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Drobyshev A, Modestov A, Suntsova M, Poddubskaya E, Seryakov A, Moisseev A, Sorokin M, Tkachev V, Zakharova G, Simonov A, Zolotovskaia MA, Buzdin A. Pan-cancer experimental characteristic of human transcriptional patterns connected with telomerase reverse transcriptase ( TERT) gene expression status. Front Genet 2024; 15:1401100. [PMID: 38859942 PMCID: PMC11163056 DOI: 10.3389/fgene.2024.1401100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/08/2024] [Indexed: 06/12/2024] Open
Abstract
The TERT gene encodes the reverse transcriptase subunit of telomerase and is normally transcriptionally suppressed in differentiated human cells but reactivated in cancers where its expression is frequently associated with poor survival prognosis. Here we experimentally assessed the RNA sequencing expression patterns associated with TERT transcription in 1039 human cancer samples of 27 tumor types. We observed a bimodal distribution of TERT expression where ∼27% of cancer samples did not express TERT and the rest showed a bell-shaped distribution. Expression of TERT strongly correlated with 1443 human genes including 103 encoding transcriptional factor proteins. Comparison of TERT- positive and negative cancers showed the differential activation of 496 genes and 1975 molecular pathways. Therein, 32/38 (84%) of DNA repair pathways were hyperactivated in TERT+ cancers which was also connected with accelerated replication, transcription, translation, and cell cycle progression. In contrast, the level of 40 positive cell cycle regulator proteins and a set of epithelial-to-mesenchymal transition pathways was specific for the TERT- group suggesting different proliferation strategies for both groups of cancer. Our pilot study showed that the TERT+ group had ∼13% of cancers with C228T or C250T mutated TERT promoter. However, the presence of promoter mutations was not associated with greater TERT expression compared with other TERT+ cancers, suggesting parallel mechanisms of its transcriptional activation in cancers. In addition, we detected a decreased expression of L1 retrotransposons in the TERT+ group, and further decreased L1 expression in promoter mutated TERT+ cancers. TERT expression was correlated with 17 genes encoding molecular targets of cancer therapeutics and may relate to differential survival patterns of TERT- positive and negative cancers.
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Affiliation(s)
- Aleksey Drobyshev
- Endocrinology Research Center, Moscow, Russia
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Alexander Modestov
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maria Suntsova
- Endocrinology Research Center, Moscow, Russia
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Elena Poddubskaya
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
- Clinical Center Vitamed, Moscow, Russia
| | | | - Aleksey Moisseev
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maksim Sorokin
- Endocrinology Research Center, Moscow, Russia
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | - Galina Zakharova
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Aleksander Simonov
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marianna A. Zolotovskaia
- Endocrinology Research Center, Moscow, Russia
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
- Moscow Center for Advanced Studies 20, Moscow, Russia
| | - Anton Buzdin
- Endocrinology Research Center, Moscow, Russia
- Institute of Personalized Oncology, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
- Moscow Center for Advanced Studies 20, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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2
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Ruiz-Arenas C, Marín-Goñi I, Wang L, Ochoa I, Pérez-Jurado L, Hernaez M. NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders. Nucleic Acids Res 2024; 52:e44. [PMID: 38597610 PMCID: PMC11109970 DOI: 10.1093/nar/gkae197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/23/2024] [Accepted: 03/12/2024] [Indexed: 04/11/2024] Open
Abstract
Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples. NetActivity generates GSAS robust to the initialization parameters and representative of the original transcriptome, and assigned higher importance to more biologically relevant genes. Moreover, NetActivity returns GSAS with a more consistent definition and higher interpretability than GSVA and hipathia, state-of-the-art gene set projection methods. Finally, NetActivity enables combining bulk RNA-seq and microarray datasets in a meta-analysis of prostate cancer progression, highlighting gene sets related to cell division, key for disease progression. When applied to metastatic prostate cancer, gene sets associated with cancer progression were also altered due to drug resistance, while a classical enrichment analysis identified gene sets irrelevant to the phenotype. NetActivity is publicly available in Bioconductor and GitHub.
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Affiliation(s)
- Carlos Ruiz-Arenas
- Computational Biology Program, CIMA University of Navarra, idiSNA, Pamplona 31008, Spain
- Department MELIS, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Irene Marín-Goñi
- Computational Biology Program, CIMA University of Navarra, idiSNA, Pamplona 31008, Spain
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA
| | - Idoia Ochoa
- Department of Electrical and Electronics Engineering, Tecnun, University of Navarra, Donostia, Spain
- Institute for Data Science and Artificial Inteligence (DATAI), University of Navarra, Pamplona 31008, Spain
| | - Luis A Pérez-Jurado
- Department MELIS, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain
- Genetics Service, Hospital del Mar & Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - Mikel Hernaez
- Computational Biology Program, CIMA University of Navarra, idiSNA, Pamplona 31008, Spain
- Institute for Data Science and Artificial Inteligence (DATAI), University of Navarra, Pamplona 31008, Spain
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3
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Raevskiy M, Sorokin M, Emelianova A, Zakharova G, Poddubskaya E, Zolotovskaia M, Buzdin A. Sample-Wise and Gene-Wise Comparisons Confirm a Greater Similarity of RNA and Protein Expression Data at the Level of Molecular Pathways and Suggest an Approach for the Data Quality Check in High-Throughput Expression Databases. BIOCHEMISTRY. BIOKHIMIIA 2024; 89:737-746. [PMID: 38831509 DOI: 10.1134/s0006297924040126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 06/05/2024]
Abstract
Identification of genes and molecular pathways with congruent profiles in the proteomic and transcriptomic datasets may result in the discovery of promising transcriptomic biomarkers that would be more relevant to phenotypic changes. In this study, we conducted comparative analysis of 943 paired RNA and proteomic profiles obtained for the same samples of seven human cancer types from The Cancer Genome Atlas (TCGA) and NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) [two major open human cancer proteomic and transcriptomic databases] that included 15,112 protein-coding genes and 1611 molecular pathways. Overall, our findings demonstrated statistically significant improvement of the congruence between RNA and proteomic profiles when performing analysis at the level of molecular pathways rather than at the level of individual gene products. Transition to the molecular pathway level of data analysis increased the correlation to 0.19-0.57 (Pearson) and 0.14-057 (Spearman), or 2-3-fold for some cancer types. Evaluating the gain of the correlation upon transition to the data analysis the pathway level can be used to refine the omics data by identifying outliers that can be excluded from the comparison of RNA and proteomic profiles. We suggest using sample- and gene-wise correlations for individual genes and molecular pathways as a measure of quality of RNA/protein paired molecular data. We also provide a database of human genes, molecular pathways, and samples related to the correlation between RNA and protein products to facilitate an exploration of new cancer transcriptomic biomarkers and molecular mechanisms at different levels of human gene expression.
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Affiliation(s)
- Mikhail Raevskiy
- Digital Biodesign and Personalized Healthcare Research Center, Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | - Maxim Sorokin
- Omicsway Corp., Walnut, CA 91789, USA.
- Oncobox Ltd., Moscow, 121205, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia
| | - Aleksandra Emelianova
- Digital Biodesign and Personalized Healthcare Research Center, Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | - Galina Zakharova
- Digital Biodesign and Personalized Healthcare Research Center, Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | - Elena Poddubskaya
- Digital Biodesign and Personalized Healthcare Research Center, Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | - Marianna Zolotovskaia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia.
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Anton Buzdin
- Digital Biodesign and Personalized Healthcare Research Center, Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
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Borisov N, Tkachev V, Simonov A, Sorokin M, Kim E, Kuzmin D, Karademir-Yilmaz B, Buzdin A. Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns. Front Mol Biosci 2023; 10:1237129. [PMID: 37745690 PMCID: PMC10511763 DOI: 10.3389/fmolb.2023.1237129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/28/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction: Co-normalization of RNA profiles obtained using different experimental platforms and protocols opens avenue for comprehensive comparison of relevant features like differentially expressed genes associated with disease. Currently, most of bioinformatic tools enable normalization in a flexible format that depends on the individual datasets under analysis. Thus, the output data of such normalizations will be poorly compatible with each other. Recently we proposed a new approach to gene expression data normalization termed Shambhala which returns harmonized data in a uniform shape, where every expression profile is transformed into a pre-defined universal format. We previously showed that following shambhalization of human RNA profiles, overall tissue-specific clustering features are strongly retained while platform-specific clustering is dramatically reduced. Methods: Here, we tested Shambhala performance in retention of fold-change gene expression features and other functional characteristics of gene clusters such as pathway activation levels and predicted cancer drug activity scores. Results: Using 6,793 cancer and 11,135 normal tissue gene expression profiles from the literature and experimental datasets, we applied twelve performance criteria for different versions of Shambhala and other methods of transcriptomic harmonization with flexible output data format. Such criteria dealt with the biological type classifiers, hierarchical clustering, correlation/regression properties, stability of drug efficiency scores, and data quality for using machine learning classifiers. Discussion: Shambhala-2 harmonizer demonstrated the best results with the close to 1 correlation and linear regression coefficients for the comparison of training vs validation datasets and more than two times lesser instability for calculation of drug efficiency scores compared to other methods.
