SNW1 is a prognostic biomarker in prostate cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Hoflmayer D
PROVIDER: S-EPMC6495565 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
Publications
SNW1 is a prognostic biomarker in prostate cancer.
Höflmayer Doris D Willich Carla C Hube-Magg Claudia C Simon Ronald R Lang Dagmar D Neubauer Emily E Jacobsen Frank F Hinsch Andrea A Luebke Andreas M AM Tsourlakis Marie Christina MC Huland Hartwig H Graefen Markus M Haese Alexander A Heinzer Hans H Minner Sarah S Büscheck Franziska F Sauter Guido G Schlomm Thorsten T Steurer Stefan S Clauditz Till S TS Burandt Eike E Wilczak Waldemar W Bernreuther Christian C
Diagnostic pathology 20190501 1
<h4>Background</h4>SNW1 is a nuclear receptor co-activator involved in splicing and transcription control, including androgen receptor signaling. Overexpression of SNW1 has been linked to adverse prognosis in different cancer types, but studies on the role of SNW1 in prostate cancer are lacking.<h4>Methods</h4>Using immunohistochemistry, we analyzed SNW1 expression in 10,310 prostate cancers in a tissue microarray (TMA) with attached clinical and molecular data.<h4>Results</h4>The comparison wit ...[more]
Similar Datasets
Project description:Prostate cancer is a complex heterogeneous disease that affects millions of males worldwide. Despite rapid advances in molecular biology and innovation in technology, few biomarkers have been forthcoming in prostate cancer. The currently available biomarkers for the prognosis of prostate cancer are inadequate and face challenges, thus having limited clinical utility. To date, there are a number of prognostic and predictive biomarkers identified for prostate cancer but lack specificity and sensitivity to guide clinical decision making. There is still tremendous scope for specific biomarkers to understand the natural history and complex biology of this heterogeneous disease, and to identify early treatment responses. Accumulative studies indicate that aquaporins (AQPs) a family of membrane water channels may serve as a prognostic biomarker for prostate cancer in monitoring disease advancement. In the present review, we discuss the existing prostate cancer biomarkers, their limitations, and aquaporins as a prospective biomarker of prognostic significance in prostate cancer.
| S-EPMC9856769 | biostudies-literature
Project description:Prostate cancer is the most frequently diagnosed cancer and the fifth leading cause of cancer death among men in 2020. The clinical decision making for prostate cancer patients is based on the stratification of the patients according to both clinical and pathological parameters such as Gleason score and prostate-specific antigen levels. However, these tools still do not adequately predict patient outcome. The aim of this study was to investigate whether ZNF750 could have a role in better stratifying patients, identifying those with a higher risk of metastasis and with the poorest prognosis. The data reported here revealed that ZNF750 protein levels are reduced in human prostate cancer samples, and this reduction is even higher in metastatic samples. Interestingly, nuclear positivity is significantly reduced in patients with metastatic prostate cancer, regardless of both Gleason score and grade group. More importantly, the bioinformatics analysis indicates that ZNF750 expression is positively correlated with better prognosis. Overall, our findings suggest that nuclear expression of ZNF750 may be a reliable prognostic biomarker for metastatic prostate cancer, which lays the foundation for the development of new biological therapies.
| S-EPMC10095592 | biostudies-literature
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.
| S-EPMC8991690 | biostudies-literature
Project description: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).
| S-EPMC6388024 | biostudies-literature
Project description:BACKGROUND TRAF2 exerts important functions in regulating the development and progression of cancer. The aim of this study is to investigate whether TRAF2 is a valuable prognostic biomarker and to determine if it regulates TRAIL-induced apoptosis in prostate cancer. MATERIAL AND METHODS Microarray gene expression data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to determine TRAF2 expression in prostate cancer. TRAF2 expression in prostate cancer was further investigated by immunohistochemistry assay. Kaplan-Meier curves and log-rank test were used to assess the recurrence-free rate. Cox regression was used to analyze prognostic factors. Effects of TRAF2 on regulating TRAIL-induced apoptosis in DU-145 cells were further investigated. RESULTS We found that TRAF2 was significantly upregulated in prostate cancer compared with normal prostate samples (P<0.001). In addition, compared with primary prostate cancer, TRAF2 was upregulated in metastatic prostate cancer (P=0.006). Furthermore, our results showed that high expression of TRAF2 was significantly associated with tumor stage of prostate cancer (P=0.035). TRAF2 high expression was associated with poorer recurrence-free survival in prostate cancer patients (P=0.013). TRAF2 was found to be a valuable independent prognostic factor for predicting recurrence-free survival (P=0.026). In addition, the present results indicate that TRAF2 affects TRAIL-induced apoptosis in prostate cancer DU-145 cells via regulating cleaved Caspase-8 and c-Flip expression. CONCLUSIONS TRAF2 could be a novel prognostic biomarker for predicting recurrence-free survival in patients with prostate cancer, which might be associated with the effects of TRAF2 in regulating TRAIL-induced apoptosis in prostate cancer cells via c-Flip/Caspase-8 signalling.
