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Cells Dec 2020The interest in fructose metabolism is based on the observation that an increased dietary fructose consumption leads to an increased risk of obesity and metabolic... (Review)
Review
The interest in fructose metabolism is based on the observation that an increased dietary fructose consumption leads to an increased risk of obesity and metabolic syndrome. In particular, obesity is a known risk factor to develop many types of cancer and there is clinical and experimental evidence that an increased fructose intake promotes cancer growth. The precise mechanism, however, in which fructose induces tumor growth is still not fully understood. In this article, we present an overview of the metabolic pathways that utilize fructose and how fructose metabolism can sustain cancer cell proliferation. Although the degradation of fructose shares many of the enzymes and metabolic intermediates with glucose metabolism through glycolysis, glucose and fructose are metabolized differently. We describe the different metabolic fates of fructose carbons and how they are connected to lipogenesis and nucleotide synthesis. In addition, we discuss how the endogenous production of fructose from glucose via the polyol pathway can be beneficial for cancer cells.
Topics: Aldehyde Reductase; Fructokinases; Fructose; Humans; L-Iditol 2-Dehydrogenase; Lipogenesis; Liver; Metabolic Syndrome; Neoplasms; Pentose Phosphate Pathway
PubMed: 33302403
DOI: 10.3390/cells9122635 -
Journal of Clinical and Experimental... 2022Excessive alcohol consumption is a global healthcare problem with enormous social, economic, and clinical consequences. While chronic, heavy alcohol consumption causes... (Review)
Review
Excessive alcohol consumption is a global healthcare problem with enormous social, economic, and clinical consequences. While chronic, heavy alcohol consumption causes structural damage and/or disrupts normal organ function in virtually every tissue of the body, the liver sustains the greatest damage. This is primarily because the liver is the first to see alcohol absorbed from the gastrointestinal tract via the portal circulation and second, because the liver is the principal site of ethanol metabolism. Alcohol-induced damage remains one of the most prevalent disorders of the liver and a leading cause of death or transplantation from liver disease. Despite extensive research on the pathophysiology of this disease, there are still no targeted therapies available. Given the multifactorial mechanisms for alcohol-associated liver disease pathogenesis, it is conceivable that a multitherapeutic regimen is needed to treat different stages in the spectrum of this disease.
PubMed: 36340300
DOI: 10.1016/j.jceh.2022.05.004 -
Autophagy Aug 2023Copper is an essential trace element in biological systems, maintaining the activity of enzymes and the function of transcription factors. However, at high... (Review)
Review
Copper is an essential trace element in biological systems, maintaining the activity of enzymes and the function of transcription factors. However, at high concentrations, copper ions show increased toxicity by inducing regulated cell death, such as apoptosis, paraptosis, pyroptosis, ferroptosis, and cuproptosis. Furthermore, copper ions can trigger macroautophagy/autophagy, a lysosome-dependent degradation pathway that plays a dual role in regulating the survival or death fate of cells under various stress conditions. Pathologically, impaired copper metabolism due to environmental or genetic causes is implicated in a variety of human diseases, such as rare Wilson disease and common cancers. Therapeutically, copper-based compounds are potential chemotherapeutic agents that can be used alone or in combination with other drugs or approaches to treat cancer. Here, we review the progress made in understanding copper metabolic processes and their impact on the regulation of cell death and autophagy. This knowledge may help in the design of future clinical tools to improve cancer diagnosis and treatment. ACSL4, acyl-CoA synthetase long chain family member 4; AIFM1/AIF, apoptosis inducing factor mitochondria associated 