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Lima CR, Antunes D, Caffarena E, Carels N. Structural Characterization of Heat Shock Protein 90β and Molecular Interactions with Geldanamycin and Ritonavir: A Computational Study. Int J Mol Sci 2024; 25:8782. [PMID: 39201468 PMCID: PMC11354266 DOI: 10.3390/ijms25168782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/02/2024] Open
Abstract
Drug repositioning is an important therapeutic strategy for treating breast cancer. Hsp90β chaperone is an attractive target for inhibiting cell progression. Its structure has a disordered and flexible linker region between the N-terminal and central domains. Geldanamycin was the first Hsp90β inhibitor to interact specifically at the N-terminal site. Owing to the toxicity of geldanamycin, we investigated the repositioning of ritonavir as an Hsp90β inhibitor, taking advantage of its proven efficacy against cancer. In this study, we used molecular modeling techniques to analyze the contribution of the Hsp90β linker region to the flexibility and interaction between the ligands geldanamycin, ritonavir, and Hsp90β. Our findings indicate that the linker region is responsible for the fluctuation and overall protein motion without disturbing the interaction between the inhibitors and the N-terminus. We also found that ritonavir established similar interactions with the substrate ATP triphosphate, filling the same pharmacophore zone.
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Affiliation(s)
- Carlyle Ribeiro Lima
- Laboratory of Biological System Modeling, Centro de Desenvolvimento Tecnológico em Saúde (CDTS), Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 21040-900, Brazil
| | - Deborah Antunes
- Laboratório de Genômica Aplicada e Bioinovações, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 21040-900, Brazil;
| | - Ernesto Caffarena
- Grupo de Biofísica Computacional e Modelagem Molecular, Programa de Computação Científica (PROCC), Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 21040-900, Brazil;
| | - Nicolas Carels
- Laboratory of Biological System Modeling, Centro de Desenvolvimento Tecnológico em Saúde (CDTS), Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro 21040-900, Brazil
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Carels N. Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy. BIOLOGY 2024; 13:482. [PMID: 39056677 PMCID: PMC11274087 DOI: 10.3390/biology13070482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/20/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
RNA-seq faces persistent challenges due to the ongoing, expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Here, we used Shannon entropy as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, such as DESeq2 and edgeR, but also by combining nine normalization methods with log2 fold change on paired samples of TCGA RNA-seq representing datasets of 515 patients and spanning 12 different cancer types with 5-year overall survival rates ranging from 20% to 98%. Our analysis revealed that TPM, RLE, and TMM normalization, coupled with a threshold of log2 fold change ≥1, for identifying differentially expressed genes, yielded the best results. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows and mRNA sequencing technologies.
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Affiliation(s)
- Nicolas Carels
- Laboratory of Biological System Modeling, Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro 21040-900, RJ, Brazil
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Liu S, Wen H, Li F, Xue X, Sun X, Li F, Hu R, Xi H, Boccellato F, Meyer TF, Mi Y, Zheng P. Revealing the pathogenesis of gastric intestinal metaplasia based on the mucosoid air-liquid interface. J Transl Med 2024; 22:468. [PMID: 38760813 PMCID: PMC11101349 DOI: 10.1186/s12967-024-05276-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 05/04/2024] [Indexed: 05/19/2024] Open
Abstract
BACKGROUND Gastric intestinal metaplasia (GIM) is an essential precancerous lesion. Although the reversal of GIM is challenging, it potentially brings a state-to-art strategy for gastric cancer therapeutics (GC). The lack of the appropriate in vitro model limits studies of GIM pathogenesis, which is the issue this work aims to address for further studies. METHOD The air-liquid interface (ALI) model was adopted for the long-term culture of GIM cells in the present work. This study conducted Immunofluorescence (IF), quantitative real-time polymerase chain reaction (qRT-PCR), transcriptomic sequencing, and mucoproteomic sequencing (MS) techniques to identify the pathways for differential expressed genes (DEGs) enrichment among different groups, furthermore, to verify novel biomarkers of GIM cells. RESULT Our study suggests that GIM-ALI model is analog to the innate GIM cells, which thus can be used for mucus collection and drug screening. We found genes MUC17, CDA, TRIM15, TBX3, FLVCR2, ONECUT2, ACY3, NMUR2, and MAL2 were highly expressed in GIM cells, while GLDN, SLC5A5, MAL, and MALAT1 showed down-regulated, which can be used as potential biomarkers for GIM cells. In parallel, these genes that highly expressed in GIM samples were mainly involved in cancer-related pathways, such as the MAPK signal pathway and oxidative phosphorylation signal pathway. CONCLUSION The ALI model is validated for the first time for the in vitro study of GIM. GIM-ALI model is a novel in vitro model that can mimic the tissue micro-environment in GIM patients and further provide an avenue for studying the characteristics of GIM mucus. Our study identified new markers of GIM as well as pathways associated with GIM, which provides outstanding insight for exploring GIM pathogenesis and potentially other related conditions.
