Long non-coding RNA (lncRNA) FYVE, RhoGEF and PH domain containing 5 antisense RNA 1 (FGD5-AS1) has been reported as an oncogene in colorectal cancer, promoting its tumorgenesis. The present paper focused on searching the potential function of FGD5-AS1 in non-small cell lung carcinoma (NSCLC). There are connections between the expression of lncRNA FGD5-AS1 and human NSCLC tumor growth and progression. Also, the relationships between FGD5-AS1, hsa-miR-107 and mRNA fibroblast growth factor receptor like 1 (FGFRL1) are going to test their interaction in NSCLC cell lines, which may cause a series of biological behaviors of NSCLC cells. qRT-PCR analysis was conducted to test the expression of RNAs in different situation. CCK-8 experiment and clone formation assay were performed to assess proliferation of NSCLC cells. Also, connection between FGD5-AS1 and hsa-miR-107 were investigated by luciferase reporter assay and RNA pull-down assay. Rescue experiments were performed to verify the modulating relationship between FGD5-AS1, hsa-miR-107 and FGFRL1. High-level expression of FGD5-AS1 was found in NSCLC. FGD5-AS1 may promote the proliferation of NSCLC cells. Also, the combination between hsa-miR-107, FGD5-AS1 and NSCLC have been proved, which means they can play an interaction function in NSCLC cells. Thence, we concluded that lncRNA FGD5-AS1 promotes non-small cell lung cancer cell proliferation through sponging hsa-miR-107 to up-regulate FGFRL1.

Background The lncRNA Colorectal Neoplasia Differentially Expressed (CRNDE) gene has been reported as a potential oncogene in NSCLC. Nevertheless, the molecular mechanism of CRNDE in NSCLC progression remains largely unknown. Material/Methods qRT-PCR assay was performed to detect the expression levels of CRNDE, miR-641, and cyclin-dependent kinase 6 (CDK6) in NSCLC. Western blot assay was employed to assess CDK6 protein level in treated NSCLC cells. si-CRNDE#1, si-CRNDE#2, miR-641 mimics, miR-641 inhibitors, or Vector-CDK6 were transfected into NSCLC cells to change the expression levels of CRNDE, miR-641, or CDK6. Dual-luciferase reporter assay was performed to validate the direct interrelated miRNA of CRNDE and the potential target of miR-641. MTT and flow cytometry assays were performed to assess the capacities of cell proliferation and apoptosis, respectively. Results CRNDE level was upregulated in NSCLC, and its knockdown suppressed NSCLC cells proliferation and enhanced apoptosis, whereas miR-641 antagonized the regulatory effect of CRNDE knockdown by directly binding to CRNDE. Moreover, CDK6 was a target of miR-641 and miR-641 exerted anti-proliferation and pro-apoptosis effects through CDK6. Conclusions CRNDE promoted proliferation and inhibited apoptosis of NSCLC cells at least in part by regulating the miR-641/CDK6 axis, suggesting that CRNDE is a potential therapeutic target for NSCLC treatment.

The aim of the present study was to investigate the effects and molecular mechanisms of GPR4 (G-protein-coupled receptor 4) in cell apoptosis and renal ischemia-reperfusion (IR) injury and GPR4 mice and wild-type (WT) mice underwent renal IR or sham procedures. For hypoxia/reoxygenation (HR), human umbilical vein endothelial cells (HUVECs) were subjected to 4 h of hypoxia, followed by 6 h of reoxygenation. Renal histological changes were observed by periodic acid-Schiff staining and myeloperoxidase activity. Apoptosis was detected by TUNEL staining. GPR4, C/EBP-homologous protein (CHOP) and cleaved caspase-3 protein expressions were detected by western blot. Both GPR4 and CHOP were up-regulated after renal IR in mice. GPR4-knockout mice had significantly less renal damage and decreased TUNEL-positive cells than WT controls after IR. Bone marrow chimeras demonstrated that it was due to the GPR4 inactivation in renal parenchymal cells. Moreover, GPR4 was mainly expressed in endothelial cells after renal IR. GPR4 knockdown markedly inhibited CHOP expression and cell apoptosis in the HUVECs after HR treatment. GPR4 blockade attenuated renal injury after IR and reduced the cell apoptosis through the suppression of CHOP expression.

Background Early identification of early death for bladder cancer patients undergoing radical cystectomy based on the laboratory findings at the time of diagnosis could improve the overall survival. The study aimed to explore preoperative factors associated with higher risk of early death (within 1 year after surgery) for bladder cancer patients. Methods A total of 186 bladder cancer patients who underwent robot‐assisted radical cystectomy (RARC) were identified between October 2014 and May 2017. The probability of dying within 1 year after RARC was defined as the end point “early death.” Predictive factors including clinical features and laboratory findings at diagnosis were retrospectively collected. Results Median follow‐up time after RARC was 20.6 months (1.2‐43.7 months). Fifty‐one patients (27.4%) died during follow‐up and 31 within 1 year from surgery (1‐year mortality rate: 16.7%). All potentially prognostic factors were assessed on univariate analyses, which revealed the following factors as being associated with higher risk of early death within 1 year after RARC: older age ( P = 0.004), advanced clinical stage ( P = 0.005), presence of hydronephrosis ( P = 0.021), higher fibrinogen ( P = 0.007), higher PLR ( P = 0.031), and lower PNI ( P = 0.016). In a multivariate Cox proportional hazard regression model analysis, age >60 years (HR = 7.303, 95% CI 1.734‐30.764; P = 0.007) and fibrinogen ≥3.295 g/L (HR = 2.396, 95% CI 1.138‐5.045; P = 0.007) at diagnosis were independent prognostic factors of early death after RARC. Conclusion Age and preoperative elevated plasma fibrinogen level were independent predictors for 1‐year mortality after RARC. We believe that plasma fibrinogen levels may become a useful biomarker, which may help guide the treatment decision‐making process for patients with bladder cancer.

