The Pharmacogenomics “Side-effect” of TP53/EGFR in Non-small Cell Lung Cancer Accompanied with Atorvastatin Therapy: A Functional Network Analysis

Author(s): Lei Zhang, Yifang Huang, Xuedong Gan, Siying He, Xiaohuan Cheng, Na Yang, Siwei Li, Zuhua Li, Fang Zheng*.

Journal Name: Anti-Cancer Agents in Medicinal Chemistry
(Formerly Current Medicinal Chemistry - Anti-Cancer Agents)

Volume 19 , Issue 17 , 2019

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Abstract:

Background: Atorvastatin belongs to the group of statins and is the leading drug for hypercholesterolemia treatment. Although, its anticancer effects are highly appreciated, its properties are still unclear. The aim of this study was to explore the underlying anticancer mechanisms induced by atorvastatin and enlarge the potential target in non-small cell lung cancer.

Methods: Target genes of atorvastatin were collected by the DrugBank database. Prediction of interaction between primary targets and secondary targets was performed, and protein-protein interaction network was constructed though the STRING. Then, KEGG pathway enrichment analysis was performed with WebGestalt and ClueGO, including the pathways in non-small cell lung cancer. Furthermore, a genomic alteration analysis of the selected seed genes of atorvastatin benefit and non-small cell lung cancer pathway was conducted by cBioPortal. Finally, a survival analysis with the selected seed genes in lung cancer (lung adenocarcinoma, lung squamous cell carcinoma) was conducted using Kaplan-Meier (KM) plotter.

Results: To identify seed genes, 65 potential candidate genes were screened as targets for atorvastatin using STRING with DrugBank database, while the KEGG pathway was enriched to get the overlap match of pathways in non-small cell lung cancer. Then 4 seed genes, Epidermal Growth Factor Receptor (EGFR), erb-b2 receptor tyrosine kinase 2 (ERBB2), AKT serine/threonine kinase 1 (AKT1) and tumor protein p53 (TP53), were selected and their genomic alternation were evaluated by cBioPortal. Survival analysis found that TP53 and EGFR showed a significant correlation (log rank P = 3e-07 and 0.023) with lung adenocarcinoma and lung squamous cell carcinoma, according to the KM analysis.

Conclusion: Gene-phenotype connectivity for atorvastatin in non-small cell lung cancer was identified using functional/activity network analysis method, and our findings demonstrated that TP53 and EGFR could be the potential targets in cancer patients with atorvastatin therapy.

Keywords: Atorvastatin, functional/activity network analysis, non-small cell lung cancer, TP53, EGFR, AKT1.

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Article Details

VOLUME: 19
ISSUE: 17
Year: 2019
Page: [2060 - 2071]
Pages: 12
DOI: 10.2174/1871520619666190712203217
Price: $95

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