1; AIFM2, apoptosis inducing factor mitochondria associated 2; ALDH, aldehyde dehydrogenase; ALOX, arachidonate lipoxygenase; AMPK, AMP-activated protein kinase; APAF1, apoptotic peptidase activating factor 1; ATF4, activating transcription factor 4; ATG, autophagy related; ATG13, autophagy related 13; ATG5, autophagy related 5; ATOX1, antioxidant 1 copper chaperone; ATP, adenosine triphosphate; ATP7A, ATPase copper transporting alpha; ATP7B, ATPase copper transporting beta; BAK1, BCL2 antagonist/killer 1; BAX, BCL2 associated X apoptosis regulator; BBC3/PUMA, BCL2 binding component 3; BCS, bathocuproinedisulfonic acid; BECN1, beclin 1; BID, BH3 interacting domain death agonist; BRCA1, BRCA1 DNA repair associated; BSO, buthionine sulphoximine; CASP1, caspase 1; CASP3, caspase 3; CASP4/CASP11, caspase 4; CASP5, caspase 5; CASP8, caspase 8; CASP9, caspase 9; CCS, copper chaperone for superoxide dismutase; CD274/PD-L1, CD274 molecule; CDH2, cadherin 2; CDKN1A/p21, cyclin dependent kinase inhibitor 1A; CDKN1B/p27, cyclin-dependent kinase inhibitor 1B; COMMD10, COMM domain containing 10; CoQ10, coenzyme Q 10; CoQ10H2, reduced coenzyme Q 10; COX11, cytochrome c oxidase copper chaperone COX11; COX17, cytochrome c oxidase copper chaperone COX17; CP, ceruloplasmin; CYCS, cytochrome c, somatic; DBH, dopamine beta-hydroxylase; DDIT3/CHOP, DNA damage inducible transcript 3; DLAT, dihydrolipoamide S-acetyltransferase; DTC, diethyldithiocarbamate; EIF2A, eukaryotic translation initiation factor 2A; EIF2AK3/PERK, eukaryotic translation initiation factor 2 alpha kinase 3; ER, endoplasmic reticulum; ESCRT-III, endosomal sorting complex required for transport-III; ETC, electron transport chain; FABP3, fatty acid binding protein 3; FABP7, fatty acid binding protein 7; FADD, Fas associated via death domain; FAS, Fas cell surface death receptor; FASL, Fas ligand; FDX1, ferredoxin 1; GNAQ/11, G protein subunit alpha q/11; GPX4, glutathione peroxidase 4; GSDMD, gasdermin D; GSH, glutathione; HDAC, histone deacetylase; HIF1, hypoxia inducible factor 1; HIF1A, hypoxia inducible factor 1 subunit alpha; HMGB1, high mobility group box 1; IL1B, interleukin 1 beta; IL17, interleukin 17; KRAS, KRAS proto-oncogene, GTPase; LOX, lysyl oxidase; LPCAT3, lysophosphatidylcholine acyltransferase 3; MAP1LC3, microtubule associated protein 1 light chain 3; MAP2K1, mitogen-activated protein kinase kinase 1; MAP2K2, mitogen-activated protein kinase kinase 2; MAPK, mitogen-activated protein kinases; MAPK14/p38, mitogen-activated protein kinase 14; MEMO1, mediator of cell motility 1; MT-CO1/COX1, mitochondrially encoded cytochrome c oxidase I; MT-CO2/COX2, mitochondrially encoded cytochrome c oxidase II; MTOR, mechanistic target of rapamycin kinase; MTs, metallothioneins; NAC, N-acetylcysteine; NFKB/NF-Κb, nuclear factor kappa B; NLRP3, NLR family pyrin domain containing 3; NPLOC4/NPL4, NPL4 homolog ubiquitin recognition factor; PDE3B, phosphodiesterase 3B; PDK1, phosphoinositide dependent protein kinase 1; PHD, prolyl-4-hydroxylase domain; PIK3C3/VPS34, phosphatidylinositol 3-kinase catalytic subunit type 3; PMAIP1/NOXA, phorbol-12-myristate-13-acetate-induced protein 1; POR, cytochrome P450 oxidoreductase; PUFA-PL, PUFA of phospholipids; PUFAs, polyunsaturated fatty acids; ROS, reactive oxygen species; SCO1, synthesis of cytochrome C oxidase 1; SCO2, synthesis of cytochrome C oxidase 2; SLC7A11, solute carrier family 7 member 11; SLC11A2/DMT1, solute carrier family 11 member 2; SLC31A1/CTR1, solute carrier family 31 member 1; SLC47A1, solute carrier family 47 member 1; SOD1, superoxide dismutase; SP1, Sp1 transcription factor; SQSTM1/p62, sequestosome 1; STEAP4, STEAP4 metalloreductase; TAX1BP1, Tax1 binding protein 1; TEPA, tetraethylenepentamine; TFEB, transcription factor EB; TM, tetrathiomolybdate; TP53/p53, tumor protein p53; TXNRD1, thioredoxin reductase 1; UCHL5, ubiquitin C-terminal hydrolase L5; ULK1, Unc-51 like autophagy activating kinase 1; ULK1, unc-51 like autophagy activating kinase 1; ULK2, unc-51 like autophagy activating kinase 2; USP14, ubiquitin specific peptidase 14; VEGF, vascular endothelial gro wth factor; XIAP, X-linked inhibitor of apoptosis.
Topics: Humans; Autophagy; Tumor Suppressor Protein p53; Apoptosis Inducing Factor; Copper; Ubiquinone; Electron Transport Complex IV; Autophagy-Related Protein-1 Homolog; Proto-Oncogene Proteins p21(ras); Apoptosis; Caspases; Hypoxia-Inducible Factor 1; Superoxide Dismutase; Neoplasms; Ions; Proto-Oncogene Proteins c-bcl-2
PubMed: 37055935
DOI: 10.1080/15548627.2023.2200554 -
Journal of Translational Medicine Jun 2023Diabetic kidney disease (DKD) has been the leading cause of chronic kidney disease in developed countries. Evidence of the benefits of resveratrol (RES) for the...
BACKGROUND
Diabetic kidney disease (DKD) has been the leading cause of chronic kidney disease in developed countries. Evidence of the benefits of resveratrol (RES) for the treatment of DKD is accumulating. However, comprehensive therapeutic targets and underlying mechanisms through which RES exerts its effects against DKD are limited.
METHODS
Drug targets of RES were obtained from Drugbank and SwissTargetPrediction Databases. Disease targets of DKD were obtained from DisGeNET, Genecards, and Therapeutic Target Database. Therapeutic targets for RES against DKD were identified by intersecting the drug targets and disease targets. GO functional enrichment analysis, KEGG pathway analysis, and disease association analysis were performed using the DAVID database and visualized by Cytoscape software. Molecular docking validation of the binding capacity between RES and targets was performed by UCSF Chimera software and SwissDock webserver. The high glucose (HG)-induced podocyte injury model, RT-qPCR, and western blot were used to verify the reliability of the effects of RES on target proteins.
RESULTS
After the intersection of the 86 drug targets and 566 disease targets, 25 therapeutic targets for RES against DKD were obtained. And the target proteins were classified into 6 functional categories. A total of 11 cellular components terms and 27 diseases, and the top 20 enriched biological processes, molecular functions, and KEGG pathways potentially involved in the RES action against DKD were recorded. Molecular docking studies showed that RES had a strong binding affinity toward PPARA, ESR1, SLC2A1, SHBG, AR, AKR1B1, PPARG, IGF1R, RELA, PIK3CA, MMP9, AKT1, INSR, MMP2, TTR, and CYP2C9 domains. The HG-induced podocyte injury model was successfully constructed and validated by RT-qPCR and western blot. RES treatment was able to reverse the abnormal gene expression of PPARA, SHBG, AKR1B1, PPARG, IGF1R, MMP9, AKT1, and INSR.
CONCLUSIONS
RES may target PPARA, SHBG, AKR1B1, PPARG, IGF1R, MMP9, AKT1, and INSR domains to act as a therapeutic agent for DKD. These findings comprehensively reveal the potential therapeutic targets for RES against DKD and provide theoretical bases for the clinical application of RES in the treatment of DKD.
