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Zolotovskaia M, Kovalenko M, Pugacheva P, Tkachev V, Simonov A, Sorokin M, Seryakov A, Garazha A, Gaifullin N, Sekacheva M, Zakharova G, Buzdin AA. Algorithmically Reconstructed Molecular Pathways as the New Generation of Prognostic Molecular Biomarkers in Human Solid Cancers. Proteomes 2023; 11:26. [PMID: 37755705 PMCID: PMC10535530 DOI: 10.3390/proteomes11030026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/18/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023] Open
Abstract
Individual gene expression and molecular pathway activation profiles were shown to be effective biomarkers in many cancers. Here, we used the human interactome model to algorithmically build 7470 molecular pathways centered around individual gene products. We assessed their associations with tumor type and survival in comparison with the previous generation of molecular pathway biomarkers (3022 "classical" pathways) and with the RNA transcripts or proteomic profiles of individual genes, for 8141 and 1117 samples, respectively. For all analytes in RNA and proteomic data, respectively, we found a total of 7441 and 7343 potential biomarker associations for gene-centric pathways, 3020 and 2950 for classical pathways, and 24,349 and 6742 for individual genes. Overall, the percentage of RNA biomarkers was statistically significantly higher for both types of pathways than for individual genes (p < 0.05). In turn, both types of pathways showed comparable performance. The percentage of cancer-type-specific biomarkers was comparable between proteomic and transcriptomic levels, but the proportion of survival biomarkers was dramatically lower for proteomic data. Thus, we conclude that pathway activation level is the advanced type of biomarker for RNA and proteomic data, and momentary algorithmic computer building of pathways is a new credible alternative to time-consuming hypothesis-driven manual pathway curation and reconstruction.
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Affiliation(s)
- Marianna Zolotovskaia
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Omicsway Corp., Walnut, CA 91789, USA
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Maks Kovalenko
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
| | - Polina Pugacheva
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
| | | | - Alexander Simonov
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Omicsway Corp., Walnut, CA 91789, USA
| | - Maxim Sorokin
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
| | | | | | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Marina Sekacheva
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Galina Zakharova
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia
| | - Anton A. Buzdin
- Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology (State University), 141701 Dolgoprudny, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, 119048 Moscow, Russia
- Laboratory of Systems Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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2
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Kamashev D, Shaban N, Lebedev T, Prassolov V, Suntsova M, Raevskiy M, Gaifullin N, Sekacheva M, Garazha A, Poddubskaya E, Sorokin M, Buzdin A. Human Blood Serum Can Diminish EGFR-Targeted Inhibition of Squamous Carcinoma Cell Growth through Reactivation of MAPK and EGFR Pathways. Cells 2023; 12:2022. [PMID: 37626832 PMCID: PMC10453612 DOI: 10.3390/cells12162022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/03/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Regardless of the presence or absence of specific diagnostic mutations, many cancer patients fail to respond to EGFR-targeted therapeutics, and a personalized approach is needed to identify putative (non)responders. We found previously that human peripheral blood and EGF can modulate the activities of EGFR-specific drugs on inhibiting clonogenity in model EGFR-positive A431 squamous carcinoma cells. Here, we report that human serum can dramatically abolish the cell growth rate inhibition by EGFR-specific drugs cetuximab and erlotinib. We show that this phenomenon is linked with derepression of drug-induced G1S cell cycle transition arrest. Furthermore, A431 cell growth inhibition by cetuximab, erlotinib, and EGF correlates with a decreased activity of ERK1/2 proteins. In turn, the EGF- and human serum-mediated rescue of drug-treated A431 cells restores ERK1/2 activity in functional tests. RNA sequencing revealed 1271 and 1566 differentially expressed genes (DEGs) in the presence of cetuximab and erlotinib, respectively. Erlotinib- and cetuximab-specific DEGs significantly overlapped. Interestingly, the expression of 100% and 75% of these DEGs restores to the no-drug level when EGF or a mixed human serum sample, respectively, is added along with cetuximab. In the case of erlotinib, EGF and human serum restore the expression of 39% and 83% of DEGs, respectively. We further assessed differential molecular pathway activation levels and propose that EGF/human serum-mediated A431 resistance to EGFR drugs can be largely explained by reactivation of the MAPK signaling cascade.
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Affiliation(s)
- Dmitri Kamashev
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia;
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia; (N.S.); (A.B.)
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia;
| | - Nina Shaban
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia; (N.S.); (A.B.)
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia;
| | - Timofey Lebedev
- Engelhardt Institute of Molecular Biology, Moscow 119991, Russia; (T.L.); (V.P.)
| | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Moscow 119991, Russia; (T.L.); (V.P.)
| | - Maria Suntsova
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia;
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia; (M.R.); (E.P.)
| | - Mikhail Raevskiy
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia; (M.R.); (E.P.)
| | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow 119992, Russia;
| | - Marina Sekacheva
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia; (M.R.); (E.P.)
| | - Andrew Garazha
- Oncobox Ltd., Moscow 121205, Russia;
- Omicsway Corp., Walnut, CA 91789, USA
| | - Elena Poddubskaya
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia; (M.R.); (E.P.)
| | - Maksim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia;
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia;
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
| | - Anton Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia; (N.S.); (A.B.)
- Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia;
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow 119991, Russia; (M.R.); (E.P.)
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
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3
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Sorokin M, Buzdin AA, Guryanova A, Efimov V, Suntsova MV, Zolotovskaia MA, Koroleva EV, Sekacheva MI, Tkachev VS, Garazha A, Kremenchutckaya K, Drobyshev A, Seryakov A, Gudkov A, Alekseenko IV, Rakitina O, Kostina MB, Vladimirova U, Moisseev A, Bulgin D, Radomskaya E, Shestakov V, Baklaushev VP, Prassolov V, Shegay PV, Li X, Poddubskaya EV, Gaifullin N. Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers. Comput Struct Biotechnol J 2023; 21:3964-3986. [PMID: 37635765 PMCID: PMC10448432 DOI: 10.1016/j.csbj.2023.07.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 07/17/2023] [Accepted: 07/30/2023] [Indexed: 08/29/2023] Open
Abstract
Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived "healthy" normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact "differential" expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice.
