Background Studies have shown that the expressions and working mechanisms of Dihydrolipoamide S-acetyltransferase (DLAT) in different cancers vary. It is necessary to analyze the expressions and regulatory roles of DLAT in tumors systematically. Methods Online public-platform literature on the relationships between DLAT expression levels and tumor prognosis, methylation status, genetic alteration, drug sensitivity, and immune infiltration has been reviewed. The literature includes such documents as The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Receiver Operating Characteristic plotter (ROC plotter). The molecular mechanisms of DLAT were explored with the Gene Set Enrichment Analysis (GSEA). The relationship between down-regulated DLAT and autophagy in two liver hepatocellular carcinoma (LIHC) cell lines was confirmed with the western blot method, colony formation assay, and transmission electron microscopy. Tissue microarrays were validated through the immunohistochemical staining of DLAT. Results DLAT is upregulated in the LIHC, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and stomach adenocarcinoma (STAD) tumors but is down-regulated in the head and neck squamous cell carcinoma (HNSC) and kidney renal clear cell carcinoma (KIRC) tumors in comparison with normal tissues. For LIHC patients treated with 5-Fluorouracil and Lenvatinib, the DLAT levels of those in the drug-resistant group are significantly high. In LIHC cells, autophagy will be inhibited, and cell death will be induced when DLAT breaks down. Moreover, there exist positive correlations between DLAT expression levels and infiltration of B cells, DC cells, Tregs, and CD8+ T cells in kidney chromophobe (KICH), breast invasive carcinoma (BRCA), prostate adenocarcinoma (PRAD), LIHC and HPV+ HNSC. In LIHC, markers of Tregs are positively correlated with DLAT. Compared with those of normal tissues, the staining intensity of DLAT and the amount of Tregs marker CD49d in LIHC increase. Conclusions Through this study, the expressions of DLAT in various cancer types can be understood comprehensively. It suggests that DLAT may be a prognostic marker for LIHC, LUAD, LUSC, STAD and KIRC. A high DLAT expression in LIHC may promote tumorigenesis by stimulating autophagy and inhibiting anti-tumor immunity.

Background. Accumulating evidence shows that the innate immune system is a key player in cardiovascular repair and regeneration, but little is known about the role of immune-related genes (IRGs) in hypertrophic cardiomyopathy (HCM). Methods. The differential mRNA expression profiles of HCM samples were downloaded from the Gene Expression Omnibus (GEO) dataset (GSE89714), and the IRG expression profile was obtained from the ImmPort database. The regulatory pathways of IRGs in HCM were screened out through discrepantly expressive genes (DEGs) analysis, enrichment of gene function/pathway analysis, and protein-protein interaction (PPI) network. Besides, hub IRGs in the PPI network were selected for drug prediction. Results. A total of 854 genes were differentially expressed in HCM, of which 88 were IRGs. Functional enrichment analysis revealed that 88 IRGs were mainly involved in the biological processes (BP) of SMAD protein pathway, smooth muscle cell proliferation, protein serine/threonine kinase, and mitogen-activated protein kinase (MAPK) cascade. Cytokine-cytokine receptor interaction, TGFβ signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway were enriched in the pathway enrichment analysis of these 88 IRGs. Furthermore, the PPI regulatory network of IRGs was constructed, and 10 hub IRGs were screened out to construct a regulatory network for HCM. 4 transcription factors (TFs) were the major regulator of 10 hub IRGs. Finally, these 10 hub IRGs were entered into the pharmacogenomics database for prediction, and the relevant drugs were obtained. Conclusions. In this study, 10 hub IRGs were coexpressed with 4 TFs to construct a regulatory network for HCM. Drug prediction of these 10 hub IRGs proposed potential therapeutic agents that could be used in HCM. These results indicate that IRGs are potential regulators and drug therapeutic targets in HCM.

Background. Dilated cardiomyopathy (DCM) is a cardiovascular disease of unknown etiology with progressive aggravation. More and more studies have shown that long noncoding RNAs (lncRNAs) play an essential role in dilated cardiomyopathy formation and development. The mechanism of action of competitive endogenous RNA (ceRNA) networks formed based on the principle that lncRNAs affect mRNAs’ expression level by competitively binding microRNAs (miRNAs) in dilated cardiomyopathy has rarely been reported. Objective. This study is aimed at constructing a lncRNA-miRNA-mRNA ceRNA network by bioinformatics analysis methods, discovering, and validating potential biomarkers of DCM in the ceRNA network and determining possible therapeutic targets from them for drug prediction. Methods. A lncRNA dataset and a mRNA microarray dataset were downloaded from the Gene Expression Omnibus Database (GEO). Gene expression was compared between blood samples from patients with dilated cardiomyopathy and blood samples from normal subjects to identify differential expression of lncRNAs and mRNAs. The lncRNA-miRNA-mRNA network was constructed using bioinformatics tools, and functional and pathway enrichment analysis and protein-protein interactions were performed. The mRNAs in the network and the proteins they encode are then used as targets for predicting drugs. Besides, the expression of lncRNAs in the ceRNA network was validated by real-time quantitative PCR (qRT-PCR) experiments in vitro. Results. The differentially expressed lncRNA-miRNA-mRNA ceRNA network in dilated cardiomyopathy was successfully established. Two differentially overexpressed key lncRNAs were found from the network: AC093817 and AC091062, and qRT-PCR experiments further validated the overexpression of AC093817 and AC091062. The mRNAs in the network and the proteins encoded by the mRNAs were used for drug prediction to get related drugs. Conclusion. This study supports a possible mechanism and drug development of dilated cardiomyopathy, AC093817 and AC091062 being potential biomarkers of dilated cardiomyopathy.