Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data
Abstract
:1. Introduction
2. Results
2.1. Signaling Pathway Activation in Drug-Resistant Cell Lines
2.2. Prediction and Experimental Testing of Drugs Combinations
3. Discussion
4. Materials and Methods
4.1. Biosamples
4.2. Cell Culturing and Viability Assay
4.3. Data Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Cell Line | Drug | 4–8 Week | 16 Weeks |
---|---|---|---|
NGP-127 | Sorafenib | Phospholipase C, JNK1-2-3/MAP2K4-7 | JAK1, JAK3 |
Sunitinib | JNK1-2-3/MAP2K4-7 | RAS, PI3K | |
Pazopanib | Phospholipase C, Adenylate cyclase | EGFR | |
Temsirolimus | JNK1-2-3/MAP2K4-7 | RAS | |
Everolimus | PRKACA | PI3K | |
SKOV-3 | Sorafenib | Akt | Phospholipase C |
Sunitinib | Notch, Akt | EGFR, ErbB2, ADCYs | |
Pazopanib | mTOR | ErbB3 | |
Temsirolimus | Notch | EGFR-ErbB2 | |
Everolimus | Notch | MAP2K6-MAP2K3 |
Drug/Inhibitor | Molecular Target |
---|---|
Temsirolimus | mTOR, FKBP12 |
Everolimus | mTOR, FKBP12 |
Sunitinib | VEGFR2 (Flk-1) and PDGFRβ |
Sorafenib | Raf-1, B-Raf and VEGFR-2 |
Pazopanib | VEGFR1, VEGFR2, VEGFR3, PDGFR, FGFR, c-Kit and c-Fms |
Afuresertib (GSK2110183) | Akt |
Sapitinib (AZD8931) | EGFR, ErbB2 and ErbB3 |
FLI-06 | Notch |
U73122 | Phospholipase C (PLC) |
Drug | SKOV-3 | NGP-127 | ||
---|---|---|---|---|
IC20 (µM) | IC50 (µM) | IC20 (µM) | IC50 (µM) | |
Afuresertib | 2.7 | 17 | 8 | 19 |
FLI-06 | 1.5 | 2 | 11 | 20 |
U73122 | 3 | 3.2 | 1 | 3.5 |
Sapitinib | 11 | 37 | 4.2 | ≥40 |
Sorafenib * | 9.6 | 5.5 | ||
Pazopanib * | ≥50 | 12 | ||
Sunitinib * | 3 | 3.1 | ||
Temsirolimus * | 17 | 11.8 | ||
Everolimus * | 17.6 | 15.5 |
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Sorokin, M.; Kholodenko, R.; Suntsova, M.; Malakhova, G.; Garazha, A.; Kholodenko, I.; Poddubskaya, E.; Lantsov, D.; Stilidi, I.; Arhiri, P.; et al. Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data. Cancers 2018, 10, 365. https://doi.org/10.3390/cancers10100365
Sorokin M, Kholodenko R, Suntsova M, Malakhova G, Garazha A, Kholodenko I, Poddubskaya E, Lantsov D, Stilidi I, Arhiri P, et al. Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data. Cancers. 2018; 10(10):365. https://doi.org/10.3390/cancers10100365
Chicago/Turabian StyleSorokin, Maxim, Roman Kholodenko, Maria Suntsova, Galina Malakhova, Andrew Garazha, Irina Kholodenko, Elena Poddubskaya, Dmitriy Lantsov, Ivan Stilidi, Petr Arhiri, and et al. 2018. "Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data" Cancers 10, no. 10: 365. https://doi.org/10.3390/cancers10100365