cell infiltration, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, dendritic cells, macrophages, and natural killer cells. SNAP25 expression also positively correlated with chemokines/chemokine receptors, suggesting that SNAP25 may regulate the migration of immune cells. In addition, our experimental results verified the low expression of SNAP25 in PCa cells.ConclusionOur findings indicate a relationship between SNAP25 expression and PCa, demonstrating that SNAP25 is a potential prognostic biomarker due to its vital role in immune infiltration.

Project description:To screen target gene cluster by bioinformatics analysis and verify them by in vitro experiment and clinicopathological correlation analysis. We try to find a new biomarker with prognostic value for prostate cancer (PCa). 42 candidate marker genes were constructed by protein protein interaction (PPI) network and enriched by KEGG pathway to find out the gene cluster we are interested in. Prognostic model was established to preliminarily analyze the prognostic value of this gene cluster in PCa, and Cox risk regression was used for comparative analysis. Immunohistochemistry was used to detect the expression of each gene in clinical tissue microarray. Finally, we analyzed the correlation between each gene and their clinicopathological features of PCa combined with TCGA clinical data. Based on the analysis of PPI and KEGG, we found the target gene cluster (FCGR3A, HAVCR2, CCR7 and CD28). Prognostic model analysis showed that this gene cluster had the ability to predict biochemical recurrence, and the survival rate and ROC analysis showed favorable prediction effect. Univariate Cox regression analysis showed that the risk scores of Gleason score (GS), T stage, N stage and PSA were significantly different (P<0.05), and the risk ratio of high expression was 2.30 times that of low expression (P=0.004). However, it was not statistically significant in multivariate Cox regression analysis (P>0.05). The results of tissue microarray showed that FCGR3A and HAVCR2 were highly expressed in PCa (P<0.01), while the expression of CCR7 and CD28 had no significant difference (P>0.05). Kaplan-Meier analysis showed that there was significant difference in BCR free survival of FCGR3A and HAVCR2 (FCGR3A, P=0.010; HAVCR2, P=0.018), while the expression of CCR7 and CD28 had no significant difference on the survival and prognosis of PCa patients (P>0.05). TCGA clinical data analysis found that the expression of FCGR3A had a unique correlation with the clinicopathological features of PCa, which was closely related to the tumor stage. The expression of FCGR3A is related to BCR free survival of PCa patients. Therefore, FCGR3A is a new biomarker with potential prognostic value of PCa.

Dataset Information

Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome.

Publications

Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome.

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