miR-198 inhibits the progression of renal cell carcinoma by targeting BIRC5.

BACKGROUND: miR-198 is involved in the formation, migration, invasion, and metastasis of various malignant cancers. However, the function and mechanism of action of miR-198 in the tumorigenesis of renal cell carcinoma (RCC) remain elusive. Here, we aimed to explore the role of miR198 in RCC. METHODS: Immunohistochemistry was performed to estimate the level of survivin in RCC sections. Quantitative real-time polymerase chain reaction was performed to determine the expression level of miR-198 in fresh RCC tissues. Furthermore, the target relationship between miR-198 and BIRC5 was predicted using the TargetScanHuman 7.2 database and verified via dual-luciferase reporter assay and western blotting. The effects of miR-198 on the viability, apoptosis, invasion, and migration of A498 and ACHN cells were studied using Cell Counting Kit-8, flow cytometry, transwell migration assay, and wound healing assay, respectively. Additionally, a xenograft nude mouse model was established to evaluate the effect of miR-198 on RCC tumorigenesis. RESULTS: The expression levels of BIRC5 and miR-198 were respectively higher and lower in RCC tissues than those in normal adjacent tissues. Furthermore, miR-198 could inhibit luciferase activity and reduce the protein level of survivin without affecting the BIRC5 mRNA levels. miR-198 inhibited cell viability, migration, and invasion and promoted cell apoptosis; co-transfection with BIRC5 could rescue these effects. Moreover, miR-198 could repress tumor growth in the xenograft nude mouse model of RCC. CONCLUSIONS: Our study demonstrates that miR-198 suppresses RCC progression by targeting BIRC5.

Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is still attracting public attention because of its outbreak in various cities in China. Predicting future outbreaks or epidemics disease based on past incidence data can help health departments take targeted measures to prevent diseases in advance. In this study, we propose a multistep prediction strategy based on extreme gradient boosting (XGBoost) for HFRS as an extension of the one-step prediction model. Moreover, the fitting and prediction accuracy of the XGBoost model will be compared with the autoregressive integrated moving average (ARIMA) model by different evaluation indicators. METHODS: We collected HFRS incidence data from 2004 to 2018 of mainland China. The data from 2004 to 2017 were divided into training sets to establish the seasonal ARIMA model and XGBoost model, while the 2018 data were used to test the prediction performance. In the multistep XGBoost forecasting model, one-hot encoding was used to handle seasonal features. Furthermore, a series of evaluation indices were performed to evaluate the accuracy of the multistep forecast XGBoost model. RESULTS: There were 200,237 HFRS cases in China from 2004 to 2018. A long-term downward trend and bimodal seasonality were identified in the original time series. According to the minimum corrected akaike information criterion (CAIC) value, the optimal ARIMA (3, 1, 0) × (1, 1, 0)12 model is selected. The index ME, RMSE, MAE, MPE, MAPE, and MASE indices of the XGBoost model were higher than those of the ARIMA model in the fitting part, whereas the RMSE of the XGBoost model was lower. The prediction performance evaluation indicators (MAE, MPE, MAPE, RMSE and MASE) of the one-step prediction and multistep prediction XGBoost model were all notably lower than those of the ARIMA model. CONCLUSIONS: The multistep XGBoost prediction model showed a much better prediction accuracy and model stability than the multistep ARIMA prediction model. The XGBoost model performed better in predicting complicated and nonlinear data like HFRS. Additionally, Multistep prediction models are more practical than one-step prediction models in forecasting infectious diseases.

Elevated MTA1 induced the migration and invasion of renal cell carcinoma through the NF-κB pathway.