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Affiliation(s)
- Nicolas Borisov
- Omicsway Corp, Walnut, CA, United States
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | | | - Alexander Simonov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Oncobox Ltd., Moscow, Russia
| | - Maxim Sorokin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Oncobox Ltd., Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Ella Kim
- Clinic for Neurosurgery, Laboratory of Experimental Neurooncology, Johannes Gutenberg University Medical Centre, Mainz, Germany
| | - Denis Kuzmin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Betul Karademir-Yilmaz
- Department of Biochemistry, School of Medicine/Genetic and Metabolic Diseases Research and Investigation Center (GEMHAM) Marmara University, Istanbul, Türkiye
| | - Anton Buzdin
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium
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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] [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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Liu H, Han Y, Liu Z, Gao L, Yi T, Yu Y, Wang Y, Qu P, Xiang L, Li Y. Depiction of neuroendocrine features associated with immunotherapy response using a novel one-class predictor in lung adenocarcinoma. Discov Oncol 2023; 14:71. [PMID: 37199872 DOI: 10.1007/s12672-023-00693-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/12/2023] [Indexed: 05/19/2023] Open
Abstract
BACKGROUND Tumours with no evidence of neuroendocrine transformation histologically but harbouring neuroendocrine features are collectively referred to as non-small cell lung cancer (NSCLC) with neuroendocrine differentiation (NED). Investigating the mechanisms underlying NED is conducive to designing appropriate treatment options for NSCLC patients. METHODS In the present study, we integrated multiple lung cancer datasets to identify neuroendocrine features using a one-class logistic regression (OCLR) machine learning algorithm trained on small cell lung cancer (SCLC) cells, a pulmonary neuroendocrine cell type, based on the transcriptome of NSCLC and named the NED index (NEDI). Single-sample gene set enrichment analysis, pathway enrichment analysis, ESTIMATE algorithm analysis, and unsupervised subclass mapping (SubMap) were performed to assess the altered pathways and immune characteristics of lung cancer samples with different NEDI values. RESULTS We developed and validated a novel one-class predictor based on the expression values of 13,279 mRNAs to quantitatively evaluate neuroendocrine features in NSCLC. We observed that a higher NEDI correlated with better prognosis in patients with LUAD. In addition, we observed that a higher NEDI was significantly associated with reduced immune cell infiltration and immune effector molecule expression. Furthermore, we found that etoposide-based chemotherapy might be more effective in the treatment of LUAD with high NEDI values. Moreover, we noted that tumours with low NEDI values had better responses to immunotherapy than those with high NEDI values. CONCLUSIONS Our findings improve the understanding of NED and provide a useful strategy for applying NEDI-based risk stratification to guide decision-making in the treatment of LUAD.
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Affiliation(s)
- Hao Liu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Yan Han
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Zhantao Liu
- Department of Oncology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No.136 Jingzhou Street, Xiangyang, 441021, Hubei, People's Republic of China
| | - Liping Gao
- Department of Gastroenterology, Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Zhongnan Hospital of Wuhan University, Wuhan, 430072, Hubei, People's Republic of China
| | - Tienan Yi
- Department of Oncology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No.136 Jingzhou Street, Xiangyang, 441021, Hubei, People's Republic of China
| | - Yuandong Yu
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Yu Wang
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Ping Qu
- Department of Science and Education, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Longchao Xiang
- Department of Oncology, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China
| | - Yong Li
- Department of Oncology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No.136 Jingzhou Street, Xiangyang, 441021, Hubei, People's Republic of China.
- Institute of Cancer Research, Renmin Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, People's Republic of China.
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Pan-cancer antagonistic inhibition pattern of ATM-driven G2/M checkpoint pathway vs other DNA repair pathways. DNA Repair (Amst) 2023; 123:103448. [PMID: 36657260 DOI: 10.1016/j.dnarep.2023.103448] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/22/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
DNA repair mechanisms keep genome integrity and limit tumor-associated alterations and heterogeneity, but on the other hand they promote tumor survival after radiation and genotoxic chemotherapies. We screened pathway activation levels of 38 DNA repair pathways in nine human cancer types (gliomas, breast, colorectal, lung, thyroid, cervical, kidney, gastric, and pancreatic cancers). We took RNAseq profiles of the experimental 51 normal and 408 tumor samples, and from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium databases - of 500/407 normal and 5752/646 tumor samples, and also 573 normal and 984 tumor proteomic profiles from Proteomic Data Commons portal. For all the samplings we observed a congruent trend that all cancer types showed inhibition of G2/M arrest checkpoint pathway compared to the normal samples, and relatively low activities of p53-mediated pathways. In contrast, other DNA repair pathways were upregulated in most of the cancer types. The G2/M checkpoint pathway was statistically significantly downregulated compared to the other DNA repair pathways, and this inhibition was strongly impacted by antagonistic regulation of (i) promitotic genes CCNB and CDK1, and (ii) GADD45 genes promoting G2/M arrest. At the DNA level, we found that ATM, TP53, and CDKN1A genes accumulated loss of function mutations, and cyclin B complex genes - transforming mutations. These findings suggest importance of activation for most of DNA repair pathways in cancer progression, with remarkable exceptions of G2/M checkpoint and p53-related pathways which are downregulated and neutrally activated, respectively.
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Zolotovskaia MA, Kovalenko MA, Tkachev VS, Simonov AM, Sorokin MI, Kim E, Kuzmin DV, Karademir-Yilmaz B, Buzdin AA. Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways. Int J Mol Sci 2022; 23:ijms23137330. [PMID: 35806337 PMCID: PMC9266372 DOI: 10.3390/ijms23137330] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 06/24/2022] [Accepted: 06/25/2022] [Indexed: 02/04/2023] Open
Abstract
In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.
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Affiliation(s)
- Marianna A. Zolotovskaia
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (M.A.K.); (A.M.S.); (M.I.S.); (D.V.K.)
- Correspondence: ; Tel.: +7-9165612175
| | - Max A. Kovalenko
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (M.A.K.); (A.M.S.); (M.I.S.); (D.V.K.)
| | | | - Alexander M. Simonov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (M.A.K.); (A.M.S.); (M.I.S.); (D.V.K.)
- Omicsway Corp., Walnut, CA 91789, USA;
| | - Maxim I. Sorokin
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (M.A.K.); (A.M.S.); (M.I.S.); (D.V.K.)
- Omicsway Corp., Walnut, CA 91789, USA;
- Laboratory of Clinical and Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
| | - Ella Kim
- Clinic for Neurosurgery, Laboratory of Experimental Neurooncology, Johannes Gutenberg University Medical Centre, Langenbeckstrasse 1, 55124 Mainz, Germany;
| | - Denis V. Kuzmin
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (M.A.K.); (A.M.S.); (M.I.S.); (D.V.K.)
| | - Betul Karademir-Yilmaz
- Department of Biochemistry, School of Medicine/Genetic and Metabolic Diseases Research and Investigation Center (GEMHAM), Marmara University, Istanbul 34854, Turkey;
| | - Anton A. Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia;
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
- PathoBiology Group, European Organization for Research and Treatment of Cancer (EORTC), 1200 Brussels, Belgium
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9
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Borisov N, Sorokin M, Zolotovskaya M, Borisov C, Buzdin A. Shambhala-2: A Protocol for Uniformly Shaped Harmonization of Gene Expression Profiles of Various Formats. Curr Protoc 2022; 2:e444. [PMID: 35617464 DOI: 10.1002/cpz1.444] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Uniformly shaped harmonization of gene expression profiles is central for the simultaneous comparison of multiple gene expression datasets. It is expected to operate with the gene expression data obtained using various experimental methods and equipment, and to return harmonized profiles in a uniform shape. Such uniformly shaped expression profiles from different initial datasets can be further compared directly. However, current harmonization techniques have strong limitations that prevent their broad use for bioinformatic applications. They can either operate with only up to two datasets/platforms or return data in a dynamic format that will be different for every comparison under analysis. This also does not allow for adding new data to the previously harmonized dataset(s), which complicates the analysis and increases calculation costs. We propose here a new method termed Shambhala-2 that can transform multi-platform expression data into a universal format that is identical for all harmonizations made using this technique. Shambhala-2 is based on sample-by-sample cubic conversion of the initial expression dataset into a preselected shape of the reference definitive dataset. Using 8390 samples of 12 healthy human tissue types and 4086 samples of colorectal, kidney, and lung cancer tissues, we verified Shambhala-2's capacity in restoring tissue-specific expression patterns for seven microarray and three RNA sequencing platforms. Shambhala-2 performed well for all tested combinations of RNAseq and microarray profiles, and retained gene-expression ranks, as evidenced by high correlations between different single- or aggregated gene expression metrics in pre- and post-Shambhalized samples, including preserving cancer-specific gene expression and pathway activation features. © 2022 Wiley Periodicals LLC. Basic Protocol: Shambhala-2 harmonizer Alternate Protocol 1: Linear Shambhala/Shambhala-1 Alternate Protocol 2: Alternative (flexible-format and uniformly shaped) normalization methods Support Protocol 1: Watermelon multisection (WM) Support Protocol 2: Calculation of cancer-to-normal log-fold-change (LFC) and pathway activation level (PAL).
