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

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.

• Authors: Lei Zhang, Yifang Huang, Xuedong Gan, Siying He, Xiaohuan Cheng, Na Yang, Siwei Li, Zuhua Li, Fang Zheng
• Journal: Anti-cancer agents in medicinal chemistry (Anticancer Agents Med Chem) Vol. 19 Issue 17 Pg. 2060-2071 ( 2019) ISSN: 1875-5992 [Electronic] Netherlands
• PMID: 31544704 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright© Bentham Science Publishers; For any queries, please email at [email protected].

Chemical References

• Antineoplastic Agents
• TP53 protein, human
• Tumor Suppressor Protein p53
• Atorvastatin
• EGFR protein, human
• ErbB Receptors

Topics

• Antineoplastic Agents (adverse effects, chemistry, pharmacology)
• Atorvastatin (adverse effects, chemistry, pharmacology)
• Carcinoma, Non-Small-Cell Lung (drug therapy, metabolism)
• Databases, Chemical
• Databases, Genetic
• ErbB Receptors (antagonists & inhibitors, genetics, metabolism)
• Humans
• Kaplan-Meier Estimate
• Lung Neoplasms (drug therapy, metabolism)
• Protein Interaction Maps
• Tumor Cells, Cultured
• Tumor Suppressor Protein p53 (antagonists & inhibitors, genetics, metabolism)