BACKGROUND: The metastasis-associated gene 1 (MTA1) has been extensively reported as a crucial oncogene, and its abnormal expression has been associated with the progression of numerous cancers. However, the role of MTA1 in renal cell carcinoma (RCC) progression and metastasis remains unclear. Herein, we investigated the expression of MTA1 and its role in RCC. METHODS: 109 matched clear cell RCCs (ccRCCs) and corresponding normal tissue samples were analyzed via immunohistochemistry to test the expression of MTA1. Human A498 cell lines were transfected with pcDNA3.1-Flag (control) or Flag-MTA1 to overexpress MTA1 or with specific interfering RNA (si-MTA1) or specific interfering negative control to knockdown MTA1 expression. Transfected cells were used in wound healing and transwell invasion assay. Quantitative real time polymerase chain reaction was used to assess the effect of MTA1 on MMP2/MMP9 and E-cadherin gene expression. Western blot was used to qualify the phosphorylation of p65. RESULTS: Herein, we found a significantly increased expression of MTA1 in 109 ccRCCs, compared to the corresponding normal tissue. In addition, the overexpression of MTA1 in A498 cells facilitated cell migration and invasion, while the down-regulation of MTA1 expression using specific interfering RNA sequences could decrease cell migration and invasion. Furthermore, we showed that MTA1 is up-regulated in ccRCCs, which contributes to the migration and invasion of human kidney cancer cells by mediating the expression of MMP2 and MMP9 through the NF-κB signaling pathway. Similarly, we found that MTA1 could regulate E-cadherin expression in RCCs. CONCLUSIONS: MTA1 is overexpressed in RCC and is involved in the progression of RCC through NF-κB.

Speckle tracking echocardiography assessment of global and regional contraction dysfunction in the mice model of pressure overload.

Speckle tracking echocardiography (STE) has been applied to the evaluation of cardiac contraction dysfunction. However, there were few studies on alteration of global and regional STE parameters in the process of myocardial hypertrophy and heart failure. In this study, STE was applied to evaluate the global and regional cardiac function under heart failure and hypertrophy in the mice model of pressure overload. Adult mice were subjected to mild or severe aortic banding with a 25 Gauge (G) or 27 G needle. After surgery, STE and conventional echocardiography were used in the sham group (n=10), mild trans-aortic banding (TAB) group (n=14) and severe TAB group (n=10) for 8 weeks. The results showed that the mice subjected to severe TAB showed a significant change in fractional shortening (FS), left ventricular (LV) mass, and left ventricular end diastolic diameter (LVEDD) (P<0.05 for each). Meanwhile, there were no significant differences in FS and LVEDD between the sham group and mild TAB group during the experimental procedures (P>0.05 for both). STE analysis revealed that longitudinal strain (LS) was significantly decreased in the severe TAB group as compared with the sham and mild TAB groups (P<0.05 for both) from the postoperative week 1. LS in the mild TAB group was reduced as compared to the sham group (P<0.05). Radial strain (RS) and circumferential strain (CS) were significantly decreased in the severe TAB group as compared to the sham group and the mild TAB group (P<0.05 for both) from the postoperative week 1 (P<0.05 for both). Compared to the sham group, CS in the mild TAB group maintained unchanged during the test period, and RS was reduced only on the postoperative week 6 (P<0.05). Finally, regional contraction dysfunction was analyzed in both hypertrophic and failing myocardium in longitudinal and radial directions. It was found that LS was largest in the apex region and RS was smallest in the apex region in the healthy and hypertrophic myocardium. It was also found that compared to the sham group, only base longitudinal strain in the mild TAB group was decreased. Each of regional strain in the severe TAB group was uniformly depressed in radial and longitudinal directions. It is concluded that STE has provided a non-invasive and highly feasible way to explore the global and regional contraction dysfunction in hypertrophic and heart failure myocardium in the murine model of pressure overload.

BAG3 as a novel prognostic biomarker in kidney renal clear cell carcinoma correlating with immune infiltrates.