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Affiliation(s)
- Nicolas Borisov
- Omicsway Corp., Walnut, California.,Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia
| | - Maksim Sorokin
- Omicsway Corp., Walnut, California.,Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marianna Zolotovskaya
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia.,Oncobox Ltd., Moscow, Russia
| | | | - Anton Buzdin
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 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
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10
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Konovalov N, Timonin S, Asyutin D, Raevskiy M, Sorokin M, Buzdin A, Kaprovoy S. Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas. Front Oncol 2022; 12:837570. [PMID: 35387112 PMCID: PMC8978956 DOI: 10.3389/fonc.2022.837570] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 02/21/2022] [Indexed: 11/30/2022] Open
Abstract
In this study, we report 31 spinal intramedullary astrocytoma (SIA) RNA sequencing (RNA-seq) profiles for 25 adult patients with documented clinical annotations. To our knowledge, this is the first clinically annotated RNA-seq dataset of spinal astrocytomas derived from the intradural intramedullary compartment. We compared these tumor profiles with the previous healthy central nervous system (CNS) RNA-seq data for spinal cord and brain and identified SIA-specific gene sets and molecular pathways. Our findings suggest a trend for SIA-upregulated pathways governing interactions with the immune cells and downregulated pathways for the neuronal functioning in the context of normal CNS activity. In two patient tumor biosamples, we identified diagnostic KIAA1549-BRAF fusion oncogenes, and we also found 16 new SIA-associated fusion transcripts. In addition, we bioinformatically simulated activities of targeted cancer drugs in SIA samples and predicted that several tyrosine kinase inhibitory drugs and thalidomide analogs could be potentially effective as second-line treatment agents to aid in the prevention of SIA recurrence and progression.
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Affiliation(s)
| | | | | | - Mikhail Raevskiy
- Omicsway Corp., Walnut, CA, United States.,Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Maxim Sorokin
- Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton Buzdin
- Omicsway Corp., Walnut, CA, United States.,Moscow Institute of Physics and Technology, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
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11
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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] [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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12
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Raevskiy M, Sorokin M, Zakharova G, Tkachev V, Borisov N, Kuzmin D, Kremenchutckaya K, Gudkov A, Kamashev D, Buzdin A. Better Agreement of Human Transcriptomic and Proteomic Cancer Expression Data at the Molecular Pathway Activation Level. Int J Mol Sci 2022; 23:ijms23052611. [PMID: 35269755 PMCID: PMC8910457 DOI: 10.3390/ijms23052611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/19/2022] [Accepted: 02/23/2022] [Indexed: 12/10/2022] Open
Abstract
Previously, we have shown that the aggregation of RNA-level gene expression profiles into quantitative molecular pathway activation metrics results in lesser batch effects and better agreement between different experimental platforms. Here, we investigate whether pathway level of data analysis provides any advantage when comparing transcriptomic and proteomic data. We compare the paired proteomic and transcriptomic gene expression and pathway activation profiles obtained for the same human cancer biosamples in The Cancer Genome Atlas (TCGA) and the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, for a total of 755 samples of glioblastoma, breast, liver, lung, ovarian, pancreatic, and uterine cancers. In a CPTAC assay, expression levels of 15,112 protein-coding genes were profiled using the Thermo QE series of mass spectrometers. In TCGA, RNA expression levels of the same genes were obtained using the Illumina HiSeq 4000 engine for the same biosamples. At the gene level, absolute gene expression values are compared, whereas pathway-grade comparisons are made between the pathway activation levels (PALs) calculated using average sample-normalized transcriptomic and proteomic profiles. We observed remarkably different average correlations between the primary RNA- and protein expression data for different cancer types: Spearman Rho between 0.017 (p = 1.7 × 10−13) and 0.27 (p < 2.2 × 10−16). However, at the pathway level we detected overall statistically significantly higher correlations: averaged Rho between 0.022 (p < 2.2 × 10−16) and 0.56 (p < 2.2 × 10−16). Thus, we conclude that data analysis at the PAL-level yields results of a greater similarity when comparing high-throughput RNA and protein expression profiles.
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Affiliation(s)
- Mikhail Raevskiy
- I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia;
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
| | - Maxim Sorokin
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
| | - Galina Zakharova
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
| | | | - Nicolas Borisov
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (N.B.); (D.K.); (K.K.)
| | - Denis Kuzmin
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (N.B.); (D.K.); (K.K.)
| | | | - Alexander Gudkov
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
| | - Dmitry Kamashev
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
| | - Anton Buzdin
- OmicsWay Corp., Walnut, CA 91789, USA; (M.S.); (G.Z.); (A.G.); (D.K.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
- Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia; (N.B.); (D.K.); (K.K.)
- Correspondence: ; Tel./Fax: +1-626-7657785
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13
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Pastrello C, Niu Y, Jurisica I. Pathway Enrichment Analysis of Microarray Data. Methods Mol Biol 2022; 2401:147-159. [PMID: 34902127 DOI: 10.1007/978-1-0716-1839-4_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Microarray analyses usually result in a list of differential genes that need to be annotated to link them the phenotype being studied, help planning validation experiments and interpretation of the results. Pathway enrichment analyses are frequently used for such purpose, where pathways are human created models of molecular activities and processes. While different types of pathway enrichment are available, we focus this protocol on the most frequent type-overrepresentation analysis. Many databases collect different sets of pathways and curate different sets of genes for the same pathways, so it is important to carefully choose the most suitable pathway source to perform enrichment analysis. To provide a comprehensive pathway analysis, in this protocol we will use pathDIP, which supports comprehensive enrichment analysis by integrating 22 main pathway databases. We will also describe the steps needed to visualize the enriched pathways using GSOAP.
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Affiliation(s)
- Chiara Pastrello
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Yun Niu
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada.
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
- Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, ON, Canada.
- Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia.
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14
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Raevskiy M, Sorokin M, Vladimirova U, Suntsova M, Efimov V, Garazha A, Drobyshev A, Moisseev A, Rumiantsev P, Li X, Buzdin A. EGFR Pathway-Based Gene Signatures of Druggable Gene Mutations in Melanoma, Breast, Lung, and Thyroid Cancers. BIOCHEMISTRY. BIOKHIMIIA 2021; 86:1477-1488. [PMID: 34906047 DOI: 10.1134/s0006297921110110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/01/2021] [Accepted: 10/01/2021] [Indexed: 06/14/2023]
Abstract
EGFR, BRAF, PIK3CA, and KRAS genes play major roles in EGFR pathway, and accommodate activating mutations that predict response to many targeted therapeutics. However, connections between these mutations and EGFR pathway expression patterns remain unexplored. Here, we investigated transcriptomic associations with these activating mutations in three ways. First, we compared expressions of these genes in the mutant and wild type tumors, respectively, using RNA sequencing profiles from The Cancer Genome Atlas project database (n = 3660). Second, mutations were associated with the activation level of EGFR pathway. Third, they were associated with the gene signatures of differentially expressed genes from these pathways between the mutant and wild type tumors. We found that the upregulated EGFR pathway was linked with mutations in the BRAF (thyroid cancer, melanoma) and PIK3CA (breast cancer) genes. Gene signatures were associated with BRAF (thyroid cancer, melanoma), EGFR (squamous cell lung cancer), KRAS (colorectal cancer), and PIK3CA (breast cancer) mutations. However, only for the BRAF gene signature in the thyroid cancer we observed strong biomarker diagnostic capacity with AUC > 0.7 (0.809). Next, we validated this signature on the independent literature-based dataset (n = 127, fresh-frozen tissue samples, AUC 0.912), and on the experimental dataset (n = 42, formalin fixed, paraffin embedded tissue samples, AUC 0.822). Our results suggest that the RNA sequencing profiles can be used for robust identification of the replacement of Valine at position 600 with Glutamic acid in the BRAF gene in the papillary subtype of thyroid cancer, and evidence that the specific gene expression levels could provide information about the driver carcinogenic mutations.
