Synergistic suppression of t(8;21)-positive leukemia cell growth by combining oridonin and MAPK1/ERK2 inhibitors.
In previous research we predicted that targeted therapy against AML2-ETO fused oncogene can be synergistically enhanced by using the MAP1/ERK2 inhibition. Here we showed that simultaneous inhibition of MAP1/ERK2 and AML2-ETO indeed works synergistically by strongly inhibiting the survival of the t(8;21) mutated leukemia cell. This article is the first published proof-of-concept that the algorithm may be used to design new efficient cancer target drugs and combination drug therapies.
VEGF blockade enhances the antitumor effect of BRAFV600E inhibition.
F, Buzdin A, Sica A, Medico E, Sangiolo D, Taverna D, Bussolino F. EMBO Molecular Medicine. 2016 Dec 14. pii: e201505774. IF: 8.7
In this paper, we explore a combinatorial anti-VEGF and anti-V600E mutant BRAF treatment therapy on a mouse model. We show it provides substantial advantages compared to its single components taken individually. We applied our original algorithm to explain these synergistic effects and to identify molecular bases of the effects observed.
A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.
Artem Artemov, Alexander Aliper, Michael Korzinkin, Ksenia Lezhnina, Leslie Jellen, Nicolay Zhukov, Sergey Roumiantsev, Nurshat Gaifullin, Alex Zhavoronkov, Nicolas Borisov, Anton Buzdin. Oncotarget. 2015 IF: 6.6
Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we published a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor samples. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs and seven cancer types with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly with the percent of tumors showing high drug scores calculated with the current algorithm (Pearson's correlation 0.77, p = 0.02).
Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs.
Larisa Venkova, Alexander Aliper, Maria Suntsova, Roman Kholodenko, Denis Shepelin, Nicolas Borisov, Galina Malakhova, Raif Vasilov, Sergey Roumiantsev, Alex Zhavoronkov, Anton Buzdin. Oncotarget. 2015 IF: 6.6
Here, we compared the experimental data obtained by us and in the Genomics of Drug Sensitivity in Cancer (GDS) project for comparing responses to anticancer drugs, and transcriptomes of various cell lines. We assayed four blockbuster anticancer target drugs: sorafenib, pazopanib, sunitinib and temsirolimus, and 238 human cell lines. Using the OncoFinder-processed data on ~600 molecular pathways, we identified pathways showing significant correlation between pathway activation strength and response scores for these drugs. For most of these pathways, we generated molecular models of their interaction with known molecular target(s) of the respective drugs. For the first time, our study uncovered mechanisms underlying cancer cell response to drugs at the high-throughput molecular interatomic level.
Pathway Activation Strength (PAS) is a Novel Independent Prognostic Biomarker for Cetuximab Sensitivity in Colorectal Cancer Patients.
Qingsong Zhu, Evgeny Izumchenko, Alexander Aliper, Evgeny Makarev, Keren Paz, Anton Buzdin, Alex Zhavoronkov, and David Sidransky. Human Genome Variation. (Nature Publishing Group) 2015.
Cetuximab, a monoclonal antibody against epidermal growth factor receptor (EGFR), has been shown to be active against colorectal cancer. However, there is no universal marker or method of clinical utility that could guide its treatment. Here, we demonstrate a method based on the OncoFinder algorithm to predict response to cetuximab in patients with colorectal cancer. The approach and models were validated using a clinical trial data set. Our approach could efficiently predict patients' response to cetuximab and thus holds promise as a selection criterion for cetuximab treatment in metastatic colorectal cancer.
Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways.
K. Lezhnina, O. Kovalchuk, A.A. Zhavoronkov, M.B. Korzinkin, A.A. Zabolotneva, P.V. Shegay, D.G. Sokov, N.M. Gaifullin, I.G. Rusakov, A.M. Aliper, S.A., Roumiantsev, B.Y. Alekseev, N.M. Borisov, and A.A. Buzdin. Oncotarget, 2014, Oct 15;5(19):9022-32. IF: 6.6
Here, for the first time, we applied OncoFinder for normal and malignant tissues to identify biomarkers of human bladder cancer. We calculated pathway activation strength values and identified signaling pathways that were regulated differently in bladder cancer tissues and in normal controls. We found 44 signaling pathways that serve as excellent new biomarkers of BC, supported by very good statistical characteristics. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from "traditional" expression biomarkers that only assess concentrations of single genes.
Signaling pathway activation profiles make better markers of cancer than expression of individual genes.
N.M. Borisov, N.V. Terekhanova, A.M. Aliper, L.S. Venkova, P.Yu. Smirnov, S.Roumiantsev, M.B. Korzinkin, A.A. Zhavoronkov, A.A. Buzdin. Oncotarget, 2014 Oct 30;5(20):10198-205 IF: 6.6
Identification of reliable and accurate molecular markers of cancer remains a major challenge. Here, we showed that the pathway activation value itself may serve as the biomarker for cancer, and compared it with the "traditional" molecular markers based on the expression of individual genes. We applied OncoFinder to profile gene expression datasets for the nine human cancer types, totally for 292 cancer and 128 normal tissue samples. We profiled activation of 82 signaling pathways featuring ~2700 gene products. For all of the cancer types tested, the PAS values showed better area-under-the-curve (AUC) scores compared to the individual genes enclosing each of the pathways. These results evidence that the PAS values can be used as a new type of cancer biomarkers, superior to the traditional gene expression biomarkers.
Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling.
Spirin PV, Lebedev TD, Orlova NN, Gornostaeva AS, Prokofjeva MM, Nikitenko NA, Dmitriev SE,Buzdin AA, Borisov NM, Aliper AM, Garazha AV, Rubtsov PM, Stocking C, Prassolov VS. Leukemia (Nature Publishing Group). 2014 Apr 14. doi: 10.1038/leu.2014.130. IF: 9.4
The t(8;21) rearrangement represents the most common chromosomal translocation in acute myeloid leukemia (AML). It results in transcript encoding for the fusion protein AML1-ETO (AE). AE is considered to be an attractive target for treating t(8;21) leukemia. However, AE expression alone is insufficient to cause transformation, and thus the potential of such therapy remains unclear. Several genes are deregulated in AML cells, including KIT that encodes a key tyrosine kinase receptor. Here, we show that AML cells transduced with short hairpin RNA vector targeting AE mRNAs have a dramatic decrease in growth rate that is caused by induction of apoptosis and deregulation of the cell cycle. A reduction in KIT mRNA levels was also observed in AE-silenced cells and while silencing KIT expression reduced cell growth, it did not induce apoptosis. OncoFinder-based profiling of cells that escape cell death revealed activation of a number of signaling pathways involved in survival and proliferation. In particular, we find that the MAPK1 protein could mediate activation of 23 out of 29 (79%) of these upregulated pathways and thus may be regarded as the key player in establishing the t(8;21)-positive leukemic cells resistant to AE suppression.
OncoFinder, a new method for the analysis of intracellular signaling pathway activation using transcriptomic data.
Buzdin AA, Zhavoronkov AA, Korzinkin MB, Venkova LS, Zenin AA, Smirnov PY, Borisov NM. Frontiers in Genetics. 2014 Mar 25;5:55. doi: 10.3389/fgene.2014.00055.
In this paper, we propose a biomathematical algorithm OncoFinder for both quantitative and qualitative analysis of the intracellular signaling pathway activation. This method may be used for the analysis of any physiological, stress, malignancy or other perturbed conditions at the molecular level. In contrast with other existing techniques for aggregation and generalization of gene expression data for individual samples, we suggest distinguishing the positive/activator and negative/repressor role of every gene product in each pathway.