PURPOSE: BCL-2-associated athanogene 3 (BAG3) is an anti-apoptotic protein that plays an essential role in the onset and progression of multiple cancer types. However, the clinical significance of BAG3 in kidney renal clear cell carcinoma (KIRC) remains unclear. METHODS: Using Tumor IMmune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) database, we explored the expression, prognostic value, and clinical correlations of BAG3 in KIRC. In addition, immunohistochemistry (IHC) of HKH cohort further validated the expression of BAG3 in KIRC and its impact on prognosis. Gene Set Cancer Analysis (GSCA) was utilized to scrutinize the prognostic value of BAG3 methylation. Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to identify potential biological functions of BAG3 in KIRC. Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between BAG3 expression and immune cell infiltration. RESULTS: BAG3 mRNA expression and protein expression were significantly downregulated in KIRC tissues compared to normal kidney tissues, associated with adverse clinical-pathological factors and poor clinical prognosis. Multivariate Cox regression analysis indicated that low expression of BAG3 was an independent prognostic factor in KIRC patients. GSEA analysis showed that BAG3 is mainly involved in DNA methylation and the immune-related pathways in KIRC. In addition, the expression of BAG3 is closely related to immune cell infiltration and immune cell marker set. CONCLUSION: BAG3 might be a potential therapeutic target and valuable prognostic biomarker of KIRC and is closely related to immune cell infiltration.

Mendelian randomization analyses identified bioavailable testosterone mediates the effect of sex hormone-binding globulin on prostate cancer.

OBJECTIVE: A better knowledge of the hormonal etiology of prostate cancer is essential for its prevention and treatment. The goal of this study was to provide causal estimates of the connection between sex hormone-binding globulin and prostate cancer and investigate the possible mediating function of other modifiable risk indicators. METHODS: We used two-step, two-sample multivariable Mendelian randomization using single-nucleotide polymorphisms as instrumental variables for exposure and mediators. Single-nucleotide polymorphisms associated with sex hormone-binding globulin and bioavailable testosterone were screened via a genome-wide association study enrolling European-descent adult male individuals. Summary-level data for prostate cancer (79,148 cases and 61,106 controls) were extracted from the PRACTICAL consortium. The total effect of sex hormone-binding globulin on prostate cancer risk was decomposed into direct and indirect effects through the mediator, bioavailable testosterone. An inverse-variance-weighted method was the primary Mendelian randomization analysis method. Sensitivity analyses were performed via Mendelian randomization-Egger regression, heterogeneity test, pleiotropy test, and leave-one-out test. The directionality that exposure causes the outcome was verified using Mendelian randomization-Steiger test. RESULTS: In the univariable Mendelian randomization analysis, genetically predicted higher sex hormone-binding globulin levels had a causal association with lower prostate cancer risk (odds ratio = 0.944, 95% confidence interval = 0.897-0.993, p = 0.027) and an inverse association with bioavailable testosterone level (odds ratio = 0.945, 95% confidence interval = 0.926-0.965, p = 1.62E-07) without controlling for other factors. Moreover, an increase of one standard deviation (59.5 pmol/L) in genetically predicted bioavailable testosterone level was significantly associated with a 22.0% increase in the overall prostate cancer risk (odds ratio = 1.220, 95% confidence interval = 1.064-1.398, p = 0.004) after adjusting for sex hormone-binding globulin level. The effect size ratio of bioavailable testosterone-mediated sex hormone-binding globulin to prostate cancer was further analyzed to clarify the importance of the mediating effect. Notably, the mediator bioavailable testosterone explained 19.28% (95% confidence interval = 10.76%, 73.78%) of the total effect of sex hormone-binding globulin level on prostate cancer risk. CONCLUSION: The results support the potentially protective causal effect of genetically predicted higher sex hormone-binding globulin levels against prostate cancer with mediation by the modifiable risk factor, bioavailable testosterone. More research is needed to determine how this possible sex hormone-binding globulin-bioavailable testosterone-prostate cancer link works. Targeting sex hormone-binding globulin and bioavailable testosterone traits may be a valuable strategy for preventing prostate cancer.

Identifying effects of genetic obesity exposure on leukocyte telomere length using Mendelian randomization.