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Affiliation(s)
- Maksim Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Omicsway Corp., Walnut, CA 91789, USA
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Anton A. Buzdin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
- World-Class Research Center "Digital biodesign and personalized healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium
| | - Anastasia Guryanova
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
| | - Victor Efimov
- World-Class Research Center "Digital biodesign and personalized healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria V. Suntsova
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Marianna A. Zolotovskaia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- Omicsway Corp., Walnut, CA 91789, USA
| | - Elena V. Koroleva
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
| | - Marina I. Sekacheva
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Victor S. Tkachev
- Omicsway Corp., Walnut, CA 91789, USA
- Oncobox Ltd., Moscow 121205, Russia
| | - Andrew Garazha
- Omicsway Corp., Walnut, CA 91789, USA
- Oncobox Ltd., Moscow 121205, Russia
| | | | - Aleksey Drobyshev
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | | | - Alexander Gudkov
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Irina V. Alekseenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", 2, Kurchatov Square, Moscow 123182, Russian
- FSBI "National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov" Ministry of Healthcare of the Russian Federation, Moscow 117198, Russia
| | - Olga Rakitina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Maria B. Kostina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Uliana Vladimirova
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
- Oncobox Ltd., Moscow 121205, Russia
| | - Aleksey Moisseev
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Dmitry Bulgin
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | - Elena Radomskaya
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | - Viktor Shestakov
- Research Institute of Medical Primatology, 177 Mira str., Veseloye, Sochi 354376, Russia
| | | | - Vladimir Prassolov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 32 Vavilova str., Moscow 119991, Russia
| | - Petr V. Shegay
- National Medical Research Radiological Center of the Ministry of Health of the Russian Federation, 249036 Obninsk, Russia
| | - Xinmin Li
- UCLA Technology Center for Genomics & Bioinformatics, Department of Pathology & Laboratory Medicine, 650 Charles E Young Dr., Los Angeles, CA 90095, USA
| | | | - Nurshat Gaifullin
- Department of Physiology and General Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow 119991, Russia
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4
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Gudkov A, Shirokorad V, Kashintsev K, Sokov D, Nikitin D, Anisenko A, Borisov N, Sekacheva M, Gaifullin N, Garazha A, Suntsova M, Koroleva E, Buzdin A, Sorokin M. Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer. Front Mol Biosci 2022; 9:753318. [PMID: 35359606 PMCID: PMC8963850 DOI: 10.3389/fmolb.2022.753318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 01/28/2022] [Indexed: 01/07/2023] Open
Abstract
Sorafenib is a tyrosine kinase inhibitory drug with multiple molecular specificities that is approved for clinical use in second-line treatments of metastatic and advanced renal cell carcinomas (RCCs). However, only 10–40% of RCC patients respond on sorafenib-containing therapies, and personalization of its prescription may help in finding an adequate balance of clinical efficiency, cost-effectiveness, and side effects. We investigated whether expression levels of known molecular targets of sorafenib in RCC can serve as prognostic biomarker of treatment response. We used Illumina microarrays to profile RNA expression in pre-treatment formalin-fixed paraffin-embedded (FFPE) samples of 22 metastatic or advanced RCC cases with known responses on next-line sorafenib monotherapy. Among them, nine patients showed partial response (PR), three patients—stable disease (SD), and 10 patients—progressive disease (PD) according to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. We then classified PR + SD patients as “responders” and PD patients as “poor responders”. We found that gene signature including eight sorafenib target genes was congruent with the drug response characteristics and enabled high-quality separation of the responders and poor responders [area under a receiver operating characteristic curve (AUC) 0.89]. We validated these findings on another set of 13 experimental annotated FFPE RCC samples (for 2 PR, 1 SD, and 10 PD patients) that were profiled by RNA sequencing and observed AUC 0.97 for 8-gene signature as the response classifier. We further validated these results in a series of qRT-PCR experiments on the third experimental set of 12 annotated RCC biosamples (for 4 PR, 3 SD, and 5 PD patients), where 8-gene signature showed AUC 0.83.
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Affiliation(s)
- Alexander Gudkov
- I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | | | - Dmitriy Sokov
- Moscow City Clinical Oncological Dispensary №. 1, Moscow, Russia
| | | | | | | | - Marina Sekacheva
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow, Russia
| | | | - Maria Suntsova
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Elena Koroleva
- Moscow Institute of Physics and Technology, Moscow, Russia
| | - Anton Buzdin
- Moscow Institute of Physics and Technology, Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
- OmicsWay Corp, Walnut, CA, United States
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Maksim Sorokin
- I. M. Sechenov First Moscow State Medical University, Moscow, Russia
- Moscow Institute of Physics and Technology, Moscow, Russia
- OmicsWay Corp, Walnut, CA, United States
- European Organization for Research and Treatment of Cancer (EORTC), Biostatistics and Bioinformatics Subgroup, Brussels, Belgium
- *Correspondence: Maksim Sorokin,
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Borisov N, Sergeeva A, Suntsova M, Raevskiy M, Gaifullin N, Mendeleeva L, Gudkov A, Nareiko M, Garazha A, Tkachev V, Li X, Sorokin M, Surin V, Buzdin A. Machine Learning Applicability for Classification of PAD/VCD Chemotherapy Response Using 53 Multiple Myeloma RNA Sequencing Profiles. Front Oncol 2021; 11:652063. [PMID: 33937058 PMCID: PMC8083158 DOI: 10.3389/fonc.2021.652063] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 03/19/2021] [Indexed: 12/17/2022] Open
Abstract
Multiple myeloma (MM) affects ~500,000 people and results in ~100,000 deaths annually, being currently considered treatable but incurable. There are several MM chemotherapy treatment regimens, among which eleven include bortezomib, a proteasome-targeted drug. MM patients respond differently to bortezomib, and new prognostic biomarkers are needed to personalize treatments. However, there is a shortage of clinically annotated MM molecular data that could be used to establish novel molecular diagnostics. We report new RNA sequencing profiles for 53 MM patients annotated with responses on two similar chemotherapy regimens: bortezomib, doxorubicin, dexamethasone (PAD), and bortezomib, cyclophosphamide, dexamethasone (VCD), or with responses to their combinations. Fourteen patients received both PAD and VCD; six received only PAD, and 33 received only VCD. We compared profiles for the good and poor responders and found five genes commonly regulated here and in the previous datasets for other bortezomib regimens (all upregulated in the good responders): FGFR3, MAF, IGHA2, IGHV1-69, and GRB14. Four of these genes are linked with known immunoglobulin locus rearrangements. We then used five machine learning (ML) methods to build a classifier distinguishing good and poor responders for two cohorts: PAD + VCD (53 patients), and separately VCD (47 patients). We showed that the application of FloWPS dynamic data trimming was beneficial for all ML methods tested in both cohorts, and also in the previous MM bortezomib datasets. However, the ML models build for the different datasets did not allow cross-transferring, which can be due to different treatment regimens, experimental profiling methods, and MM heterogeneity.
