Autophagy-linked FYVE (Alfy) is a protein implicated in the selective degradation of aggregated proteins. In our present study, we found that Alfy was recruited into the aggregated G93A-SOD1 in transgenic mice with amyotrophic lateral sclerosis (ALS). We demonstrated that Alfy overexpression could decrease the expression of mutant proteins via the autophagosome-lysosome pathway, and thereby, the toxicity of mutant proteins was reduced. The clearance of the mutant proteins in NSC34 cells was significantly inhibited in an Alfy knockdown cellular model. We therefore deduced that Alfy translocalization likely is involved in the pathogenesis of ALS. Alfy may be developed into a useful target for ALS therapy.
Background: Acute ischemic stroke (AIS) is a severe neurological disease with complex pathophysiology, resulting in the disability and death. The goal of this study is to explore the underlying molecular mechanisms of AIS and search for new potential biomarkers and therapeutic targets.Methods: Integrative analysis of mRNA and miRNA profiles downloaded from Gene Expression Omnibus (GEO) was performed. We explored differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMirs) after AIS. Target mRNAs of DEMirs and target miRNAs of DEGs were predicted with target prediction tools, and the intersections between DEGs and target genes were determined. Subsequently, Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses, Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), competitive endogenous RNA (ceRNA) (lncRNA-miRNA-mRNA) network, protein–protein interaction (PPI) network, and gene transcription factors (TFs) network analyses were performed to identify hub genes and associated pathways. Furthermore, we obtained AIS samples with evaluation of immune cell infiltration and used CIBERSORT to determine the relationship between the expression of hub genes and infiltrating immune cells. Finally, we used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the effect of the identified targets on drug sensitivity.Result: We identified 293 DEGs and 26 DEMirs associated with AIS. DEGs were found to be mainly enriched in inflammation and immune-related signaling pathways through enrichment analysis. The ceRNA network included nine lncRNAs, 13 miRNAs, and 21 mRNAs. We used the criterion AUC >0.8, to screen a 3-gene signature (FBL, RPS3, and RPS15) and the aberrantly expressed miRNAs (hsa-miR-125a-5p, hsa-miR-125b-5p, hsa-miR-148b-3p, and hsa-miR-143-3p) in AIS, which were verified by a method of quantitative PCR (qPCR) in HT22 cells. T cells CD8, B cells naïve, and activated NK cells had statistical increased in number compared with the acute cerebral infarction group. By predicting the IC50 of the patient to the drug, AZD0530, Z.LLNle.CHO and NSC-87877 with significant differences between the groups were screened out. AIS demonstrated heterogeneity in immune infiltrates that correlated with the occurrence and development of diseases.Conclusion: These findings may contribute to a better understanding of the molecular mechanisms of AIS and provide the basis for the development of novel treatment targets in AIS.
Background: The systemic inflammation response index (SIRI) and prognostic nutritional index (PNI) have been shown to be correlated with the prognosis of various solid tumors. This study sought to investigate the prognostic value of the SIRI and the PNI individually and in combination in locally advanced elderly esophageal squamous cell carcinoma (ESCC) patients treated with radical radiotherapy.
Methods:The data of 192 ESCC patients aged ≥65 years, who had been treated with definitive radiotherapy between 2013 and 2016, were retrospectively analyzed. The optimal cutoff values of SIRI and PNI were determined by receiver operating characteristic curves. Kaplan-Meier curves and Cox proportional hazards models were used to analyze the effect of the SIRI and PNI on overall survival (OS) and progressionfree survival (PFS). The areas under the curve were measured to evaluate the predictive ability of the SIRI, PNI, and SIRI combined with PNI for OS.
Results:The optimal cutoff values of the pretreatment SIRI and PNI were 1.03 and 49.60, respectively.The univariate and multivariate analyses demonstrated that T stage (P=0.021), TNM stage (P=0.022), synchronous chemotherapy (P=0.032), the SIRI (P=0.001), and the PNI (P=0.045) were independent prognostic factors for OS and N stage (P=0.004), synchronous chemotherapy (P=0.016) and the SIRI (P=0.004) were independent prognostic factors for PFS. The AUC of the combined SIRI and PNI (0.706; 0.612-0.801) was higher than those of the SIRI (0.648; 0.540-0.756) and the PNI (0.621; 0.523-0.720).Patients in the low-SIRI and high-PNI groups, especially those in clinical stage II or who received synchronous chemotherapy (P<0.001, P=0.002), had better OS and PFS than those in the other groups (P<0.001).
Conclusions:The SIRI and PNI are simple and reliable biomarkers for predicting long-term survival in elderly patients with locally advanced ESCC after radical radiotherapy. A high SIRI and a low PNI indicated poor prognosis, and the combination of the SIRI and PNI improved the accuracy of prognosis prediction and could be used to guide individualized treatment of patients.
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