Background: Observational studies have shown that obesity is closely associated with leukocyte telomere length (LTL). However, the causal relationship between obesity and LTL remains unclear. This study investigated the causal relationship between obesity and LTL through the Mendelian randomization approach. Materials and Methods: The genome-wide association study (GWAS) summary data of several studies on obesity-related traits with a sample size of more than 600,000 individuals were extracted from the UK Biobank cohort. The summary-level data of LTL-related GWAS (45 6,717 individuals) was obtained from the IEU Open GWAS database. An inverse-variance-weighted (IVW) algorithm was utilized as the primary MR analysis method. Sensitivity analyses were conducted via MR-Egger regression, IVW regression, leave-one-out test, MR-pleiotropy residual sum, and outlier methods. Results: High body mass index was correlated with a short LTL, and the odds ratio (OR) was 0.957 (95% confidence interval [CI] 0.942-0.973, p = 1.17E-07). The six body fat indexes (whole body fat mass, right leg fat mass, left leg fat mass, right arm fat mass, left arm fat mass, and trunk fat mass) were consistently inversely associated with LTL. Multiple statistical sensitive analysis approaches showed that the adverse effect of obesity on LTL was steady and dependable. Conclusion: The current study provided robust evidence supporting the causal assumption that genetically caused obesity is negatively associated with LTL. The findings may facilitate the formulation of persistent strategies for maintaining LTL.

Mendelian randomization study on the causal relationship between leukocyte telomere length and prostate cancer.

BACKGROUND: Leukocyte telomere length (LTL) is related to prostate cancer (PCa). However, the causal relationship between them remains unknown. This study was aimed at identifying the causal direction between LTL and PCa with Mendelian randomization (MR). METHODS: Single-nucleotide polymorphisms associated with LTL were identified from a genome-wide association study (GWAS) involving 472,174 individuals. Summary-level data of PCa-related GWAS were extracted from four cohorts comprising 456,717 individuals. An inverse-variance-weighted (IVW) algorithm was used for MR. Sensitivity analyses were performed with MR-Egger regression, IVW regression, leave-one-out test, and MR-Pleiotropy Residual Sum and Outlier analyses. A meta-analysis was also performed to compute the average genetically determined effect of LTL on PCa. RESULTS: A long LTL was associated with an increased risk of PCa in all cohorts, with odds ratios of 1.368 (95% confidence interval [CI]: 1.247 to 1.500, P = 2.84×10-11), 1.503 (95% CI: 1.243 to 1.816, P = 2.57×10-5), 1.722 (95% CI: 1.427 to 2.077, P = 1.48×10-8), and 1.358 (95% CI: 1.242 to 1.484, P = 1.73×10-11) in the IVW analysis. Sensitivity analyses showed that the genetically determined effect of LTL on PCa was stable and reliable. The meta-analysis showed that the genetically determined per 1-standard deviation rise in LTL correlated significantly with an average 40.6% increase in the PCa risk, with an average odds ratio of 1.406 (95% CI: 1.327 to 1.489, P < 0.001). CONCLUSION: The results of this study supported the causal hypothesis that the genetically determined longer LTL was associated with a higher risk of PCa. This finding could serve as a basis for therapeutic strategies for PCa.

Putative causal inference for the relationship between obesity and sex hormones in males: a bidirectional Mendelian randomization study.