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Affiliation(s)
- Nicolas Borisov
- Moscow Institute of Physics and Technology, Laboratory for Translational Genomic Bioinformatics, Dolgoprudny, Russia
| | - Anna Sergeeva
- National Research Center for Hematology, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Maria Suntsova
- I.M. Sechenov First Moscow State Medical University, Institute of Personalized Medicine, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Group for Genomic Analysis of Cell Signaling Systems, Moscow, Russia
| | - Mikhail Raevskiy
- Moscow Institute of Physics and Technology, Laboratory for Translational Genomic Bioinformatics, Dolgoprudny, Russia
| | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow, Russia
| | - Larisa Mendeleeva
- National Research Center for Hematology, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Alexander Gudkov
- I.M. Sechenov First Moscow State Medical University, Institute of Personalized Medicine, Moscow, Russia
| | - Maria Nareiko
- National Research Center for Hematology, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Andrew Garazha
- Omicsway Corp., Research Department, Walnut, CA, United States
- Oncobox Ltd., Research Department, Moscow, Russia
| | - Victor Tkachev
- Omicsway Corp., Research Department, Walnut, CA, United States
- Oncobox Ltd., Research Department, Moscow, Russia
| | - Xinmin Li
- Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Institute of Personalized Medicine, Moscow, Russia
- Omicsway Corp., Research Department, Walnut, CA, United States
- Oncobox Ltd., Research Department, Moscow, Russia
| | - Vadim Surin
- National Research Center for Hematology, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, Institute of Personalized Medicine, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Group for Genomic Analysis of Cell Signaling Systems, Moscow, Russia
- Omicsway Corp., Research Department, Walnut, CA, United States
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6
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Vladimirova U, Rumiantsev P, Zolotovskaia M, Albert E, Abrosimov A, Slashchuk K, Nikiforovich P, Chukhacheva O, Gaifullin N, Suntsova M, Zakharova G, Glusker A, Nikitin D, Garazha A, Li X, Kamashev D, Drobyshev A, Kochergina-Nikitskaya I, Sorokin M, Buzdin A. DNA repair pathway activation features in follicular and papillary thyroid tumors, interrogated using 95 experimental RNA sequencing profiles. Heliyon 2021; 7:e06408. [PMID: 33748479 PMCID: PMC7970325 DOI: 10.1016/j.heliyon.2021.e06408] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 12/22/2020] [Accepted: 02/26/2021] [Indexed: 12/12/2022] Open
Abstract
DNA repair can prevent mutations and cancer development, but it can also restore damaged tumor cells after chemo and radiation therapy. We performed RNA sequencing on 95 human pathological thyroid biosamples including 17 follicular adenomas, 23 follicular cancers, 3 medullar cancers, 51 papillary cancers and 1 poorly differentiated cancer. The gene expression profiles are annotated here with the clinical and histological diagnoses and, for papillary cancers, with BRAF gene V600E mutation status. DNA repair molecular pathway analysis showed strongly upregulated pathway activation levels for most of the differential pathways in the papillary cancer and moderately upregulated pattern in the follicular cancer, when compared to the follicular adenomas. This was observed for the BRCA1, ATM, p53, excision repair, and mismatch repair pathways. This finding was validated using independent thyroid tumor expression dataset PRJEB11591. We also analyzed gene expression patterns linked with the radioiodine resistant thyroid tumors (n = 13) and identified 871 differential genes that according to Gene Ontology analysis formed two functional groups: (i) response to topologically incorrect protein and (ii) aldo-keto reductase (NADP) activity. We also found RNA sequencing reads for two hybrid transcripts: one in-frame fusion for well-known NCOA4-RET translocation, and another frameshift fusion of ALK oncogene with a new partner ARHGAP12. The latter could probably support increased expression of truncated ALK downstream from 4th exon out of 28. Both fusions were found in papillary thyroid cancers of follicular histologic subtype with node metastases, one of them (NCOA4-RET) for the radioactive iodine resistant tumor. The differences in DNA repair activation patterns may help to improve therapy of different thyroid cancer types under investigation and the data communicated may serve for finding additional markers of radioiodine resistance.