| S-EPMC5590516 | biostudies-literature
Project description:Rapid advances in the discovery of long noncoding RNAs (lncRNAs) have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa). Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA) and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P=.00126), PSS (P=.0385), and MFS (P=.000609), with trends for OS as well (P=.056). An RNA in-situ hybridization (ISH) assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence.
| S-EPMC5018094 | biostudies-literature
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.
| S-EPMC9730230 | biostudies-literature
Project description:Long Noncoding RNAs (LncRNAs) have recently been identified as key regulator in tumor progression. The LncRNA MAFG-AS1 has been reported to facilitate the progression of multiple cancers, however, its role in prostate cancer is still unknown. Here, we reported that MAFG-AS1 was upregulated in prostate cancer. Importantly, high expression of MAFG-AS1 indicated advanced stage prostate cancer. Univariate and Multivariate Cox regression analyses showed that high MAFG-AS1 expression was independently correlated with poor progression-free interval (PFI). According to the result of The Cancer Genome Atlas (TCGA) database and tissue microarray, high MAFG-AS1 expression indicated a poor prognosis in prostate cancer patients. In addition, gene functional enrichment analysis revealed that MAFG-AS1 may be involved in ribosome biogenesis, ribonucleoprotein complex subunit organization, ribonucleoprotein complex assembly, rRNA metabolic process, structural constituent of ribosome, and ribonucleoprotein complex binding. Furthermore, MAFG-AS1 knockdown by siRNA markedly impaired prostate cancer cell proliferation, migration, and invasion.
| S-EPMC9389335 | biostudies-literature
Project description:BackgroundWhile prostate cancer can often manifest as an indolent disease, the development of locally-advanced or metastatic disease can cause significant morbidity or mortality. Elucidation of molecular mechanisms contributing to disease progression is crucial for more accurate prognostication and effective treatments. R-Spondin 3 (RSPO3) is a protein previously implicated in the progression of colorectal and lung cancers. However, a role for RSPO3 in prostate cancer prognosis and behaviour has not been explored.MethodsWe compare the relative levels of RSPO3 expression between normal prostate tissue and prostate cancer in two independent patient cohorts (Taylor and GSE70768-Cambridge). We also examine the association of biochemical relapse with RSPO3 levels in these cohorts. For elucidation of the biological effect of RSPO3, we use siRNA technology to reduce the levels of RSPO3 in established prostate cancer cell lines, and perform in vitro proliferation, invasion, western blotting for EMT markers and clonogenic survival assays for radiation resistance. Furthermore, we show consequences of RSPO3 knockdown in an established chick chorioallantoic membrane (CAM) assay model of metastasis.ResultsRSPO3 levels are lower in prostate cancer than normal prostate, with a tendency for further loss in metastatic disease. Patients with lower RSPO3 expression have lower rates of biochemical relapse-free survival. SiRNA-mediated loss of RSPO3 results in no change to clonogenic survival and a lower proliferative rate, but increased invasiveness in vitro with induction of epithelial-mesenchymal transition (EMT) markers. Consistent with these results, lower RSPO3 expression translates to greater metastatic capacity in the CAM assay. Together, our preclinical findings identify a role of RSPO3 downregulation in prostate cancer invasiveness, and provide a potential explanation for how RSPO3 functions as a positive prognostic marker in prostate cancer.
| S-EPMC6466739 | biostudies-literature
Project description:Predicting the risk of metastasis before starting prostate cancer (PCa) treatment can minimize the overtreatment of indolent cases and help choosing appropriate treatment. The levels of circulating microRNAs (miRNAs) from body fluids can be used as noninvasive prognostic biomarkers. In this study, urinary exosomal miRNA expression profiles of 149 PCas were determined and the miRNAs associated with metastasis were identified: miR-21, miR-16, miR-142-3p, miR-451, and miR-636. When evaluating clinical factors together, miR-21, miR-451, miR-636, and preoperative prostate-specific antigen (PSA) level remained significant in the multivariate analysis. Based on them, we developed a "Prostate Cancer Metastasis Risk Scoring (PCa-MRS)" model. The PCa-MRS showed superior stratification power (AUC = 0.925) to preoperative PSA or clinical Gleason score. Patients with high scores showed significantly poorer biochemical recurrence-free survival than those with low scores (P = 6.53 × 10-10). Our results showed the potential of urinary exosomal miRNAs as noninvasive markers for predicting metastasis and prognosis in PCa patients.
| S-EPMC8196022 | biostudies-literature