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Affiliation(s)
- Mikhail Raevskiy
- Omicsway Corp., Walnut, CA 91789, USA.
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia
| | - Maxim Sorokin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia.
- Oncobox Ltd., Moscow, 121205, Russia
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Uliana Vladimirova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia.
| | - Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia.
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Victor Efimov
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, 141701, Russia.
| | | | - Alexei Drobyshev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia.
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Aleksey Moisseev
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia.
| | | | - Xinmin Li
- Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, 90095 USA.
| | - Anton Buzdin
- 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
- Sechenov First Moscow State Medical University, Moscow, 119991, Russia
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15
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Brief relaxation training is associated with long-term endocrine therapy adherence among women with breast cancer: post hoc analysis of a randomized controlled trial. Breast Cancer Res Treat 2021; 190:79-88. [PMID: 34410568 DOI: 10.1007/s10549-021-06361-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 08/08/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE Despite life-saving potential, many women struggle to adhere to adjuvant endocrine therapy (AET) for their breast cancer (BCa). Prior research has demonstrated that emotional distress is a barrier to AET adherence. We followed women from a trial to test the long-term effects of two 5-week post-surgical group-based stress management interventions, cognitive behavioral therapy (CBT), and relaxation training versus an attention-matched health education control, on AET adherence. METHODS We conducted a long-term follow-up (median = 8 years) of women randomized to CBT, relaxation training, or health education after surgery for stage 0-3 BCa. We measured adherence with the Endocrine Therapy Medication Usage Questionnaire (ETMUQ). First, we established factors on the ETMUQ via confirmatory factor analysis. We then used Bayesian structural equation modeling to regress these factors on study arm, controlling for age and treatments received. RESULTS Of those who completed long-term follow-up (n = 59, 44.7%), over half (n = 33; 55.9%) reported problems with adherence generally. Women receiving relaxation training (n = 15) had better adherence than those receiving health education (n = 24) on the Forgetfulness/Inconsistency [B(SE) = 0.25(0.14), p = 0.049] and Intentional Nonadherence [B(SE) = 0.31(0.14), p = 0.018] factors of the ETMUQ. Similar results were observed for those receiving relaxation training compared to CBT (n = 20): Forgetfulness/Inconsistency [B(SE) = - 0.47(0.25), p = 0.031]; Intentional Nonadherence [B(SE) = - 0.31(0.15), p = 0.027]. CONCLUSION Women receiving relaxation training were less likely to (1) forget to take their AET and (2) intentionally miss doses of AET in the long term compared to women receiving health education or CBT. This is evidence for the need of randomized trials that aim to improve adherence by incorporating theoretically based behavioral change techniques. TRIAL REGISTRATION AND DATES Trial 2R01-CA-064710 was registered March 26, 2006.
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Wang H, Li J, Qin J, Li J, Chen Y, Song D, Zeng H, Wang S. Confocal Raman microspectral analysis and imaging of the drug response of osteosarcoma to cisplatin. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:2527-2536. [PMID: 34008598 DOI: 10.1039/d1ay00626f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Confocal Raman microspectral analysis and imaging were used to elucidate the drug response of osteosarcoma (OS) to cisplatin. Raman spectral data were obtained from OS cells that were untreated (UT group) and treated with 20 µM (20T group) and 40 µM (40T group) cisplatin for 24 hours. Statistical analysis of the changes in specific Raman signals was performed using a one-way ANOVA and multiple Tukey's honest significant difference (HSD) post hoc tests. Principal component analysis-linear discriminant analysis (PCA-LDA) was used to highlight the featured cellular drug responses based on the obtained spectral information. For spectral imaging analysis, k-means cluster analysis (KCA) was adopted to clarify the effect of cisplatin dose changes on the subcellular structure and its biochemical composition. The results suggest that the major biochemical changes induced by cisplatin in OS cells undergoing apoptosis are reduced protein and nucleic acid content. Through univariate analysis, the changes in the distribution of nucleic acids in OS cells induced by different doses of cisplatin were obtained. The combination of Raman spectroscopy and multivariate analysis shows that cisplatin mainly acts on the nucleus and causes changes in the secondary structure of proteins. These results indicate that Raman imaging technology has the potential to offer the basis of dose optimization for personalized cancer treatment by helping to understand in vitro cellular drug interactions.
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Affiliation(s)
- Haifeng Wang
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, #1 Xuefu Avenue, Guodu Education and Technology Industrial Zone Chang'an District, Xi'an, Shaanxi 710127, China.
| | - Jing Li
- Department of Orthopedics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710004, China
| | - Jie Qin
- Department of Orthopedics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710004, China
| | - Jie Li
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, #1 Xuefu Avenue, Guodu Education and Technology Industrial Zone Chang'an District, Xi'an, Shaanxi 710127, China.
| | - Yishen Chen
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, #1 Xuefu Avenue, Guodu Education and Technology Industrial Zone Chang'an District, Xi'an, Shaanxi 710127, China.
| | - Dongliang Song
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, #1 Xuefu Avenue, Guodu Education and Technology Industrial Zone Chang'an District, Xi'an, Shaanxi 710127, China.
| | - Haishan Zeng
- Imaging Unit - Integrative Oncology Department, BC Cancer Research Center, Vancouver, BC V5Z1L3, Canada
| | - Shuang Wang
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, #1 Xuefu Avenue, Guodu Education and Technology Industrial Zone Chang'an District, Xi'an, Shaanxi 710127, China.
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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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18
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Kamashev D, Sorokin M, Kochergina I, Drobyshev A, Vladimirova U, Zolotovskaia M, Vorotnikov I, Shaban N, Raevskiy M, Kuzmin D, Buzdin A. Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth. Heliyon 2021; 7:e06394. [PMID: 33748471 PMCID: PMC7966997 DOI: 10.1016/j.heliyon.2021.e06394] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 10/29/2020] [Accepted: 02/25/2021] [Indexed: 02/09/2023] Open
Abstract
Many patients fail to respond to EGFR-targeted therapeutics, and personalized diagnostics is needed to identify putative responders. We investigated 1630 colorectal and lung squamous carcinomas and 1357 normal lung and colon samples and observed huge variation in EGFR pathway activation in both cancerous and healthy tissues, irrespectively on EGFR gene mutation status. We investigated whether human blood serum can affect squamous carcinoma cell growth and EGFR drug response. We demonstrate that human serum antagonizes the effects of EGFR-targeted drugs erlotinib and cetuximab on A431 squamous carcinoma cells by increasing IC50 by about 2- and 20-fold, respectively. The effects on clonogenicity varied significantly across the individual serum samples in every experiment, with up to 100% differences. EGF concentration could explain many effects of blood serum samples, and EGFR ligands-depleted serum showed lesser effect on drug sensitivity.
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Affiliation(s)
- Dmitry Kamashev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
| | - Maksim Sorokin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Irina Kochergina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
| | - Aleksey Drobyshev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Uliana Vladimirova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
| | - Marianna Zolotovskaia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Igor Vorotnikov
- Blokhin National Medical Research Center of Oncology of the Ministry of Health of Russia
| | - Nina Shaban
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Mikhail Raevskiy
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
- OmicsWay Corp., Walnut, CA, USA
| | - Denis Kuzmin
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
| | - Anton Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya St., Moscow 117997, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., Moscow 119992, Russia
- Moscow Institute of Physics and Technology (National Research University), Moscow Region 141700, Russia
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19
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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] [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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20
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Sorokin M, Borisov N, Kuzmin D, Gudkov A, Zolotovskaia M, Garazha A, Buzdin A. Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways. Front Genet 2021; 12:617059. [PMID: 33633781 PMCID: PMC7900570 DOI: 10.3389/fgene.2021.617059] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/20/2021] [Indexed: 12/16/2022] Open
Abstract
Current methods of high-throughput molecular and genomic analyses enabled to reconstruct thousands of human molecular pathways. Knowledge of molecular pathways structure and architecture taken along with the gene expression data can help interrogating the pathway activation levels (PALs) using different bioinformatic algorithms. In turn, the pathway activation profiles can characterize molecular processes, which are differentially regulated and give numeric characteristics of the extent of their activation or inhibition. However, different pathway nodes may have different functions toward overall pathway regulation, and calculation of PAL requires knowledge of molecular function of every node in the pathway in terms of its activator or inhibitory role. Thus, high-throughput annotation of functional roles of pathway nodes is required for the comprehensive analysis of the pathway activation profiles. We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data. We also provide a bioinformatic tool for PAL data calculations using the current pathway knowledgebase.