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Affiliation(s)
- Uliana Vladimirova
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Pirogov Russian National Research Medical University, Moscow, 117997, Russia
| | - Pavel Rumiantsev
- Endocrinology Research Centre, Moscow, 117312, Russia
- Pirogov Russian National Research Medical University, Moscow, 117997, Russia
| | | | | | | | | | | | | | - Nurshat Gaifullin
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119992, Russia
| | - Maria Suntsova
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | | | - Alexander Glusker
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Daniil Nikitin
- Omicsway Corp., Walnut, CA, 91789, USA
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | | | - Xinmin Li
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Dmitriy Kamashev
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Alexei Drobyshev
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | | | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Omicsway Corp., Walnut, CA, 91789, USA
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia
| | - Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Omicsway Corp., Walnut, CA, 91789, USA
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
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7
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Sorokin M, Ignatev K, Barbara V, Vladimirova U, Muraveva A, Suntsova M, Gaifullin N, Vorotnikov I, Kamashev D, Bondarenko A, Baranova M, Poddubskaya E, Buzdin A. Molecular Pathway Activation Markers Are Associated with Efficacy of Trastuzumab Therapy in Metastatic HER2-Positive Breast Cancer Better than Individual Gene Expression Levels. Biochemistry Moscow 2020; 85:758-772. [DOI: 10.1134/s0006297920070044] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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8
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Poddubskaya E, Sorokin M, Garazha A, Glusker A, Moisseev A, Sekacheva M, Suntsova M, Kim EL, Gaifullin N, Tkachev V, Giese A, Barbara V, Borisov N, Buzdin A. Clinical use of RNA sequencing and oncobox analytics to predict personalized targeted therapeutic efficacy. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.e13676] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13676 Background: Analysis of mutation profiles in cancer patients does not provide clinical benefits in 80-90% of cases in the US (Marquart et al., 2018). Gene expression analysis potentially complements standard detection of clinically relevant mutations. Methods: 239 adult late-stage cancer patients. RNA gene expression sequencing completed on solid tumor samples using FFPE blocks. Patient mRNA profiles were analyzed using Oncobox bioinformatics, prioritizing target drugs according to their personalized predicted efficacy. Summary reports were provided to oncologists and resulting treatment selection and outcomes were assessed. Results: As of February 2020, feedback was received from participating doctors for 224 patients; 34 patients died before therapy prescription, 52 patients received treatment other than targeted therapy (chemo, surgery, radiation, or palliative care), 75 patients received at least one targeted therapy (single or combination therapy) predicted to be effective based on Oncobox analysis (“RNAseq cohort”). 63 patients received chemo or other drug therapy predicted to be potentially ineffective from Oncobox analysis (“other cohort”). Therapeutic response was obtained on 46 patients with biopsies collected no longer than 6 months prior to analysis who had no further surgery (30 in the RNAseq cohort and 16 in the other cohort). 63% of the RNAseq cohort obtained either partial response or stable disease using Oncobox guided therapies, compared to 44% of the other cohort (19% increase of disease control). The RNAseq cohort had higher mean prior therapies (1.3) compared to the other cohort (0.8) indicating more advanced disease. The similarly designed WINTHER trial reported ~8% increase of disease control using gene expression-guided vs mutation-guided therapeutics in a cohort of advanced cancer patients averaging three prior therapies (Rodon et al., 2019). Conclusions: Collectively these data suggest that gene expression profiling provides a more clinically relevant therapeutic match, and better response rates, than mutation guided therapeutic treatments. This potentially results in improved clinical outcomes for cancer patients. Clinical trial information: NCT03724097.
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Affiliation(s)
| | | | | | | | - Alexey Moisseev
- I.M. Sechenov First Moscow Medical University, Moscow, Russian Federation
| | - Marina Sekacheva
- I.M. Sechenov First Moscow Medical University, Moscow, Russian Federation
| | - Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, CA, Russian Federation
| | - Ella L Kim
- Johannes Gutenberg University Medical Centre Mainz, Mainz, Germany
| | - Nurshat Gaifullin
- M.V. Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russian Federation
| | | | - Alf Giese
- Orthozentrum Hamburg, Hamburg, Germany
| | - Viktoria Barbara
- Oncological Dispensary of the Republic of Karelia, Petrozavodsk, Russian Federation
| | - Nikolay Borisov
- I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation
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9
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Sorokin M, Ignatev K, Poddubskaya E, Vladimirova U, Gaifullin N, Lantsov D, Garazha A, Allina D, Suntsova M, Barbara V, Buzdin A. RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens. Biomedicines 2020; 8:E114. [PMID: 32397474 PMCID: PMC7277916 DOI: 10.3390/biomedicines8050114] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 05/02/2020] [Accepted: 05/07/2020] [Indexed: 12/11/2022] Open
Abstract
RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman's rho 0.65-0.798) and statistically significant (p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.
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Affiliation(s)
- Maxim Sorokin
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Omicsway Corp., Walnut, CA 91789, USA;
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
| | - Kirill Ignatev
- Karelia Republic Oncological Hospital, 185000 Petrozavodsk, Russia;
| | - Elena Poddubskaya
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Vitamed Oncological Clinical Center, 121309 Moscow, Russia
| | - Uliana Vladimirova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
| | - Nurshat Gaifullin
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 119991 Moscow, Russia;
| | - Dmitriy Lantsov
- Kaluga Regional Oncological Hospital, 248007 Kaluga, Russia;
| | | | - Daria Allina
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
| | - Maria Suntsova
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
| | - Victoria Barbara
- Oncological Dispensary of the Republic of Karelia, 185002 Petrozavodsk, Russia;
| | - Anton Buzdin
- Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119048 Moscow, Russia; (M.S.); (E.P.); (D.A.); (M.S.)
- Omicsway Corp., Walnut, CA 91789, USA;
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
- Moscow Institute of Physics and Technology, 141701 Moscow, Russia
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10
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Buzdin A, Sorokin M, Garazha A, Glusker A, Aleshin A, Poddubskaya E, Sekacheva M, Kim E, Gaifullin N, Giese A, Seryakov A, Rumiantsev P, Moshkovskii S, Moiseev A. RNA sequencing for research and diagnostics in clinical oncology. Semin Cancer Biol 2019; 60:311-323. [PMID: 31412295 DOI: 10.1016/j.semcancer.2019.07.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 07/16/2019] [Indexed: 12/26/2022]
Abstract
Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.