Background: Obesity is a chronic disease with a high prevalence rate and is an established risk factor for human health. Body mass index (BMI) is a common and primary indicator used in assessing obesity. This work aims to investigate the putative causal relationship among BMI, sex hormone-binding globulin (SHBG), bioavailable testosterone (BioT), and estradiol levels. Materials and Methods: We conducted a bidirectional Mendelian randomization study, using single-nucleotide polymorphisms (SNPs) strongly associated with BMI, SHBG, BioT, and estradiol as instrumental variables. All SNPs were identified from the genome-wide association study (GWAS) summary data of large sample studies recruiting more than 150,000 European adult male individuals. The inverse-variance-weighted (IVW) approach was used as a primary algorithm for putative causal estimation. Results: Genetically predicted elevated BMI was associated with decreased SHBG (IVW, ß = -0.103, 95% confidence interval [CI] [-0.113 to -0.092], P = 1.50 × 10-77) and BioT levels (IVW, ß = -0.139, 95% CI [-0.165 to -0.113], P = 9.54 × 10-26) and high estradiol levels (IVW, ß = 0.014, 95% CI [0.009-0.019], P = 2.19 × 10-7). Increased SHBG levels were causally associated with low BMI (IVW, ß = -0.051, 95% CI [-0.098 to -0.005], P = 0.030) and BioT (IVW, ß = -0.126, 95% CI [-0.175 to -0.077], P = 5.97 × 10-7) and high estradiol levels (IVW, ß = 0.046, 95% CI [0.035-0.056], P = 6.51 × 10-17). Conversely, no evidence of an effect of estradiol imbalance on SHBG levels (IVW, ß = 1.035, 95% CI [-0.854 to 2.926], P = 0.283) and BMI (IVW, ß = 0.091, 95% CI [-0.094 to 0.276], P = 0.336) was obtained. However, increased BioT levels were causally associated with lower SHBG levels (IVW, ß = -0.044, 95% CI [-0.061 to -0.026], P = 8.76 × 10-7), not BMI (IVW, ß = -0.006, 95% CI [-0.035 to 0.023], P = 0.679). Conclusions: The findings support a network putative causal relationship among BMI, SHBG, BioT, and estradiol. SHBG, BioT, and estradiol may partly mediate the effect of obesity on male health. Reasonably modulating BioT and estradiol, especially SHBG, facilitated the attenuation of the harmful effects of obesity on male health.

The current landscape of m6A modification in urological cancers.

N6-methyladenosine (m6A) methylation is a dynamic and reversible procession of epigenetic modifications. It is increasingly recognized that m6A modification has been involved in the tumorigenesis, development, and progression of urological tumors. Emerging research explored the role of m6A modification in urological cancer. In this review, we will summarize the relationship between m6A modification, renal cell carcinoma, bladder cancer, and prostate cancer, and discover the biological function of m6A regulators in tumor cells. We will also discuss the possible mechanism and future application value used as a potential biomarker or therapeutic target to benefit patients with urological cancers.

Multiomics analysis of the mechanisms behind flavonoid differences between purple and green tender shoots of Camellia sinensis var. assamica.

Flavonoids are rich in tea plants (Camellia sinensis), and responsible for the flavor and healthful benefits of tea beverage. The anthocyanin levels in the purple tender shoots are higher than in the general green leaves of tea plant, which provide special materials to search metabolic mechanisms of flavonoid enrichment in plant. In this work, flavonoid differences between purple and green shoots from tea cultivars "Zijuan" (ZJ) and "Yunkang10" (YK-10) were investigated through metabolomic analysis, and mechanisms for their difference were surveyed by comparative transcriptomic and proteomic analysis. Levels of 34 flavonoids were different between ZJ and YK-10 shoots. Among them, 8 and 6 were marker metabolites in ZJ and YK-10, respectively. The differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and different-level metabolites (DLMs) between ZJ and YK-10 were researched, respectively; and interactions including DEG-DLM, DEP-DLM, DEG-DEP, and DEG-DEP-DLM were analyzed; the contents of 18 characteristic flavonoids in tea leaves and expressions of 34 flavonoid metabolic genes were measured to verify the omics results. Integrated above analyses, a proposed model of flavonoids biosynthesis in tea shoots were established. The differential expression of the leucoanthocyanidin reductase (LAR), anthocyanidin synthase (ANS), anthocyanidin reductase (ANR), UDPG-flavonoid glucosyltransferase (UGT) 75L12 and 94P1 at gene level, and the ANS, ANR, and UGT78A15 at protein level, were closely associated with differences in flavonoids between ZJ and YK-10 shoot. Together, this study provides new information on the flavonoid accumulation mechanism in tea plant.

Application of a data-driven XGBoost model for the prediction of COVID-19 in the USA: a time-series study.

