Investigation of key signaling pathways and appropriate diagnostic biomarkers selection between non-invasive to invasive stages in pancreatic cancer: a computational observation
Authors: Javanshir Hamid Taghvaei ,   Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran,   Department of Biology, School of Basic Science, Science and Research Branch, Islamic Azad University, Tehran, Iran, Malekraeisi Mohammad Amin ,   Student Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Iran, Ebrahimi Seyedeh Sanaz Seyed ,   Kurdistan Immunology & Haematology Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran, Bereimipour Ahmad ,   Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran,   Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran, Kashani Sara Fakharian ,   Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran,   Medical Genomics Research Center, Tehran Medical Sciences Islamic Azad University, Tehran, Iran, Bostaki Amir Abbas ,   Medical Genomics Research Center, Tehran Medical Sciences Islamic Azad University, Tehran, Iran, Mahmoodzadeh Habibollah ,   Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran,   Habibollah Mahmoodzadeh, Cancer Research Center, Tehran University of Medical Sciences, Tehran, Iran. E-mail: hmahmoodzadeh@tums.ac.ir, Nayernia Karim ,   International Center for Personalized Medicine, Düsseldorf, Germany
Published: November 2022

Pancreatic cancer is the seventh most lethal cancer in the world. Despite its moderate prevalence, the 5-year survival rate of patients with pancreatic cancer is about 10%. Despite different therapeutic and diagnostic strategies for pancreatic cancer, this cancer is still uncontrollable in the invasive stage and can invade various body organs and cause death. Early detection for pancreatic cancer can be an excellent solution to manage treatment better and increase patients' survival rates. This study aimed to find diagnostic biomarkers between non-invasive to invasive stages of pancreatic cancer in the extracellular matrix to facilitate the early diagnosis of this cancer. Using bioinformatics analysis, we selected the appropriate datasets between non-invasive and invasive pancreatic cancer stages and categorized their genes. Then, we charted and confirmed the signaling pathways, gene ontology, protein relationships, and protein expression levels in the human samples using bioinformatics databases. Cell adhesion and hypoxia signaling pathways were observed in up-regulated genes, different phases of the cell cycle, and metabolic signaling pathways with down-regulated genes between non-invasive and invasive pancreatic cancer stages. For proper diagnostic biomarkers selection, the overexpressed genes that released protein into the extracellular matrix were examined in more detail, with 62 proteins selected and SPARC, THBS2, COL11A1, COL1A1, COL1A2, COL3A1, SERPINH1, PLAU proteins chosen. Bioinformatics analysis can more accurately assess the relationship between molecular mechanisms and key actors in pancreatic cancer invasion and metastasis to facilitate early detection and improve treatment management for patients with pancreatic cancer.