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Affiliation(s)
- Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia; Omicsway Corp., Walnut, CA, USA; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.
| | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia; Omicsway Corp., Walnut, CA, USA; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | | | - Alex Aleshin
- Stanford University School of Medicine, Stanford, 94305, CA, USA
| | - Elena Poddubskaya
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia; Vitamed Oncological Clinics, Moscow, Russia
| | - Marina Sekacheva
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Ella Kim
- Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nurshat Gaifullin
- Lomonosov Moscow State University, Faculty of Medicine, Moscow, Russia
| | | | | | | | - Sergey Moshkovskii
- Institute of Biomedical Chemistry, Moscow, 119121, Russia; Pirogov Russian National Research Medical University (RNRMU), Moscow, 117997, Russia
| | - Alexey Moiseev
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia
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11
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Nikitin D, Garazha A, Sorokin M, Penzar D, Tkachev V, Markov A, Gaifullin N, Borger P, Poltorak A, Buzdin A. Correction: Nikitin, D., et al. Retroelement-Linked Transcription Factor Binding Patterns Point to Quickly Developing Molecular Pathways in Human Evolution. Cells 2019, 8, 130. Cells 2019; 8:cells8080832. [PMID: 31387291 PMCID: PMC6721673 DOI: 10.3390/cells8080832] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Accepted: 08/01/2019] [Indexed: 01/13/2023] Open
Affiliation(s)
- Daniil Nikitin
- I.M. Sechenov First Moscow State Medical University, 119992 Moscow, Russia
- Omicsway Corp., Walnut, CA 91798, USA
| | - Andrew Garazha
- Omicsway Corp., Walnut, CA 91798, USA
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, 117198 Moscow, Russia
| | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, 119992 Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117198 Moscow, Russia
| | - Dmitry Penzar
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119992 Moscow, Russia
| | | | - Alexander Markov
- Faculty of Biology, Moscow State University, 119192 Moscow, Russia
| | - Nurshat Gaifullin
- Faculty of Fundamental Medicine, Moscow State University, 119992 Moscow, Russia
| | - Pieter Borger
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Raemistrasse 100, Zürich CH-8091, Switzerland
| | - Alexander Poltorak
- Program in Immunology, Sackler Graduate School, Tufts University, Boston, MA 02111, USA
| | - Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, 119992 Moscow, Russia.
- Omicsway Corp., Walnut, CA 91798, USA.
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117198 Moscow, Russia.
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12
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Poddubskaya E, Buzdin A, Garazha A, Sorokin M, Glusker A, Aleshin A, Allina D, Moiseev A, Sekacheva M, Suntsova M, Kim EL, Gaifullin N, Tkachev V, Giese A, Barbara V, Borger P, Borisov N. Oncobox, gene expression-based second opinion system for predicting response to treatment in advanced solid tumors. J Clin Oncol 2019. [DOI: 10.1200/jco.2019.37.15_suppl.e13143] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to personalize selection of targeted drugs for individual cancer patients. Based on RNA-seq gene expression data, pathway activation levels are calculated and along with the concentrations of molecular target genes products used as predictors of tumor response to ATDs. Results: The Oncobox method was tested first on the retrospective samples of advanced tumors: gastric, renal cell, ovarian and colorectal cancers, thus showing ROC AUC values > 0.7. In currently ongoing prospective trial for advanced solid tumor patients, the Oncobox tests were completed for 239 patients, primary feedback information received for 144 patients. 25 patients (17%) died before prescription of the therapy, 19% received palliative care treatment, 39% received Oncobox-recommended therapies and 25% received other therapies (February 2019). Tumor responses were estimated for 30 patients (breast, colorectal, ovarian and other cancers) receiving therapies, with disease control rate of 71% for Oncobox-recommended ATDs (Bevacizumab, Crizotinib, Trastuzumab and others) and 44% for other therapies. Our results also suggest that cancer metastases and primary tumors may have different gene expression, molecular pathway activation and drug scoring patterns, thus pointing to the importance of testing multiple tumor sites. Conclusions: Our study suggests that profound analysis of gene expression profiles of tumor tissues may be useful for ATDs treatment of advanced and metastatic cancers. Clinical trial information: NCT03724097.
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Affiliation(s)
| | | | | | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | | | | | - Daria Allina
- Pathology department, Morozov Children's City Hospital, Moscow, Russian Federation
| | | | - Marina Sekacheva
- I.M. Sechenov First Moscow Medical University, Moscow, Russian Federation
| | - Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, CA, Russian Federation
| | - Ella L Kim
- Johannes Gutenberg University Medical Centre Mainz, Mainz, Germany
| | - Nurshat Gaifullin
- M.V. Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russian Federation
| | | | - Alf Giese
- Orthozentrum Hamburg, Hamburg, Germany
| | - Viktoria Barbara
- Oncological Dispensary of the Republic of Karelia, Petrozavodsk, Russian Federation
| | - Pieter Borger
- Swiss Hepato-Pancreatico-Biliary and Transplantation Center, Department of Surgery, University Hospital Zurich, Zurich, Switzerland
| | - Nikolay Borisov
- I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation
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13
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Buzdin A, Garazha A, Sorokin M, Glusker A, Aleshin A, Allina D, Suntsova M, Tkachev V, Borger P, Borisov N, Gaifullin N. RNA sequencing analysis for profiling activation of cancer-associated molecular pathways. J Clin Oncol 2019. [DOI: 10.1200/jco.2019.37.15_suppl.e13032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e13032 Background: Intracellular molecular pathways (IMPs) control all major events in the living cell. They are considered hotspots in contemporary oncology because knowledge of IMPs activation is essential for understanding mechanisms of molecular pathogenesis in oncology. Profiling IMPs requires RNA-seq data for tumors and for a collection of reference normal tissues. However, there is a shortage now in such profiles for normal tissues from healthy human donors, uniformly profiled in a single series of experiments. Access to the largest dataset of normal profiles GTEx is only partly available through the dbGaP. In TCGA database, norms are adjacent to surgically removed tumors and may be affected by tumor-linked growth factors, inflammation and altered vascularization. ENCODE datasets were for the autopsies of normal tissues, but they can’t form statistically significant reference groups. Methods: Tissue samples representing 20 organs were taken from post-mortal human healthy donors killed in road accidents no later than 36 hours after death, blood samples were taken from healthy volunteers. Gene expression was profiled in RNA-seq experiments using the same reagents, equipment and protocols. Bioinformatic algorithms for IMP analysis were developed and validated using experimental and public gene expression datasets. Results: From original sequencing data we constructed the biggest fully open reference expression database of normal human tissues including 465 profiles termed Oncobox Atlas of Normal Tissue Expression (ANTE, original data: GSE120795). We next developed a method termed Oncobox for interrogating activation of IMPs in human cancers. It includes modules of expression data harmonization and comparison and an algorithm for automatic annotation of molecular pathways. The Oncobox system enables accurate scoring of thousands molecular pathways using RNA-seq data. Oncobox pathway analysis is also applicable for quantitative proteomics and microRNA data in oncology. Conclusions: The Oncobox system can be used for a plethora of applications in cancer research including finding differentially regulated genes and IMPs, and for discovery of new pathway-related diagnostic and prognostic biomarkers.
