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Kansu G, Ozturk N, Karagac MS, Yesilkent EN, Ceylan H. The interplay between doxorubicin chemotherapy, antioxidant system, and cardiotoxicity: Unrevealing of the protective potential of tannic acid. Biotechnol Appl Biochem 2024. [PMID: 39099314 DOI: 10.1002/bab.2648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 07/23/2024] [Indexed: 08/06/2024]
Abstract
Cardiotoxicity is the leading side effect of anthracycline-based chemotherapy. Therefore, it has gained importance to reveal chemotherapy-supporting strategies and reliable agents with their mechanisms of action. Tannic acid (TA), a naturally occurring plant polyphenol, has diverse physiological effects, including anti-inflammatory, anticarcinogenic, antioxidant, and radical scavenging properties. Therefore, this study was designed to investigate whether TA exerts a protective effect on mechanisms contributing to anthracycline-induced cardiotoxicity in rat heart tissues exposed to doxorubicin (DOX). Rats were randomly divided into control and experimental groups and treated with (18 mg/kg) DOX, TA (50 mg/kg), and DOX + TA during the 2 weeks. Cardiac gene markers and mitochondrial DNA (mtDNA) content were evaluated in the heart tissues of all animals. In addition to major metabolites, mRNA expression changes and biological activity responses of components of antioxidant metabolism were examined in the heart tissues of all animals. The expression of cardiac gene markers increased by DOX exposure was significantly reduced by TA treatment, whereas mtDNA content, which was decreased by DOX exposure, was significantly increased. TA also improved antioxidant metabolism members' gene expression and enzymatic activity, including glutathione peroxidase, glutathione s-transferase, superoxide dismutase, catalase, and thioredoxin reductase. This study provides a detailed overview of the current understanding of DOX-induced cardiotoxicity and preventive or curative measures involving TA.
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Affiliation(s)
- Guldemet Kansu
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Türkiye
| | - Neslihan Ozturk
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Türkiye
| | - Medine Sibel Karagac
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Türkiye
| | - Esra Nur Yesilkent
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Türkiye
| | - Hamid Ceylan
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Türkiye
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Karagac MS, Ceylan H. Neuroprotective Potential of Tannic Acid Against Neurotoxic Outputs of Monosodium Glutamate in Rat Cerebral Cortex. Neurotox Res 2023; 41:670-680. [PMID: 37713032 DOI: 10.1007/s12640-023-00667-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 08/29/2023] [Accepted: 09/08/2023] [Indexed: 09/16/2023]
Abstract
Glutamate in monosodium glutamate (MSG), which is widely used in the food industry, has an important role in major brain functions such as memory, learning, synapse formation, and stabilization. However, extensive use of MSG has been linked with neurotoxicity. Therefore, in addition to clarifying the underlying mechanisms of MSG-induced neurotoxicity, it is also important to determine safe agents that can diminish the damage caused by MSG. Tannic acid (TA) is a naturally occurring plant polyphenol that exhibits versatile physiological effects such as anti-inflammatory, anti-carcinogenic, antioxidant, and radical scavenging. This study was conducted to assess the neurotoxic and neuroprotective effects of these two dietary components in the rat cerebral cortex. Twenty-four Sprague Dawley rats were divided into 4 equal groups and were treated with MSG (2 g/kg) and TA (50 mg/kg) alone and in combination for 3 weeks. Alterations in oxidative stress indicators (MDA and GSH) were measured in the cortex tissues. In addition, changes in enzymatic activities and gene expression patterns of antioxidant system components (GST, GPx, CAT, and SOD) were investigated. Furthermore, mRNA expressions of FoxO transcription factors (Foxo1 and Foxo3) and apoptotic markers (Casp3 and Casp9) were assessed. Results revealed that dietary TA intake significantly rehabilitated MSG-induced dysregulation in cortical tissue by regulating redox balance, cellular homeostasis, and apoptosis. The present study proposes that MSG-induced detrimental effects on cortical tissue are potentially mitigated by TA via modulation of oxidative stress, cell metabolism, and programmed cell death.
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Affiliation(s)
- Medine Sibel Karagac
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Turkey
| | - Hamid Ceylan
- Department of Molecular Biology and Genetics, Faculty of Science, Atatürk University, Erzurum, Turkey.
