Integrated analysis revealing a novel stemness-metabolism-related gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

Identification of Lipophagy-Related Gene Signature for Diagnosis and Risk Prediction of Alzheimer's Disease

Background: Recent research indicates that lipid metabolism and autophagy play crucial roles in the development of Alzheimer's disease (AD). Investigating the relationship between AD diagnosis and gene expression related to lipid metabolism, autophagy, and lipophagy may improve early diagnosis and the identification of therapeutic targets. Methods: Transcription datasets from AD patients were obtained from the Gene Expression Omnibus (GEO). Genes associated with lipid metabolism, autophagy, and lipophagy were sourced from the Gene Set Enrichment Analysis (GSEA) database and the Human Autophagy Database (HADb). Lipophagy-related hub genes were identified using a combination of Limma analysis, weighted gene co-expression network analysis (WGCNA), and machine learning techniques. Based on these hub genes, we developed an AD risk prediction nomogram and validated its diagnostic accuracy using three external validation datasets. Additionally, the expression levels of the hub genes were assessed through quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results: Our analysis identified three hub genes-ACBD5, GABARAPL1, and HSPA8-as being associated with AD progression. The nomogram constructed from these hub genes achieved an area under the curve (AUC) value of 0.894 for AD risk prediction, with all validation sets yielding AUC values greater than 0.8, indicating excellent diagnostic efficacy. qRT-PCR results further corroborated the associations between these hub genes and AD development. Conclusions: This study identified and validated three lipophagy-related hub genes and developed a reliable diagnostic model, offering insights into the pathology of AD and facilitating the diagnosis of AD patients.

A pan-cancer analysis of the prognostic implication and oncogenic role of tubulin epsilon and delta complex 2 (TEDC2) in human tumors

Introduction

Tubulin epsilon and delta complex 2 (TEDC2) is widely expressed in various human tissues and primarily governs centriole stability. However, the biological significance of TEDC2 in pan-cancer is unclear.

Methods

In this study, we employed R software and various online bioinformatics analysis tools to investigate the functional attributes of TEDC2 in human tumours and its potential involvement in immune response. The status of TEDC2 expression was evaluated in samples from the TCGA and GEO datasets, as well as in tumour and corresponding normal samples from the TCGA database. Subsequently, Kaplan-Meier estimates, clinical correlations, and univariate Cox regressions were used to analyze the 33 types of tumors from TCGA and determine the prognostic significance of TEDC2. Moreover, nomogram models were formulated using three distinct tumours, namely kidney renal clear cell carcinoma (KIRC), lung adenocarcinoma (LUAD), and liver hepatocellular carcinoma (LIHC), to evaluate the prognostic significance of TEDC2 in tumours. Furthermore, TEDC2 was investigated for its correlation with the levels of immune cell infiltration, and a functional enrichment analysis was conducted to identify potential signalling pathways involving TEDC2.

Results

Differential analysis revealed that 16 tumour types expressed TEDC2 to a greater extent than normal tissues. The abnormal expression of TEDC2 can predict survival outcomes in patients with adrenocortical carcinoma (ACC), KIRC, kidney renal papillary cell carcinoma (KIRP), LUAD, LIHC, lower grade glioma (LGG), and thymoma (THYM). Subsequent results indicated that TEDC2 has the ability to influence ECM regulators, cell cycle, and Immune checkpoint-associated signalling pathways, which could potentially lead to a poor prognosis and tumour progression.

Discussion

TEDC2 has been identified as a potential therapeutic target that could predict the prognosis of multiple tumour types, making it a promising target for reversing tumour development.

Blocking cholesterol formation and turnover improves cellular and mitochondria function in murine heart microvascular endothelial cells and cardiomyocytes

Background: Statins and proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) are cornerstones of therapy to prevent cardiovascular disease, acting by lowering lipid concentrations and only partially identified pleiotropic effects. This study aimed to analyze impacts of atorvastatin and synthetic peptide PCSK9i on bioenergetics and function of microvascular endothelial cells and cardiomyocytes. Methods: Mitochondrial function and abundance as well as intracellular nucleotides, membrane potential, cytoskeleton structure, and cell proliferation rate were evaluated in mouse heart microvascular endothelial cells (H5V) and cardiomyocytes (HL-1) under normal and hypoxia-mimicking conditions (CoCl2 exposure). Results: In normal conditions PCSK9i, unlike atorvastatin, enhanced mitochondrial respiratory parameters, increased nucleotide levels, prevented actin cytoskeleton disturbances and stimulated endothelial cell proliferation. Under hypoxia-mimicking conditions both atorvastatin and PCSK9i improved the mitochondrial respiration and membrane potential in both cell types. Conclusion: This study demonstrated that both treatments benefited the endothelial cell and cardiomyocyte bioenergetics, but the effects of PCSK9i were superior.