Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data.

Elena Poddubskaya,Maria Suntsova,Galina Malakhova,Petr Arhiri,Andreyan Osipov,Ivan Stilidi,Roman Kholodenko,Dmitriy Lantsov,Andrew Garazha,Maxim Sorokin,Irina Kholodenko,Anton Buzdin

doi:10.3390/cancers10100365

Abstract

Sequential courses of anticancer target therapy lead to selection of drug-resistant cells, which results in continuous decrease of clinical response. Here we present a new approach for predicting effective combinations of target drugs, which act in a synergistic manner. Synergistic combinations of drugs may prevent or postpone acquired resistance, thus increasing treatment efficiency. We cultured human ovarian carcinoma SKOV-3 and neuroblastoma NGP-127 cancer cell lines in the presence of Tyrosine Kinase Inhibitors (Pazopanib, Sorafenib, and Sunitinib) and Rapalogues (Temsirolimus and Everolimus) for four months and obtained cell lines demonstrating increased drug resistance. We investigated gene expression profiles of intact and resistant cells by microarrays and analyzed alterations in 378 cancer-related signaling pathways using the bioinformatical platform Oncobox. This revealed numerous pathways linked with development of drug resistant phenotypes. Our approach is based on targeting proteins involved in as many as possible signaling pathways upregulated in resistant cells. We tested 13 combinations of drugs and/or selective inhibitors predicted by Oncobox and 10 random combinations. Synergy scores for Oncobox predictions were significantly higher than for randomly selected drug combinations. Thus, the proposed approach significantly outperforms random selection of drugs and can be adopted to enhance discovery of new synergistic combinations of anticancer target drugs.

Highlights

Emergence of target drugs significantly increased success rates for the therapy of many cancer types
Oncobox utilizes an algorithm that quantitatively analyzes the extents of molecular pathway activation by calculating the value of pathway activation strength (PAS) for each molecular pathway under investigation [9,10]
Positive PAS value indicates upregulation of a molecular pathway compared to the control biosample or group of biosamples, negative PAS value—downregulation, and zero value suggests no changes in pathway activation

Summary

Introduction

Emergence of target drugs significantly increased success rates for the therapy of many cancer types. In renal cell carcinoma, which is not sensitive to radiation or generalized chemotherapy, the introduction into the clinical practice of a new class of target drugs—tyrosine kinase inhibitors (TKIs) increased the response rate of the therapy to the impressive value of up to. 70% of patients [1] Another successful example is the use of a TKI Pazopanib in ovarian cancer patients, which resulted in significant increase of progression-free survival [2]. Target therapeutics (anti-angiogenic and tyrosine kinase inhibitors) significantly improved treatment of differentiated thyroid carcinoma [3]. Novel Janus Kinase-2 inhibitor, Fedratinib, showed promising results in patients with myelofibrosis [4]

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Discussion

Conclusion