Background/Aims: Nephrolithiasis is one of the most prevalent diseases of the urinary system. Approximately 80% of human kidney stones are composed of calcium oxalate (CaOx), and hypercalciuria is one of the most common metabolic disorders. Emerging evidence indicates that autophagy and inflammatory responses are related to the formation of CaOx nephrolithiasis. However, the roles of autophagy and inflammation in patients with hypercalciuria remain unclear. Ethyl pyruvate (EP) displays protective effects in experimental models of many illnesses. In this study, we investigated the protective effects of EP in vitro through its inhibition of autophagy and inflammatory responses after CaCl2-induced tubular epithelial cell injury. Methods: First, we cultured human tubular epithelial (HK-2) cells in the presence of various concentrations of CaCl2 (0, 0.1, 0.25, 0.5, 1.0, 1.5, and 2.0 mg/ml) for 12 h and EP (0, 1.0, 2.5, 5.0, and 10.0 mM) for 2 h to select the optimum concentration using the Cell Counting Kit-8 assay and lactate dehydrogenase (LDH) assay. Cells in culture were stimulated with CaCl2 (1.0 mg/ml, 12 h) with or without EP pretreatment (2.5 mM, 2 h). After the exposure, we detected the expression of inflammation-related proteins using an enzyme-linked immunosorbent assay and Western blot analysis. Finally, the levels of autophagy-related proteins were determined through Western blot analysis, and the number of GFP-LC3 dots and autophagic vacuoles was detected under confocal microscopy. Results: With the use of the Cell Counting Kit-8 assay and the LDH assay, we identified the optimum concentration for CaCl2 (1.0 mg/ml) treatment and EP pretreatment (2.5 mM). Our research indicated that CaCl2 can induce autophagy and inflammatory responses in HK-2 cells. Furthermore, treatment with EP prior to CaCl2 stimulation attenuated HK-2 cell injury by inhibiting autophagy and inflammation. Conclusion: Our results provide evidence that EP attenuates CaCl2-induced injury of HK-2 cells by downregulating the expression of inflammation and autophagy proteins that may be associated with the inhibition of the high-mobility group box-1 (HMGB1)/toll-like receptor 4 (TLR4)/NF-κB pathway and the competitive interaction with Beclin-1 of HMGB1.
Objective. To evaluate the value of preoperative red cell distribution width-to-lymphocyte ratio (RLR) and albumin-to-fibrinogen ratio (AFR) to the prognosis of patients after renal cell carcinoma (RCC). Methods. From 2012 to 2016, a total of 273 RCC patients underwent radical nephrectomy or partial nephrectomy. This study retrospectively analyzed this group of patients. X-tile software was used to determine the optimal values of RLR and AFR in the peripheral blood. The nomogram constructed with independent factors was used to predict the survival outcome of the patients after RCC. Results. The RLR of the RCC group was higher than that of the normal control group ( P = 0.002 ), whereas the AFR of the RCC group was lower than that of the normal control group ( P < 0.001 ). RLR and AFR are related to tumour type and tumour-node-metastasis (TNM) stage ( P < 0.05 for all). Cox regression analysis showed that the independent prognostic factors affecting overall survival and disease-free survival in the RCC group were symptom, tumour type, TNM stage, Fuhrman grade, RLR, and AFR ( P < 0.05 for all). The nomogram constructed by multiple factors has better predictive power for patients after RCC. Conclusion. Preoperative RLR and AFR can serve as potential biomarkers to predict the prognosis of postoperative RCC patients and improve the predictability of patient recurrence and survival.
PurposeThe present study aims to comprehensively investigate the prognostic value of a radiomic nomogram that integrates contrast-enhanced computed tomography (CECT) radiomic signature and clinicopathological parameters in kidney renal clear cell carcinoma (KIRC).MethodsA total of 136 and 78 KIRC patients from the training and validation cohorts were included in the retrospective study. The intraclass correlation coefficient (ICC) was used to assess reproducibility of radiomic feature extraction. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) as well as multivariate Cox analysis were utilized to construct radiomic signature and clinical signature in the training cohort. A prognostic nomogram was established containing a radiomic signature and clinicopathological parameters by using a multivariate Cox analysis. The predictive ability of the nomogram [relative operating characteristic curve (ROC), concordance index (C-index), Hosmer–Lemeshow test, and calibration curve] was evaluated in the training cohort and validated in the validation cohort. Patients were split into high- and low-risk groups, and the Kaplan–Meier (KM) method was conducted to identify the forecasting ability of the established models. In addition, genes related with the radiomic risk score were determined by weighted correlation network analysis (WGCNA) and were used to conduct functional analysis.ResultsA total of 2,944 radiomic features were acquired from the tumor volumes of interest (VOIs) of CECT images. The radiomic signature, including ten selected features, and the clinical signature, including three selected clinical variables, showed good performance in the training and validation cohorts [area under the curve (AUC), 0.897 and 0.712 for the radiomic signature; 0.827 and 0.822 for the clinical signature, respectively]. The radiomic prognostic nomogram showed favorable performance and calibration in the training cohort (AUC, 0.896, C-index, 0.846), which was verified in the validation cohort (AUC, 0.768). KM curves indicated that the progression-free interval (PFI) time was dramatically shorter in the high-risk group than in the low-risk group. The functional analysis indicated that radiomic signature was significantly associated with T cell activation.ConclusionsThe nomogram combined with CECT radiomic and clinicopathological signatures exhibits excellent power in predicting the PFI of KIRC patients, which may aid in clinical management and prognostic evaluation of cancer patients.
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