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INTRODUCTION: Chloroquine supplementation may show some potential in improving the efficacy for glioblastoma, and this meta-analysis aimed to identify the efficacy of chloroquine supplementation for patients with glioblastoma. METHODS: Several databases including PubMed, Embase, Web of Science, EBSCO, and Cochrane Library databases have been systematically searched through August 2022, and we included randomized controlled trials assessing the efficacy of chloroquine supplementation for glioblastoma. This meta-analysis was performed using the random-effect model or fixed-effect model based on the heterogeneity. RESULTS: Four randomized controlled trials were finally included in this meta-analysis. In comparison with control group for glioblastoma, chloroquine supplementation was associated with substantially decreased mortality (odd ratio [OR], 0.17; 95% confidence interval [CI], 0.06-0.53; P = 0.002), improved survival time (mean difference, 15.63; 95% CI, 2.27-28.99; P = 0.02), and remission (OR, 15.63; 95% CI, 2.27-28.99; P = 0.02), but unraveled no obvious impact on the incidence of adverse events (OR, 3.27; 95% CI, 0.29-36.44; P = 0.34) or seizure (OR, 2.57; 95% CI, 0.05-127.68; P = 0.64). CONCLUSIONS: Chloroquine supplementation may be effective to improve the treatment efficacy for glioblastoma.

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BACKGROUND: RNA binding proteins (RBPs) play an important role in a variety of cancers. However, their mechanisms in cancer progression are still limited especially in colorectal adenocarcinoma (COAD). Integrated analysis of RBPs will provide a better understanding of disease genesis and new insights into COAD treatment. METHODS: The gene expression data and corresponding clinical information for COAD were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was used to screen for RBPs associated with COAD recurrence, and multivariate Cox proportional hazards regression analyses were used to identify genes that were associated with COAD recurrence. A nomogram was constructed to predict the recurrence of COAD, and a receiver operating characteristic (ROC) curve analysis was performed to determine the accuracy of the prediction models. The Human Protein Atlas database was used in prediction models to confirm the expression of key genes in COAD patients. RESULTS: A total of 177 differentially expressed RBPs was obtained, comprising 123 upregulated and 54 downregulated. GO and KEGG enrichment analysis showed that the differentially expressed RBPs were mainly related to mRNA metabolism, RNA processing and translation regulation. Seven RBP genes (TDRD6, POP1, TDRD7, PPARGC1A, LIN28B, LRRFIP2 and PNLDC1) were identified as prognosis-associated genes and were used to construct the prognostic model. CONCLUSIONS: We constructed a COAD prognostic model through bioinformatics analysis and the nomogram can effectively predict the 1-year, 2-year, and 3-year survival rate for COAD patients.