Topics: Humans; Matrix Metalloproteinase 9; Diabetic Nephropathies; Molecular Docking Simulation; Network Pharmacology; Resveratrol; PPAR gamma; Reproducibility of Results; Diabetes Mellitus; Aldehyde Reductase
PubMed: 37308949
DOI: 10.1186/s12967-023-04233-0 -
Acta Pharmaceutica Sinica. B Jan 2020Microbes inhabiting the intestinal tract of humans represent a site for xenobiotic metabolism. The gut microbiome, the collection of microorganisms in the... (Review)
Review
Microbes inhabiting the intestinal tract of humans represent a site for xenobiotic metabolism. The gut microbiome, the collection of microorganisms in the gastrointestinal tract, can alter the metabolic outcome of pharmaceuticals, environmental toxicants, and heavy metals, thereby changing their pharmacokinetics. Direct chemical modification of xenobiotics by the gut microbiome, either through the intestinal tract or re-entering the gut enterohepatic circulation, can lead to increased metabolism or bioactivation, depending on the enzymatic activity within the microbial niche. Unique enzymes encoded within the microbiome include those that reverse the modifications imparted by host detoxification pathways. Additionally, the microbiome can limit xenobiotic absorption in the small intestine by increasing the expression of cell-cell adhesion proteins, supporting the protective mucosal layer, and/or directly sequestering chemicals. Lastly, host gene expression is regulated by the microbiome, including CYP450s, multi-drug resistance proteins, and the transcription factors that regulate them. While the microbiome affects the host and pharmacokinetics of the xenobiotic, xenobiotics can also influence the viability and metabolism of the microbiome. Our understanding of the complex interconnectedness between host, microbiome, and metabolism will advance with new modeling systems, technology development and refinement, and mechanistic studies focused on the contribution of human and microbial metabolism.
PubMed: 31998605
DOI: 10.1016/j.apsb.2019.12.001 -
Genome Medicine Aug 2022Lung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and...
BACKGROUND
Lung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and failure. Single-cell RNA sequencing (scRNA-seq) has been widely used to dissect the cellular composition and characterize the molecular properties of cancer cells and their tumor microenvironment in lung cancer. However, the transcriptomic heterogeneity among various cancer cells in non-small cell lung cancer (NSCLC) warrants further illustration.
METHODS
To comprehensively analyze the molecular heterogeneity of NSCLC, we performed high-precision single-cell RNA-seq analyses on 7364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient.
RESULTS
In 6 of 16 patients sequenced, we identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or even three histologic subtypes of NSCLC-adenocarcinoma (ADC), squamous cell carcinoma (SCC), and neuroendocrine tumor (NET) in the same individual cell, which we defined as mixed-lineage tumor cells; this was verified by both co-immunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. In addition, gene signatures specific to mixed-lineage tumor cells were identified, including AKR1B1. Gene knockdown and small molecule inhibition of AKR1B1 can significantly decrease cell proliferation and promote cell apoptosis, suggesting that AKR1B1 plays an important role in tumorigenesis and can serve as a candidate target for tumor therapy of NSCLC patients with mixed-lineage tumor features.
CONCLUSIONS
In summary, our work provides novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined signatures of SCC, ADC, and NET and offers clues for potential treatment strategies in these patients.
