Proteogenomics of clear cell renal cell carcinoma response to tyrosine kinase inhibitor.

The tyrosine kinase inhibitor (TKI) Sunitinib is one the therapies approved for advanced renal cell carcinoma. Here, we undertake proteogenomic profiling of 115 tumors from patients with clear cell renal cell carcinoma (ccRCC) undergoing Sunitinib treatment and reveal the molecular basis of differential clinical outcomes with TKI therapy. We find that chromosome 7q gain-induced mTOR signaling activation is associated with poor therapeutic outcomes with Sunitinib treatment, whereas the aristolochic acid signature and VHL mutation synergistically caused enhanced glycolysis is correlated with better prognosis. The proteomic and phosphoproteomic analysis further highlights the responsibility of mTOR signaling for non-response to Sunitinib. Immune landscape characterization reveals diverse tumor microenvironment subsets in ccRCC. Finally, we construct a multi-omics classifier that can detect responder and non-responder patients (receiver operating characteristic-area under the curve, 0.98). Our study highlights associations between ccRCC molecular characteristics and the response to TKI, which can facilitate future improvement of therapeutic responses.

The function and mechanisms of action of circular RNAs in Urologic Cancer.

Kidney, bladder, and prostate cancer are the three major tumor types of the urologic system that seriously threaten human health. Circular RNAs (CircRNAs), special non-coding RNAs with a stabile structure and a unique back-splicing loop-forming ability, have received recent scientific attention. CircRNAs are widely distributed within the body, with important biologic functions such as sponges for microRNAs, as RNA binding proteins, and as templates for regulation of transcription and protein translation. The abnormal expression of circRNAs in vivo is significantly associated with the development of urologic tumors. CircRNAs have now emerged as potential biomarkers for the diagnosis and prognosis of urologic tumors, as well as targets for the development of new therapies. Although we have gained a better understanding of circRNA, there are still many questions to be answered. In this review, we summarize the properties of circRNAs and detail their function, focusing on the effects of circRNA on proliferation, metastasis, apoptosis, metabolism, and drug resistance in kidney, bladder, and prostate cancers.

Proteogenomic characterization of MiT family translocation renal cell carcinoma.

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

A proteogenomic analysis of clear cell renal cell carcinoma in a Chinese population.

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of renal cancer. Here we conduct a comprehensive proteogenomic analysis of 232 tumor and adjacent non-tumor tissue pairs from Chinese ccRCC patients. By comparing with tumor adjacent tissues, we find that ccRCC shows extensive metabolic dysregulation and an enhanced immune response. Molecular subtyping classifies ccRCC tumors into three subtypes (GP1-3), among which the most aggressive GP1 exhibits the strongest immune phenotype, increased metastasis, and metabolic imbalance, linking the multi-omics-derived phenotypes to clinical outcomes of ccRCC. Nicotinamide N-methyltransferase (NNMT), a one-carbon metabolic enzyme, is identified as a potential marker of ccRCC and a drug target for GP1. We demonstrate that NNMT induces DNA-dependent protein kinase catalytic subunit (DNA-PKcs) homocysteinylation, increases DNA repair, and promotes ccRCC tumor growth. This study provides insights into the biological underpinnings and prognosis assessment of ccRCC, revealing targetable metabolic vulnerabilities.

Identification of prognostic biomarkers in papillary renal cell carcinoma and PTTG1 may serve as a biomarker for predicting immunotherapy response.

