In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment
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Peter A. van Dam1,2, Pieter-Jan H. H. van Dam1, Christian Rolfo1,2,3, Marco Giallombardo1,3, Christophe van Berckelaer1, Xuan Bich Trinh2, Sevilay Altintas2, Manon Huizing2, Kostas Papadimitriou2, Wiebren A. A. Tjalma1,2, Steven van Laere1
1Antwerp University Hospital, Centre of Oncologic Research (CORE) Antwerp University, Edegem, Belgium
2Multidisciplinary Oncologic Centre Antwerp (MOCA), Edegem, Belgium
3Phase I - Early Clinical Trials Unit, Oncology Department, University Hospital Antwerp UZA, Edegem, Belgium
Christian Rolfo, e-mail: [email protected]
Keywords: cervical carcinoma, cancer, in silico pathway analysis, treatment targets
Received: August 26, 2015 Accepted: November 21, 2015 Published: December 19, 2015
An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability.
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