{"title":"Identification of key hub genes in pancreatic ductal adenocarcinoma: an integrative bioinformatics study.","authors":"Kankana Bhattacharjee, Avik Sengupta, Rahul Kumar, Aryya Ghosh","doi":"10.3389/fbinf.2025.1536783","DOIUrl":null,"url":null,"abstract":"<p><p>Pancreatic Ductal Adenocarcinoma (PDAC) poses a significant health threat characterized by poor clinical outcomes, largely attributable to late detection, chemotherapy resistance, and the absence of tailored therapies. Despite progress in surgical, radiation, and chemotherapy treatments, 80% of PDAC patients do not benefit optimally from systemic therapy, often due to asymptomatic presentation or disease regression upon diagnosis. The disease's progression is influenced by complex interactions involving immunological, genetic, and environmental factors, among others. However, the precise molecular mechanisms underlying PDAC remain incompletely understood. A major challenge in elucidating PDAC's origins lies in deciphering the genetic variations governing its network. PDAC exhibits heterogeneity, manifesting diverse genetic compositions, cellular attributes, and behaviors across patients and within tumors. This diversity complicates diagnosis, treatment strategies, and prognostication. Identification of \"Differentially Expressed Genes\" (DEGs) between PDAC and healthy controls is vital for addressing these challenges. These DEGs serve as the foundation for constructing the PDAC protein interaction network, with their network properties being assessed for further insights. Our analysis revealed five key hub genes (KHGs): <i>EGF, SRC, SDC1, ICAM1 and CEACAM5</i>. The KHGs were predominantly enriched in pathways such as: ErbB signaling pathway, Rap1 signaling pathway, etc. Acknowledging the therapeutic promise and biomarker importance of PDAC KHGs, we have also pinpointed approved medications for the identified key genes. Nevertheless, it is crucial to conduct experimental validation on KHGs to confirm their effectiveness within the PDAC context. Overall, this study identified potential key hub genes implicated in the progression of PDAC, offering significant guidance for personalized clinical decision-making and molecular-targeted therapy for PDAC patients.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1536783"},"PeriodicalIF":2.8000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985535/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fbinf.2025.1536783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Pancreatic Ductal Adenocarcinoma (PDAC) poses a significant health threat characterized by poor clinical outcomes, largely attributable to late detection, chemotherapy resistance, and the absence of tailored therapies. Despite progress in surgical, radiation, and chemotherapy treatments, 80% of PDAC patients do not benefit optimally from systemic therapy, often due to asymptomatic presentation or disease regression upon diagnosis. The disease's progression is influenced by complex interactions involving immunological, genetic, and environmental factors, among others. However, the precise molecular mechanisms underlying PDAC remain incompletely understood. A major challenge in elucidating PDAC's origins lies in deciphering the genetic variations governing its network. PDAC exhibits heterogeneity, manifesting diverse genetic compositions, cellular attributes, and behaviors across patients and within tumors. This diversity complicates diagnosis, treatment strategies, and prognostication. Identification of "Differentially Expressed Genes" (DEGs) between PDAC and healthy controls is vital for addressing these challenges. These DEGs serve as the foundation for constructing the PDAC protein interaction network, with their network properties being assessed for further insights. Our analysis revealed five key hub genes (KHGs): EGF, SRC, SDC1, ICAM1 and CEACAM5. The KHGs were predominantly enriched in pathways such as: ErbB signaling pathway, Rap1 signaling pathway, etc. Acknowledging the therapeutic promise and biomarker importance of PDAC KHGs, we have also pinpointed approved medications for the identified key genes. Nevertheless, it is crucial to conduct experimental validation on KHGs to confirm their effectiveness within the PDAC context. Overall, this study identified potential key hub genes implicated in the progression of PDAC, offering significant guidance for personalized clinical decision-making and molecular-targeted therapy for PDAC patients.