OBJECTIVE: This study aims to identify potential prognostic and therapeutic biomarkers in papillary renal cell carcinoma (pRCC). METHODS: Two microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified. The protein-protein interaction (PPI) networks and functional annotations of DEGs were established. Survival analysis was utilized to evaluate the prognostic significance of the DEGs and the association between the expression level of candidate biomarkers and various tumour-infiltrating immune cells was explored. The role of PTTG1 in tumour microenvironments (TME) was further explored using Single-cell RNA-seq and its prognostic and therapeutic significance was validated in Fudan University Shanghai Cancer Centre (FUSCC) cohort. RESULTS: Eight genes, including BUB1B, CCNB1, CCNB2, MAD2L1, TTK, CDC20, PTTG1, and MCM were found to be negatively associated with patients' prognosis. The expression level of PTTG1 was found to be significantly associated with lymphocytes, immunomodulators, and chemokine in the TCGA cohort. Single-cell RNA-seq information indicated that PTTG1 was strongly associated with the proliferation of T cells. In the FUSCC cohort, the expression level of PTTG1 was also statistically significant for both progression-free survival (PFS) and overall survival (OS) prediction (HR = 2.683, p < .001; HR = 2.673, p = .001). And higher expression level of PTTG1 was significantly associated with immune checkpoint blockade (ICB) response in the FUSCC cohort (χ2=3.99, p < .05). CONCLUSIONS: Eight genes were identified as a prognostic biomarker and the expression level of PTTG1 was also found to serve as a potential predictor for ICB response in pRCC patients.Key messages:Eight genes, including BUB1B, CCNB1, CCNB2, MAD2L1, TTK, CDC20, PTTG1, and MCM were found to be negatively associated with pRCC patients' prognosis.Expression level of PTTG1 was significantly associated with tumour microenvironment including lymphocytes, immunomodulators, and chemokines.Higher expression level of PTTG1 was significantly associated with immune checkpoint blockade (ICB) response in FUSCC cohort.

Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data.

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large-scale multiomics analysis and real-world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis-related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI's GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki-67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients' prognosis using proteomic data, gene expression data and real-world data and this prognostic model showed stronger predictive value than other biomarkers (Ki-67, Beta-catenin, etc) in multi-cohorts.

Identification and validation of novel metastasis-related signatures of clear cell renal cell carcinoma using gene expression databases.

Patients with clear cell renal cell carcinoma (ccRCC) typically face aggressive disease progression when metastasis occurs. Here, we screened and identified differentially expressed genes in three microarray datasets from the Gene Expression Omnibus database. We identified 112 differentially expressed genes with functional enrichment as candidate prognostic biomarkers. Lasso Cox regression suggested 10 significant oncogenic hub genes involved in earlier recurrence and poor prognosis of ccRCC. Receiver operating characteristic curves validated the specificity and sensitivity of the Cox regression penalty used to predict prognosis. The area under the curve indexes of the integrated genes scores were 0.758 and 0.772 for overall and disease-free survival, respectively. The prognostic values of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2, and TRIB3 were validated through an analysis of 10 hub genes in 380 patients with ccRCC from a real-world cohort. The expression levels of were of high prognostic value for predicting metastatic potential. These findings will likely significantly contribute to our understanding of the underlying mechanisms of ccRCC, which will enhance efforts to optimize therapy.

Large-scale transcriptome profiles reveal robust 20-signatures metabolic prediction models and novel role of G6PC in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post-operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20-mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA (P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts (P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC, a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis (P < 0.0001, HR = 0.316) and aggressive progression (P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check-point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large-scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.

Development and validation of a robust multigene signature as an aid to predict early relapse in stage I-III clear cell and papillary renal cell cancer.

Background and objectives: Multi-gene signature can be used as prognostic indicator in many types of cancer, but the association with early-relapse in patients with stage I-III clear cell and papillary renal cell cancer (RCC) is unknown. We aim to establish a mRNAs signature for improving prediction of early-relapse in patients with stage I-III clear cell and papillary RCC. Methods: The data of 610 patients with stage I-III RCC from The Cancer Genome Atlas (TCGA) and 270 patients from Fudan University Shanghai Cancer Center (FUSCC) were extracted. Propensity score matching analysis, linear models for microarray data VOOM method, least absolute shrinkage and selection operation Cox regression modeling analysis was conducted in turn for selecting multi-mRNA signature. Survival differences were assessed by Kaplan-Meier estimate and compared using log-rank test. Multivariable Cox regression and time-dependent receiver operating characteristic curves were used to evaluate the association of mRNAs signature with relapse-free survival (RFS). Results: Seventeen mRNAs were identified to constitute the early-relapse signature. Among patients with stage I-III RCC, those with high-risk score calculated from 17 mRNAs signature showed shorter RFS than those with low-risk score, both in TCGA discovery and internal validation sets, and in FUSCC discovery and internal validation sets (all p < 0.05). In multivariable Cox regression analysis, the 17 mRNAs signature remained an independent prognostic factor both in TCGA discovery (HR 2.43, 95%CI 1.98-2.96) and internal validation sets (HR 1.66, 95%CI 1.19-2.30), and FUSCC discovery (HR 1.28, 95%CI 1.13-1.43) and internal validation sets (HR 1.65, 95%CI 1.11-2.48). Additionally, the 17 mRNAs signature achieved a higher accuracy for RFS estimation beyond clinical indicator. Conclusion: The 17 mRNAs signature could classify stage I-III RCC patients into low- or high-risk of early-relapse, and will help to guide interventions to optimize survival outcomes.

