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Background: Clear cell renal cell carcinoma (ccRCC) is associated with a high prevalence of cancer-related deaths. The survival rates of patients are significantly lower in late-stage ccRCC than in early-stage ccRCC, due to the spread and metastasis of late-stage ccRCC, surgery has not reached the goal of radical cure, and the effect of traditional radiotherapy and chemotherapy is poor. Thus, it is crucial to accurately assess the prognosis and provide personalized treatment at an early stage in ccRCC. This study aims to develop an efficient nomogram model for stratifying and predicting the survival of ccRCC patients based on tumor stage. Methods: We first analyzed the microarray expression data of ccRCC patients from the Gene Expression Omnibus (GEO) database and categorized them into two groups based on the disease stage (early and late stage). Subsequently, the GEO2R tool was applied to screen out the genes that were highly expressed in all GEO datasets. Finally, the clinicopathological data of the two patient groups were obtained from The Cancer Genome Atlas (TCGA) database, and the differences were compared between groups. Survival analysis was performed to evaluate the prognostic value of candidate genes (PSAT1, PRAME, and KDELR3) in ccRCC patients. Based on the screened gene PSAT1 and clinical parameters that were significantly associated with patient prognosis, we established a new nomogram model, which was further optimized to a single clinical variable-based model. The expression level of PSAT1 in ccRCC tissues was further verified by qRT-PCR, Western blotting, and immunohistochemical analysis. Results: The datasets GSE73731, GSE89563, and GSE150404 identified a total of 22, 89, and 120 over-expressed differentially expressed genes (DEGs), respectively. Among these profiles, there were three genes that appeared in all three datasets based on different stage groups. The overall survival (OS) of late-stage patients was significantly shorter than that of early-stage patients. Among the three candidate genes (PSAT1, PRAME, and KDELR3), PSAT1 was shown to be associated with the OS of patients with late-stage ccRCC. Multivariate Cox regression analysis showed that age, tumor grade, neoadjuvant therapy, and PSAT1 level were significantly associated with patient prognosis. The concordance indices were 0.758 and 0.725 for the 3-year and 5-year OS, respectively. The new model demonstrated superior discrimination and calibration compared with the single clinical variable model. The enhancer PSAT1 used in the new model was shown to be significantly overexpressed in tissues from patients with late-stage ccRCC, as demonstrated by the mRNA level, protein level, and pathological evaluation. Conclusion: The new prognostic prediction nomogram model of PSAT1 and clinicopathological variables combined was thus established, which may provide a new direction for individualized treatment for different-stage ccRCC patients. [ABSTRACT FROM AUTHOR]

Background: The study aimed to investigate the association between nonalcoholic fatty liver disease (NAFLD) and ischemic stroke events after revascularization in patients with Moyamoya disease (MMD). Methods: This study prospectively enrolled 275 MMD patients from September 2020 to December 2021. Patients with alcoholism and other liver diseases were excluded. NAFLD was confirmed by CT imaging or abdominal ultrasonography. Stroke events and modified Rankin Scale (mRS) scores at the latest follow-up were compared between the two groups. Results: A total of 275 patients were enrolled in the study, among which 65 were diagnosed with NAFLD. Univariate logistic regression analysis showed that NAFLD (P = 0.029) was related to stroke events. Multivariate logistic regression analysis showed that NAFLD is a predictor of postoperative stroke in MMD patients (OR = 27.145, 95% CI = 2.031–362.81, P = 0.013). Kaplan-Meier analysis showed that compared with MMD patients with NAFLD, patients in the control group had a longer stroke-free time (P = 0.004). Univariate Cox analysis showed that NAFLD (P = 0.016) was associated with ischemic stroke during follow-up in patients with MMD. Multivariate Cox analysis showed that NAFLD was an independent risk factor for stroke in patients with MMD (HR = 10.815, 95% CI = 1.259–92.881, P = 0.030). Furthermore, fewer patients in the NAFLD group had good neurologic status (mRS score ≤ 2) than the control group (P = 0.005). Conclusion: NAFLD was an independent risk factor for stroke in patients with MMD after revascularization and worse neurological function outcomes. [ABSTRACT FROM AUTHOR]