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Purpose We sought to develop diagnostic models incorporating mpMRI examination to identify PCa (Gleason score≥3+3) and CSPCa (Gleason score≥3+4) to reduce overdiagnosis and overtreatment. Methods We retrospectively identified 784 patients according to inclusion criteria between 2016 and 2020. The cohort was split into a training cohort of 548 (70%) patients and a validation cohort of 236 (30%) patients. Age, PSA derivatives, prostate volume, and mpMRI parameters were assessed as predictors for PCa and CSPCa. The multivariable models based on clinical parameters were evaluated using area under the curve (AUC), calibration plots, and decision curve analysis (DCA). Results Univariate analysis showed that age, tPSA, PSAD, prostate volume, MRI-PCa, MRI-seminal vesicle invasion, and MRI-lymph node invasion were significant predictors for both PCa and CSPCa (each p ≤0.001). PSAD has the highest diagnostic accuracy in predicting PCa (AUC=0.79) and CSPCa (AUC=0.79). The multivariable models for PCa (AUC=0.92, 95% CI: 0.88–0.96) and CSPCa (AUC=0.95, 95% CI: 0.92–0.97) were significantly higher than the combination of derivatives for PSA ( p =0.041 and 0.009 for PCa and CSPCa, respectively) or mpMRI (each p <0.001) in diagnostic accuracy. And the multivariable models for PCa and CSPCa illustrated better calibration and substantial improvement in DCA at threshold above 10%, compared with PSA or mpMRI derivatives. The PCa model with a 30% cutoff or CSPCa model with a 20% cutoff could spare the number of biopsies by 53%, and avoid the number of benign biopsies over 80%, while keeping a 95% sensitivity for detecting CSPCa. Conclusion Our multivariable models could reduce unnecessary biopsy without comprising the ability to diagnose CSPCa. Further prospective validation is required.

The aim of the present study was to investigate the effects of acidosis on the apoptosis of renal epithelial and endothelial cells, and the molecular pathways responsible for this. A human proximal tubular cell line, HK-2, and human umbilical vein endothelial cells (HUVECs), were transfected with control or G protein-coupled receptor 4 siRNA for 36 h. Cells were exposed to normal (pH 7.4) or acidic (pH 6.4) media. Western blot analysis was used to assess the protein expression levels of G protein-coupled receptor 4 (GPR4), CCAAT/enhancer-binding protein homologous protein (CHOP) and cleaved caspase-3. Cell apoptosis was examined using the TUNEL assay and the lactate dehydrogenase (LDH) release assay. Using these techniques, it was demonstrated that acidosis increased the protein expression levels of GPR4, CHOP, cleaved caspase-3 and intracellular cyclic adenosine monophosphate levels in hypoxia/reoxygenation (HR)-treated cell lines. Knockdown of GPR4 in HK-2 cells and HUVECs markedly reduced the protein expression levels of acidosis-mediated GPR4, CHOP and cleaved caspase-3, as well as the rate of cell apoptosis. Therefore, the results of the present study suggested that acidosis promotes the apoptosis of HK-2 cells and HUVECs by regulating the GPR4/CHOP pathway.

Background Machine learning has many attractive theoretic properties, specifically, the ability to handle non predefined relations. Additionally, studies have validated the clinical utility of mpMRI for the detection and localization of CSPCa (Gleason score ≥ 3 + 4). In this study, we sought to develop and compare machine-learning models incorporating mpMRI parameters with traditional logistic regression analysis for prediction of PCa (Gleason score ≥ 3 + 3) and CSPCa on initial biopsy. Methods A total of 688 patients with no prior prostate cancer diagnosis and tPSA ≤ 50 ng/ml, who underwent mpMRI and prostate biopsy were included between 2016 and 2020. We used four supervised machine-learning algorithms in a hypothesis-free manner to build models to predict PCa and CSPCa. The machine-learning models were compared to the logistic regression analysis using AUC, calibration plot, and decision curve analysis. Results The artificial neural network (ANN), support vector machine (SVM), and random forest (RF) yielded similar diagnostic accuracy with logistic regression, while classification and regression tree (CART, AUC = 0.834 and 0.867) had significantly lower diagnostic accuracy than logistic regression (AUC = 0.894 and 0.917) in prediction of PCa and CSPCa (all P < 0.05). However, the CART illustrated best calibration for PCa (SSR = 0.027) and CSPCa (SSR = 0.033). The ANN, SVM, RF, and LR for PCa had higher net benefit than CART across the threshold probabilities above 5%, and the five models for CSPCa displayed similar net benefit across the threshold probabilities below 40%. The RF (53% and 57%, respectively) and SVM (52% and 55%, respectively) for PCa and CSPCa spared more unnecessary biopsies than logistic regression (35% and 47%, respectively) at 95% sensitivity for detection of CSPCa. Conclusion Machine-learning models (SVM and RF) yielded similar diagnostic accuracy and net benefit, while spared more biopsies at 95% sensitivity for detection of CSPCa, compared with logistic regression. However, no method achieved desired performance. All methods should continue to be explored and used in complementary ways.