Prognostic value of epithelial-mesenchymal transition markers in clear cell renal cell carcinoma.

Epithelial-to-mesenchymal transition (EMT) is important in tumor invasiveness and metastasis. We aimed to determine prognostic value of six key EMT markers (CDH1, CDH2, SNAI1, SNAI2, VIM, TWIST1) in clear cell renal cell carcinoma (ccRCC). A total of 533 ccRCC patients with RNASeq data from The Cancer Genome Atlas (TCGA) cohort were included for analysis. Gene expression of these EMT markers was compared between tumor and normal tissues based on Oncomine database and TCGA cohort. Their correlations with progression-free survival (PFS) and overall survival (OS) were also examined in both TCGA cohort and FUSCC (Fudan University Shanghai Cancer Center) cohort. Cox proportional hazards regression model and Kaplan-Meier plot were used to assess the relative factors. Functional enrichment analyses were utilized to describe biologic function annotations and significantly involved hallmarks pathways of each gene. We found that Epithelial marker, CDH1 expression was lower, while mesenchymal markers (CDH2, SNAI1, VIM, TWIST1) expression was higher in ccRCC primary tumors. In the TCGA cohort, we found that patients with higher expression of VIM, TWIST1 or lower expression of CDH1 had worse prognosis. Further, in the FUSCC cohort, we confirmed the predictive ability of mesenchymal markers and epithelial marker expression in PFS and OS of ccRCC patients. After generating Cox regression models, EMT markers (CDH1, SNAI1, VIM, and TWIST1) were independent prognostic factors of both PFS and OS in ccRCC patients. Our preliminary EMT prediction model can facilitate further screening of EMT biomarkers and cast a better understanding of EMT gene function in ccRCC.

The Role of Serine Peptidase Inhibitor Kazal Type 13 (SPINK13) as a Clinicopathological and Prognostic Biomarker in Patients with Clear Cell Renal Cell Carcinoma.

BACKGROUND The serine peptidase inhibitor Kazal type 13 (SPINK13) gene has tumor suppressor activity, but its role in renal cell carcinoma (RCC) remains unknown. This study aimed to investigate mRNA expression of SPINK13 in clear cell renal cell carcinoma (CCRCC) in human tissue and to use bioinformatics data to investigate the role of SPINK13 expression as a clinicopathological and prognostic biomarker for patients with CCRCC. MATERIAL AND METHODS Patients with CCRCC (N=533) with available RNA sequence data from The Cancer Genome Atlas (TCGA)-CCRCC database were analyzed with patients who had a tissue diagnosis of CCRCC (N=305) at the Fudan University Shanghai Cancer Center (FUSCC). Differential transcriptional and proteome expression profiles were obtained from the ONCOMINE cancer microarray database, TCGA, and the Human Protein Atlas (HPA) database. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) measured SPINK13 mRNA expression in 305 samples of CCRCC tissue from the FUSCC. The effects of clinicopathological parameters on progression-free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier and log-rank test. RESULTS Transcriptional and proteome expression of SPINK13 were significantly increased CCRCC tissue samples. Increased SPINK13 mRNA expression was significantly associated with reduced PFS and OS in 838 patients with CCRCC patients from the two independent cohorts, the FUSCC and the TCGA-CCRCC cohorts (p<0.01). Gene set enrichment analysis (GSEA) showed that SPINK13 expression was involved in complement, apical junction, epithelial-mesenchymal transition (EMT), glycolysis, hypoxia, and inflammation signaling pathways. CONCLUSIONS Increased expression of SPINK13 was associated with poor prognosis in patients with CCRCC.