OBJECTIVE: The COVID-19 outbreak was first reported in Wuhan, China, and has been acknowledged as a pandemic due to its rapid spread worldwide. Predicting the trend of COVID-19 is of great significance for its prevention. A comparison between the autoregressive integrated moving average (ARIMA) model and the eXtreme Gradient Boosting (XGBoost) model was conducted to determine which was more accurate for anticipating the occurrence of COVID-19 in the USA. DESIGN: Time-series study. SETTING: The USA was the setting for this study. MAIN OUTCOME MEASURES: Three accuracy metrics, mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE), were applied to evaluate the performance of the two models. RESULTS: In our study, for the training set and the validation set, the MAE, RMSE and MAPE of the XGBoost model were less than those of the ARIMA model. CONCLUSIONS: The XGBoost model can help improve prediction of COVID-19 cases in the USA over the ARIMA model.

The correlation between temperature and the incidence of COVID-19 in four first-tier cities of China: a time series study.

The COVID-19 outbreak emerged in Wuhan, China, and was declared a global pandemic in March 2020. This study aimed to explore the association of daily mean temperature with the daily counts of COVID-19 cases in Beijing, Shanghai, Guangzhou, and Shenzhen, China. Data on daily confirmed cases of COVID-19 and daily mean temperatures were retrieved from the 4 first-tier cities in China. Distributed lag nonlinear models (DLNMs) were used to assess the association between daily mean temperature and the daily cases of COVID-19 during the study period. After controlling for the imported risk index and long-term trends, the distributed lag nonlinear model showed that there were nonlinear and lag relationships. The daily cumulative relative risk decreased for every 1.0 °C change in temperature in Shanghai, Guangzhou, and Shenzhen. However, the cumulative relative risk increased with a daily mean temperature below - 3 °C in Beijing and then decreased. Moreover, the delayed effects of lower temperatures mostly occurred within 6-7 days of exposure. There was a negative correlation between the cumulative relative risk of COVID-19 incidence and temperature, especially when the temperature was higher than - 3 °C. The conclusions from this paper will help government and health regulators in these cities take prevention and protection measures to address the COVID-19 crisis and the possible collapse of the health system in the future.

NlugOBP8 in Nilaparvata lugens Involved in the Perception of Two Terpenoid Compounds from Rice Plant.

Odorant binding proteins (OBPs) play an important role in insect peripheral olfactory systems and exploring the physiological function of OBPs could facilitate the understanding of insects' chemical communication. Here, the functional analysis of an antenna-based NlugOBP8 from brown planthopper (BPH) Nilaparvata lugens (Stål) was performed both in vitro and in vivo. Recombinant NlugOBP8 exhibited strong binding affinity to 13 out of 26 rice plant volatiles and could form a stable complex with 9 of them according to the fluorescence binding and fluorescence quenching experiments. Circular dichroism spectra demonstrated that six volatiles could give rise to significant conformational change of recombinant NlugOBP8. H-tube olfactometer bioassay confirmed that BPHs were significantly attracted by nerolidol and significantly repelled by linalool, caryophyllene oxide, and terpinolene, respectively. Antennae of dsNlugOBP8-injected BPHs exhibited significantly lower electrophysiological response to linalool and caryophyllene oxide. Moreover, the repellent responses of BPHs to these two volatiles were also impaired upon silencing NlugOBP8. These data suggest that NlugOBP8 is involved in recognizing linalool and caryophyllene oxide and provide additional target for the sustainable control of BPHs.

Spatiotemporal cluster analysis of COVID-19 and its relationship with environmental factors at the city level in mainland China.

