No abstract

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease that primarily affects motor neurons, causing muscle atrophy, bulbar palsy, and pyramidal tract signs. However, the aetiology and pathogenesis of ALS have not been elucidated to date. In this study, a competitive endogenous RNA (ceRNA) network was constructed by analyzing the expression profiles of messenger RNAs (mRNAs) and long noncoding RNAs (lncRNAs) that were matched by 7 ALS samples and 4 control samples, and then a protein-protein interaction (PPI) network was constructed to identify the genes related to ALS. Gene Ontology (GO) was used to study the potential functions of differentially expressed mRNAs (DEmRNAs) in the ceRNA network. For the ALS and control groups, 247177 potential lncRNA-mRNA ceRNA relationship pairs were screened. Analysis of significant relationship pairs demonstrated that the PPI modules formed by the MALAT1-regulated SYNRG, ITSN2, PICALM, AP3B1, and AAK1 genes may play important roles in the pathogenesis of ALS, and these results may help to characterize the pathogenesis of ALS.

Recent studies have identified a role for ALKBH7 in the occurrence and progression of cancer, and this protein is related to cellular immunity and immune cell infiltration. However, the prognostic and immunotherapeutic value of ALKBH7 in different cancers have not been explored. In this study, we observed high ALKBH7 expression in 17 cancers and low expression in 5 cancers compared to paired normal tissues. Although ALKBH7 expression did not correlate relatively significantly with the clinical parameters of age (6/33), sex (3/33) and stage (3/27) in the cancers studied, the results of the survival analysis reflect the pan-cancer prognostic value of ALKBH7. In addition, ALKBH7 expression was significantly correlated with the TMB (7/33), MSI (13/33), mDNAsi (12/33) and mRNAsi (13/33) in human cancers. Moreover, ALKBH7 expression was associated and predominantly negatively correlated with the expression of immune checkpoint (ICP) genes in many cancers. Furthermore, ALKBH7 correlated with infiltrating immune cells and ESTIMATE scores, especially in PAAD, PRAD and THCA. Finally, the ALKBH7 gene coexpression network is involved in the regulation of cellular immune, oxidative, phosphorylation, and metabolic pathways. In conclusion, ALKBH7 may serve as a potential prognostic pan-cancer biomarker and is involved in the immune response. Our pan-cancer analysis provides insight into the role of ALKBH7 in different cancers.

Alzheimer's disease (AD), the most common neurodegenerative disease, remains unclear in terms of its underlying causative genes and effective therapeutic approaches. Meanwhile, abnormalities in iron metabolism have been demonstrated in patients and mouse models with AD. Therefore, this study sought to find hub genes based on iron metabolism that can influence the diagnosis and treatment of AD. First, gene expression profiles were downloaded from the GEO database, including non-demented (ND) controls and AD samples. Fourteen iron metabolism-related gene sets were downloaded from the MSigDB database, yielding 520 iron metabolism-related genes. The final nine hub genes associated with iron metabolism and AD were obtained by differential analysis and WGCNA in brain tissue samples from GSE132903. GO analysis revealed that these genes were mainly involved in two major biological processes, autophagy and iron metabolism. Through stepwise regression and logistic regression analyses, we selected four of these genes to construct a diagnostic model of AD. The model was validated in blood samples from GSE63061 and GSE85426, and the AUC values showed that the model had a relatively good diagnostic performance. In addition, the immune cell infiltration of the samples and the correlation of different immune factors with these hub genes were further explored. The results suggested that these genes may also play an important role in immunity to AD. Finally, eight drugs targeting these nine hub genes were retrieved from the DrugBank database, some of which were shown to be useful for the treatment of AD or other concomitant conditions, such as insomnia and agitation. In conclusion, this model is expected to guide the diagnosis of patients with AD by detecting the expression of several genes in the blood. These hub genes may also assist in understanding the development and drug treatment of AD.