👤 Majid Rezaei Tavirani

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

The current study aimed to determine crucial genes targeted by toxin-A through network analysis. The significant differentially expressed genes (DEGs) of human intestinal Caco-2 cells treated by toxin-A versus control were retrieved from gene expression omnibus (GEO). The queried DEGs were analyzed using by protein-protein interaction (PPI) network analysis through STRING database and Cytoscape software v.3.7.2. Among 157 significant DEGs, JUN, VEGFA, CDKN1A, ATF3, SNAI1, DUSP1, HSPB1, MCL1, KLF4, FOSL1, HSPA1A, and SQSTM1 were determined as hubs and JUN, DUSP1, DUSP5, EZR, MAP1LC3B, and SQSTM1 were highlighted as bottlenecks. JUN, DUSP1, and SQSTM1 are possible drug targets to prevent and treat Show less

Thyroid carcinomas have comprised the fastest rising incidence of cancer in the past decade. Currently, the diagnosis of thyroid tumors is performed by the fine-needle aspiration biopsy (FNAB) method, which still holds some challenges and limitations, mostly in discriminating malignant and benign lesions. Therefore, the development of molecular markers to distinguish between these lesion types are in progress. A 2D-PAGE separation of proteins was performed followed by tandem mass spectrometry with the aim of discovering potential serum protein markers for papillary thyroid carcinoma and multinodular goiter. Protein-protein interaction network analysis revealed the most important pathways involved in the progression of papillary thyroid cancer. The enzyme-linked immunosorbent assay method was used to confirm a part of the results. The significantly altered proteins included C3, C4A, GC, HP, TTR, APOA4, APOH, ORM2, KRT10, AHSG, IGKV3-20, and IGKC. We also confirmed that increased complement component 3 and decreased apolipoprotein A4 occurred in papillary thyroid cancer. Network investigations demonstrated that complement activation cascades and PPAR signaling might play a role in the pathogenesis of thyroid cancer. The results demonstrated that serum proteomics could serve as a viable method for proposing novel potential markers for thyroid tumors. Surely, further research must be performed in larger cohorts to validate the results. Show less

Identification of crucial genes and possible biomarkers which are involved in Barrett's esophagus (BE) disease was aim of this study. BE is diagnosed by endoscopy and biopsy and is characterized by esophageal columnar metaplastic epithelium. BE can convert into dysplasia that finally results cancer condition. Gene expression profiles of BE and normal gastric cardia which are characterized by GSE34619 and GPL6244 platform (1) were retrieved from gene expression omnibus (GEO). The significant differentially expressed genes (DEGs) were analyzed via protein-protein interaction network (PPI) analysis. The nodes of network were enriched via gene ontology (GO) to find biological terms. Action map of network elements was provided. Among 250 top DEGs, 100 ones were included in PPI network and KIT, CFTR, IMPDH2, MYB, FLT1, ATP4A, and CPS1 were recognized as prominent genes related to BE. Seven amino acids including arginine, alanine, aspartate, glutamate, valine, leucine and isoleucine which are related to BE were highlighted. In conclusion five central DEGs; KIT, CFTR, IMPDH2, MYB, and FLT1 were proposed as possible biomarkers for BE. However, validation and more experimental information is require to finalize the findings. Show less