Identification of Biomarkers and enriched pathways involved in lung cancer using statistical techniques

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Published: Mar 15, 2022
Keywords:
Lung cancer, biomarker, gene ontology, survival analysis

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Nikita Singh
Department of Bioinformatics, MMV, Banaras Hindu University, Varanasi, India
Mukesh Kumar
Department of Statistics, M.M.V., Banaras Hindu University, Varanasi, India
Atanu Bhattacharjee
Section of Biostatistics, Centre for Cancer Epidemiology, TMC, Mumbai, India
Prashant Kumar Sonker
Department of Statistics, I. Sc., Banaras Hindu University, Varanasi, India
Agni Saroj
Department of Statistics, I. Sc., Banaras Hindu University, Varanasi, India

Abstract

The aim of the study is to find key genes and enriched pathways associated with lung cancer using bioinformatics and statistical techniques. A total of 54674 differentially expressed genes (DEGs) data genes based on clinical information of  lung cancer was taken from 66 patients of African American (AAs) origin.  The data was retrieved from https://www.ncbi.nlm.nih.gov/geo/. The accession number of data is GSE102287. The Protein-protein interaction (PPI) network, gene ontology (GO) and KEGG pathways were used to find association among DEGs. Total 33 common DEGs were found from stage, tumor and status of lung cancer patients. GO and KEGG pathway enrichment analysis is performed and 49 significant pathways were obtained, out of which 10 pathways were found that were exclusively involved in lung cancer development. PPI network analysis found 69 nodes and 324 edges and identified 10 hub genes based on their highest degrees. Additionally, module analysis of PPI found that ‘Viral carcinogenesis’, ‘pathways in cancer’, ‘notch signaling pathway’, ‘AMPK signaling pathways’ had closed association with lung cancer. It is seen that these identified DEGs do not directly participate in growth of lung cancer but regulate other genes which play important role in growth of lung cancer. The key genes and enriched pathways identified can thus help in better identification and prediction of lung cancer.

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1.
Singh N, Kumar M, Bhattacharjee A, Sonker PK, Saroj A. Identification of Biomarkers and enriched pathways involved in lung cancer using statistical techniques. J. Int. Acad. Phys. Sci. [Internet]. 2022 Mar. 15 [cited 2024 May 17];26(1):65-78. Available from: https://www.iaps.org.in/journal/index.php/journaliaps/article/view/934
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Vol. 26 No. 1 (2022): Table of Content
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Author Biography

Mukesh Kumar, Department of Statistics, M.M.V., Banaras Hindu University, Varanasi, India

Department of Statistics, MMV, Banaras Hindu University, Varanasi-221005, India

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