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Combined overexpression of HIVEP3 and SOX9 predicts unfavorable biochemical recurrence-free survival in patients with prostate cancer.

ABSTRACT: BACKGROUND:To clarify the involvement of HIVEP3 and SOX9 coexpression in prostate cancer (PCa). METHODS:A small interfering RNA was used to knockdown SOX9 expression in a PCa cell line and to analyze the effects of SOX9 inhibition on the expression of HIVEP3 in vitro. Then, HIVEP3 and SOX9 expression patterns in the human PCa tissues were detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry. RESULTS:We found that the downregulation of SOX9 could inhibit the expression of HIVEP3 in the PCa cells in vitro. In addition, both HIVEP3 and SOX9 messenger RNA expression levels in the PCa tissues were significantly higher than those in the noncancerous prostate tissues (P=0.006 and P<0.001, respectively). Moreover, the immunohistochemical staining scores of HIVEP3 in the PCa tissues with PSA failure were significantly higher than those without (P=0.042); the increased SOX9 protein expression was more frequently found in the PCa tissues with a high Gleason score (P=0.045) and a high clinical stage (P=0.012). The tumors showing the HIVEP3-high/SOX9-high expression more frequently had PSA failure (P=0.024). When the patients with an HIVEP3 overexpression combined with the SOX9 overexpression, this group had a worse biochemical recurrence-free survival (P<0.001). Furthermore, the multivariate analysis showed that the HIVEP3/SOX9 coexpression was an independent predictor of an unfavorable biochemical recurrence-free survival. CONCLUSION:Our data offer the convincing evidence for the first time that a combined analysis of HIVEP3 and SOX9 may help to predict the tumor progression and prognosis of PCa patients. In particular, the overexpression of HIVEP3 in PCa might partly explain the poor prognosis of patients with an upregulation of SOX9.

SUBMITTER: Qin GQ

PROVIDER: S-EPMC3908830 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Combined overexpression of HIVEP3 and SOX9 predicts unfavorable biochemical recurrence-free survival in patients with prostate cancer.

Qin Guo-Qiang GQ He Hui-Chan HC Han Zhao-Dong ZD Liang Yu-Xiang YX Yang Sheng-Bang SB Huang Ya-Qiang YQ Zhou Liang L Fu Hao H Li Jie-Xian JX Jiang Fu-Neng FN Zhong Wei-de WD

OncoTargets and therapy 20140124

<h4>Background</h4>To clarify the involvement of HIVEP3 and SOX9 coexpression in prostate cancer (PCa).<h4>Methods</h4>A small interfering RNA was used to knockdown SOX9 expression in a PCa cell line and to analyze the effects of SOX9 inhibition on the expression of HIVEP3 in vitro. Then, HIVEP3 and SOX9 expression patterns in the human PCa tissues were detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry.<h4>Results</h4>We found ...[more]

PMID: 24493929

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Project description:Background: D'Amico high-risk prostate cancer (Pca) patients experience poor and heterogeneous oncological outcomes. This heterogeneity highlights a need to extensively explore factors associated with poor outcomes to guide decision-making. Objective: To assess predictors of biochemical recurrence (BCR)-free survival in high-risk patients following radical prostatectomy (RP), and subsequently establish a model predicting outcomes. Methods: We retrospectively identified D'Amico high-risk non-metastatic Pca patients who underwent RP between 2013 and 2019 in our hospital. We collected data including PSA level, clinical stage, biopsy Gleason score (GS), number of D'Amico high-risk factors (RF), the inflammatory status (Neutrophil-to-lymphocyte ratio [NLR], derived NLR [dNLR], platelet-to-lymphocyte ratio [PLR] and LDH). Kaplan–Meier methods were used to analyze BCR-free survival. Univariate and multivariate analyses were performed using Cox proportional hazards model to evaluate the association between clinicopathological parameters and BCR-free survival. Results: The median follow-up time for the 101 patients' cohort was 26 months (range: 3–81 months). The number of RF (1RF vs. ?2RF), biopsy GS (<8 vs. ?8), clinical stage (?cT2c vs. >cT2c), pathological stage, and the presence of adverse pathological features were significant predictors of BCR (P < 0.05). Other parameters including inflammatory status (dNLR, NLR, PLR, and LDH) were not of predictive value. On multivariable analysis, biopsy GS (<8 vs. ?8; HR 2.439) and clinical stage (?cT2c vs. >cT2c; HR 3.271) were the independent predictors of BCR. Based on these two independent predictors, patients were stratified into three risk subgroups: favorable (0 risk factor; 47% of patients), intermediate (1 risk factor; 42 %), unfavorable (2 risk factors; 11%). The intermediate and unfavorable subgroups have a significantly shorter median BCR-free survival compared to the favorable subgroup (P < 0.001). Conclusion: Several factors are associated with BCR. Clinical stage (?cT2c vs. >cT2c) and biopsy GS (<8 vs. ?8) are the independent predictors of BCR. The stratification of high-risk patients into risk subgroups based on these two predictors shows that the intermediate and unfavorable subgroups have a significantly shorter median BCR-free survival compared to the favorable subgroup. The preoperative stratification model may help urologists and patients during decision-making. In non-metastatic high-risk patients, preoperative inflammatory markers (NLR, dNLR, PLR, and LDH) are not of prognostic value.

