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Poster Display

229P - Identify the impact of SARS-CoV-2 on Lung Cancer tumorigenesis using host-pathogen interaction network analysis

Date

08 Dec 2022

Session

Poster Display

Presenters

Ravindra Kumar

Citation

Annals of Oncology (2022) 16 (suppl_1): 100105-100105. 10.1016/iotech/iotech100105

Authors

R. Kumar

Author affiliations

  • National Institute of Technology Calicut, Kozhikode/IN

Resources

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Abstract 229P

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the coronavirus variant that started the global pandemic and infected more than 12 million victims around the world. SARS-CoV-2, similar to other viruses, interacts with the host proteins to reach the host cells and replicate its genome. Consequently, viral-host protein-protein interaction (PPI) identification could help predict the virus's behavior and its overlap with other pathogenic pathways. Several viruses have been known to closely trigger cancer pathways, serving as the starting point for tumorigenic mutations and even metastatic relapse. This cancer-causing nature of viruses encourages us to investigate the differentially expressed genes (DEGs) and associated enriched pathways in patients during and after SARS-CoV-2 infection.

Methods

RNA microarray data of Covid-19 infected patients, available in the GEO database through the studies done by Gordon et al. and Blanco Melo et al., were used as Covid-19 differential expression dataset. Lung cancer differential expression datasets obtained from the GEPIA database and individual networks for both diseases were created using Cytoscape, keeping the entire human gene-gene interactions as the background (HIPPIE Database).

Results

In this study, we determined 287 DEGs for SARS-CoV-2, 4242 DEGs for lung adenocarcinoma (LUAD) and 5958 for lung squamous cell carcinoma (LUSC) through network analysis. Clustering of these networks was done using the Leiden clustering algorithm, and clusters with overlapping genes in both the diseases were chosen for pathway enrichment using CytoKEGG and Gene Ontology analysis using the GOC tool (based on PANTHER). These analyses revealed 71 genes involved in 6 significant pathways involved in tumor immune evasion, cancer proliferation and immune signaling, namely the TLR Pathway, cAMP signaling pathway, the VEGF signaling pathway, the G-protein Coupled Receptor signaling pathway, the IL-6 amplification Pathway, and the MAPK Signalling Pathway.

Conclusions

The findings suggest that SARS-CoV-2 can play a significant role in cancer relapse by supporting tumorigenic conditions in the tumor microenvironment and facilitating tumor cell migration.

Legal entity responsible for the study

National Institute of Technology Calicut, Kerala, India.

Funding

Has not received any funding.

Disclosure

The author has declared no conflicts of interest.

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