Title

Exploring potential genes and pathways related to lung cancer: a graph theoretical analysis

Authors

Shaheen Hayat¹ & Romana Ishrat¹*

Affiliation

¹Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, *Corresponding author

Email

Shaheen Hayat - Email: shaheen2008755@st.jmi.ac.in & hayatshaheen2@gmail.com

Romana Ishrat:Email::rishrat@jmi.ac.in

Article Type

Research Article

Date

Received September 1, 2023; Revised September 30, 2023; Accepted September 30, 2023, Published September 30, 2023

Lung cancer is the primary and third most frequently detected form of cancer in both males and females. The present study tries to perform integrated analysis in male as well as female patients inclusively both smoker and non-smokers. This study aims to identify diagnostic biomarkers and therapeutic targets for lung cancer patients using human microarray profile datasets. Differentially expressed genes (DEGs) were identified using a PPI network from the String database, and major modules or clusters were extracted using MCODE. The Cytohubba plug-in was used to find hub genes from the PPI network using centralities approaches. Twenty significant hub genes (CCND1, CDK1, CCNB1, CDH1, TP53, CTNNB1, EGFR, ESR1, CDK2, CCNA2, RHOA, EGF, FN1, HSP90AA1, STAT3, JUN, NOTCH1, IL6, SRC, and CD44) were identified as promising diagnostic biomarkers and therapeutic targets for lung cancer treatment. Survival analysis and hub gene validation were also conducted. GO enrichment and pathway analysis were conducted to identify their important functions. These hub genes were also used to identify targeted drugs. The findings suggest that the identified genes have the potential to be used as diagnostic biomarkers and therapeutic targets for lung cancer treatment.

Keywords

Differentially Expressed Genes, Protein-Protein Interaction Network, Lung Cancer.

Citation

Hayat & Ishrat, Bioinformation 19(9): 954-963 (2023)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.