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Muneeb Hassan M, Ameeq M, Jamal F, Tahir MH, Mendy JT. Prevalence of covid-19 among patients with chronic obstructive pulmonary disease and tuberculosis. Ann Med 2023; 55:285-291. [PMID: 36594409 PMCID: PMC9815254 DOI: 10.1080/07853890.2022.2160491] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND The exhaustive information about non-communicable diseases associated with COVID-19 and severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) are getting easier to find in the literature. However, there is a lack of knowledge regarding tuberculosis (TB) and chronic obstructed pulmonary disease (COPD), with numerous infections in COVID-19 patients. OBJECTIVES Priority is placed on determining the patient's prognosis based on the presence or absence of TB and COPD. Additionally, a comparison is made between the risk of death and the likelihood of recovery in terms of time in COVID-19 patients who have either COPD or TB. METHODOLOGY At the DHQ Hospital in Muzaffargarh, Punjab, Pakistan, 498 COVID-19 patients with TB and COPD were studied retrospectively. The duration of study started in February 2022 and concluded in August 2022. The Kaplan-Meier curves described time-to-death and time-to-recovery stratified by TB and COPD status. The Wilcoxon test compared the survival rates of people with TB and COPD in two matched paired groups and their status differences with their standard of living. RESULTS The risk of death in COVID-19 patients with TB was 1.476 times higher than in those without (95% CI: 0.949-2.295). The recovery risk in COVID-19 patients with TB was 0.677 times lower than in those without (95% CI: 0.436-1.054). Similarly, patients with TB had a significantly shorter time to death (p=.001) and longer time to recovery (p=.001). CONCLUSIONS According to the findings, the most significant contributor to an increased risk of morbidity and mortality in TB and COPD patients was the COVID-19.KEY MESSAGESSARS-Cov-19 is a new challenge for the universe in terms of prevention and treatment for people with tuberculosis and chronic obstructive pulmonary disease, among other diseases.Propensity score matching to control for potential biases.Compared to hospitalized patients with and without (TB and COPD) had an equivalently higher mortality rate.
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Affiliation(s)
| | - Muhammad Ameeq
- Department of Statistics, The Islamia University, Bahawalpur, Pakistan
| | - Farrukh Jamal
- Department of Statistics, The Islamia University, Bahawalpur, Pakistan
| | - Muhammad H Tahir
- Department of Statistics, The Islamia University, Bahawalpur, Pakistan
| | - John T Mendy
- Department of Mathematics, School of Arts and Science, University of The Gambia, Serekunda, The Gambia
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Zanjirband M, Baharlooie M, Safaeinejad Z, Nasr-Esfahani MH. Transcriptomic screening to identify hub genes and drug signatures for PCOS based on RNA-Seq data in granulosa cells. Comput Biol Med 2023; 154:106601. [PMID: 36738709 DOI: 10.1016/j.compbiomed.2023.106601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/14/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND Polycystic ovary syndrome (PCOS) is one of the most incident reproductive diseases, and remains the main cause of female infertility. Granulosa cells play a critical role in normal follicle development and steroid hormones synthesis. In spite of extensive research, no sole medication has been approved by FDA to treat PCOS. This study aimed to investigate the novel therapeutics targets in PCOS, focusing on granulosa cells transcriptome functional analysis with a drug repositioning approach. METHODS PCOS microarray and RNA-Seq datasets in granulosa cells were screened and reanalyzed. KEGG pathway enrichment and interaction network analyses were performed and followed by a set of drug signature screening and Poly-pharmacology survey. RESULTS 545 deregulated genes were identified via filters including padj < 0.05 and |log2FC| > 1. Amongst the top 15 KEGG pathways significantly enriched, metabolism of xenobiotics by cytochrome P450, steroid hormone biosynthesis and ovarian steroidogenesis were observed. The Protein-Protein Interaction network identified 18 hub genes amongst this set. Interestingly, most candidate drug signatures have been introduced by databases are either FDA approved or entered into clinical trials, including melatonin, resveratrol and raloxifene. Investigational or experimental introduced drugs obey rules of drug-likeness with almost safe and acceptable ADMET properties. Notably, 21 top target genes of the final drug set were also included in the granulosa significant differentially expressed genes. CONCLUSION Results of the current study represent approved, investigational and experimental drug signatures according to the differentially expressed genes in granulosa cells with supported literature reviews. This data might be useful for researchers and clinicians to pave the way for better management of PCOS.