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Affiliation(s)
- Maxim Sorokin
- Omicsway Corp., Walnut, CA, United States.,Laboratory of Clinical Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Nicolas Borisov
- Omicsway Corp., Walnut, CA, United States.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Denis Kuzmin
- Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | - Alexander Gudkov
- Laboratory of Clinical Genomic Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Marianna Zolotovskaia
- Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia
| | | | - Anton Buzdin
- Omicsway Corp., Walnut, CA, United States.,Laboratory for Translational Bioinformatics, Moscow Institute of Physics and Technology, Moscow, Russia.,Laboratory of Systems Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University, Moscow, Russia
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21
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Borisov N, Ilnytskyy Y, Byeon B, Kovalchuk O, Kovalchuk I. System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation. Int J Mol Sci 2020; 22:ijms22010388. [PMID: 33396562 PMCID: PMC7795809 DOI: 10.3390/ijms22010388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 12/26/2020] [Accepted: 12/28/2020] [Indexed: 12/19/2022] Open
Abstract
There are many varieties of Cannabis sativa that differ from each other by composition of cannabinoids, terpenes and other molecules. The medicinal properties of these cultivars are often very different, with some being more efficient than others. This report describes the development of a method and software for the analysis of the efficiency of various cannabis extracts to detect the anti-inflammatory properties of the various cannabis extracts. The method uses high-throughput gene expression profiling data but can potentially use other omics data as well. According to the signaling pathway topology, the gene expression profiles are convoluted into the signaling pathway activities using a signaling pathway impact analysis (SPIA) method. The method was tested by inducing inflammation in human 3D epithelial tissues, including intestine, oral and skin, and then exposing these tissues to various extracts and then performing transcriptome analysis. The analysis showed a different efficiency of the various extracts in restoring the transcriptome changes to the pre-inflammation state, thus allowing to calculate a different cannabis drug efficiency index (CDEI).
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Affiliation(s)
- Nicolas Borisov
- Moscow Institute of Physics and Technology, 9 Institutsky lane, Dolgoprudny, Moscow Region 141701, Russia;
| | - Yaroslav Ilnytskyy
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; (Y.I.); (B.B.); (O.K.)
- Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada
| | - Boseon Byeon
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; (Y.I.); (B.B.); (O.K.)
- Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada
- Biomedical and Health Informatics, Computer Science Department, State University of New York, 2 S Clinton St, Syracuse, NY 13202, USA
| | - Olga Kovalchuk
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; (Y.I.); (B.B.); (O.K.)
- Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada
| | - Igor Kovalchuk
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; (Y.I.); (B.B.); (O.K.)
- Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada
- Correspondence:
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22
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Shi XJ, Wei Y, Ji B. Systems Biology of Gastric Cancer: Perspectives on the Omics-Based Diagnosis and Treatment. Front Mol Biosci 2020; 7:203. [PMID: 33005629 PMCID: PMC7479200 DOI: 10.3389/fmolb.2020.00203] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 07/27/2020] [Indexed: 12/14/2022] Open
Abstract
Gastric cancer is the fifth most diagnosed cancer in the world, affecting more than a million people and causing nearly 783,000 deaths each year. The prognosis of advanced gastric cancer remains extremely poor despite the use of surgery and adjuvant therapy. Therefore, understanding the mechanism of gastric cancer development, and the discovery of novel diagnostic biomarkers and therapeutics are major goals in gastric cancer research. Here, we review recent progress in application of omics technologies in gastric cancer research, with special focus on the utilization of systems biology approaches to integrate multi-omics data. In addition, the association between gastrointestinal microbiota and gastric cancer are discussed, which may offer insights in exploring the novel microbiota-targeted therapeutics. Finally, the application of data-driven systems biology and machine learning approaches could provide a predictive understanding of gastric cancer, and pave the way to the development of novel biomarkers and rational design of cancer therapeutics.
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Affiliation(s)
- Xiao-Jing Shi
- Laboratory Animal Center, State Key Laboratory of Esophageal Cancer Prevention and Treatment, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Yongjun Wei
- School of Pharmaceutical Sciences, Key Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, Zhengzhou University, Zhengzhou, China
| | - Boyang Ji
- Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
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23
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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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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24
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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] [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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25
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Sorokin M, Poddubskaya E, Baranova M, Glusker A, Kogoniya L, Markarova E, Allina D, Suntsova M, Tkachev V, Garazha A, Sekacheva M, Buzdin A. RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer. Cold Spring Harb Mol Case Stud 2020; 6:a004945. [PMID: 32060041 PMCID: PMC7133748 DOI: 10.1101/mcs.a004945] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/03/2020] [Indexed: 02/06/2023] Open
Abstract
Gastric cancer (GC) is the fifth-ranked cancer type by associated mortality. The proportion of early diagnosis is low, and most patients are diagnosed at the advanced stages. First-line therapy standardly includes fluoropyrimidines and platinum compounds with trastuzumab for HER2-positive cases. For recurrent disease, there are several alternative options including ramucirumab, a monoclonal therapeutic antibody that inhibits VEGF-mediated tumor angiogenesis by binding with VEGFR2, alone or in combination with other cancer drugs. However, overall response rate following ramucirumab or its combinations is 30%-80% of the patients, suggesting that personalization of drug prescription is needed to increase efficacy of treatment. We report here original tumor RNA sequencing profiles for 15 advanced GC patients linked with data on clinical response to ramucirumab or its combinations. Three genes showed differential expression in the tumors for responders versus nonresponders: CHRM3, LRFN1, and TEX15 Of them, CHRM3 was up-regulated in the responders. Using the bioinformatic platform Oncobox we simulated ramucirumab efficiency and compared output model results with actual tumor response data. An agreement was observed between predicted and real clinical outcomes (AUC ≥ 0.7). These results suggest that RNA sequencing may be used to personalize the prescription of ramucirumab for GC and indicate potential molecular mechanisms underlying ramucirumab resistance. The RNA sequencing profiles obtained here are fully compatible with the previously published Oncobox Atlas of Normal Tissue Expression (ANTE) data.
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Affiliation(s)
- Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Omicsway Corp., Walnut, California 91789, USA
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | - Elena Poddubskaya
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Madina Baranova
- N.N. Blokhin Russian Cancer Research Center, Moscow, 115478, Russia
- Clinical Center Vitamed, Moscow, 121309, Russia
| | - Alex Glusker
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Lali Kogoniya
- M.F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, 129110, Russia
| | - Ekaterina Markarova
- M.F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, 129110, Russia
| | - Daria Allina
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Maria Suntsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | | | | | - Marina Sekacheva
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
- Omicsway Corp., Walnut, California 91789, USA
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
- Moscow Institute of Physics and Technology, Moscow Region, 141701, Russia
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26
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Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma. Cancers (Basel) 2020; 12:cancers12020520. [PMID: 32102350 PMCID: PMC7072286 DOI: 10.3390/cancers12020520] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 12/22/2022] Open
Abstract
Background: Inevitable recurrence after radiochemotherapy is the major problem in the treatment of glioblastoma, the most prevalent type of adult brain malignancy. Glioblastomas are notorious for a high degree of intratumor heterogeneity manifest through a diversity of cell types and molecular patterns. The current paradigm of understanding glioblastoma recurrence is that cytotoxic therapy fails to target effectively glioma stem cells. Recent advances indicate that therapy-driven molecular evolution is a fundamental trait associated with glioblastoma recurrence. There is a growing body of evidence indicating that intratumor heterogeneity, longitudinal changes in molecular biomarkers and specific impacts of glioma stem cells need to be taken into consideration in order to increase the accuracy of molecular diagnostics still relying on readouts obtained from a single tumor specimen. Methods: This study integrates a multisampling strategy, longitudinal approach and complementary transcriptomic investigations in order to identify transcriptomic traits of recurrent glioblastoma in whole-tissue specimens of glioblastoma or glioblastoma stem cells. In this study, 128 tissue samples of 44 tumors including 23 first diagnosed, 19 recurrent and 2 secondary recurrent glioblastomas were analyzed along with 27 primary cultures of glioblastoma stem cells by RNA sequencing. A novel algorithm was used to quantify longitudinal changes in pathway activities and model efficacy of anti-cancer drugs based on gene expression data. Results: Our study reveals that intratumor heterogeneity of gene expression patterns is a fundamental characteristic of not only newly diagnosed but also recurrent glioblastomas. Evidence is provided that glioblastoma stem cells recapitulate intratumor heterogeneity, longitudinal transcriptomic changes and drug sensitivity patterns associated with the state of recurrence. Conclusions: Our results provide a transcriptional rationale for the lack of significant therapeutic benefit from temozolomide in patients with recurrent glioblastoma. Our findings imply that the spectrum of potentially effective drugs is likely to differ between newly diagnosed and recurrent glioblastomas and underscore the merits of glioblastoma stem cells as prognostic models for identifying alternative drugs and predicting drug response in recurrent glioblastoma. With the majority of recurrent glioblastomas being inoperable, glioblastoma stem cell models provide the means of compensating for the limited availability of recurrent glioblastoma specimens.
