Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma
Abanti Bhattacharjya, Md Manowarul Islam, Md Ashraf Uddin, Md. Alamin, Talukder, AKM Azad, Sunil Aryal, Bikash Kumar Paul, Wahia Tasnim, Muhammad, Ali Abdulllah Almoyad, Mohammad Ali Moni

TL;DR
This study constructs gene regulatory networks for Hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma, identifying common therapeutic molecules through bioinformatics analysis of gene expression data.
Contribution
It introduces a novel approach to identify shared therapeutic targets for two related cancers using hub gene analysis and network topology methods.
Findings
Identified 10 hub genes with high interaction degrees
Suggested potential therapeutic molecules for both diseases
Demonstrated the utility of gene network analysis in drug discovery
Abstract
With the advent of Information technology, the Bioinformatics research field is becoming increasingly attractive to researchers and academicians. The recent development of various Bioinformatics toolkits has facilitated the rapid processing and analysis of vast quantities of biological data for human perception. Most studies focus on locating two connected diseases and making some observations to construct diverse gene regulatory interaction networks, a forerunner to general drug design for curing illness. For instance, Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. In this study, we select EGFR-mutated lung adenocarcinoma and Hypopharyngeal cancer by finding the Lung metastases in hypopharyngeal cancer. To conduct this study, we collect Mircorarray datasets from GEO (Gene Expression Omnibus), an online database controlled by NCBI.…
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Taxonomy
TopicsBioinformatics and Genomic Networks · Lung Cancer Treatments and Mutations · Gene expression and cancer classification
MethodsFocus