Prognostic implications of Aquaporin 9 expression in clear cell renal cell carcinoma.

BACKGROUND: Growing evidence has demonstrated immune reactivity as a confirmed important carcinogenesis and therapy efficacy for clear cell renal cell carcinoma (ccRCC). Aquaporin 9 (AQP9) is involved in many immune-related signals; however, its role in ccRCC remains to be elucidated. This study investigated AQP9 expression in tumor tissues and defined the prognostic value in ccRCC patients. METHODS: A total of 913 ccRCC patients with available RNA-sequence data from the Cancer Genome Atlas (TCGA) database and Fudan University Shanghai Cancer Center (FUSCC) were consecutively recruited in analyses. Differential transcriptional and proteome expression profiles were obtained and validated using multiple datasets. A partial likelihood test from Cox regression analysis was developed to address the influence of independent factors on progression-free survival (PFS) and overall survival (OS). The Kaplan-Meier method and log-rank test were performed to assess survival. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of AQP9 using area under the curve (AUC) score. Functional enrichment analyses and immune infiltration analysis were used to describe significantly involved hallmark pathways of hub genes. RESULTS: Significantly elevated transcriptional and proteomic AQP9 expressions were found in ccRCC samples. Increased AQP9 mRNA expression was significantly associated with advanced clinicopathological parameters and correlated with shorter PFS and OS in TCGA and FUSCC cohorts (p < 0.001). ROC curves suggested the significant diagnostic and prognostic ability of AQP9 (PFS, AUC = 0.823; OS, AUC = 0.828). Functional annotations indicated that AQP9 is involved in the most significant hallmarks including complement, coagulation, IL6/JAK-STAT3, inflammatory response and TNF-alpha signaling pathways. CONCLUSION: Our study revealed that elevated AQP9 expression was significantly correlated with aggressive progression, poor survival and immune infiltrations in ccRCC patients, and we validated its prognostic value in a real-world cohort. These data suggest that AQP9 may act as an oncogene and a promising prognostic marker in ccRCC.

C-Reactive Protein Levels and Survival Following Cytoreductive Nephrectomy in 118 Patients with Metastatic Renal Cell Carcinoma Treated with Sunitinib: A Retrospective Study.

BACKGROUND This study aimed to evaluate the factors associated with a survival benefit for patients with metastatic renal cell carcinoma (mRCC) treated with sunitinib, with and without cytoreductive nephrectomy (CN). MATERIAL AND METHODS This retrospective clinical study included 118 patients with mRCC who were treated with CN and sunitinib (CN-sunitinib) (N=70) and with sunitinib-alone (N=48). Categorical clinicopathological variables were compared with hypothesis tests using contingency tables and a chi-squared test. Independent indicators for progression-free survival (PFS) and overall survival (OS) were analyzed with univariate and multivariate Cox regression models. The Kaplan-Meier method and log-rank test were used to evaluate patient survival. RESULTS The median PFS and OS for the 118 patients were 8.38 and 15.48 months, respectively. There were no significant differences between the CN-sunitinib group and the sunitinib-alone group for either PFS (7.2 months vs. 11.6 months; P=0.525) or OS (16.7 months vs. 15.2 months; P=0.839). Stratification of patients based on clinicopathological characteristics showed that CN was significantly associated with reduced PFS and OS for patients with lymph node metastasis (PFS, P<0.001; OS, P<0.001) and high International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk scores (PFS, P=0.003; OS, P=0.011). However, CN was associated with a significant survival benefit for patients with low levels of serum C-reactive protein (CRP<10 mg/L) (PFS, P=0.026; OS, P=0.007). CONCLUSIONS Sunitinib-alone without CN improved the survival of patients with mRCC who had high IMDC risk scores or lymph node metastasis. CN and sunitinib resulted in significantly improved survival in patients with low serum CRP.

Screening and Identification of Potential Prognostic Biomarkers in Adrenocortical Carcinoma.

Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. The Kaplan-Meier method for the integrated expression score was applied to analyze survival outcomes. A receiver operating characteristic (ROC) curve was constructed with area under curve (AUC) analysis to determine the diagnostic ability of the candidate biomarkers. Results: A total of 150 DEGs and 24 significant hub genes with functional enrichment were identified as candidate prognostic biomarkers. LASSO Cox regression suggested that ZWINT, PRC1, CDKN3, CDK1 and CCNA2 were independent prognostic factors in ACC. In multivariate Cox analysis, the integrated expression scores of the modules showed statistical significance in predicting disease-free survival (DFS, P = 0.019) and overall survival (OS, P < 0.001). Meanwhile, ROC curves were generated to validate the ability of the Cox model to predict prognosis. The AUC index for the integrated genes scores was 0.861 (P < 0.0001). Conclusion: In conclusion, the present study identifies DEGs and hub genes that may be involved in poor prognosis and early recurrence of ACC. The expression levels of ZWINT, PRC1, CDKN3, CDK1 and CCNA2 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ACC. Further studies are required to elucidate molecular pathogenesis and alteration in signaling pathways for these genes in ACC.

Prognostic value and immune infiltration of novel signatures in clear cell renal cell carcinoma microenvironment.

Growing evidence has highlighted the immune response as an important feature of carcinogenesis and therapeutic efficacy in clear cell renal cell carcinoma (ccRCC). This study categorized ccRCC cases into high and low score groups based on their immune/stromal scores generated by the ESTIMATE algorithm, and identified an association between these scores and prognosis. Differentially expressed tumor environment (TME)-related genes extracted from common upregulated components in immune and stromal scores were described using functional annotations and protein-protein interaction (PPI) networks. Most PPIs were selected for further prognostic investigation. Many additional previously neglected signatures, including AGPAT9, AQP7, HMGCS2, KLF15, MLXIPL, PPARGC1A, exhibited significant prognostic potential. In addition, multivariate Cox analysis indicated that MIXIPL and PPARGC1A were the most significant prognostic signatures, and were closely related to immune infiltration in TCGA cohort. External prognostic validation of MIXIPL and PPARGC1A was undertaken in 380 ccRCC cases from a real-world cohort. These findings indicate the relevance of monitoring and manipulation of the microenvironment for ccRCC prognosis and precision immunotherapy.

Association of glutathione S-transferase T1 and M1 polymorphisms with prostate cancer susceptibility in populations of Asian descent: a meta-analysis.

BACKGROUND: Genetic polymorphism was hypothesized to be reason of variation in prostate cancer incidence among different racial group. Based on that published data on the association of prostate cancer susceptibility with polymorphisms in genes encoding Glutathione S-transferases (GSTs) were inconclusive, the aim of this study was to more precisely address the role of GSTs polymorphisms (especially, GSTT1 and GSTM1 deletions) on prostate cancer risk in Asian descent. METHODS: A meta-analysis including 8 articles with 711 cases and 1122 controls for GSTT1 and 1098 cases and 1588 controls for GSTM1 was performed. RESULTS: Significantly increased prostate cancer risk was found among subjects carrying GSTM1 null genotype (odds ratio (OR) = 1.403; 95% confidence interval (CI) = 1.088 - 1.808) but not among subjects carrying GSTT1 deletion genotype (OR = 0.959; 95%CI = 0.709 - 1.297). When stratified by country, the null genotype of GSTT1 neither increased nor decreased prostate cancer risk significantly in China (OR = 1.355; 95%CI = 0.895 - 2.049), Japan (OR = 0.812; 95%CI = 0.545 - 1.211), and Korea (OR = 1.056; 95%CI = 0.727 - 1.534). While significant association of elevated prostate cancer risk with GSTM1 deletion were found in China (OR = 1.665; 95%CI = 1.324 - .094) and Korea (OR = 1.914; 95%CI = 1.311 - 2.793) but not in Japan (OR = 0.980; 95%CI = 0.726 - 1.321). CONCLUSIONS: In summary, this meta-analysis suggested that the null genotype of GSTM1 rather than GSTT1 may be involved in the etiology of prostate cancer in Asian population.

