0% Complete
صفحه اصلی
/
4th international edition and 13th Iranian Conference on Bioinformatics
Investigating hsa-miR-146b and Its Targets TRAF6 and IRAK1 In Gastric Cancer Using Bioinformatic Tools
نویسندگان :
Ali Nosrat
1
Vahid Asghariazar
2
Elham Safarzadeh
3
1- Cancer Immunology and Immunotherapy Research Center, Ardabil University of Medical Sciences, Ardabil, Iran.
2- Cancer Immunology and Immunotherapy Research Center, Ardabil University of Medical Sciences, Ardabil, Iran.
3- Cancer Immunology and Immunotherapy Research Center, Ardabil University of Medical Sciences, Ardabil, Iran.
کلمات کلیدی :
Gastric Cancer،hsa-miR-146b،TRAF6،IRAK1
چکیده :
Background: Gastric cancer is one of the leading causes of cancer-related mortality worldwide, often diagnosed at late stages with poor prognostic outcomes. Gastric cancer development is a multifactorial process with complicated interactions among genetic, environmental, and lifestyle factors (Morgan, Arnold et al. 2022). MicroRNAs (miRNAs) are small non-coding RNAs established as major regulators of gene expression involved in various biological processes, such as cell proliferation, differentiation, and apoptosis (Statello, Guo et al. 2021). Specific miRNAs, like hsa-mir-146b, have been identified in gastric carcinoma as key players in controlling inflammatory pathways and tumor progression (Azari, Nazari et al. 2023). Methods: Clinical data and expression levels of hsa-miR-146b in gastric cancer patients were obtained from The Cancer Genome Atlas (TCGA) based on the following selection criteria including basic clinical information of sample types (normal and primary tumor), individual cancer stage, tumor histology and nodal metastasis status. To identify potential target genes of hsa-miR-146b, we utilized TargetScan and miRDB. From the list of predicted target genes, the 10 genes with the highest target scores were selected for further analysis (Target score>95). To investigate the interactions and relationships between hsa-miR-146b target genes, we utilized STRING. Data for TRAF6 and IRAK1 were retrieved from TCGA Stomach Adenocarcinoma (STAD). Cell line data were obtained from DepMap database. Results: Our results demonstrate that the expression level of hsa-miR-146b is increased in STAD in comparison with normal tissue. This increase was discovered in different nodal metastasis status (N0-N3), different GC stages (1-4) and in seven different histological subtypes. TargetScan and miRDB identified TRAF6 and IRAK1 as high-confidence targets of hsa-miR-146b, with scores of 100 and 99, respectively. STRING network analysis further highlighted a strong functional relationship between TRAF6 and IRAK1. Additionally, analysis of TCGA Stomach Adenocarcinoma (STAD) data revealed altered expression of TRAF6 and IRAK1 in gastric cancer tissues compared to normal gastric tissues. Data from the DepMap database confirmed consistent expression of both genes in gastric cancer cell lines, with variability across lines, highlighting their active roles in gastric cancer biology. Conclusion: Our investigation places significant importance on hsa-miR-146b in the development of gastric cancer and identifies that its potential regulatory role for two high target score genes, TRAF6 and IRAK1, was determined by bioinformatic analyses. The findings suggest that hsa-miR-146b exhibits altered expression levels in gastric cancer, potentially influencing key signaling pathways mediated by TRAF6 and IRAK1, which are critical components of the NF-κB pathway and immune response regulation (Wang, Wu et al. 2020). These findings provide insights into the molecular mechanisms underlying gastric cancer progression and suggest that hsa-miR-146b and its target genes might act as promising biomarkers or therapeutic targets for managing gastric cancer.
لیست مقالات
لیست مقالات بایگانی شده
Phylogenetic and In Silico Analysis of SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) Gene Family in Crops
Amin Nasirpour - Abbasali Emamjomeh - Nasibe Chenarani
Investigation of Missense Mutations in the SHBG Gene: Bioinformatic Analysis and Pathogenesis Prediction in binding and regulating the bioavailability of sex hormones
Mohammad Amin Shohadaee - Helena Choobineh - Mehri Khatami
A New LDA-based Genetic Algorithm for Feature Selection and Classification in Gene Expression Data Analysis
Parisa Pouyamanesh - Mahdi Vasighi
Comprehensive Multi-Omics Analysis Reveals NPC2 and ITGAV Genes as Potential Prognostic Biomarkers in Gastrointestinal Cancers
Mohammad Reza Zabihi - Moein Piroozkhah - Pooya Jalali - Zahra Salehi
Morphine pathway analysis with bioinformatics
Nazila Bagheri - Alireza Tarinejad - Mohammad Majidi - Karim Hassanpour
Predicting Anticancer Drug Repurposing Candidates using Knowledge Graphs
Marzieh Khodadadi AghGhaleh - Rooholah Abedian - Reza Zarghami - Sajjad Gharaghani
Identification of Driver Genes in Glioblastoma Based on Single-Cell Gene Expression Data Using Integrated Pseudotime and Phylogenetic Analysis
Fateme Mirza-Abolhassani - Sobhan Ahmadian Moghadam - Fatemeh Zare-Mirakabad - Kaveh Kavousi
BiogenExplorer: A Robust Solution for Rapid Gene Presence Detection and Allelic Diversity Analysis in large Genomic Datasets
Mohammadreza Najafi Disfani - Danial Ghofrani - Mahdiar Mansouri - Parastoo Saniee
Enhancing Predictive Accuracy of CRISPR-Cas9 on-target efficiency using Deep Learning and Active Learning Optimization for Small Datasets
Masoud Mahdavifar - Fateme Zaremirakabad
Astrocyte-Mediated Regulation of Neurogenesis in the Anterior Hippocampus of Alzheimer's Disease Patients
Sarvenaz Sahebekhtiari - Morteza Hadizadeh - Hamid Forootanfar - Masoud Rezaei - Alieh Ameri - Mojtaba Shakibaie
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.4.1