Expression2Kinases (E2K) analysis indentifies potential drugable kinases for targeted treatment of cervical carcinoma

Date

20 Dec 2015

Session

Poster presentation 2

Presenters

Peter van Dam

Citation

Annals of Oncology (2015) 26 (suppl_9): 80-84. 10.1093/annonc/mdv525

Authors

P.A. van Dam1, P. van Dam2, C.D. Rolfo3, X.B. Trinh1, S. Altintas1, M.T. Huizing1, K. Papadimitriou1, W. Tjalma1, S. van Laere2

Author affiliations

  • 1 Gynecologic Oncology And Breast Unit, U.Z.A. University Hospital Antwerp, 2650 - Edegem/BE
  • 2 Translational Cancer Research Unit, St-Augustinus Ziekenhuis, 2610 - Wilrijk/BE
  • 3 Oncology Unit, U.Z.A. University Hospital Antwerp, 2650 - Edegem/BE
More

Resources

Aim/Background

Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK1, MAPK1, ERBB2 and KRAS as well as several copy number alterations in the pathogenesis of cervical carcinomas. Although some of these mutations are potential targets for treatment they remain infrequent events. Single gene mutations are an important cause of pathway disruption, but there are many other factors implicated in pathway (in)activation (such as altered gene expression, gene interactions, effects of miRNAs, methylation, etc.) that may be of functional importance. We therefore used a different approach, gene set enrichment and pathway analysis, to unravel the major signaling networks that are common in most cervical cancer patients and could be drugable.

Methods

Four publicly available gene expression data (i.e. GSE5787, GSE7803, GSE9750 and GSE7410) were retrieved (9 cervical cancer cell lines, 39 normal cervical samples and 111 cervical cancer samples). One data set (i.e. GSE7410) was set apart for validation purposes. Validated biomarkers were interrogated using gene set enrichment analysis (GSEA) and Expression2Kinases (E2K) to delineate the driving signalling network.

Results

GSEA showed that the pathways with most genes involved were cell cycle, DNA replication, mRNA splicing, purine metabolism, E2F transcription, pyrimidine metabolism, direct p53 effectors, Aurora B signalling, PLK1 signaling events, and Fanconi anemia pathway. E2K identified a protein-protein interaction (PPI) network of 162 nodes and 20 drugable kinases: CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3, TRRAP, MAPK14, GSK3B, CSNK2A1, MAPK8, ATR, TAF1, HIPK2, TRRAP, PRLDC, CSNK2A2, RPS6KA2, CD7, RPS6KA1. This implicates that drugs such as olaparib, veliparib, imatinib, dactolisib, buparlisib, copanlisib, iparsertib, etc have the potential to be effective in the treatment of cervical cancer.

Conclusions

The potential targets for systemic treatment of advanced cervical cancer identified in this study should be considered as hypothesis raising. Further detailed in vitro and in vivo studies, linking genotype to phenotypes, are necessary to explore the effectivity of manipulating the interesting pathways we proposed.

Clinical trial identification

Not applicable

Disclosure

All authors have declared no conflicts of interest.

Resources from the same session

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings