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Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2021; 127:1-53. [PMID: 34340765 DOI: 10.1016/bs.apcsb.2021.02.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.
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Borisov N, Sorokin M, Garazha A, Buzdin A. Quantitation of Molecular Pathway Activation Using RNA Sequencing Data. Methods Mol Biol 2020; 2063:189-206. [PMID: 31667772 DOI: 10.1007/978-1-0716-0138-9_15] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Intracellular molecular pathways (IMPs) control all major events in the living cell. IMPs are considered hotspots in biomedical sciences and thousands of IMPs have been discovered for humans and model organisms. Knowledge of IMPs activation is essential for understanding biological functions and differences between the biological objects at the molecular level. Here we describe the Oncobox system for accurate quantitative scoring activities of up to several thousand molecular pathways based on high throughput molecular data. Although initially designed for gene expression and mainly RNA sequencing data, Oncobox is now also applicable for quantitative proteomics, microRNA and transcription factor binding sites mapping data. The Oncobox system includes modules of gene expression data harmonization, aggregation and comparison and a recursive algorithm for automatic annotation of molecular pathways. The universal rationale of Oncobox enables scoring of signaling, metabolic, cytoskeleton, immunity, DNA repair, and other pathways in a multitude of biological objects. The Oncobox system can be helpful to all those working in the fields of genetics, biochemistry, interactomics, and big data analytics in molecular biomedicine.
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Affiliation(s)
- Nicolas Borisov
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Omicsway Corp., Walnut, CA, USA
| | - Maxim Sorokin
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Omicsway Corp., Walnut, CA, USA
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | - Anton Buzdin
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
- Omicsway Corp., Walnut, CA, USA.
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.
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Zolotovskaia M, Sorokin M, Garazha A, Borisov N, Buzdin A. Molecular Pathway Analysis of Mutation Data for Biomarkers Discovery and Scoring of Target Cancer Drugs. Methods Mol Biol 2020; 2063:207-234. [PMID: 31667773 DOI: 10.1007/978-1-0716-0138-9_16] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
DNA mutations govern cancer development. Cancer mutation profiles vary dramatically among the individuals. In some cases, they may serve as the predictors of disease progression and response to therapies. However, the biomarker potential of cancer mutations can be dramatically (several orders of magnitude) enhanced by applying molecular pathway-based approach. We developed Oncobox system for calculation of pathway instability (PI) values for the molecular pathways that are aggregated mutation frequencies of the pathway members normalized on gene lengths and on number of genes in the pathway. PI scores can be effective biomarkers in different types of comparisons, for example, as the cancer type biomarkers and as the predictors of tumor response to target therapies. The latter option is implemented using mutation drug score (MDS) values, which algorithmically rank the drugs capacity of interfering with the mutated molecular pathways. Here, describe the mathematical basis and algorithms for PI and MDS values calculation, validation and implementation. The example analysis is provided encompassing 5956 human tumor mutation profiles of 15 cancer types from The Cancer Genome Atlas (TCGA) project, that totally make 2,316,670 mutations in 19,872 genes and 1748 molecular pathways, thus enabling ranking of 128 clinically approved target drugs. Our results evidence that the Oncobox PI and MDS approaches are highly useful for basic and applied aspects of molecular oncology and pharmacology research.
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Affiliation(s)
- Marianna Zolotovskaia
- Omicsway Corp., Walnut, CA, USA
- Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Maxim Sorokin
- Omicsway Corp., Walnut, CA, USA
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | - Nikolay Borisov
- Omicsway Corp., Walnut, CA, USA
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton Buzdin
- Omicsway Corp., Walnut, CA, USA.
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.
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Zolotovskaia MA, Sorokin MI, Emelianova AA, Borisov NM, Kuzmin DV, Borger P, Garazha AV, Buzdin AA. Pathway Based Analysis of Mutation Data Is Efficient for Scoring Target Cancer Drugs. Front Pharmacol 2019; 10:1. [PMID: 30728774 PMCID: PMC6351482 DOI: 10.3389/fphar.2019.00001] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 01/03/2019] [Indexed: 12/20/2022] Open
Abstract
Despite the significant achievements in chemotherapy, cancer remains one of the leading causes of death. Target therapy revolutionized this field, but efficiencies of target drugs show dramatic variation among individual patients. Personalization of target therapies remains, therefore, a challenge in oncology. Here, we proposed molecular pathway-based algorithm for scoring of target drugs using high throughput mutation data to personalize their clinical efficacies. This algorithm was validated on 3,800 exome mutation profiles from The Cancer Genome Atlas (TCGA) project for 128 target drugs. The output values termed Mutational Drug Scores (MDS) showed positive correlation with the published drug efficiencies in clinical trials. We also used MDS approach to simulate all known protein coding genes as the putative drug targets. The model used was built on the basis of 18,273 mutation profiles from COSMIC database for eight cancer types. We found that the MDS algorithm-predicted hits frequently coincide with those already used as targets of the existing cancer drugs, but several novel candidates can be considered promising for further developments. Our results evidence that the MDS is applicable to ranking of anticancer drugs and can be applied for the identification of novel molecular targets.
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Affiliation(s)
- Marianna A Zolotovskaia
- Oncobox Ltd., Moscow, Russia.,Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Maxim I Sorokin
- The Laboratory of Clinical Bioinformatics, IM Sechenov First Moscow State Medical University, Moscow, Russia.,Omicsway Corp., Walnut, CA, United States.,Science-Educational Center Department, M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Anna A Emelianova
- Science-Educational Center Department, M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Nikolay M Borisov
- The Laboratory of Clinical Bioinformatics, IM Sechenov First Moscow State Medical University, Moscow, Russia.,Omicsway Corp., Walnut, CA, United States
| | - Denis V Kuzmin
- Science-Educational Center Department, M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Pieter Borger
- Laboratory of the Swiss Hepato-Pancreato-Biliary, Department of Surgery, Transplantation Center, University Hospital Zurich, Zurich, Switzerland
| | | | - Anton A Buzdin
- Oncobox Ltd., Moscow, Russia.,The Laboratory of Clinical Bioinformatics, IM Sechenov First Moscow State Medical University, Moscow, Russia.,Science-Educational Center Department, M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
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Molecular pathway activation – New type of biomarkers for tumor morphology and personalized selection of target drugs. Semin Cancer Biol 2018; 53:110-124. [DOI: 10.1016/j.semcancer.2018.06.003] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 06/19/2018] [Accepted: 06/19/2018] [Indexed: 02/06/2023]
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Hung ML, McWilliams JP. Portal vein embolization prior to hepatectomy: Techniques, outcomes and novel therapeutic approaches. INTERNATIONAL JOURNAL OF GASTROINTESTINAL INTERVENTION 2018. [DOI: 10.18528/gii180010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
- Matthew L. Hung
- Division of Interventional Radiology, Department of Radiology, UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Justin P. McWilliams
- Division of Interventional Radiology, Department of Radiology, UCLA Medical Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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Emond J. Commentary on: Temporary portal vein embolization is as efficient as permanent portal vein embolization in mice. Surgery 2017; 162:82-83. [PMID: 28389023 DOI: 10.1016/j.surg.2017.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 02/17/2017] [Indexed: 11/25/2022]
Affiliation(s)
- Jean Emond
- College of Physicians and Surgeons of Columbia University, Center for Liver Disease and Transplantation, New York, NY.
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