This study sought to identify the spatial, temporal, and spatiotemporal clusters of COVID-19 cases in 366 cities in mainland China with the highest risks and to explore the possible influencing factors of imported risks and environmental factors on the spatiotemporal aggregation, which would be useful to the design and implementation of critical preventative measures. The retrospective analysis of temporal, spatial, and spatiotemporal clustering of COVID-19 during the period (January 15 to February 25, 2020) was based on Kulldorff's time-space scanning statistics using the discrete Poisson probability model, and then the logistic regression model was used to evaluate the impact of imported risk and environmental factors on spatiotemporal aggregation. We found that the spatial distribution of COVID-19 cases was nonrandom; the Moran's I value ranged from 0.017 to 0.453 (P < 0.001). One most likely cluster and three secondary likely clusters were discovered in spatial cluster analysis. The period from February 2 to February 9, 2020, was identified as the most likely cluster in the temporal cluster analysis. One most likely cluster and seven secondary likely clusters were discovered in spatiotemporal cluster analysis. Imported risk, humidity, and inhalable particulate matter PM2.5 had a significant impact on temporal and spatial accumulation, and temperature and PM10 had a low correlation with the spatiotemporal aggregation of COVID-19. The information is useful for health departments to develop a better prevention strategy and potentially increase the effectiveness of public health interventions.

MiR-155-5p promotes metastasis and epithelial-mesenchymal transition of renal cell carcinoma by targeting apoptosis-inducing factor.

BACKGROUND: Although renal cell carcinoma remains one of the most malignant cancers, our understanding of progression and recurrence of this disease is limited. The present study explored the precise role of miR-155-5p in renal cancer metastasis. METHODS: The expression of miR-155-5p in renal carcinoma clinical tissues and cells was determined using quantitative real time-polymerase chain reaction. The role of miR-155-5p on tumor cell growth were examined using CCK-8 and colony formation assays. Transwell assay was utilized to identify the role of miR-155-5p on the invasion and migration of renal cancer cells. Markers of epithelial-mesenchymal transition were determined using western blot. The in vivo effects of miR-155-5p on renal cancer cell growth, apoptosis, and metastasis were explored using xenograft mice. Luciferase reporter assay was performed to identify the potential target of miR-155-5p. RESULTS: Levels of miR-155-5p were significantly elevated in renal cancer tissues and cell lines. Suppression of miR-155-5p decreased the growth, colony formation, migration, and invasiveness of renal cancer cells. In contrast, overexpression of miR-155-5p led to opposite effects on renal cancer cells. Mechanically, the apoptosis-inducing factor was identified as the target of miR-155-5p. Interference of miR-155-5p significantly increased mRNA and protein expression of the apoptosis-inducing factor, whereas overexpression of miR-155-5p remarkably suppressed the apoptosis-inducing factor levels in renal cancer cells. The xenograft model identified that suppression of miR-155-5p restrained tumor growth and promoted apoptosis, whereas overexpression of miR-155-5p decreased apoptosis and accelerated tumor growth. Moreover, the number of lung metastasis nodules were decreased following injection with anti-miR-155-5p transfected cells, whereas the nodules were remarkably increased after overexpression of miR-155-5p. In addition, in vitro and in vivo assays both confirmed that suppression of miR-155-5p increased the expression of E-cadherin and decreased levels of N-cadherin and Snail, whereas overexpression of miR-155-5p accelerated epithelial-mesenchymal transition progression in renal cancer cells. CONCLUSION: These findings demonstrate that miR-155-5p enhances metastasis and epithelial-mesenchymal transition by targeting the apoptosis-inducing factor, suggesting that miR-155-5p represents a novel therapeutic target for renal cancer.

Identification of genes of prognostic value in the ccRCC microenvironment from TCGA database.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma. Bioinformatics analyses were used to screen candidate genes associated with the prognosis and microenvironment of ccRCC and elucidate the underlying molecular mechanisms of action. METHODS: The gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. The ESTIMATE algorithm was used to compute the immune and stromal scores of patients. Based on the median immune/stromal scores, all patients were sorted into low- and high-immune/stromal score groups. Differentially expressed genes (DEGs) were extracted from high- versus low-immune/stromal score groups and were described using functional annotations and protein-protein interaction (PPI) network. RESULTS: Patients in the high-immune/stromal score group had poorer survival outcome. In total, 95 DEGs (48 upregulated and 47 downregulated genes) were screened from the gene expression profiles of patients with high immune and stromal scores. The genes were primarily involved in six signaling pathways. Among the 95 DEGs, 43 were markedly related to overall survival of patients. The PPI network identified the top 10 hub genes-CD19, CD79A, IL10, IGLL5, POU2AF1, CCL19, AMBP, CCL18, CCL21, and IGJ-and four modules. Enrichment analyses revealed that the genes in the most important module were involved in the B-cell receptor signaling pathway. CONCLUSION: This study mainly revealed the relationship between the ccRCC microenvironment and prognosis of patients. These results also increase the understanding of how gene expression patterns can impact the prognosis and development of ccRCC by modulating the tumor microenvironment. The results could contribute to the search for ccRCC biomarkers and therapeutic targets.