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Affiliation(s)
| | | | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | | | | | - Daria Allina
- Pathology department, Morozov Children's City Hospital, Moscow, Russian Federation
| | - Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, CA, Russian Federation
| | | | - Pieter Borger
- Swiss Hepato-Pancreatico-Biliary and Transplantation Center, Department of Surgery, University Hospital Zurich, Zurich, Switzerland
| | - Nikolay Borisov
- I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Nurshat Gaifullin
- M.V. Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russian Federation
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14
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Suntsova M, Gaifullin N, Allina D, Reshetun A, Li X, Mendeleeva L, Surin V, Sergeeva A, Spirin P, Prassolov V, Morgan A, Garazha A, Sorokin M, Buzdin A. Atlas of RNA sequencing profiles for normal human tissues. Sci Data 2019; 6:36. [PMID: 31015567 PMCID: PMC6478850 DOI: 10.1038/s41597-019-0043-4] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 03/12/2019] [Indexed: 11/09/2022] Open
Abstract
Comprehensive analysis of molecular pathology requires a collection of reference samples representing normal tissues from healthy donors. For the available limited collections of normal tissues from postmortal donors, there is a problem of data incompatibility, as different datasets generated using different experimental platforms often cannot be merged in a single panel. Here, we constructed and deposited the gene expression database of normal human tissues based on uniformly screened original sequencing data. In total, 142 solid tissue samples representing 20 organs were taken from post-mortal human healthy donors of different age killed in road accidents no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. We then compared them with the 758 transcriptomic profiles taken from the other databases. We found that overall 463 biosamples showed tissue-specific rather than platform- or database-specific clustering and could be aggregated in a single database termed Oncobox Atlas of Normal Tissue Expression (ANTE). Our data will be useful to all those working with the analysis of human gene expression.
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Affiliation(s)
- Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | - Nurshat Gaifullin
- Department of Pathology, Faculty of Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Daria Allina
- Pathology Department, Morozov Children's City Hospital, 4th Dobryninsky Lane 1/9, Moscow, 119049, Russia
| | | | - Xinmin Li
- Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Larisa Mendeleeva
- National Research Center for Hematology, Novy Zykovsky proezd, 4, Moscow, 125167, Russia
| | - Vadim Surin
- National Research Center for Hematology, Novy Zykovsky proezd, 4, Moscow, 125167, Russia
| | - Anna Sergeeva
- National Research Center for Hematology, Novy Zykovsky proezd, 4, Moscow, 125167, Russia
| | - Pavel Spirin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilova Street, 32, Moscow, 119991, Russia
| | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Vavilova Street, 32, Moscow, 119991, Russia
| | | | - Andrew Garazha
- Omicsway Corp., 340S Lemon Ave, 6040, Walnut, 91789 CA, USA
- Oncobox ltd., Moscow, 121205, Russia
| | - Maxim Sorokin
- Omicsway Corp., 340S Lemon Ave, 6040, Walnut, 91789 CA, USA.
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | - Anton Buzdin
- Omicsway Corp., 340S Lemon Ave, 6040, Walnut, 91789 CA, USA
- Oncobox ltd., Moscow, 121205, Russia
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
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15
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Petrov I, Suntsova M, Ilnitskaya E, Roumiantsev S, Sorokin M, Garazha A, Spirin P, Lebedev T, Gaifullin N, Larin S, Kovalchuk O, Konovalov D, Prassolov V, Roumiantsev A, Buzdin A. Gene expression and molecular pathway activation signatures of MYCN-amplified neuroblastomas. Oncotarget 2017; 8:83768-83780. [PMID: 29137381 PMCID: PMC5663553 DOI: 10.18632/oncotarget.19662] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 05/05/2017] [Indexed: 12/30/2022] Open
Abstract
Neuroblastoma is a pediatric cancer arising from sympathetic nervous system. Remarkable heterogeneity in outcomes is one of its widely known features. One of the traits strongly associated with the unfavorable subtype is the amplification of oncogene MYCN. Here, we performed cross-platform biomarker detection by comparing gene expression and pathway activation patterns from the two literature reports and from our experimental dataset, combining profiles for the 761 neuroblastoma patients with known MYCN amplification status. We identified 109 / 25 gene expression / pathway activation biomarkers strongly linked with the MYCN amplification. The marker genes/pathways are involved in the processes of purine nucleotide biosynthesis, ATP-binding, tetrahydrofolate metabolism, building mitochondrial matrix, biosynthesis of amino acids, tRNA aminoacylation and NADP-linked oxidation-reduction processes, as well as in the tyrosine phosphatase activity, p53 signaling, cell cycle progression and the G1/S and G2/M checkpoints. To connect molecular functions of the genes involved in MYCN-amplified phenotype, we built a new molecular pathway using known intracellular protein interaction networks. The activation of this pathway was highly selective in discriminating MYCN-amplified neuroblastomas in all three datasets. Our data also suggest that the phosphoinositide 3-kinase (PI3K) inhibitors may provide new opportunities for the treatment of the MYCN-amplified neuroblastoma subtype.
