Search

Subarachnoid hemorrhage (SAH) is a hemorrhagic cerebrovascular disease with an extremely poor prognosis. The molecular mechanism and biomarkers involved in neurological outcome after SAH still need to be explored. This study assessed the microRNA expression characteristics of SAH patients with different neurological outcomes by meta-analysis. Public databases were searched from database inception until December 2022. The study reported that microRNA expression data in SAH patients with different neurological outcomes were included in the analysis. The differential expression of miRNAs was evaluated by meta-analysis. Overrepresentation analysis was performed for the targeted genes of significant miRNAs. The XGBoost algorithm was used to assess the predictive ability for neurological outcomes with clinical characteristics and significantly expressed miRNAs. Seven studies were finally included in the meta-analysis. The results showed that the levels of miR-152-3p (SMD: − 0.230; 95% CI − 0.389, − 0.070; padj = 0.041), miR-221-3p (SMD: − 0.286; 95% CI − 0.446, − 0.127; padj = 0.007), and miR-34a-5p (SMD: − 0.227; 95% CI − 0.386, − 0.067; padj = 0.041) were significantly lower in SAH patients with good neurological outcomes than in those with poor neurological outcomes. The PI3K-AKT signaling pathway may have an important role in neurological recovery after SAH. Based on the XGBoost algorithm, the neurological outcome could be accurately predicted with clinical characteristics plus the three miRNAs. The expression levels of miR-152-3p, miR-221-3p, and miR-34a-5p were significantly lower in patients with good neurological outcomes than in those with poor outcomes. These miRNAs can serve as potential predictive biomarkers for neurological outcomes. The molecular mechanism and biomarkers involved in neurological outcome after SAH still need to be explored. Our study analyzed microRNA expression characteristics of SAH patients with different neurological outcomes by meta-analysis. After analyze studies reporting the microRNA expression data in SAH patients with different neurological outcomes, results show that the levels of miR-152-3p, miR-221-3p, and miR-34a-5p were significantly lower in SAH patients with good neurological outcomes than in those with poor neurological outcomes. The PI3K-AKT signaling pathway may have an important role in neurological recovery after SAH. Based on the XGBoost algorithm, the neurological outcome could be accurately predicted with clinical characteristics plus the three miRNAs. [ABSTRACT FROM AUTHOR]

Background. Accurate and effective biomarkers for the prognosis of patients with hepatocellular carcinoma (HCC) are poorly identified. A network-based gene signature may serve as a valuable biomarker to improve the accuracy of risk discrimination in patients. Methods. The expression levels of cancer hallmarks were determined by Cox regression analysis. Various bioinformatic methods, such as GSEA, WGCNA, and LASSO, and statistical approaches were applied to generate an MTORC1 signaling-related gene signature (MSRS). Moreover, a decision tree and nomogram were constructed to aid in the quantification of risk levels for each HCC patient. Results. Active MTORC1 signaling was found to be the most vital predictor of overall survival in HCC patients in the training cohort. MSRS was established and proved to hold the capacity to stratify HCC patients with poor outcomes in two validated datasets. Analysis of the patient MSRS levels and patient survival data suggested that the MSRS can be a valuable risk factor in two validated datasets and the integrated cohort. Finally, we constructed a decision tree which allowed to distinguish subclasses of patients at high risk and a nomogram which could accurately predict the survival of individuals. Conclusions. The present study may contribute to the improvement of current prognostic systems for patients with HCC. [ABSTRACT FROM AUTHOR]