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International Journal of Research and Scientific Innovation (IJRSI) |Volume X, Issue I, January 2023|ISSN 2321-2705

Computational Identification of Biomarker Signatures, Pathways and Regulators to Discover Therapeutic Target for Non-Small Cell Lung Cancer

Amina Rownaq1*, S. M. Shahinul Islam1, Samme Amena Tasmia2, Md. Selim Reza2 and Md. Nurul Haque Mollah2
1Plant Biotechnology and Genetic Engineering Lab, Institute of Biological Sciences, University of Rajshahi, Bangladesh.
2Bioinformatics Lab, Department of Statistics, University of Rajshahi, Bangladesh
*Correspondence Author

IJRISS Call for paper

Abstract
Background
Lung cancer is a critical health issue of human neoplasm in worldwide. Non-small cell lung cancer (NSCLC) is the most common lung cancer from malignant disease. This study is analyses to identify biomarkers for targeting systemic drugs based on systems biology in NSCLC. The aim of this study was to select the genes expressions and pathways to discover biomolecules at protein and RNA levels which could identify potential therapeutic targets.
Methods
Different statistical method: LIMMA, ANOVA, SAM and Kruskal Wallis (KW) were used to identify DEGs with significance from the transcriptome data which was obtained from the Gene Expression Omnibus (NCBI-GEO) dataset. By using Robust Multi-Array Average (RMA) expression measure DEGs were normalized and identified from the gene expression data set and it was applied in the “Affy” package of Bioconductor platform in R. Gene expression profiles were analyzed with genome-scale biomolecular networks (i,e., protein-protein interaction, DAVID, Kaplan-Meier Plot, molecular docking).
Results
Ten (10) hub proteins and four (4) transcription factors (TFs) were significant biomarkers as a potential drug target. Risk discrimination performance of the hub proteins- AURKB, CDK1, CDC20, MAD2L1, CCNB1, BUB1, CCNB2, AURKA, NDC80 and NUF2 were also evaluated. In the molecular docking simulation study, we are suggesting Lurbinectedin, Etopophos, Entrectinib, Imatinib, mesylate, and Irinotecanas candidate drugs that have high binding affinity scores with most of the key proteins. Among 10 hub proteins two were confirmed as novel and provided a prognostic model and suggested three candidate drugs.
Conclusion
Based on these molecular signatures and proposed drugs further experimental studies can continued. These findings not only demonstrate the diagnosis, but also provide prognostic markers and therapeutic targets for NSCLC.

Keywords: Differentially expressed genes, molecular signature, molecular pathway, non-small cell lung cancer, protein-protein interaction and reporter biomolecule

I. Introduction

Lung cancer is the second major human cancer in the world. Lung cancer deaths are 1.33% of total deaths according to the latest WHO data published in May 2014 in Bangladesh. Cancer-related death rates in Bangladesh were 7.5% in 2005 and assumed it will be 13% in 2030 calculated by International Agency for Research on Cancer. Smoking is the main risk factor of lung cancer, high air pollutions and alcohol are also harmful for lung (Alberg et al., 2013). Approximately 75% of all of lung cancers are non-small cell lung cancer, which is the most common type of lung tumor in the world (Jemal et al., 2007). Based on tumor histology conventional diagnosis of lung cancer is occurred. The main histological types of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Both sub-types of adenocarcinoma and squamous cell carcinoma are very dissimilar in DNA methylation, genetic mutations, transcriptome, proteome and biomarkers. Despite significant progress in the development of targeted therapy, the high mortality rate in lung cancer firmly emphasizes the need for prevention and efficient detection of lung