Project description:ObjectiveThis study aimed to establish a prognostic model related to prostate cancer (PCa) recurrence-free survival (RFS) and identify biomarkers.MethodsThe RFS prognostic model and key genes associated with PCa were established using Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression from the Cancer Genome Atlas (TCGA)-PRAD and the Gene Expression Omnibus (GEO) GSE46602 datasets. The weighted gene co-expression network (WGCNA) was used to analyze the obtained key modules and genes, and gene set enrichment analysis (GSEA) was performed. The phenotype and mechanism were verified in vitro.ResultsA total of 18 genes were obtained by LASSO regression, and an RFS model was established and verified (TCGA, AUC: 0.774; GSE70768, AUC: 0.759). Three key genes were obtained using multivariate Cox regression. WGCNA analysis obtained the blue module closely related to the Gleason score (cor = -0.22, P = 3.3e - 05) and the unique gene glutathione peroxidase 2 (GPX2). Immunohistochemical analysis showed that the expression of GPX2 was significantly higher in patients with PCa than in patients with benign prostatic hyperplasia (P < 0.05), but there was no significant correlation with the Gleason score (GSE46602 and GSE6919 verified), which was also verified in the GSE46602 and GSE6919 datasets. The GSEA results showed that GPX2 expression was mainly related to the epithelial-mesenchymal transition (EMT) and Wnt pathways. Additionally, GPX2 expression significantly correlated with eight kinds of immune cells. In human PCa cell lines LNCaP and 22RV1, si-GPX2 inhibited proliferation and invasion, and induced apoptosis when compared with si-NC. The protein expression of Wnt3a, glycogen synthase kinase 3β (GSK3β), phosphorylated (p)-GSK3β, β-catenin, p-β-catenin, c-myc, cyclin D1, and vimentin decreased; the expression of E-cadherin increased; and the results for over-GPX2 were opposite to those for over-NC. The protein expression of GPX2 decreased, and β-catenin was unchanged in the si-GPX2+ SKL2001 group compared with the si-NC group.ConclusionWe successfully constructed the PCa RFS prognostic model, obtained RFS-related biomarker GPX2, and found that GPX2 regulated PCa progression and triggered Wnt/β-catenin/EMT pathway molecular changes.

Project description:NR6A1/CT150, as an orphan receptor, is a novel member of the cancer-testis (CT) antigen family. Here, we investigated the expression and function of NR6A1 and its underlying mechanisms in prostate cancer (PCa) patients who underwent radical prostatectomy. A total of 303 cases of prostate cancer after radical prostatectomy were analysed in a tissue microarray (TMA) for NR6A1 immunohistochemistry-based protein expression. Kaplan-Meier/log-rank analysis and Cox regression analysis were used to investigate the relationship between NR6A1 expression and clinicopathological factors in PCa. NR6A1 mRNA expression was examined by reversing transcriptase-polymerase chain reaction (RT-PCR). Knockdown of NR6A1 by small interfering RNA mediated gene silencing and overexpression of NR6A1 through lentivirus were utilized to investigate its potential role in prostate cancer cells. NR6A1 protein expression was 29.7% (90/303) and mRNA expression was 28.1%(9/32) in PCa patients. NR6A1 expression was significantly associated with Gleason score (GS) (P=0.003) and tumor stage (P=0.042). The patients with positive NR6A1 expression have a shorter biochemical recurrence-free survival. NR6A1 predicted biochemical recurrence in univariate (P=0.0159) and multivariate models (P=0.0317). In addition, gene silencing of NR6A1 resulted in G0/G1 phase cell cycle arrest, and decreased metastatic and invasive potential of prostate cancer cells DU145 and PC3. In contrast, overexpression of NR6A1 reduced G0/G1 phase cell cycle arrest, and promoted metastatic and invasive potential of prostate cancer cells 22RV1. And overexpression of NR6A1 significantly promoted tumor growth in vivo. What's more, down regulation of NR6A1 could reverse epithelial-to-mesenchymal transition (EMT) process in DU145 and PC3 cell lines, and the overexpression could enhance EMT process in 22RV1 cell line. NR6A1 played a prominent role in migration and invasion of PCa cells, and it is indicated that NR6A1 may act as a novel marker for biochemical recurrence after radical prostatectomy.

Project description:BackgroundBiochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival.MethodsWe analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings.ResultsA total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model.ConclusionWe constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.

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Combined overexpression of HIVEP3 and SOX9 predicts unfavorable biochemical recurrence-free survival in patients with prostate cancer.

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Combined overexpression of HIVEP3 and SOX9 predicts unfavorable biochemical recurrence-free survival in patients with prostate cancer.

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