Topics: Adenocarcinoma; Aldehyde Reductase; Biomarkers, Tumor; Carcinoma, Non-Small-Cell Lung; Carcinoma, Squamous Cell; DNA Copy Number Variations; Gene Expression Regulation, Neoplastic; Humans; Lung Neoplasms; Prognosis; RNA-Seq; Tumor Microenvironment
PubMed: 35962452
DOI: 10.1186/s13073-022-01089-9 -
Molecules (Basel, Switzerland) Jun 2023The mitochondrial amidoxime-reducing component (mARC) is the most recently discovered molybdoenzyme in humans after sulfite oxidase, xanthine oxidase and aldehyde... (Review)
Review
The mitochondrial amidoxime-reducing component (mARC) is the most recently discovered molybdoenzyme in humans after sulfite oxidase, xanthine oxidase and aldehyde oxidase. Here, the timeline of mARC's discovery is briefly described. The story begins with investigations into -oxidation of pharmaceutical drugs and model compounds. Many compounds are -oxidized extensively in vitro, but it turned out that a previously unknown enzyme catalyzes the reduction of the -oxygenated products in vivo. After many years, the molybdoenzyme mARC could finally be isolated and identified in 2006. mARC is an important drug-metabolizing enzyme and -reduction by mARC has been exploited very successfully for prodrug strategies, that allow oral administration of otherwise poorly bioavailable therapeutic drugs. Recently, it was demonstrated that mARC is a key factor in lipid metabolism and likely involved in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). The exact link between mARC and lipid metabolism is not yet fully understood. Regardless, many now consider mARC a potential drug target for the prevention or treatment of liver diseases. This article focusses on discoveries related to mammalian mARC enzymes. mARC homologues have been studied in algae, plants and bacteria. These will not be discussed extensively here.
Topics: Animals; Humans; Oxidoreductases; Oxidation-Reduction; Sulfite Oxidase; Oximes; Mammals; Molybdenum
PubMed: 37375270
DOI: 10.3390/molecules28124713 -
Computational and Structural... 2022Tick-borne encephalitis virus (TBEV), the most medically relevant tick-transmitted flavivirus in Eurasia, targets the host central nervous system and frequently causes...
Tick-borne encephalitis virus (TBEV), the most medically relevant tick-transmitted flavivirus in Eurasia, targets the host central nervous system and frequently causes severe encephalitis. The severity of TBEV-induced neuropathogenesis is highly cell-type specific and the exact mechanism responsible for such differences has not been fully described yet. Thus, we performed a comprehensive analysis of alterations in host poly-(A)/miRNA/lncRNA expression upon TBEV infection in human primary neurons (high cytopathic effect) and astrocytes (low cytopathic effect). Infection with severe but not mild TBEV strain resulted in a high neuronal death rate. In comparison, infection with either of TBEV strains in human astrocytes did not. Differential expression and splicing analyses with an prediction of miRNA/mRNA/lncRNA/vd-sRNA networks found significant changes in inflammatory and immune response pathways, nervous system development and regulation of mitosis in TBEV Hypr-infected neurons. Candidate mechanisms responsible for the aforementioned phenomena include specific regulation of host mRNA levels via differentially expressed miRNAs/lncRNAs or vd-sRNAs mimicking endogenous miRNAs and virus-driven modulation of host pre-mRNA splicing. We suggest that these factors are responsible for the observed differences in the virulence manifestation of both TBEV strains in different cell lines. This work brings the first complex overview of alterations in the transcriptome of human astrocytes and neurons during the infection by two TBEV strains of different virulence. The resulting data could serve as a starting point for further studies dealing with the mechanism of TBEV-host interactions and the related processes of TBEV pathogenesis.
PubMed: 35685361
DOI: 10.1016/j.csbj.2022.05.052 -
Computers in Biology and Medicine Jul 2022Based on bioinformatics and network pharmacology, the treatment of Saussurea involucrata (SAIN) on novel coronavirus (COVID-19) was evaluated by the GEO clinical sample...
OBJECTIVE
Based on bioinformatics and network pharmacology, the treatment of Saussurea involucrata (SAIN) on novel coronavirus (COVID-19) was evaluated by the GEO clinical sample gene difference analysis, compound-target molecular docking, and molecular dynamics simulation. role in the discovery of new targets for the prevention or treatment of COVID-19, to better serve the discovery and clinical application of new drugs.