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Affiliation(s)
- M Zanjirband
- Department of Animal Biotechnology, Reproductive Biomedicine Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran.
| | - M Baharlooie
- Department of Animal Biotechnology, Reproductive Biomedicine Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran; Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran.
| | - Z Safaeinejad
- Department of Animal Biotechnology, Reproductive Biomedicine Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran.
| | - M H Nasr-Esfahani
- Department of Animal Biotechnology, Reproductive Biomedicine Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran.
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Identification of Potential Key Genes and Prognostic Biomarkers of Lung Cancer Based on Bioinformatics. BIOMED RESEARCH INTERNATIONAL 2023; 2023:2152432. [PMID: 36714024 PMCID: PMC9876670 DOI: 10.1155/2023/2152432] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/31/2022] [Accepted: 11/17/2022] [Indexed: 01/19/2023]
Abstract
Objective To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment. Methods Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein-protein interaction (PPI) network was constructed by STRING online software for further study, and the core genes were determined by Cytoscape software and KEGG pathway enrichment analysis. The clustering heat map was drawn by Excel software to verify its accuracy. In addition, we used the University of Alabama at Birmingham Cancer (UALCAN) website to analyze the expression of core genes in P53 mutation status, confirmed the expression of crucial core genes in lung cancer tissues with Gene Expression Profiling Interactive Analysis (GEPIA) and GEPIA2 online software, and evaluated their prognostic value in lung cancer patients with the Kaplan-Meier online plotter tool. Results CHEK1, CCNB1, CCNB2, and CDK1 were selected. The expression levels of these four genes in lung cancer tissues were significantly higher than those in normal tissues. Their increased expression was negatively correlated with lung cancer patients (including LUAD and LUSC) prognosis and survival rate. Conclusion CHEK1, CCNB1, CCNB2, and CDK1 are the critical core genes of lung cancer and are highly expressed in lung cancer. They are negatively correlated with the prognosis of lung cancer patients (including LUAD and LUSC) and closely related to the formation and prediction of lung cancer. They are valuable predictors and may be predictive biomarkers of lung cancer.
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Islam MR, Alam MK, Paul BK, Koundal D, Zaguia A, Ahmed K. Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach. BIOMED RESEARCH INTERNATIONAL 2022; 2022:5908402. [PMID: 35071597 PMCID: PMC8769846 DOI: 10.1155/2022/5908402] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/10/2021] [Accepted: 12/23/2021] [Indexed: 12/24/2022]
Abstract
Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC.
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Affiliation(s)
- Md. Rakibul Islam
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka 1342, Bangladesh
| | - Mohammad Khursheed Alam
- Preventive Dentistry Department, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia
- Center for Transdisciplinary Research (CFTR), Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
- Department of Public Health, Faculty of Allied Health Sciences, Daffodil International University, Dhaka, Bangladesh
| | - Bikash Kumar Paul
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka 1342, Bangladesh
- Group of Bio-Photomatix, Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
| | - Deepika Koundal
- Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand 248007, India
| | - Atef Zaguia
- Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Kawsar Ahmed
- Group of Bio-Photomatix, Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
- Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, Canada S7N 5A9
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Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer. J Pers Med 2021; 11:jpm11050363. [PMID: 33946372 PMCID: PMC8147030 DOI: 10.3390/jpm11050363] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/13/2021] [Accepted: 04/19/2021] [Indexed: 12/31/2022] Open
Abstract
Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.
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Islam R, Ahmed L, Paul BK, Ahmed K, Bhuiyan T, Moni MA. Identification of molecular biomarkers and pathways of NSCLC: insights from a systems biomedicine perspective. J Genet Eng Biotechnol 2021; 19:43. [PMID: 33742334 PMCID: PMC7979844 DOI: 10.1186/s43141-021-00134-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 02/14/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Worldwide, more than 80% of identified lung cancer cases are associated to the non-small cell lung cancer (NSCLC). We used microarray gene expression dataset GSE10245 to identify key biomarkers and associated pathways in NSCLC. RESULTS To collect Differentially Expressed Genes (DEGs) from the dataset GSE10245, we applied the R statistical language. Functional analysis was completed using the Database for Annotation Visualization and Integrated Discovery (DAVID) online repository. The DifferentialNet database was used to construct Protein-protein interaction (PPI) network and visualized it with the Cytoscape software. Using the Molecular Complex Detection (MCODE) method, we identify clusters from the constructed PPI network. Finally, survival analysis was performed to acquire the overall survival (OS) values of the key genes. One thousand eighty two DEGs were unveiled after applying statistical criterion. Functional analysis showed that overexpressed DEGs were greatly involved with epidermis development and keratinocyte differentiation; the under-expressed DEGs were principally associated with the positive regulation of nitric oxide biosynthetic process and signal transduction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway investigation explored that the overexpressed DEGs were highly involved with the cell cycle; the under-expressed DEGs were involved with cell adhesion molecules. The PPI network was constructed with 474 nodes and 2233 connections. CONCLUSIONS Using the connectivity method, 12 genes were considered as hub genes. Survival analysis showed worse OS value for SFN, DSP, and PHGDH. Outcomes indicate that Stratifin may play a crucial role in the development of NSCLC.