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Affiliation(s)
- Simeng Liu
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
- Department of Molecular Biology, Max Planck Institute for Infection Biology, 10117, Berlin, Germany
| | - Huijuan Wen
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
| | - Fazhan Li
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
| | - Xia Xue
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
| | - Xiangdong Sun
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
| | - Fuhao Li
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
| | - Ruoyu Hu
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 453000, China
| | - Huayuan Xi
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 453000, China
| | - Francesco Boccellato
- Department of Molecular Biology, Max Planck Institute for Infection Biology, 10117, Berlin, Germany
- Nuffield Department of Clinical Medicine, Ludwig Institute for Cancer Research, University of Oxford, Oxford, 11743, UK
| | - Thomas F Meyer
- Department of Molecular Biology, Max Planck Institute for Infection Biology, 10117, Berlin, Germany
- Laboratory of Infection Oncology, Institute of Clinical Molecular Biology, Christian Albrecht University of Kiel and University Hospital Schleswig-Holstein - Campus Kiel, Rosalind-Franklin- Straße 12, 24105, Kiel, Germany
| | - Yang Mi
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China.
| | - Pengyuan Zheng
- Henan Key Laboratory of Helicobacter pylori & Microbiota and Gastrointestinal Cancer, Marshall Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, No. 3, Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450002, China.
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 453000, China.
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Sgariglia D, Carneiro FRG, Vidal de Carvalho LA, Pedreira CE, Carels N, da Silva FAB. Optimizing therapeutic targets for breast cancer using boolean network models. Comput Biol Chem 2024; 109:108022. [PMID: 38350182 DOI: 10.1016/j.compbiolchem.2024.108022] [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] [Received: 02/19/2023] [Revised: 09/18/2023] [Accepted: 01/31/2024] [Indexed: 02/15/2024]
Abstract
Studying gene regulatory networks associated with cancer provides valuable insights for therapeutic purposes, given that cancer is fundamentally a genetic disease. However, as the number of genes in the system increases, the complexity arising from the interconnections between network components grows exponentially. In this study, using Boolean logic to adjust the existing relationships between network components has facilitated simplifying the modeling process, enabling the generation of attractors that represent cell phenotypes based on breast cancer RNA-seq data. A key therapeutic objective is to guide cells, through targeted interventions, to transition from the current cancer attractor to a physiologically distinct attractor unrelated to cancer. To achieve this, we developed a computational method that identifies network nodes whose inhibition can facilitate the desired transition from one tumor attractor to another associated with apoptosis, leveraging transcriptomic data from cell lines. To validate the model, we utilized previously published in vitro experiments where the downregulation of specific proteins resulted in cell growth arrest and death of a breast cancer cell line. The method proposed in this manuscript combines diverse data sources, conducts structural network analysis, and incorporates relevant biological knowledge on apoptosis in cancer cells. This comprehensive approach aims to identify potential targets of significance for personalized medicine.