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Affiliation(s)
- Ivan Petrov
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,First Oncology Research and Advisory Center, Moscow, Russia.,Moscow Institute of Physics and Technology, Moscow, Russia.,V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia
| | - Maria Suntsova
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | - Sergey Roumiantsev
- Department of Oncology, Hematology and Radiology, N.I.Pirogov Russian National Research Medical University, Moscow, Russia
| | - Maxim Sorokin
- National Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia.,Pathway Pharmaceuticals, Hong Kong, China
| | - Andrew Garazha
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Centre for Biogerontology and Regenerative Medicine, IC Skolkovo, Moscow, Russia
| | - Pavel Spirin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Mosow, Russia
| | - Timofey Lebedev
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Mosow, Russia
| | - Nurshat Gaifullin
- Moscow State University, Faculty of Fundamental Medicine, Moscow, Russia
| | - Sergey Larin
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Olga Kovalchuk
- Department of Biological Sciences, University of Lethbridge, Lethbridge, Canada
| | - Dmitry Konovalov
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Federal State Budgetary Educational Institution of Further Professional Education "Russian Medical Academy of Continuous Professional Education" of the Ministry of Healthcare of the Russian Federation, Moscow, Russia
| | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Mosow, Russia
| | - Alexander Roumiantsev
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Anton Buzdin
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,National Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
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16
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Buzdin A, Sorokin M, Glusker A, Garazha A, Poddubskaya E, Shirokorad V, Naskhletashvili D, Kashintsev K, Sokov D, Suntsova M, Roumiantsev S, Kovalchuk O, Gaifullin N, Tkachev V, Borisov N. Activation of intracellular signaling pathways as a new type of biomarkers for selection of target anticancer drugs. J Clin Oncol 2017. [DOI: 10.1200/jco.2017.35.15_suppl.e23142] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e23142 Background: Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in tumorigenesis. More than 150 different ATDs have been approved for clinical use worldwide, and the clinicians are faced with the problem of choosing the best therapeutic solution for each patient. The problem of efficient ATD selection remains largely unsolved and personalized approaches are needed to select the best ATD candidates for individual patients. Methods: We propose a new approach termed OncoFinder. It is based on digesting gene expression profiles for the analysis of activation of intracellular signalling pathways as a marker for the selection of target therapies. The original bioinformatic algorithms were integrated with the databases featuring molecular drug targets, compositions of signalling pathways, including the functional role of each gene product, for more than 1700 pathways (Buzdin, Front.Genet 2014; Ozerov, Nature Communications 2016). Results: We showed that pathway activation strengths are more stable and reliable biomarkers of cancer than the expressions of individual genes. OncoFinder allows to detect changes at the level of pathway activation and to predict the effectiveness of drugs based on the knowledge of their molecular targets. We applied it to find new biomarkers of clinical response to the ATD cetuximab; for modelling the combined chemotherapy of acute myeloid leukemia and combined anti-VEGF/BRAF therapy of melanoma. For two unrelated datasets obtained for colon cancer patients before treatment with the ATD bevacizumab, we were able to distinguish between those who responded to treatment and not (p < 0.01). We next assayed biopsies for kidney cancer patients with known responses to the ATD sorafenib. The responders and non-responders showed a significant difference (p = 0.02). Finally, the OncoFinder platform was prospectively used for decision making support to patients with advanced metastatic solid tumors (n = 23). The efficiency of the ATD treatment was 61% (complete + partial response, RECIST). Conclusions: OncoFinder method may be effective for predicting response to ATD based on high throughput gene expression profiles.
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Affiliation(s)
- Anton Buzdin
- First Oncology Research and Advisory Center, Moscow, Russian Federation
| | | | - Alexander Glusker
- First Oncology Research and Advisory Center, Moscow, Russian Federation
| | | | | | | | | | | | - Dmitry Sokov
- 1st Moscow Oncological Clinical Dispenser, Moscow, Russian Federation
| | | | | | | | - Nurshat Gaifullin
- M.V. Lomonosov Moscow State University, Faculty of Fundamental Medicine, Moscow, Russian Federation
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Artcibasova AV, Korzinkin MB, Sorokin MI, Shegay PV, Zhavoronkov AA, Gaifullin N, Alekseev BY, Vorobyev NV, Kuzmin DV, Kaprin АD, Borisov NM, Buzdin AA. MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways. Cell Cycle 2016; 15:689-98. [PMID: 27027999 PMCID: PMC4845938 DOI: 10.1080/15384101.2016.1147633] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs - known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets – miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.
