Inhibition of Ganglioside Synthesis Suppressed Liver Cancer Cell Proliferation through Targeting Kinetochore Metaphase Signaling

Novel insights into the circadian modulation of lipid metabolism in chicken livers revealed by RNA sequencing and weighted gene co-expression network analysis

The circadian clock is crucial for maintaining lipid metabolism homeostasis in mammals. Despite the economic importance of fat content in poultry, research on the regulatory effects and molecular mechanisms of the circadian clock on avian hepatic lipid metabolism has been limited. In this study, we observed significant diurnal variations (P<0.05) in triglyceride (TG), free fatty acids (FFA), fatty acid synthase (FAS), and total cholesterol (TC) levels in the chicken embryonic liver under 12-h light/12-h dark incubation conditions, with TG, FFA, and TC concentrations showing significant cosine rhythmic oscillations (P<0.05). However, such rhythmic variations were not observed under complete darkness incubation conditions. Using transcriptome sequencing technology, we identified 157 genes significantly upregulated at night and 313 genes significantly upregulated during the 12-h light/12-h dark cycle. These circadian differential genes are involved in processes and pathways such as lipid catabolic process regulation, meiotic cell cycle, circadian rhythm regulation, positive regulation of the MAPK cascade, and glycerolipid metabolism. Weighted gene co-expression network analysis (WGCNA) revealed 3 modules-green, blue, and red-that significantly correlate with FFA, FAS, and TG, respectively. Genes within these modules were enriched in processes and pathways including the cell cycle, light stimulus response, circadian rhythm regulation, phosphorylation, positive regulation of the MAPK cascade, and lipid biosynthesis. Notably, we identified ten hub genes, including protein kinase C delta (PRKCD), polo like kinase 4 (PLK4), clock circadian regulator (CLOCK), steroid 5 alpha-reductase 3 (SRD5A3), BUB1 mitotic checkpoint serine/threonine kinase (BUB1B), shugoshin 1 (SGO1), NDC80 kinetochore complex component (NDC80), NIMA related kinase 2 (NEK2), minichromosome maintenance complex component 4 (MCM4), polo like kinase 1 (PLK1), potentially link circadian regulation with lipid metabolic homeostasis. These findings demonstrate the regulatory role of the circadian clock in chicken liver lipid metabolism homeostasis and provide a theoretical basis and molecular targets for optimizing the circadian clock to reduce excessive fat deposition in chickens, which is significant for the healthy development of the poultry industry.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Identification of metabolic biomarkers associated with nonalcoholic fatty liver disease

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for the diagnosis and treatment of NAFLD patients.

METHODS

GSE48452, GSE63067, and GSE89632 datasets including nonalcoholic steatohepatitis (NASH) and healthy controls (HC) analyzed in this study were retrieved from the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) between NASH and HC samples were obtained. Next, metabolism-related DEGs (MR-DEGs) were identified by overlapping DEGs and metabolism-related genes (MRG). Further, a protein-protein interaction (PPI) network was developed to show the interaction among MR-DEGs. Subsequently, the "Least absolute shrinkage and selection operator regression" and "Random Forest" algorithms were used to screen metabolism-related genes (MRGs) in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses (GSEA) were performed on these metabolism-related genes. Finally, the expression of metabolism-related gene was determined at the transcription level.

RESULTS

First, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1, were identified using machine learning algorithms. Moreover, a regulatory network consisting of four genes, 25 microRNAs (miRNAs), and 41 transcription factors (TFs) was constructed. Finally, a significant increase in FMO1 and LPL expression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the HC group.

CONCLUSION

Metabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD.

Identification of Novel Diagnostic and Prognostic Gene Signature Biomarkers for Breast Cancer Using Artificial Intelligence and Machine Learning Assisted Transcriptomics Analysis

BACKGROUND

Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed genes (DEGs) for BC diagnosis and prognosis.

METHODS

A cohort of 701 samples from 11 GEO BC microarray datasets was used for the identification of significant DEGs. Seven ML methods, including RFECV-LR, RFECV-SVM, LR-L1, SVC-L1, RF, and Extra-Trees were applied for gene reduction and the construction of a diagnostic model for cancer classification. Kaplan-Meier survival analysis was performed for prognostic signature construction. The potential biomarkers were confirmed via qRT-PCR and validated by another set of ML methods including GBDT, XGBoost, AdaBoost, KNN, and MLP.

RESULTS

We identified 355 DEGs and predicted BC-associated pathways, including kinetochore metaphase signaling, PTEN, senescence, and phagosome-formation pathways. A hub of 28 DEGs and a novel diagnostic nine-gene signature (COL10A, S100P, ADAMTS5, WISP1, COMP, CXCL10, LYVE1, COL11A1, and INHBA) were identified using stringent filter conditions. Similarly, a novel prognostic model consisting of eight-gene signatures (CCNE2, NUSAP1, TPX2, S100P, ITM2A, LIFR, TNXA, and ZBTB16) was also identified using disease-free survival and overall survival analysis. Gene signatures were validated by another set of ML methods. Finally, qRT-PCR results confirmed the expression of the identified gene signatures in BC.