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Affiliation(s)
| | - Flavia Raquel Gonçalves Carneiro
- Center of Technological Development in Health (CDTS), FIOCRUZ, Rio de Janeiro, Brazil; Laboratório Interdisciplinar de Pesquisas Médicas Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil; Program of Immunology and Tumor Biology, Brazilian National Cancer Institute(INCA), Rio de Janeiro 20231050, Brazil
| | | | | | - Nicolas Carels
- Platform of Biological System Modeling, Center of Technological Development in Health (CDTS), FIOCRUZ, Rio de Janeiro, Brazil
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Carels N, Sgariglia D, Junior MGV, Lima CR, Carneiro FRG, da Silva GF, da Silva FAB, Scardini R, Tuszynski JA, de Andrade CV, Monteiro AC, Martins MG, da Silva TG, Ferraz H, Finotelli PV, Balbino TA, Pinto JC. A Strategy Utilizing Protein-Protein Interaction Hubs for the Treatment of Cancer Diseases. Int J Mol Sci 2023; 24:16098. [PMID: 38003288 PMCID: PMC10671768 DOI: 10.3390/ijms242216098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 09/04/2023] [Accepted: 09/12/2023] [Indexed: 11/26/2023] Open
Abstract
We describe a strategy for the development of a rational approach of neoplastic disease therapy based on the demonstration that scale-free networks are susceptible to specific attacks directed against its connective hubs. This strategy involves the (i) selection of up-regulated hubs of connectivity in the tumors interactome, (ii) drug repurposing of these hubs, (iii) RNA silencing of non-druggable hubs, (iv) in vitro hub validation, (v) tumor-on-a-chip, (vi) in vivo validation, and (vii) clinical trial. Hubs are protein targets that are assessed as targets for rational therapy of cancer in the context of personalized oncology. We confirmed the existence of a negative correlation between malignant cell aggressivity and the target number needed for specific drugs or RNA interference (RNAi) to maximize the benefit to the patient's overall survival. Interestingly, we found that some additional proteins not generally targeted by drug treatments might justify the addition of inhibitors designed against them in order to improve therapeutic outcomes. However, many proteins are not druggable, or the available pharmacopeia for these targets is limited, which justifies a therapy based on encapsulated RNAi.
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Affiliation(s)
- Nicolas Carels
- Platform of Biological System Modeling, Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil; (C.R.L.); (G.F.d.S.)
| | - Domenico Sgariglia
- Engenharia de Sistemas e Computação, Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, RJ, Brazil;
| | - Marcos Guilherme Vieira Junior
- Computational Modeling of Biological Systems, Scientific Computing Program (PROCC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil or (M.G.V.J.); (F.A.B.d.S.)
| | - Carlyle Ribeiro Lima
- Platform of Biological System Modeling, Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil; (C.R.L.); (G.F.d.S.)
| | - Flávia Raquel Gonçalves Carneiro
- Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil; (F.R.G.C.); (R.S.)
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil
- Program of Immunology and Tumor Biology, Brazilian National Cancer Institute (INCA), Rio de Janeiro 20231-050, RJ, Brazil
| | - Gilberto Ferreira da Silva
- Platform of Biological System Modeling, Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil; (C.R.L.); (G.F.d.S.)
| | - Fabricio Alves Barbosa da Silva
- Computational Modeling of Biological Systems, Scientific Computing Program (PROCC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil or (M.G.V.J.); (F.A.B.d.S.)
| | - Rafaela Scardini
- Center of Technological Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040-900, RJ, Brazil; (F.R.G.C.); (R.S.)
- Program of Immunology and Tumor Biology, Brazilian National Cancer Institute (INCA), Rio de Janeiro 20231-050, RJ, Brazil
- Centro de Ciências Biológicas e da Saúde (CCBS), Universidade Federal do Estado do Rio de Janeiro (UNIRIO), Rio de Janeiro 22290-255, RJ, Brazil
| | - Jack Adam Tuszynski
- Dipartimento di Ingegneria Meccanica e Aerospaziale (DIMEAS), Politecnico di Torino, 10129 Turin, Italy;
- Department of Data Science and Engineering, The Silesian University of Technology, 44-100 Gliwice, Poland
- Department of Physics, University of Alberta, Edmonton, AB T6G 2J1, Canada
| | - Cecilia Vianna de Andrade
- Department of Pathology, Instituto Fernandes Figueira, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 22250-020, RJ, Brazil;
| | - Ana Carolina Monteiro
- Laboratory of Osteo and Tumor Immunology, Department of Immunobiology, Fluminense Federal University, Rio de Janeiro 24210-201, RJ, Brazil;
| | - Marcel Guimarães Martins
- Chemical Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-594, RJ, Brazil; (M.G.M.); (T.G.d.S.); (H.F.); (J.C.P.)