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Affiliation(s)
- Rakibul Islam
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh
| | - Liton Ahmed
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh
| | - Bikash Kumar Paul
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh.,Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail, 1902, Bangladesh.,Group of Bio-photomatiχ, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh
| | - Kawsar Ahmed
- Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail, 1902, Bangladesh. .,Group of Bio-photomatiχ, Mawlana Bhashani Science and Technology University (MBSTU), Santosh, Tangail, 1902, Bangladesh.
| | - Touhid Bhuiyan
- Department of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh
| | - Mohammad Ali Moni
- WHO Collaborating Centre on eHealth, School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, Australia
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Yumiceba V, López-Cortés A, Pérez-Villa A, Yumiseba I, Guerrero S, García-Cárdenas JM, Armendáriz-Castillo I, Guevara-Ramírez P, Leone PE, Zambrano AK, Paz-y-Miño C. Oncology and Pharmacogenomics Insights in Polycystic Ovary Syndrome: An Integrative Analysis. Front Endocrinol (Lausanne) 2020; 11:585130. [PMID: 33329391 PMCID: PMC7729301 DOI: 10.3389/fendo.2020.585130] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 10/05/2020] [Indexed: 12/12/2022] Open
Abstract
Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. Epidemiological findings revealed that women with PCOS are prone to develop certain cancer types due to their shared metabolic and endocrine abnormalities. However, the mechanism that relates PCOS and oncogenesis has not been addressed. Herein, in this review article the genomic status, transcriptional and protein profiles of 264 strongly PCOS related genes (PRG) were evaluated in endometrial cancer (EC), ovarian cancer (OV) and breast cancer (BC) exploring oncogenic databases. The genomic alterations of PRG were significantly higher when compared with a set of non-diseases genes in all cancer types. PTEN had the highest number of mutations in EC, TP53, in OC, and FSHR, in BC. Based on clinical data, women older than 50 years and Black or African American females carried the highest ratio of genomic alterations among all cancer types. The most altered signaling pathways were p53 in EC and OC, while Fc epsilon RI in BC. After evaluating PRG in normal and cancer tissue, downregulation of the differentially expressed genes was a common feature. Less than 30 proteins were up and downregulated in all cancer contexts. We identified 36 highly altered genes, among them 10 were shared between the three cancer types analyzed, which are involved in the cell proliferation regulation, response to hormone and to endogenous stimulus. Despite limited PCOS pharmacogenomics studies, 10 SNPs are reported to be associated with drug response. All were missense mutations, except for rs8111699, an intronic variant characterized as a regulatory element and presumably binding site for transcription factors. In conclusion, in silico analysis revealed key genes that might participate in PCOS and oncogenesis, which could aid in early cancer diagnosis. Pharmacogenomics efforts have implicated SNPs in drug response, yet still remain to be found.
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Affiliation(s)
- Verónica Yumiceba
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Andrés López-Cortés
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
- Latin American Network for the Implementation and Validation of Clinical Pharmacogenomics Guidelines (RELIVAF-CYTED), Madrid, Spain
| | - Andy Pérez-Villa
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Iván Yumiseba
- Centro de Atención Ambulatorio, Hospital del Día El Batán, Instituto Ecuatoriano de Seguridad Social (IESS), Quito, Ecuador
| | - Santiago Guerrero
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Jennyfer M. García-Cárdenas
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Isaac Armendáriz-Castillo
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Patricia Guevara-Ramírez
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Paola E. Leone
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - Ana Karina Zambrano
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
| | - César Paz-y-Miño
- Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador
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