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Bernardo L, Lomagno A, Mauri PL, Di Silvestre D. Integration of Omics Data and Network Models to Unveil Negative Aspects of SARS-CoV-2, from Pathogenic Mechanisms to Drug Repurposing. BIOLOGY 2023; 12:1196. [PMID: 37759595 PMCID: PMC10525644 DOI: 10.3390/biology12091196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/25/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 health emergency, affecting and killing millions of people worldwide. Following SARS-CoV-2 infection, COVID-19 patients show a spectrum of symptoms ranging from asymptomatic to very severe manifestations. In particular, bronchial and pulmonary cells, involved at the initial stage, trigger a hyper-inflammation phase, damaging a wide range of organs, including the heart, brain, liver, intestine and kidney. Due to the urgent need for solutions to limit the virus' spread, most efforts were initially devoted to mapping outbreak trajectories and variant emergence, as well as to the rapid search for effective therapeutic strategies. Samples collected from hospitalized or dead COVID-19 patients from the early stages of pandemic have been analyzed over time, and to date they still represent an invaluable source of information to shed light on the molecular mechanisms underlying the organ/tissue damage, the knowledge of which could offer new opportunities for diagnostics and therapeutic designs. For these purposes, in combination with clinical data, omics profiles and network models play a key role providing a holistic view of the pathways, processes and functions most affected by viral infection. In fact, in addition to epidemiological purposes, networks are being increasingly adopted for the integration of multiomics data, and recently their use has expanded to the identification of drug targets or the repositioning of existing drugs. These topics will be covered here by exploring the landscape of SARS-CoV-2 survey-based studies using systems biology approaches derived from omics data, paying particular attention to those that have considered samples of human origin.
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Affiliation(s)
| | | | | | - Dario Di Silvestre
- Institute for Biomedical Technologies—National Research Council (ITB-CNR), 20054 Segrate, Italy; (L.B.); (A.L.); (P.L.M.)
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Sokouti B. A systems biology approach for investigating significantly expressed genes among COVID-19, hepatocellular carcinoma, and chronic hepatitis B. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2022; 23:146. [PMID: 37521843 PMCID: PMC9584277 DOI: 10.1186/s43042-022-00360-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 10/12/2022] [Indexed: 01/08/2023] Open
Abstract
Background Worldwide, COVID-19's death rate is about 2%, considering the incidence and mortality. However, the information on its complications in other organs, specifically the liver and its disorders, is limited in mild or severe cases. In this study, we aimed to computationally investigate the typical relationships between liver-related diseases [i.e., hepatocellular carcinoma (HCC), and chronic hepatitis B (CHB)] and COVID-19, considering the involved significant genes and their molecular mechanisms. Methods We investigated two GEO microarray datasets (GSE164805 and GSE58208) to identify differentially expressed genes (DEGs) among the generated four datasets for mild/severe COVID-19, HCC, and CHB. Then, the overlapping genes among them were identified for GO and KEGG enrichment analyses, protein-protein interaction network construction, hub genes determination, and their associations with immune cell infiltration. Results A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB. Moreover, the analysis of immune cell infiltration revealed that these genes are mostly positively correlated with tumor immune and inflammatory responses. Conclusions In summary, the current study demonstrated that 22 identified DEGs might play an essential role in understanding the associations between the mild/severe COVID-19 patients with HCC and CHB. So, the HCC and CHB patients involved in different types of COVID-19 can benefit from immune-based targets for therapeutic interventions. Supplementary Information The online version contains supplementary material available at 10.1186/s43042-022-00360-3.
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Affiliation(s)
- Babak Sokouti
- Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
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Charitou T, Kontou PI, Tamposis IA, Pavlopoulos GA, Braliou GG, Bagos PG. Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach. THE PHARMACOGENOMICS JOURNAL 2022; 22:294-302. [PMID: 36171417 PMCID: PMC9517961 DOI: 10.1038/s41397-022-00289-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 07/16/2022] [Accepted: 09/08/2022] [Indexed: 01/08/2023]
Abstract
Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.