CONCLUSION

The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively.

Targeting transglutaminase 2 mediated exostosin glycosyltransferase 1 signaling in liver cancer stem cells with acyclic retinoid

Transglutaminase 2 (TG2) is a multifunctional protein that promotes or suppresses tumorigenesis, depending on intracellular location and conformational structure. Acyclic retinoid (ACR) is an orally administered vitamin A derivative that prevents hepatocellular carcinoma (HCC) recurrence by targeting liver cancer stem cells (CSCs). In this study, we examined the subcellular location-dependent effects of ACR on TG2 activity at a structural level and characterized the functional role of TG2 and its downstream molecular mechanism in the selective depletion of liver CSCs. A binding assay with high-performance magnetic nanobeads and structural dynamic analysis with native gel electrophoresis and size-exclusion chromatography-coupled multi-angle light scattering or small-angle X-ray scattering showed that ACR binds directly to TG2, induces oligomer formation of TG2, and inhibits the transamidase activity of cytoplasmic TG2 in HCC cells. The loss-of-function of TG2 suppressed the expression of stemness-related genes, spheroid proliferation and selectively induced cell death in an EpCAM+ liver CSC subpopulation in HCC cells. Proteome analysis revealed that TG2 inhibition suppressed the gene and protein expression of exostosin glycosyltransferase 1 (EXT1) and heparan sulfate biosynthesis in HCC cells. In contrast, high levels of ACR increased intracellular Ca²⁺ concentrations along with an increase in apoptotic cells, which probably contributed to the enhanced transamidase activity of nuclear TG2. This study demonstrates that ACR could act as a novel TG2 inhibitor; TG2-mediated EXT1 signaling is a promising therapeutic target in the prevention of HCC by disrupting liver CSCs.

Effects of Sodium Chromate Exposure on Gene Expression Profiles of Primary Rat Hepatocytes (In Vitro)

Chromium exposure has adverse impacts on human health and the environment, whereas chromate-induced hepatotoxicity's detailed mechanism is still unclear. Therefore, the purpose of the current study was to reveal the crucial signaling pathways and genes linked to sodium chromate-induced hepatotoxicity. GSE19662, a gene expression microarray, was obtained from Gene Expression Omnibus (GEO). Six primary rat hepatocyte (PRH) samples from GSE19662 include sodium chromate-treated (n = 3) and the control PRH samples (n = 3). A total of 2,525 differentially expressed genes (DEGs) were obtained, especially 962, and 1,563 genes were up- and downregulated in sodium chromate-treated PRHs compared to the control. Gene ontology (GO) enrichment analysis suggested that those DEGs were involved in multiple biological processes, including the response to toxic substances, the positive regulation of apoptotic process, lipid and cholesterol metabolic process, and others. Signaling pathway enrichment analysis indicated that the DEGs were mainly enriched in MAPK, PI3K-Akt, PPAR, AMPK, cellular senescence, hepatitis B, fatty acid biosynthesis, etc. Moreover, many genes, including CYP2E1, CYP1A2, CYP2C13, CDK1, NDC80, and CCNB1, might contribute to sodium chromate-induced hepatotoxicity. Taken together, this study enhances our knowledge of the potential molecular mechanisms of sodium chromate-induced hepatotoxicity.

Advancements in Hepatocellular Carcinoma: Potential Preclinical Drugs and their Future

Hepatocellular carcinoma (HCC) is one of the foremost causes of tumor-affiliated demises globally. The HCC treatment has undergone numerous developments in terms of both drug and non-drug treatments. The United States Food and Drug Administration (FDA) has authorized the usage of a variety of drugs for the treatment of HCC in recent years, involving multi-kinase inhibitors (lenvatinib, regorafenib, ramucirumab, and cabozantinib), immune checkpoint inhibitors (ICIs) (pembrolizumab and nivolumab), and combination therapies like atezolizumab along with bevacizumab. There are currently over a thousand ongoing clinical and preclinical studies for novel HCC drugs, which portrays a competent setting in the field. This review discusses the i. FDA-approved HCC drugs, their molecular targets, safety profiles, and potential disadvantages; ii. The intrial agents/drugs, their molecular targets, and possible benefits compared to alternatives, and iii. The current and future status of potential preclinical drugs with novel therapeutic targets for HCC. Consequently, existing drug treatments and novel strategies with their balanced consumption could ensure a promising future for a universal remedy of HCC in the near future.