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27
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Mutation Enrichment and Transcriptomic Activation Signatures of 419 Molecular Pathways in Cancer. Cancers (Basel) 2020; 12:cancers12020271. [PMID: 31979117 PMCID: PMC7073226 DOI: 10.3390/cancers12020271] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 01/16/2020] [Accepted: 01/20/2020] [Indexed: 12/13/2022] Open
Abstract
Carcinogenesis is linked with massive changes in regulation of gene networks. We used high throughput mutation and gene expression data to interrogate involvement of 278 signaling, 72 metabolic, 48 DNA repair and 47 cytoskeleton molecular pathways in cancer. Totally, we analyzed 4910 primary tumor samples with individual cancer RNA sequencing and whole exome sequencing profiles including ~1.3 million DNA mutations and representing thirteen cancer types. Gene expression in cancers was compared with the corresponding 655 normal tissue profiles. For the first time, we calculated mutation enrichment values and activation levels for these pathways. We found that pathway activation profiles were largely congruent among the different cancer types. However, we observed no correlation between mutation enrichment and expression changes both at the gene and at the pathway levels. Overall, positive median cancer-specific activation levels were seen in the DNA repair, versus similar slightly negative values in the other types of pathways. The DNA repair pathways also demonstrated the highest values of mutation enrichment. However, the signaling and cytoskeleton pathways had the biggest proportions of representatives among the outstandingly frequently mutated genes thus suggesting their initiator roles in carcinogenesis and the auxiliary/supporting roles for the other groups of molecular pathways.
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28
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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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29
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Tkachev V, Sorokin M, Garazha A, Borisov N, Buzdin A. Oncobox Method for Scoring Efficiencies of Anticancer Drugs Based on Gene Expression Data. Methods Mol Biol 2020; 2063:235-255. [PMID: 31667774 DOI: 10.1007/978-1-0716-0138-9_17] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
We describe here the Oncobox method for scoring efficiencies of anticancer target drugs (ATDs) using high throughput gene expression data. The method rationale, design, and validation are given along with the examples of its practical applications in biomedicine. The method is based on the analysis of intracellular molecular pathways activation and measuring expressions of molecular target genes for every ATD under consideration. Using Oncobox method requires collection of normal (control) expression profiles and annotated databases of molecular pathways and drug target genes. Both microarray and RNA sequencing profiles are acceptable, although the latter type of data prevails in the most recent applications of this technique.
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Affiliation(s)
| | - Maxim Sorokin
- Omicsway Corp., Walnut, CA, USA
- Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | - Nicolas 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 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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Borger P, Schneider M, Frick L, Langiewicz M, Sorokin M, Buzdin A, Kachaylo E, Graf R, Humar B, Clavien PA. Exploration of the Transcriptional Landscape of ALPPS Reveals the Pathways of Accelerated Liver Regeneration. Front Oncol 2019; 9:1206. [PMID: 31824837 PMCID: PMC6882302 DOI: 10.3389/fonc.2019.01206] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 10/23/2019] [Indexed: 12/16/2022] Open
Abstract
Background and Aims: ALPPS (associating liver partition and portal vein ligation for staged hepatectomy), a novel 2-staged hepatectomy, dramatically accelerates liver regeneration and thus enables extensive liver tumor resection. The signaling networks underlying the ALPPS-induced accelerated regeneration process are largely unknown. Methods: We performed transcriptome profiling (TP) of liver tissue obtained from a mouse model of ALPPS, standard hepatectomy (68% model), and additional control surgeries (sham, PVL and Tx). We also performed TP using human liver biopsies (n = 5) taken from the occluded lobe and the future liver remnant (FLR) during the first step of ALPPS surgery (4–5 h apart). We used Oncofinder computational tools, which covers 378 ISPs, for unsupervised, unbiased quantification of ISP activity. Results: Gene expression cluster analysis revealed an ALPPS specific signature: the IGF1R Signaling Pathway (Cell survival), the ILK Pathway (Induced cell proliferation), and the IL-10 Pathway (Stability determination) were significantly enriched, whereas the activity of the Interferon Pathway (Transcription) was reduced (p < 0.05). Further, the PAK- and ILK-associated ISPs were activated at an earlier time point, reflecting significant acceleration of liver regeneration (p < 0.001). These pathways, which were also recovered in human liver biopsies, control cell growth and proliferation, inflammatory response, and hypoxia-related processes. Conclusions: ALPPS is not a straightforward addition of portal vein ligation (PVL) plus transection—it is more. The early stages of normal and accelerated liver regeneration are clearly discernible by a significantly increased and earlier activation of a small number of signaling pathways. Compounds mimicking these responses may help to improve the ALPPS method and further reduce the hospitalization time of the patient.
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Affiliation(s)
- Pieter Borger
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Marcel Schneider
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Lukas Frick
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Magda Langiewicz
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Maksim Sorokin
- OmicsWay Corp., Walnut, CA, United States.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Anton Buzdin
- OmicsWay Corp., Walnut, CA, United States.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
| | - Ekaterina Kachaylo
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Rolf Graf
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Bostjan Humar
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
| | - Pierre-Alain Clavien
- Laboratory of the Swiss Hepato-Pancreato-Biliary (HPB) and Transplantation Center, Department of Surgery, University Hospital Zürich, Zurich, Switzerland
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Igolkina AA, Zinkevich A, Karandasheva KO, Popov AA, Selifanova MV, Nikolaeva D, Tkachev V, Penzar D, Nikitin DM, Buzdin A. H3K4me3, H3K9ac, H3K27ac, H3K27me3 and H3K9me3 Histone Tags Suggest Distinct Regulatory Evolution of Open and Condensed Chromatin Landmarks. Cells 2019; 8:E1034. [PMID: 31491936 PMCID: PMC6770625 DOI: 10.3390/cells8091034] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 08/28/2019] [Accepted: 09/03/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Transposons are selfish genetic elements that self-reproduce in host DNA. They were active during evolutionary history and now occupy almost half of mammalian genomes. Close insertions of transposons reshaped structure and regulation of many genes considerably. Co-evolution of transposons and host DNA frequently results in the formation of new regulatory regions. Previously we published a concept that the proportion of functional features held by transposons positively correlates with the rate of regulatory evolution of the respective genes. METHODS We ranked human genes and molecular pathways according to their regulatory evolution rates based on high throughput genome-wide data on five histone modifications (H3K4me3, H3K9ac, H3K27ac, H3K27me3, H3K9me3) linked with transposons for five human cell lines. RESULTS Based on the total of approximately 1.5 million histone tags, we ranked regulatory evolution rates for 25075 human genes and 3121 molecular pathways and identified groups of molecular processes that showed signs of either fast or slow regulatory evolution. However, histone tags showed different regulatory patterns and formed two distinct clusters: promoter/active chromatin tags (H3K4me3, H3K9ac, H3K27ac) vs. heterochromatin tags (H3K27me3, H3K9me3). CONCLUSION In humans, transposon-linked histone marks evolved in a coordinated way depending on their functional roles.
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Affiliation(s)
- Anna A Igolkina
- Mathematical Biology & Bioinformatics Laboratory, Institute of Applied Mathematics and Mechanics, Peter the Great St.Petersburg Polytechnic University, Polytechnicheskaya 29, St. Petersburg 195251, Russia.
- Laboratory of Microbiological Monitoring and Bioremediation of Soil, All-Russia Research Institute for Agricultural Microbiology, Podbel'skogo, 3, St. Petersburg 196608, Russia.
| | - Arsenii Zinkevich
- Lomonosov Moscow State University, Vorobiovy Gory 1, Moscow 119991, Russia
| | | | - Aleksey A Popov
- Lomonosov Moscow State University, Vorobiovy Gory 1, Moscow 119991, Russia
| | - Maria V Selifanova
- Lomonosov Moscow State University, Vorobiovy Gory 1, Moscow 119991, Russia
| | - Daria Nikolaeva
- Lomonosov Moscow State University, Vorobiovy Gory 1, Moscow 119991, Russia
| | | | - Dmitry Penzar
- Lomonosov Moscow State University, Vorobiovy Gory 1, Moscow 119991, Russia
- Vavilov Institute of General Genetics Russian Academy of Sciences, Gubkina 3, Moscow 119991, Russia
| | - Daniil M Nikitin
- Omicsway Corp., Walnut, CA 91789, USA
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia
| | - Anton Buzdin
- Omicsway Corp., Walnut, CA 91789, USA.
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow 117997, Russia.
- I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia.
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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] [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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Retroelement-Linked Transcription Factor Binding Patterns Point to Quickly Developing Molecular Pathways in Human Evolution. Cells 2019; 8:cells8020130. [PMID: 30736359 PMCID: PMC6406739 DOI: 10.3390/cells8020130] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 01/29/2019] [Accepted: 01/30/2019] [Indexed: 12/12/2022] Open
Abstract
Background: Retroelements (REs) are transposable elements occupying ~40% of the human genome that can regulate genes by providing transcription factor binding sites (TFBS). RE-linked TFBS profile can serve as a marker of gene transcriptional regulation evolution. This approach allows for interrogating the regulatory evolution of organisms with RE-rich genomes. We aimed to characterize the evolution of transcriptional regulation for human genes and molecular pathways using RE-linked TFBS accumulation as a metric. Methods: We characterized human genes and molecular pathways either enriched or deficient in RE-linked TFBS regulation. We used ENCODE database with mapped TFBS for 563 transcription factors in 13 human cell lines. For 24,389 genes and 3124 molecular pathways, we calculated the score of RE-linked TFBS regulation reflecting the regulatory evolution rate at the level of individual genes and molecular pathways. Results: The major groups enriched by RE regulation deal with gene regulation by microRNAs, olfaction, color vision, fertilization, cellular immune response, and amino acids and fatty acids metabolism and detoxication. The deficient groups were involved in translation, RNA transcription and processing, chromatin organization, and molecular signaling. Conclusion: We identified genes and molecular processes that have characteristics of especially high or low evolutionary rates at the level of RE-linked TFBS regulation in human lineage.
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Borisov N, Shabalina I, Tkachev V, Sorokin M, Garazha A, Pulin A, Eremin II, Buzdin A. Shambhala: a platform-agnostic data harmonizer for gene expression data. BMC Bioinformatics 2019; 20:66. [PMID: 30727942 PMCID: PMC6366102 DOI: 10.1186/s12859-019-2641-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 01/18/2019] [Indexed: 11/10/2022] Open
Abstract
Background Harmonization techniques make different gene expression profiles and their sets compatible and ready for comparisons. Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple human gene expression datasets obtained using different experimental methods and platforms of microarray hybridization and RNA sequencing. Results Unlike previously published methods enabling good quality data harmonization for only two datasets, Shambhala allows conversion of multiple datasets into the universal form suitable for further comparisons. Shambhala harmonization is based on the calibration of gene expression profiles using the auxiliary standardization dataset. Each profile is transformed to make it similar to the output of microarray hybridization platform Affymetrix Human Gene. This platform was chosen because it has the biggest number of human gene expression profiles deposited in public databases. We evaluated Shambhala ability to retain biologically important features after harmonization. The same four biological samples taken in multiple replicates were profiled independently using three and four different experimental platforms, respectively, then Shambhala-harmonized and investigated by hierarchical clustering. Conclusion Our results showed that unlike other frequently used methods: quantile normalization and DESeq/DESeq2 normalization, Shambhala harmonization was the only method supporting sample-specific and platform-independent biologically meaningful clustering for the data obtained from multiple experimental platforms. Electronic supplementary material The online version of this article (10.1186/s12859-019-2641-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Nicolas Borisov
- I.M. Sechenov First Moscow State Medical University, Sechenov University, Moscow, 119991, Russia. .,Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA.
| | - Irina Shabalina
- Faculty of Mathematics and Information Technologies, Petrozavodsk State University, Anokhina str., 20, Petrozavodsk, 185910, Russia
| | - Victor Tkachev
- Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA
| | - Maxim Sorokin
- I.M. Sechenov First Moscow State Medical University, Sechenov University, Moscow, 119991, Russia.,Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA.,Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, Russia
| | - Andrew Garazha
- Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA.,Laboratory of Bioinformatics, Oncology and Immunology, D. Rogachyov Federal Research Center of Pediatric Hematology, Moscow, 117198, Russia
| | - Andrey Pulin
- Laboratory for Cell Biology and Developmental Pathology, Federal State Institution "Institute of General Pathology and Pathophysiology", FSBSI "IGPP", Moscow, Russia
| | - Ilya I Eremin
- Department for Regenerative Medicine, JSC Generium, Moscow, Russia
| | - Anton Buzdin
- I.M. Sechenov First Moscow State Medical University, Sechenov University, Moscow, 119991, Russia.,Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA.,Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, 117997, 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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Zolotovskaia MA, Sorokin MI, Roumiantsev SA, Borisov NM, Buzdin AA. Pathway Instability Is an Effective New Mutation-Based Type of Cancer Biomarkers. Front Oncol 2019; 8:658. [PMID: 30662873 PMCID: PMC6328788 DOI: 10.3389/fonc.2018.00658] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 12/12/2018] [Indexed: 01/20/2023] Open
Abstract
DNA mutations play a crucial role in cancer development and progression. Mutation profiles vary dramatically in different cancer types and between individual tumors. Mutations of several individual genes are known as reliable cancer biomarkers, although the number of such genes is tiny and does not enable differential diagnostics for most of the cancers. We report here a technique enabling dramatically increased efficiency of cancer biomarkers development using DNA mutations data. It includes a quantitative metric termed Pathway instability (PI) based on mutations enrichment of intracellular molecular pathways. This method was tested on 5,956 tumor mutation profiles of 15 cancer types from The Cancer Genome Atlas (TCGA) project. Totally, we screened 2,316,670 mutations in 19,872 genes and 1,748 molecular pathways. Our results demonstrated considerable advantage of pathway-based mutation biomarkers over individual gene mutation profiles, as reflected by more than two orders of magnitude greater numbers by high-quality [ROC area-under-curve (AUC)>0.75] biomarkers. For example, the number of such high-quality mutational biomarkers distinguishing between different cancer types was only six for the individual gene mutations, and already 660 for the pathway-based biomarkers. These results evidence that PI value can be used as a new generation of complex cancer biomarkers significantly outperforming the existing gene mutation biomarkers.
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Affiliation(s)
- Marianna A Zolotovskaia
- Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, Russia.,Oncobox Ltd., Moscow, Russia
| | - Maxim I Sorokin
- The Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Omicsway Corp., Walnut, CA, United States
| | - Sergey A Roumiantsev
- Department of Oncology, Hematology and Radiotherapy of Pediatric Faculty, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Nikolay M Borisov
- Oncobox Ltd., Moscow, Russia.,The Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Anton A Buzdin
- The Laboratory of Clinical Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.,Omicsway Corp., Walnut, CA, United States.,The Laboratory of Systems Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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Emelianova AA, Kuzmin DV, Panteleev PV, Sorokin M, Buzdin AA, Ovchinnikova TV. Anticancer Activity of the Goat Antimicrobial Peptide ChMAP-28. Front Pharmacol 2018; 9:1501. [PMID: 30622471 PMCID: PMC6308165 DOI: 10.3389/fphar.2018.01501] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 12/07/2018] [Indexed: 12/14/2022] Open
Abstract
Cytotoxic effect of the antimicrobial peptide ChMAP-28 from leucocytes of the goat Capra hircus was examined against five cancer and two normal human cell lines. ChMAP-28 has the amino acid sequence GRFKRFRKKLKRLWHKVGPFVGPILHY and is homologous to other α-helical mammalian antimicrobial peptides. ChMAP-28 shows considerably higher cytotoxicity against cultured tumor cells than toward normal cells at concentrations of <10 μM. Our findings suggest that ChMAP-28 can initiate necrotic death of cancer cells. Its cytotoxic effect is accomplished due to disruption of the plasma membrane integrity and is not abrogated by the addition of the caspase inhibitor Z-VAD-FMK. ChMAP-28 causes permeabilization of cytoplasmic membrane of human leukemia cells HL-60 already after 15 min of incubation. Here, we show that ChMAP-28 has one of the highest antitumor activity in vitro among all known antimicrobial peptides. We speculate that the observed specificity of ChMAP-28 cytotoxic effect against tumor cells is due to its relatively low hydrophobicity and high cationicity. In the meantime, this peptide has low hemolytic activity, which generates a potential for its use as a therapeutic agent.