Progress of research into circular RNAs in urinary neoplasms.

Circular RNAs (circRNAs) are a large class of endogenous RNA that form a covalently closed continuous loop without 5' or 3' tails and are diffusely expressed in mammalian cells. Through the development of high-throughput sequencing, microarray, and bioinformatics analyses, recent studies have shown that the expression of circRNAs is dysregulated in human tumor tissues and cells, as well as in the blood of patients, and closely correlates with the development of tumors. circRNAs can regulate the progression of tumors through various mechanisms. An increasing number of studies have shown that circRNAs may play critical roles in the early diagnosis, targeted therapy, and prognostic prediction of cancer as biomarkers or therapeutic targets. This review briefly describes the definitions and functions of circRNAs, and the main content includes the most recent progress in research into their function, regulation, and clinical relevance to bladder, renal, and prostate cancers. We also provide some novel ideas regarding the treatment of these diseases.

Prognostic value of immune-related genes in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma, and immune-related genes (IRGs) are key contributors to its development. In this study, the gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database and the cBioPortal database, respectively. IRGs were obtained from the ImmPort database. We analyzed the expression of IRGs in ccRCC, and discovered 681 that were differentially expressed between ccRCC and normal kidney tissues. Univariate Cox regression analysis was used to identify prognostic differentially expressed IRGs (PDEIRGs). Using Lasso regression and multivariate Cox regression analyses, we detected seven optimal PDEIRGs (PLAU, ISG15, IRF9, ARG2, RNASE2, SEMA3G and UCN) and used them to construct a risk model to predict the prognosis of ccRCC patients. This model accurately stratified patients with different survival outcomes and precisely identified patients with different mutation burdens. Our findings suggest the seven PDEIRGs identified in this study are valuable prognostic predictors in ccRCC patients. These genes could be used to investigate the developmental mechanisms of ccRCC and to design individualized treatments for ccRCC patients.

Differentially expressed autophagy-related genes are potential prognostic and diagnostic biomarkers in clear-cell renal cell carcinoma.

We examined the role of differentially expressed autophagy-related genes (DEARGs) in clear cell Renal Cell Carcinoma (ccRCC) using high-throughput RNA-seq data from The Cancer Genome Atlas (TCGA). Cox regression analyses showed that 5 DEARGs (PRKCQ, BID, BAG1, BIRC5, and ATG16L2) correlated with overall survival (OS) and 4 DEARGs (EIF4EBP1, BAG1, ATG9B, and BIRC5) correlated with disease-free survival (DFS) in ccRCC patients. Multivariate Cox regression analysis using the OS and DFS prognostic risk models showed that expression of the nine DEARGs accurately and independently predicted the risk of disease recurrence or progression in ccRCC patients (area under curve or AUC values > 0.70; all p < 0.05). Moreover, the DEARGs accurately distinguished healthy individuals from ccRCC patients based on receiver operated characteristic (ROC) analyses (area under curve or AUC values > 0.60), suggesting their potential as diagnostic biomarkers for ccRCC. The expression of DEARGs also correlated with the drug sensitivity of ccRCC cell lines. The ccRCC cell lines were significantly sensitive to Sepantronium bromide, a drug that targets BIRC5. This makes BIRC5 a potential therapeutic target for ccRCC. Our study thus demonstrates that DEARGs are potential diagnostic and prognostic biomarkers and therapeutic targets in ccRCC.