The altered lipidome of hepatocellular carcinoma

Alterations in metabolic pathways are a hallmark of cancer. A deeper understanding of the contribution of different metabolites to carcinogenesis is thus vitally important to elucidate mechanisms of tumor initiation and progression to inform therapeutic strategies. Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide and its altered metabolic landscape is beginning to unfold with the advancement of technologies. In particular, characterization of the lipidome of human HCCs has accelerated, and together with biochemical analyses, are revealing recurrent patterns of alterations in glycerophospholipid, sphingolipid, cholesterol and bile acid metabolism. These widespread alterations encompass a myriad of lipid species with numerous roles affecting multiple hallmarks of cancer, including aberrant growth signaling, metastasis, evasion of cell death and immunosuppression. In this review, we summarize the current trends and findings of the altered lipidomic landscape of HCC and discuss their potential biological significance for hepatocarcinogenesis.

Update on Glycosphingolipids Abundance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most frequent type of primary liver cancer. Low numbers of HCC patients being suitable for liver resection or transplantation and multidrug resistance development during pharmacotherapy leads to high death rates for HCC patients. Understanding the molecular mechanisms of HCC etiology may contribute to the development of novel therapeutic strategies for prevention and treatment of HCC. UDP-glucose ceramide glycosyltransferase (UGCG), a key enzyme in glycosphingolipid metabolism, generates glucosylceramide (GlcCer), which is the precursor for all glycosphingolipids (GSLs). Since UGCG gene expression is altered in 0.8% of HCC tumors, GSLs may play a role in cellular processes in liver cancer cells. Here, we discuss the current literature about GSLs and their abundance in normal liver cells, Gaucher disease and HCC. Furthermore, we review the involvement of UGCG/GlcCer in multidrug resistance development, globosides as a potential prognostic marker for HCC, gangliosides as a potential liver cancer stem cell marker, and the role of sulfatides in tumor metastasis. Only a limited number of molecular mechanisms executed by GSLs in HCC are known, which we summarize here briefly. Overall, the role GSLs play in HCC progression and their ability to serve as biomarkers or prognostic indicators for HCC, requires further investigation.

ARHGAP11A Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric Cancer

Background: ARHGAP11A, belongs to RhoGAPs family, is vital for cell motility. However, the role of ARHGAP11A in gastric cancer is obscure. Methods: The expression level of ARHGAP11A was analyzed by Oncomine database. The correlation of ARHGAP11A expression with immune infiltrates and associated gene markers was clarified by Tumor IMmune Estimation Resource and Gene Expression Profiling Interactive Analysis database. The correlation between ARHGAP11A expression and the patient prognosis was identified by Kaplan-Meier plotter and PrognoScan. Genetic changes of ARHGAP11A were analyzed by cBioPortal. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by GeneMANIA and Metascape. Results: We found that the expression levels of ARHGAP11A were elevated in various cancers including gastric cancer when compared with normal tissues. High expression of ARHGAP11A was significantly correlated with a better prognosis in gastric cancer. We revealed that the expression of ARHGAP11A was negatively associated with infiltration levels of CD8+ T cells, CD4+ T cells, macrophages and dendritic cells. In addition, ARHGAP11A expression was significantly correlated with gene markers of these immune cells. Lastly, gene functional enrichment analysis indicated that ARHGAP11A involved in regulating lymphocyte activation, cell division, cell killing, myeloid leukocyte differentiation and leukocyte apoptosis. Conclusion: Our findings demonstrated that ARHGAP11A was a valuable prognostic biomarker in gastric cancer. Further work is needed to validate its role and underlying mechanisms in regulating immune infiltrates.

Cellular Uptake Pathways of Nanoparticles: Process of Endocytosis and Factors Affecting Their Fate

BACKGROUND

Efficient and controlled internalization of NPs into the cells depends on their physicochemical properties and dynamics of the plasma membrane. NPs-cell interaction is a complex process that decides the fate of NPs internalization through different endocytosis pathways.

OBJECTIVE

The aim of this review is to highlight the physicochemical properties of synthesized nanoparticles (NPs) and their interaction with the cellular-dynamics and pathways like phagocytosis, pinocytosis, macropinocytosis, clathrin, and caveolae-mediated endocytosis and the involvement of effector proteins domain such as clathrin, AP2, caveolin, Arf6, Cdc42, dynamin and cell surface receptors during the endocytosis process of NPs.

METHOD

An electronic search was performed to explore the focused reviews and research articles on types of endocytosis and physicochemical properties of nanoparticles and their impact on cellular internalizations. The search was limited to peer-reviewed journals in the PubMed database.

RESULTS

This article discusses in detail how different types of NPs and their physicochemical properties such as size, shape, aspect ratio, surface charge, hydrophobicity, elasticity, stiffness, corona formation, surface functionalization changes the pattern of endocytosis in the presence of different pharmacological blockers. Some external forces like a magnetic field, electric field, and ultrasound exploit the cell membrane dynamics to permeabilize them for efficient internalization with respect to fundamental principles of membrane bending and pore formation.

CONCLUSION

This review will be useful to attract and guide the audience to understand the endocytosis mechanism and their pattern with respect to physicochemical properties of NPs to improve their efficacy and targeting to achieve the impactful outcome in drug-delivery and theranostics applications.