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A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates.
Chapola, Henrique; de Bastiani, Marco Antônio; Duarte, Marcelo Mendes; Freitas, Matheus Becker; Schuster, Jussara Severo; de Vargas, Daiani Machado; Klamt, Fábio.
  • Chapola H; Laboratory of Cellular Biochemistry, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS 90035-003, Brazil.
  • de Bastiani MA; Laboratory of Cellular Biochemistry, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS 90035-003, Brazil; Zimmer Lab, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (U
  • Duarte MM; Laboratory of Cellular Biochemistry, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS 90035-003, Brazil.
  • Freitas MB; Estacio College of Rio Grande do Sul (ESTACIO FARGS), Porto Alegre, RS 90020-060, Brazil.
  • Schuster JS; Estacio College of Rio Grande do Sul (ESTACIO FARGS), Porto Alegre, RS 90020-060, Brazil.
  • de Vargas DM; Laboratory of Cellular Biochemistry, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS 90035-003, Brazil. Electronic address: daianibio@yahoo.com.br.
  • Klamt F; Laboratory of Cellular Biochemistry, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS 90035-003, Brazil; Zimmer Lab, Biochemistry Department, Institute of Health Sciences (ICBS), Federal University of Rio Grande do Sul (U
Virus Res ; 326: 199053, 2023 03.
Article in English | MEDLINE | ID: covidwho-2211635
ABSTRACT
Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed significant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Virus Res Journal subject: Virology Year: 2023 Document Type: Article Affiliation country: J.virusres.2023.199053

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Virus Res Journal subject: Virology Year: 2023 Document Type: Article Affiliation country: J.virusres.2023.199053