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Identification of potential regulatory mechanisms and therapeutic targets for lung cancer.
Priya, Anjali; Dashti, Mohammed; Thanaraj, Thangavel Alphonse; Irshad, Mohammad; Singh, Virendra; Tandon, Ravi; Mehrotra, Rekha; Singh, Alok Kumar; Mago, Payal; Singh, Vishal; Malik, Md Zubbair; Ray, Ashwini Kumar.
Afiliação
  • Priya A; Department of Environmental Studies, University of Delhi, New Delhi, India.
  • Dashti M; School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
  • Thanaraj TA; Dasman Diabetes Institute, Kuwait City, Kuwait.
  • Irshad M; Dasman Diabetes Institute, Kuwait City, Kuwait.
  • Singh V; Dasman Diabetes Institute, Kuwait City, Kuwait.
  • Tandon R; School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
  • Mehrotra R; School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
  • Singh AK; Department of Microbiology, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, New Delhi, India.
  • Mago P; Department of Zoology, Ramjas College, University of Delhi, New Delhi, India.
  • Singh V; Department of Botany, Shri Aurobindo College, University of Delhi, New Delhi, India to Campus Of Open Learning, University of Delhi, New Delhi, India.
  • Malik MZ; Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, New Delhi, India.
  • Ray AK; Delhi School of Public Health, Institution of Eminence, University of Delhi, New Delhi, India.
J Biomol Struct Dyn ; : 1-18, 2024 Feb 06.
Article em En | MEDLINE | ID: mdl-38319037
ABSTRACT
Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article