MATERIALS AND METHODS
Taking the Traditional Chinese Medicine System Pharmacology Database (TCMSP) as the starting point for the preliminary selection of compounds and targets, we used tools such as Cytoscape 3.8.0, TBtools 1.098, AutoDock vina, R 4.0.2, PyMol, and GROMACS to analyze the compounds of SAIN and targets were initially screened. To further screen the active ingredients and targets, we carried out genetic difference analysis (n = 72) through clinical samples of COVID-19 derived from GEO and carried out biological process (BP) analysis on these screened targets (P ≤ 0.05)., gene = 9), KEGG pathway analysis (FDR≤0.05, gene = 9), protein interaction network (PPI) analysis (gene = 9), and compounds-target-pathway network analysis (gene = 9), to obtain the target Point-regulated biological processes, disease pathways, and compounds-target-pathway relationships. Through the precise molecular docking between the compounds and the targets, we further screened SAIN's active ingredients (Affinity ≤ -7.2 kcal/mol) targets and visualized the data. After that, we performed molecular dynamics simulations and consulted a large number of related Validation of the results in the literature.
RESULTS
Through the screening, analysis, and verification of the data, it was finally confirmed that there are five main active ingredients in SAIN, which are Quercitrin, Rutin, Caffeic acid, Jaceosidin, and Beta-sitosterol, and mainly act on five targets. These targets mainly regulate Tuberculosis, TNF signaling pathway, Alzheimer's disease, Pertussis, Toll-like receptor signaling pathway, Influenza A, Non-alcoholic fatty liver disease (NAFLD), Neuroactive ligand-receptor interaction, Complement and coagulation cascades, Fructose and mannose metabolism, and Metabolic pathways, play a role in preventing or treating COVID-19. Molecular dynamics simulation results show that the four active ingredients of SAIN, Quercitrin, Rutin, Caffeic acid, and Jaceosidin, act on the four target proteins of COVID-19, AKR1B1, C5AR1, GSK3B, and IL1B to form complexes that can be very stable in the human environment. Tertiary structure exists.
CONCLUSION
Our study successfully explained the effective mechanism of SAIN in improving COVID-19, and at the same time predicted the potential targets of SAIN in the treatment of COVID-19, AKR1B1, IL1B, and GSK3B. It provides a new basis and provides great support for subsequent research on COVID-19.
Topics: Aldehyde Reductase; Computational Biology; Drugs, Chinese Herbal; Humans; Medicine, Chinese Traditional; Molecular Docking Simulation; Molecular Targeted Therapy; Network Pharmacology; Rutin; Saussurea; COVID-19 Drug Treatment
PubMed: 35751193
DOI: 10.1016/j.compbiomed.2022.105549 -
Metabolites May 2021We provide an overview of the physiological roles of aldehyde reductase (AKR1A) and also discuss the functions of aldose reductase (AKR1B) and other family members when... (Review)
Review
We provide an overview of the physiological roles of aldehyde reductase (AKR1A) and also discuss the functions of aldose reductase (AKR1B) and other family members when necessary. Many types of aldehyde compounds are cytotoxic and some are even carcinogenic. Such toxic aldehydes are detoxified via the action of AKR in an NADPH-dependent manner and the resulting products may exert anti-diabetic and anti-tumorigenic activity. AKR1A is capable of reducing 3-deoxyglucosone and methylglyoxal, which are reactive intermediates that are involved in glycation, a non-enzymatic glycosylation reaction. Accordingly, AKR1A is thought to suppress the formation of advanced glycation end products (AGEs) and prevent diabetic complications. AKR1A and, in part, AKR1B are responsible for the conversion of d-glucuronate to l-gulonate which constitutes a process for ascorbate (vitamin C) synthesis in competent animals. AKR1A is also involved in the reduction of -nitrosylated glutathione and coenzyme A and thereby suppresses the protein -nitrosylation that occurs under conditions in which the production of nitric oxide is stimulated. As the physiological functions of AKR1A are currently not completely understood, the genetic modification of could reveal the latent functions of AKR1A and differentiate it from other family members.
PubMed: 34073440
DOI: 10.3390/metabo11060343