Prognostic significance of the TREK-1 K2P potassium channels in prostate cancer.

BACKGROUND: TREK-1 channels belong to the two-pore domain potassium channel superfamily and play an important role in central nervous system diseases. However, few studies have examined their role in carcinogenesis. METHODS: In this study, we assessed the expression of TREK-1 in 100 prostate cancer (PCa) tissues using immunohistochemistry and further analyzed its clinicopathological significance. Next, cell proliferation and cell cycle analysis were carried out on human PCa PC-3 cell lines where TREK-1 was stably knockdown. RESULTS: We found that compared with normal prostate tissues, PCa tissues showed overexpressed TREK-1 levels and TREK-1 levels were positively associated with Gleason score and T staging. High level of TREK-1 expression was related to shorter castration resistance free survival (CRFS). Furthermore, knockdown of TREK-1 significantly inhibited PCa cell proliferation in vitro and in vivo, and induced a G1/S cell cycle arrest. CONCLUSIONS: Our results suggest that TREK-1 might be a biomarker in CRFS judgment of PCa, as well as a potential therapeutic target.

MicroRNA-302a Suppresses Tumor Cell Proliferation by Inhibiting AKT in Prostate Cancer.

Micro (mi) RNAs are important regulators involved in various physical and pathological processes, including cancer. The miRNA-302 family has been documented as playing a critical role in carcinogenesis. In this study, we investigated the role of miRNA-302a in prostate cancer (PCa). MiRNA-302a expression was detected in 44 PCa tissues and 10 normal prostate tissues, and their clinicopathological significance was analyzed. Cell proliferation and cell cycle analysis were performed on PCa cells that stably expressed miRNA-302a. The target gene of miRNA-302a and the downstream pathway were further investigated. Compared with normal prostate tissues, miRNA-302a expression was downregulated in PCa tissues, and was even lower in PCa tissues with a Gleason score ≥8. Overexpression of miRNA-302a induced G1/S cell cycle arrest in PCa cells, and suppressed PCa cell proliferation both in vitro and in vivo. Furthermore, miRNA-302a inhibits AKT expression by directly binding to its 3΄ untranslated region, resulting in subsequent alterations of the AKT-GSK3ß-cyclin D1 and AKT-p27Kip1 pathway. These results reveal miRNA-302a as a tumor suppressor in PCa, suggesting that miRNA-302a may be used as a potential target for therapeutic intervention in PCa.

An elevated serum miR-141 level in patients with bone-metastatic prostate cancer is correlated with more bone lesions.

The skeleton is the most common metastatic organ in patients with prostate cancer (PCa). Non-invasive biomarkers that can facilitate the detection and monitoring of bone metastases are highly desirable. We designed this study to assess the expression patterns of serum miR-141 in patients with bone-metastatic PCa. Serum samples were collected to measure the miR-141 level in 56 patients, including six with benign prostatic hyperplasia (BPH), 20 with localized PCa and 30 with bone-metastatic PCa (10 with hormone-naive PCa, 10 with hormone-sensitive PCa and 10 with hormone-refractory PCa). A bone scan was performed for each patient with PCa to assess the number of bone lesions. The quantification of serum miR-141 levels was assayed by specific TaqMan qRT-PCR. The results showed that serum miR-141 levels were elevated in patients with bone metastasis (P<0.001). There was no statistically significant difference in the serum miR-141 levels between patients with BPH and patients with localized PCa. Using Kendall's bivariate correlation test, both the Gleason score and the number of bone-metastatic lesions were found to correlate with serum miR-141 levels (P=0.012 and P<0.001, respectively). The serum miR-141 level was found to be positively correlated with alkaline phosphatase (ALP) level in patients with skeletal metastasis, using Pearson's bivariate correlation test. No relationship was found between the serum miR-141 level and the serum prostate-specific antigen (PSA) level. We concluded that serum miR-141 levels are elevated in patients with bone-metastatic PCa and that patients with higher levels of serum miR-141 developed more bone lesions. Furthermore, serum miR-141 levels are correlated with serum ALP levels but not serum PSA levels.