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Affiliation(s)
- Anna A Emelianova
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, The Russian Academy of Sciences, Moscow, Russia
| | - Denis V Kuzmin
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, The Russian Academy of Sciences, Moscow, Russia
| | - Pavel V Panteleev
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, The Russian Academy of Sciences, Moscow, Russia
| | - Maxim Sorokin
- Department of Bioinformatics and Molecular Networks, OmicsWay Corporation, Walnut, CA, United States
| | - Anton A Buzdin
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, The Russian Academy of Sciences, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Tatiana V Ovchinnikova
- M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry, The Russian Academy of Sciences, Moscow, Russia.,I.M. Sechenov First Moscow State Medical University, Moscow, Russia
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39
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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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Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data. Cancers (Basel) 2018; 10:cancers10100365. [PMID: 30274248 PMCID: PMC6209915 DOI: 10.3390/cancers10100365] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 09/24/2018] [Accepted: 09/25/2018] [Indexed: 12/22/2022] Open
Abstract
Sequential courses of anticancer target therapy lead to selection of drug-resistant cells, which results in continuous decrease of clinical response. Here we present a new approach for predicting effective combinations of target drugs, which act in a synergistic manner. Synergistic combinations of drugs may prevent or postpone acquired resistance, thus increasing treatment efficiency. We cultured human ovarian carcinoma SKOV-3 and neuroblastoma NGP-127 cancer cell lines in the presence of Tyrosine Kinase Inhibitors (Pazopanib, Sorafenib, and Sunitinib) and Rapalogues (Temsirolimus and Everolimus) for four months and obtained cell lines demonstrating increased drug resistance. We investigated gene expression profiles of intact and resistant cells by microarrays and analyzed alterations in 378 cancer-related signaling pathways using the bioinformatical platform Oncobox. This revealed numerous pathways linked with development of drug resistant phenotypes. Our approach is based on targeting proteins involved in as many as possible signaling pathways upregulated in resistant cells. We tested 13 combinations of drugs and/or selective inhibitors predicted by Oncobox and 10 random combinations. Synergy scores for Oncobox predictions were significantly higher than for randomly selected drug combinations. Thus, the proposed approach significantly outperforms random selection of drugs and can be adopted to enhance discovery of new synergistic combinations of anticancer target drugs.
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Nikitin D, Penzar D, Garazha A, Sorokin M, Tkachev V, Borisov N, Poltorak A, Prassolov V, Buzdin AA. Profiling of Human Molecular Pathways Affected by Retrotransposons at the Level of Regulation by Transcription Factor Proteins. Front Immunol 2018; 9:30. [PMID: 29441061 PMCID: PMC5797644 DOI: 10.3389/fimmu.2018.00030] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 01/04/2018] [Indexed: 12/22/2022] Open
Abstract
Endogenous retroviruses and retrotransposons also termed retroelements (REs) are mobile genetic elements that were active until recently in human genome evolution. REs regulate gene expression by actively reshaping chromatin structure or by directly providing transcription factor binding sites (TFBSs). We aimed to identify molecular processes most deeply impacted by the REs in human cells at the level of TFBS regulation. By using ENCODE data, we identified ~2 million TFBS overlapping with putatively regulation-competent human REs located in 5-kb gene promoter neighborhood (~17% of all TFBS in promoter neighborhoods; ~9% of all RE-linked TFBS). Most of REs hosting TFBS were highly diverged repeats, and for the evolutionary young (0–8% diverged) elements we identified only ~7% of all RE-linked TFBS. The gene-specific distributions of RE-linked TFBS generally correlated with the distributions for all TFBS. However, several groups of molecular processes were highly enriched in the RE-linked TFBS regulation. They were strongly connected with the immunity and response to pathogens, with the negative regulation of gene transcription, ubiquitination, and protein degradation, extracellular matrix organization, regulation of STAT signaling, fatty acids metabolism, regulation of GTPase activity, protein targeting to Golgi, regulation of cell division and differentiation, development and functioning of perception organs and reproductive system. By contrast, the processes most weakly affected by the REs were linked with the conservative aspects of embryo development. We also identified differences in the regulation features by the younger and older fractions of the REs. The regulation by the older fraction of the REs was linked mainly with the immunity, cell adhesion, cAMP, IGF1R, Notch, Wnt, and integrin signaling, neuronal development, chondroitin sulfate and heparin metabolism, and endocytosis. The younger REs regulate other aspects of immunity, cell cycle progression and apoptosis, PDGF, TGF beta, EGFR, and p38 signaling, transcriptional repression, structure of nuclear lumen, catabolism of phospholipids, and heterocyclic molecules, insulin and AMPK signaling, retrograde Golgi-ER transport, and estrogen signaling. The immunity-linked pathways were highly represented in both categories, but their functional roles were different and did not overlap. Our results point to the most quickly evolving molecular pathways in the recent and ancient evolution of human genome.
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Affiliation(s)
- Daniil Nikitin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.,D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Dmitry Penzar
- The Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia
| | - Andrew Garazha
- D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,OmicsWay Corp., Walnut, CA, United States
| | - Maxim Sorokin
- OmicsWay Corp., Walnut, CA, United States.,National Research Centre Kurchatov Institute, Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia.,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | - Nicolas Borisov
- OmicsWay Corp., Walnut, CA, United States.,National Research Centre Kurchatov Institute, Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
| | - Alexander Poltorak
- Program in Immunology, Sackler Graduate School, Tufts University, Boston, MA, United States
| | - Vladimir Prassolov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Anton A Buzdin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.,D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia.,OmicsWay Corp., Walnut, CA, United States.,National Research Centre Kurchatov Institute, Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow, Russia
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Borisov N, Tkachev V, Suntsova M, Kovalchuk O, Zhavoronkov A, Muchnik I, Buzdin A. A method of gene expression data transfer from cell lines to cancer patients for machine-learning prediction of drug efficiency. Cell Cycle 2018; 17:486-491. [PMID: 29251172 DOI: 10.1080/15384101.2017.1417706] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
Personalized medicine implies that distinct treatment methods are prescribed to individual patients according several features that may be obtained from, e.g., gene expression profile. The majority of machine learning methods suffer from the deficiency of preceding cases, i.e. the gene expression data on patients combined with the confirmed outcome of known treatment methods. At the same time, there exist thousands of various cell lines that were treated with hundreds of anti-cancer drugs in order to check the ability of these drugs to stop the cell proliferation, and all these cell line cultures were profiled in terms of their gene expression. Here we present a new approach in machine learning, which can predict clinical efficiency of anti-cancer drugs for individual patients by transferring features obtained from the expression-based data from cell lines. The method was validated on three datasets for cancer-like diseases (chronic myeloid leukemia, as well as lung adenocarcinoma and renal carcinoma) treated with targeted drugs - kinase inhibitors, such as imatinib or sorafenib.
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Affiliation(s)
- Nicolas Borisov
- a National Research Centre "Kurchatov Institute" , Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow , Russia.,b Department of R&D , First Oncology Research and Advisory Center, Moscow , Russia
| | - Victor Tkachev
- b Department of R&D , First Oncology Research and Advisory Center, Moscow , Russia.,c Department of R&D , OmicsWay Corporation, Walnut , CA , USA
| | - Maria Suntsova
- b Department of R&D , First Oncology Research and Advisory Center, Moscow , Russia.,d Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry , Moscow , Russia.,e Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology , Oncology and Immunology, Moscow , 117198 , Russia
| | - Olga Kovalchuk
- f Department of Biological Sciences , University of Lethbridge , Lethbridge , AB , Canada.,g Canada Cancer and Aging Research Laboratories , Lethbridge , AB , Canada
| | - Alex Zhavoronkov
- h Insilico Medicine, Inc, ETC, Johns Hopkins University , Baltimore , MD , USA
| | - Ilya Muchnik
- i Rutgers University , Hill Center, Busch Campus, Piscataway , NJ , USA
| | - Anton Buzdin
- a National Research Centre "Kurchatov Institute" , Centre for Convergence of Nano-, Bio-, Information and Cognitive Sciences and Technologies, Moscow , Russia.,b Department of R&D , First Oncology Research and Advisory Center, Moscow , Russia.,c Department of R&D , OmicsWay Corporation, Walnut , CA , USA.,d Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry , Moscow , Russia.,e Laboratory of Bioinformatics, D. Rogachyov Federal Research Center of Pediatric Hematology , Oncology and Immunology, Moscow , 117198 , Russia
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Prediction of Drug Efficiency by Transferring Gene Expression Data from Cell Lines to Cancer Patients. BRAVERMAN READINGS IN MACHINE LEARNING. KEY IDEAS FROM INCEPTION TO CURRENT STATE 2018. [DOI: 10.1007/978-3-319-99492-5_9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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