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Zhang F, Yu C, Xu W, Li X, Feng J, Shi H, Yang J, Sun Q, Cao X, Zhang L, Peng M. Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis. PLoS One 2022; 17:e0269386. [PMID: 35749386 PMCID: PMC9231758 DOI: 10.1371/journal.pone.0269386] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/19/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND There is growing evidence of a strong relationship between COVID-19 and myocarditis. However, there are few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 Myocarditis. This study aimed to identify critical genes related to COVID-19 Myocarditis by bioinformatic methods, explore the biological mechanisms and gene regulatory networks, and probe related drugs. METHODS The gene expression data of GSE150392 and GSE167028 were obtained from the Gene Expression Omnibus (GEO), including cardiomyocytes derived from human induced pluripotent stem cells infected with SARS-CoV-2 in vitro and GSE150392 from patients with myocarditis infected with SARS-CoV-2 and the GSE167028 gene expression dataset. Differentially expressed genes (DEGs) (adjusted P-Value <0.01 and |Log2 Fold Change| ≥2) in GSE150392 were assessed by NetworkAnalyst 3.0. Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes. Functional enrichment analyses were performed by using the "clusterProfiler" package in the R software, and protein-protein interaction (PPI) networks were constructed on the STRING website (https://cn.string-db.org/). Critical genes were identified by the CytoHubba plugin of Cytoscape by 5 algorithms. Transcription factor-gene (TF-gene) and Transcription factor-microRibonucleic acid (TF-miRNA) coregulatory networks construction were performed by NetworkAnalyst 3.0 and displayed in Cytoscape. Finally, Drug Signatures Database (DSigDB) was used to probe drugs associated with COVID-19 Myocarditis. RESULTS Totally 850 DEGs (including 449 up-regulated and 401 down-regulated genes) and 159 significant genes in turquoise modules were identified from GSE150392 and GSE167028, respectively. Functional enrichment analysis indicated that common genes were mainly enriched in biological processes such as cell cycle and ubiquitin-protein hydrolysis. 6 genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) were identified as critical genes. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Etoposide, Methotrexate, Troglitazone, etc) were considered as target drugs for COVID-19 Myocarditis. CONCLUSIONS Through bioinformatics method analysis, this study provides a new perspective to explore the pathogenesis, gene regulatory networks and provide drug compounds as a reference for COVID-19 Myocarditis. It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.
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Affiliation(s)
- Fengjun Zhang
- College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China
| | - Cheng Yu
- Department of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, 250014, Shandong, China
| | - Wenchang Xu
- College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xiao Li
- Department of Cardiology, Shandong University of Traditional Chinese Medicine Affiliated Hospital, Jinan, 250014, Shandong, China
| | - Junchen Feng
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Hongshuo Shi
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jingrong Yang
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Qinhua Sun
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xianyi Cao
- First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Lin Zhang
- Department of Clinical Pharmacy, Shaoxing People’s Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China
| | - Min Peng
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China
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Liu G, Luo S, Lei Y, Wu J, Huang Z, Wang K, Yang P, Huang X. A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics. Bioengineered 2021; 12:5727-5738. [PMID: 34516309 PMCID: PMC8806918 DOI: 10.1080/21655979.2021.1968249] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 12/13/2022] Open
Abstract
Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected so far the largest MetS-associated peripheral blood high-throughput transcriptomics data and put forward a novel feature selection strategy by combining weighted gene co-expression network analysis, protein-protein interaction network analysis, LASSO regression and random forest approaches. Two gene modules and 51 hub genes as well as a 9-hub-gene signature associated with metabolic syndrome were identified. Then, based on this 9-hub-gene signature, we performed logistic analysis and subsequently established a web nomogram calculator for metabolic syndrome risk (https://xjtulgz.shinyapps.io/DynNomapp/). This 9-hub-gene signature showed excellent classification and calibration performance (AUC = 0.968 in training set, AUC = 0.883 in internal validation set, AUC = 0.861 in external validation set) as well as ideal potential clinical benefit.
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Affiliation(s)
- Guanzhi Liu
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Sen Luo
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yutian Lei
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jianhua Wu
- Department of Cardiovascular Medicine, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Zhuo Huang
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Kunzheng Wang
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Pei Yang
- Bone and Joint Surgery Center, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Xin Huang
- Department of Cardiovascular Medicine, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Integrated Bioinformatics Analysis to Identify Alternative Therapeutic Targets for Alzheimer's Disease: Insights from a Synaptic Machinery Perspective. J Mol Neurosci 2021; 72:273-286. [PMID: 34414562 DOI: 10.1007/s12031-021-01893-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/19/2021] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD), the most common type of dementia, is a serious neurodegenerative disease that has no cure yet, but whose symptoms can be alleviated with available medications. Therefore, early and accurate diagnosis of the disease and elucidation of the molecular mechanisms involved in the progression of pathogenesis are critically important. This study aimed to identify dysregulated miRNAs and their target mRNAs through the integrated analysis of miRNA and mRNA expression profiling in AD patients versus unaffected controls. Expression profiles in postmortem brain samples from AD patients and healthy individuals were extracted from the Gene Expression Omnibus database and were analyzed using bioinformatics approaches to identify gene ontologies, pathways, and networks. Finally, the module analysis of the PPI network and hub gene selection was carried out. A total of five differentially expressed miRNAs were extracted from the miRNA dataset, and 4312 differentially expressed mRNAs were obtained from the mRNA dataset. By comparing the DEGs and the putative targets of the altered miRNAs, 116 (3 upregulated and 113 downregulated) coordinated genes were determined. Also, six hub genes (SNAP25, GRIN2A, GRIN2B, DLG2, ATP2B2, and SCN2A) were identified by constructing a PPI network. The results of the present study provide insight into mechanisms such as synaptic machinery and neuronal communication underlying AD pathogenesis, specifically concerning miRNAs.
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