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Iannuccelli M, Vitriolo A, Licata L, Lo Surdo P, Contino S, Cheroni C, Capocefalo D, Castagnoli L, Testa G, Cesareni G, Perfetto L. Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders. Mol Psychiatry 2024; 29:186-196. [PMID: 38102483 PMCID: PMC11078740 DOI: 10.1038/s41380-023-02317-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 10/14/2023] [Accepted: 10/31/2023] [Indexed: 12/17/2023]
Abstract
Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.
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Affiliation(s)
- Marta Iannuccelli
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy
| | - Alessandro Vitriolo
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Via Adamello 16, 20139, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122, Milan, Italy
| | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy
- Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
| | - Prisca Lo Surdo
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy
- Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
| | - Silvia Contino
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy
| | - Cristina Cheroni
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122, Milan, Italy
| | - Daniele Capocefalo
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122, Milan, Italy
| | - Luisa Castagnoli
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy
| | - Giuseppe Testa
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy.
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Via Adamello 16, 20139, Milan, Italy.
- Department of Oncology and Hemato-Oncology, University of Milan, Via Santa Sofia 9, 20122, Milan, Italy.
| | - Gianni Cesareni
- Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, 00133, Rome, Italy.
| | - Livia Perfetto
- Computational Biology Research Centre, Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy.
- Department of Biology and Biotechnologies 'Charles Darwin', Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy.
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Iannuccelli M, Lo Surdo P, Licata L, Castagnoli L, Cesareni G, Perfetto L. A Resource to Infer Molecular Paths Linking Cancer Mutations to Perturbation of Cell Metabolism. Front Mol Biosci 2022; 9:893256. [PMID: 35664677 PMCID: PMC9158333 DOI: 10.3389/fmolb.2022.893256] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/19/2022] [Indexed: 12/20/2022] Open
Abstract
Some inherited or somatically-acquired gene variants are observed significantly more frequently in the genome of cancer cells. Although many of these cannot be confidently classified as driver mutations, they may contribute to shaping a cell environment that favours cancer onset and development. Understanding how these gene variants causally affect cancer phenotypes may help developing strategies for reverting the disease phenotype. Here we focus on variants of genes whose products have the potential to modulate metabolism to support uncontrolled cell growth. Over recent months our team of expert curators has undertaken an effort to annotate in the database SIGNOR 1) metabolic pathways that are deregulated in cancer and 2) interactions connecting oncogenes and tumour suppressors to metabolic enzymes. In addition, we refined a recently developed graph analysis tool that permits users to infer causal paths leading from any human gene to modulation of metabolic pathways. The tool grounds on a human signed and directed network that connects ∼8400 biological entities such as proteins and protein complexes via causal relationships. The network, which is based on more than 30,000 published causal links, can be downloaded from the SIGNOR website. In addition, as SIGNOR stores information on drugs or other chemicals targeting the activity of many of the genes in the network, the identification of likely functional paths offers a rational framework for exploring new therapeutic strategies that revert the disease phenotype.
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Affiliation(s)
| | - Prisca Lo Surdo
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
- Fondazione Human Technopole, Milan, Italy
| | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
- Fondazione Human Technopole, Milan, Italy
| | - Luisa Castagnoli
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
| | - Gianni Cesareni
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
- *Correspondence: Gianni Cesareni, ; Livia Perfetto,
| | - Livia Perfetto
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
- Fondazione Human Technopole, Milan, Italy
- *Correspondence: Gianni Cesareni, ; Livia Perfetto,
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De Marinis I, Lo Surdo P, Cesareni G, Perfetto L. SIGNORApp: a Cytoscape 3 application to access SIGNOR data. Bioinformatics 2022; 38:1764-1766. [PMID: 34954787 DOI: 10.1093/bioinformatics/btab865] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/20/2021] [Accepted: 12/23/2021] [Indexed: 02/03/2023] Open
Abstract
SUMMARY SIGNORApp is a Cytoscape 3 (3.8 and later) application that provides access to causal interactions annotated in the SIGNOR resource. The application builds networks that can be represented as weighted, signed, directed graphs, where nodes are interacting biological entities and edges represent causal interactions captured by expert curators from experiments reported in peer reviewed journals. