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Adler N, Bahcheli AT, Cheng KC, Al-Zahrani KN, Slobodyanyuk M, Pellegrina D, Schramek D, Reimand J. Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes. Sci Adv 2023; 9:eadh3083. [PMID: 37922356 PMCID: PMC10624356 DOI: 10.1126/sciadv.adh3083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 10/04/2023] [Indexed: 11/05/2023]
Abstract
Mutational signatures represent a genomic footprint of endogenous and exogenous mutational processes through tumor evolution. However, their functional impact on the proteome remains incompletely understood. We analyzed the protein-coding impact of single-base substitution (SBS) signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) (i.e., nonsense mutations) were strongly enriched in SBS signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes alter specific trinucleotide contexts and thereby substitute serines and glutamic acids with stop codons. SGMs frequently affect cancer hallmark pathways and tumor suppressors such as TP53, FAT1, and APC. Tobacco-driven SGMs in lung cancer correlate with smoking history and highlight a preventable determinant of these harmful mutations. APOBEC-driven SGMs are enriched in YTCA motifs and associate with APOBEC3A expression. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes directly contribute to protein loss of function, oncogenesis, and tumor heterogeneity.
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Affiliation(s)
- Nina Adler
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Alexander T. Bahcheli
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kevin C. L. Cheng
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | | | - Mykhaylo Slobodyanyuk
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Diogo Pellegrina
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Daniel Schramek
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Toronto, ON, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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Pellegrina D, Prayitno K, Azhie A, Pasini E, Baciu C, Fischer S, Reimand J, Bhat M. Transcriptomic changes in liver transplant recipients with non-alcoholic steatohepatitis indicate dysregulation of wound healing. Front Endocrinol (Lausanne) 2023; 14:1111614. [PMID: 37223041 PMCID: PMC10200958 DOI: 10.3389/fendo.2023.1111614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/12/2023] [Indexed: 05/25/2023] Open
Abstract
Background Non-alcoholic steatohepatitis (NASH) has become a leading indication for liver transplantation. However, it often recurs in the graft and can also arise de novo in individuals transplanted for other indications. Post-transplant NASH (PT-NASH) is more aggressive and leads to accelerated fibrosis. The mechanistic basis of PT-NASH has not yet been defined and no specific therapeutic strategies are currently available. Methods Here, we profiled the transcriptomes of livers with PT-NASH from liver transplant recipients to identify dysregulated genes, pathways, and molecular interaction networks. Results Transcriptomic changes in the PI3K-Akt pathway were observed in association with metabolic alterations in PT-NASH. Other significant changes in gene expression were associated with DNA replication, cell cycle, extracellular matrix organization, and wound healing. A systematic comparison with non-transplant NASH (NT-NASH) liver transcriptomes indicated an increased activation of wound healing and angiogenesis pathways in the post-transplant condition. Conclusion Beyond altered lipid metabolism, dysregulation of wound healing and tissue repair mechanisms may contribute to the accelerated development of fibrosis associated with PT-NASH. This presents an attractive therapeutic avenue to explore for PT-NASH to optimize the benefit and survival of the graft.
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Affiliation(s)
- Diogo Pellegrina
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Khairunnadiya Prayitno
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Amirhossein Azhie
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Elisa Pasini
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Cristina Baciu
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Sandra Fischer
- Department of Laboratory Medicine and Pathology, University of Toronto, Toronto, ON, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Mamatha Bhat
- Multi-Organ Transplant Program, Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Ajmera Transplant Center, Toronto General Hospital, University Health Network, Toronto, ON, Canada
- Division of Gastroenterology & Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada
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Pellegrina D, Bahcheli AT, Krassowski M, Reimand J. Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants. Mol Syst Biol 2022; 18:e10823. [PMID: 35579274 PMCID: PMC9112486 DOI: 10.15252/msb.202110823] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 11/23/2022] Open
Abstract
SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the genetic variation in these signaling networks remains uncharacterized. Here, we studied human missense single nucleotide variants (SNVs) altering phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid substitutions altering kinase-bound sequence motifs. We found 2,033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle and host responses, including RNA splicing, interferon response (TRIM28), and glucose homeostasis (TBC1D4) with potential associations with COVID-19 comorbidities. pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs of Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of signaling networks. Several pSNVs associate with severe COVID-19 and hospitalization (STARD13, ARFGEF2). Our analysis highlights potential genetic factors contributing to inter-individual variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.
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Affiliation(s)
- Diogo Pellegrina
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
| | - Alexander T Bahcheli
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
- Department of Molecular GeneticsUniversity of TorontoTorontoONCanada
| | - Michal Krassowski
- Medical Sciences DivisionNuffield Department of Women's and Reproductive HealthUniversity of OxfordOxfordUK
| | - Jüri Reimand
- Computational Biology ProgramOntario Institute for Cancer ResearchTorontoONCanada
- Department of Molecular GeneticsUniversity of TorontoTorontoONCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoONCanada
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Krassowski M, Pellegrina D, Mee MW, Fradet-Turcotte A, Bhat M, Reimand J. ActiveDriverDB: Interpreting Genetic Variation in Human and Cancer Genomes Using Post-translational Modification Sites and Signaling Networks (2021 Update). Front Cell Dev Biol 2021; 9:626821. [PMID: 33834021 PMCID: PMC8021862 DOI: 10.3389/fcell.2021.626821] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 02/08/2021] [Indexed: 12/14/2022] Open
Abstract
Deciphering the functional impact of genetic variation is required to understand phenotypic diversity and the molecular mechanisms of inherited disease and cancer. While millions of genetic variants are now mapped in genome sequencing projects, distinguishing functional variants remains a major challenge. Protein-coding variation can be interpreted using post-translational modification (PTM) sites that are core components of cellular signaling networks controlling molecular processes and pathways. ActiveDriverDB is an interactive proteo-genomics database that uses more than 260,000 experimentally detected PTM sites to predict the functional impact of genetic variation in disease, cancer and the human population. Using machine learning tools, we prioritize proteins and pathways with enriched PTM-specific amino acid substitutions that potentially rewire signaling networks via induced or disrupted short linear motifs of kinase binding. We then map these effects to site-specific protein interaction networks and drug targets. In the 2021 update, we increased the PTM datasets by nearly 50%, included glycosylation, sumoylation and succinylation as new types of PTMs, and updated the workflows to interpret inherited disease mutations. We added a recent phosphoproteomics dataset reflecting the cellular response to SARS-CoV-2 to predict the impact of human genetic variation on COVID-19 infection and disease course. Overall, we estimate that 16-21% of known amino acid substitutions affect PTM sites among pathogenic disease mutations, somatic mutations in cancer genomes and germline variants in the human population. These data underline the potential of interpreting genetic variation through the lens of PTMs and signaling networks. The open-source database is freely available at www.ActiveDriverDB.org.
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Affiliation(s)
- Michal Krassowski
- Nuffield Department of Women’s and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Diogo Pellegrina
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Miles W. Mee
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Amelie Fradet-Turcotte
- Department of Molecular Biology, Medical Biochemistry and Pathology, Universite Laval, Quebec, QC, Canada
- Oncology Division, Centre Hospitalier Universitaire (CHU) de Quebec-Universite Laval Research Center, Quebec, QC, Canada
| | - Mamatha Bhat
- Multiorgan Transplant Program, University Health Network, Toronto, ON, Canada
- Division of Gastroenterology & Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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