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Affiliation(s)
- Alina V Artcibasova
- a Pathway Pharmaceuticals , Wan Chai , Hong Kong, Hong Kong SAR.,b Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology , Moscow , Russia
| | | | - Maksim I Sorokin
- a Pathway Pharmaceuticals , Wan Chai , Hong Kong, Hong Kong SAR.,c First Oncology Research and Advisory Center , Moscow , Russia
| | - Peter V Shegay
- d P.A. Herzen Moscow Oncological Research Institute , Moscow , Russia
| | - Alex A Zhavoronkov
- b Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology , Moscow , Russia
| | - Nurshat Gaifullin
- e Moscow State University, Faculty of Fundamental Medicine , Moscow , Russia
| | - Boris Y Alekseev
- d P.A. Herzen Moscow Oncological Research Institute , Moscow , Russia
| | | | - Denis V Kuzmin
- f Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry , Moscow , Russia
| | - Аndrey D Kaprin
- d P.A. Herzen Moscow Oncological Research Institute , Moscow , Russia
| | - Nikolay M Borisov
- g National Research Centre "Kurchatov Institute," Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies , Moscow , Russia
| | - Anton A Buzdin
- b Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology , Moscow , Russia.,f Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry , Moscow , Russia.,g National Research Centre "Kurchatov Institute," Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies , Moscow , Russia
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18
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Shepelin D, Korzinkin M, Vanyushina A, Aliper A, Borisov N, Vasilov R, Zhukov N, Sokov D, Prassolov V, Gaifullin N, Zhavoronkov A, Bhullar B, Buzdin A. Molecular pathway activation features linked with transition from normal skin to primary and metastatic melanomas in human. Oncotarget 2016; 7:656-70. [PMID: 26624979 PMCID: PMC4808024 DOI: 10.18632/oncotarget.6394] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Accepted: 11/11/2015] [Indexed: 12/14/2022] Open
Abstract
Melanoma is the most aggressive and dangerous type of skin cancer, but its molecular mechanisms remain largely unclear. For transcriptomic data of 478 primary and metastatic melanoma, nevi and normal skin samples, we performed high-throughput analysis of intracellular molecular networks including 592 signaling and metabolic pathways. We showed that at the molecular pathway level, the formation of nevi largely resembles transition from normal skin to primary melanoma. Using a combination of bioinformatic machine learning algorithms, we identified 44 characteristic signaling and metabolic pathways connected with the formation of nevi, development of primary melanoma, and its metastases. We created a model describing formation and progression of melanoma at the level of molecular pathway activation. We discovered six novel associations between activation of metabolic molecular pathways and progression of melanoma: for allopregnanolone biosynthesis, L-carnitine biosynthesis, zymosterol biosynthesis (inhibited in melanoma), fructose 2, 6-bisphosphate synthesis and dephosphorylation, resolvin D biosynthesis (activated in melanoma), D-myo-inositol hexakisphosphate biosynthesis (activated in primary, inhibited in metastatic melanoma). Finally, we discovered fourteen tightly coordinated functional clusters of molecular pathways. This study helps to decode molecular mechanisms underlying the development of melanoma.
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Affiliation(s)
- Denis Shepelin
- Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.,Group for Genomic Analysis of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Mikhail Korzinkin
- Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.,First Oncology Research and Advisory Center, Moscow, Russia
| | - Anna Vanyushina
- Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Alexander Aliper
- Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Nicolas Borisov
- First Oncology Research and Advisory Center, Moscow, Russia.,National Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
| | - Raif Vasilov
- National Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
| | - Nikolay Zhukov
- First Oncology Research and Advisory Center, Moscow, Russia.,Pirogov Russian National Research Medical University, Department of Oncology, Hematology and Radiotherapy, Moscow, Russia
| | | | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Mosow, Russia
| | - Nurshat Gaifullin
- Moscow State University, Faculty of Fundamental Medicine, Moscow, Russia
| | - Alex Zhavoronkov
- Insilico Medicine, Inc, ETC, Johns Hopkins University, Baltimore, MD, USA
| | | | - Anton Buzdin
- Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.,Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,National Research Centre "Kurchatov Institute", Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
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19
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Artemov A, Aliper A, Korzinkin M, Lezhnina K, Jellen L, Zhukov N, Roumiantsev S, Gaifullin N, Zhavoronkov A, Borisov N, Buzdin A. A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation. Oncotarget 2016; 6:29347-56. [PMID: 26320181 PMCID: PMC4745731 DOI: 10.18632/oncotarget.5119] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Accepted: 07/24/2015] [Indexed: 02/07/2023] Open
Abstract
A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.
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Affiliation(s)
- Artem Artemov
- Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.,D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Alexander Aliper
- D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,First Oncology Research and Advisory Center, Moscow, Russia
| | | | | | - Leslie Jellen
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Nikolay Zhukov
- D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,First Oncology Research and Advisory Center, Moscow, Russia.,Pirogov Russian National Research Medical University, Department of Oncology, Hematology and Radiotherapy, Moscow, Russia
| | - Sergey Roumiantsev
- D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Pirogov Russian National Research Medical University, Department of Oncology, Hematology and Radiotherapy, Moscow, Russia
| | - Nurshat Gaifullin
- Moscow State University, Faculty of Fundamental Medicine, Moscow, Russia
| | - Alex Zhavoronkov
- Insilico Medicine, Inc., ETC, Johns Hopkins University, Baltimore, MD, USA
| | | | - Anton Buzdin
- Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.,D. Rogachyov Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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Alekseev B, Vorobyev N, Shegay P, Zabolotneva A, Rusakov I, Buzdin A, Gaifullin N, Kovalchuk O. MP22-18 IDENTIFICATION OF NOVEL GENE EXPRESSION MARKERS FOR BLADDER CANCER DIAGNOSTICS. J Urol 2014. [DOI: 10.1016/j.juro.2014.02.866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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21
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Baskaev K, Garazha A, Gaifullin N, Suntsova MV, Zabolotneva AA, Buzdin AA. nMETR: technique for facile recovery of hypomethylation genomic tags. Gene 2012; 498:75-80. [PMID: 22353364 DOI: 10.1016/j.gene.2012.01.097] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2011] [Revised: 01/28/2012] [Accepted: 01/30/2012] [Indexed: 11/27/2022]
Abstract
Genome-wide methylation studies frequently lack adequate controls to estimate proportions of background reads in the resulting datasets. To generate appropriate control pools, we developed technique termed nMETR (non-methylated tag recovery) based on digestion of genomic DNA with methylation-sensitive restriction enzyme, ligation of adapter oligonucleotide and PCR amplification of non-methylated sites associated with genomic repetitive elements. The protocol takes only two working days to generate amplicons for deep sequencing. We applied nMETR for human DNA using BspFNI enzyme and retrotransposon Alu-specific primers. 454-sequencing enabled identification of 1113 nMETR tag sites, of them ~65% were parts of CpG islands. Representation of reads inversely correlated with methylation levels, thus confirming nMETR fidelity. We created software that eliminates background reads and enables to map and annotate individual tags on human genome. nMETR tags may serve as the controls for large-scale epigenetic studies and for identifying unmethylated transposable elements located close to genomic CpG islands.
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Affiliation(s)
- Konstantin Baskaev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 16/10 Miklukho-Maklaya, Moscow 117997, Russia
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