| | - Talita Goulart da Silva
- Chemical Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-594, RJ, Brazil; (M.G.M.); (T.G.d.S.); (H.F.); (J.C.P.)
| | - Helen Ferraz
- Chemical Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-594, RJ, Brazil; (M.G.M.); (T.G.d.S.); (H.F.); (J.C.P.)
| | - Priscilla Vanessa Finotelli
- Laboratório de Nanotecnologia Biofuncional, Departamento de Produtos Naturais e Alimentos, Faculdade de Farmácia, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-902, RJ, Brazil;
| | - Tiago Albertini Balbino
- Nanotechnology Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-594, RJ, Brazil;
| | - José Carlos Pinto
- Chemical Engineering Program, Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-594, RJ, Brazil; (M.G.M.); (T.G.d.S.); (H.F.); (J.C.P.)
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Barbosa-Silva A, Magalhães M, Da Silva GF, Da Silva FAB, Carneiro FRG, Carels N. A Data Science Approach for the Identification of Molecular Signatures of Aggressive Cancers. Cancers (Basel) 2022; 14:2325. [PMID: 35565454 PMCID: PMC9103663 DOI: 10.3390/cancers14092325] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/04/2022] [Accepted: 03/12/2022] [Indexed: 02/05/2023] Open
Abstract
The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, kidney, prostate, and thyroid) into classes of high (H) and low (L) aggressiveness considering the TCGA data, and their correlations between Shannon entropy and 5-year overall survival (OS). Then, we used principal component analysis (PCA), a random forest classifier (RFC), and protein-protein interactions (PPI) to find the genes that correlated with aggressiveness. Using PCA, we found GRB2, CTNNB1, SKP1, CSNK2A1, PRKDC, HDAC1, YWHAZ, YWHAB, and PSMD2. Except for PSMD2, the RFC analysis showed a different list, which was CAD, PSMD14, APH1A, PSMD2, SHC1, TMEFF2, PSMD11, H2AFZ, PSMB5, and NOTCH1. Both methods use different algorithmic approaches and have different purposes, which explains the discrepancy between the two gene lists. The key genes of aggressiveness found by PCA were those that maximized the separation of H and L classes according to its third component, which represented 19% of the total variance. By contrast, RFC classified whether the RNA-seq of a tumor sample was of the H or L type. Interestingly, PPIs showed that the genes of PCA and RFC lists were connected neighbors in the PPI signaling network of WNT and cross-linked pathways.
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Affiliation(s)
- Adriano Barbosa-Silva
- Center for Medical Statistics, Informatics and Intelligent Systems, Institute for Artificial Intelligence, Medical University of Vienna, 1090 Vienna, Austria
- Centre for Translational Bioinformatics, William Harvey Research Institute, Queen Mary University of London, London E14NS, UK
- ITTM S.A.-Information Technology for Translational Medicine, Esch-sur-Alzette, 4354 Luxembourg, Luxembourg
| | - Milena Magalhães
- Plataforma de Modelagem de Sistemas Biológicos, Center for Technology Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
| | - Gilberto Ferreira Da Silva
- Plataforma de Modelagem de Sistemas Biológicos, Center for Technology Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
| | - Fabricio Alves Barbosa Da Silva
- Laboratório de Modelagem Computacional de Sistemas Biológicos, Scientific Computing Program, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
| | - Flávia Raquel Gonçalves Carneiro
- Center for Technology Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
- Program of Immunology and Tumor Biology, Brazilian National Cancer Institute (INCA), Rio de Janeiro 20231050, Brazil
| | - Nicolas Carels
- Plataforma de Modelagem de Sistemas Biológicos, Center for Technology Development in Health (CDTS), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro 21040900, Brazil
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