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Stage analysis of pancreatic ductal adenocarcinoma via network analysis.
Bahadorimonfared, Ayad; Farahani, Masoumeh; Rezaei Tavirani, Mostafa; Razzaghi, Zahra; Arjmand, Babak; Rezaei, Mitra; Nikzamir, Abdolrahim; Ehsani Ardakani, Mohammad Javad; Mansouri, Vahid.
Afiliación
  • Bahadorimonfared A; Department of Health & Community Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Farahani M; Skin Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Rezaei Tavirani M; Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Razzaghi Z; Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Arjmand B; Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
  • Rezaei M; Iranian Cancer Control Center (MACSA), Tehran, Iran.
  • Nikzamir A; Genomic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Ehsani Ardakani MJ; Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Mansouri V; Celiac Disease and Gluten Related Disorders Research Center, Research Institute for Gastroenterology and Liver Disease, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Gastroenterol Hepatol Bed Bench ; 17(3): 297-3030, 2024.
Article en En | MEDLINE | ID: mdl-39308540
ABSTRACT

Aim:

This study aimed to introduce a biomarker panel to detect pancreatic ductal adenocarcinoma (PDAC) in the early stage, and also differentiate of stages from each other.

Background:

PDAC is a lethal cancer with poor prognosis and overall survival.

Methods:

Gene expression profiles of PDAC patients were extracted from the Gene Expression Omnibus (GEO) database. The genes that were significantly differentially expressed (DEGs) for Stages I, II, and III in comparison to the healthy controls were identified. The determined DEGs were assessed via protein-protein interaction (PPI) network analysis, and the hub-bottleneck nodes of analyzed networks were introduced.

Results:

A number of 140, 874, and 1519 significant DEGs were evaluated via PPI network analysis. A biomarker panel including ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 is presented as a biomarker panel to detect PDAC in the early stage. Two biomarker panels are suggested to recognize other stages of illness.

Conclusion:

It can be concluded that ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 and also FN1, HSP90AA1, LOX, ANXA5, SERPINE1, and WWP2 beside GAPDH, AKT1, EGF, CASP3 are suitable sets of gene to separate stages of PDAC.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Gastroenterol Hepatol Bed Bench Año: 2024 Tipo del documento: Article País de afiliación: Irán

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Gastroenterol Hepatol Bed Bench Año: 2024 Tipo del documento: Article País de afiliación: Irán