Identification of potential prognostic biomarkers in lung adenocarcinoma: A networkbased approach
- سال انتشار: 1402
- محل انتشار: دوازدهمین همایش ملی و سومین همایش بین المللی بیوانفورماتیک
- کد COI اختصاصی: IBIS12_189
- زبان مقاله: انگلیسی
- تعداد مشاهده: 120
نویسندگان
Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
Genetics Department, Faculty of Science, Shahrekord University, Shahrekord, Iran
Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran- Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
چکیده
Non-small cell lung cancer (NSCLC), one of the most common malignant tumor globallywith an extremely high mortality rate, is classified into adenocarcinoma, squamous cell carcinoma, andlarge cell carcinoma (۱, ۲). Adenocarcinoma is the most common type among these three (۳). Longtermsurvival remains low because most patients are diagnosed late. Therefore, it is vital to understandthe molecular mechanisms and identify biomarkers for prognosis and early detection of patients.Two gene expression profiles related to lung adenocarcinoma (GSE۳۲۸۶۳ and GSE۷۵۰۳۷) wereobtained from gene expression omnibus (GEO). To identify differentially expressed genes (DEGs)between tumor and normal samples, GEO۲R was used. Enrichr was employed for enrichment analysis.Using Enrichr, GO terms and KEGG pathway enrichment analysis was accomplished. Moreover, toreconstruct the protein-protein interaction (PPI) network, STRING was used. Cytoscape ۳.۹.۱ wasutilized to visualize and analyze the network of DEGs. Using the CytoHubba plugin and based onbetweenness, the top ۱۵ hub genes were selected. Hub genes were validated using GEPIA.Considering GO biological process, DEGs are associated with “Cellular Response To CytokineStimulus”. GO Molecular function revealed the relationship of DEGs with “Calcium Ion Binding”. GOcellular components showed that DEGs are related to “Collagen-Containing Extracellular Matrix”.KEGG pathway enrichment analysis revealed the relationship of DEGs with “Complement andcoagulation cascades”. Based on betweenness centrality, GAPDH, IL۶, IL۱B, CDH۱, UBB, CD۴۴,JUN, ERBB۲, CAV۱, PPARG, PECAM۱, CDH۵, CD۳۴, MMP۹, and COL۱A۱ were considered as hubgenes. By performing overall survival analysis using GEPIA, we observed that GAPDH, and PECAM۱have a reverse relationship with the survival of lung adenocarcinoma patients.By analyzing microarray data and using a network-based approach, we identified GAPDH, andPECAM۱ as potential prognostic biomarkers in lung adenocarcinoma.کلیدواژه ها
Lung Adenocarcinoma; Differentially Expressed Genes; DEGs; Hub Genesمقالات مرتبط جدید
- Resource Optimization in Large Language Model Deployment Using Reinforcement Learning and Adaptive Software Engineering
- کاربرد یادگیری ماشین در پیشبینی خطاهای نرم افزاری در مراحل اولیه توسعه سیستم های پیچیده
- A review of the application of silver nanoparticles in improving the performance of ultrathin silicon solar cells
- نگرشی برنانو و نقش آن در تصفیه آب در نیروگاه های برق
- The Biomechanical Effect of Knee Flexion Angles on Squat Lifting with a Flat Back Position
اطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.