CDK1 and HSP90AA1 Appear as the Novel Regulatory Genes in Non-Small Cell Lung Cancer: A Bioinformatics Approach

Nirjhar Bhattacharyya; Samriddhi Gupta; Shubham Sharma; Aman Soni; Sali Abubaker Bagabir; Malini Bhattacharyya; Atreyee Mukherjee; Atiah H Almalki; Mustfa F Alkhanani; Shafiul Haque; Ashwini Kumar Ray; Md Zubbair Malik

doi:10.3390/jpm12030393

CDK1 and HSP90AA1 Appear as the Novel Regulatory Genes in Non-Small Cell Lung Cancer: A Bioinformatics Approach

J Pers Med. 2022 Mar 4;12(3):393. doi: 10.3390/jpm12030393.

Authors

Affiliations

¹ School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India.
² Department of Biochemistry, University of Hyderabad, Hyderabad 500046, India.
³ School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
⁴ Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, Jazan University, Jazan 45142, Saudi Arabia.
⁵ Department of Environmental Plant Biology, Hemvati Nandan Bahuguna, Garhwal Central University, Srinagar 246174, India.
⁶ Department of Life Sciences, Presidency University, Kolkata 700073, India.
⁷ Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, Taif 21944, Saudi Arabia.
⁸ Addiction and Neuroscience Research Unit, College of Pharmacy, Taif University, Taif 21944, Saudi Arabia.
⁹ Emergency Service Department, College of Applied Sciences, Al Maarefa University, Riyadh 11597, Saudi Arabia.
¹⁰ Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan 45142, Saudi Arabia.
¹¹ Faculty of Medicine, Bursa Uludağ University, Görükle Campus, Bursa 16059, Turkey.
¹² Department of Environmental Studies, University Delhi, New Delhi 110007, India.

Abstract

Lung cancer is one of the most invasive cancers affecting over a million of the population. Non-small cell lung cancer (NSCLC) constitutes up to 85% of all lung cancer cases, and therefore, it is essential to identify predictive biomarkers of NSCLC for therapeutic purposes. Here we use a network theoretical approach to investigate the complex behavior of the NSCLC gene-regulatory interactions. We have used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, and GSE31210 and meta-analyzed them to find differentially expressed genes (DEGs) and further constructed a protein-protein interaction (PPI) network. We analyzed its topological properties and identified significant modules of the PPI network using cytoscape network analyzer and MCODE plug-in. From the PPI network, top ten genes of each of the six topological properties like closeness centrality, maximal clique centrality (MCC), Maximum Neighborhood Component (MNC), radiality, EPC (Edge Percolated Component) and bottleneck were considered for key regulator identification. We further compared them with top ten hub genes (those with the highest degrees) to find key regulator (KR) genes. We found that two genes, CDK1 and HSP90AA1, were common in the analysis suggesting a significant regulatory role of CDK1 and HSP90AA1 in non-small cell lung cancer. Our study using a network theoretical approach, as a summary, suggests CDK1 and HSP90AA1 as key regulator genes in complex NSCLC network.

Keywords: differentially expressed genes; key regulator; non-small cell lung cancer; protein–protein interaction.

Grants and funding

R.12014/01/2018-HR, FTS No. 3146887/Ministry of Health and Family Welfare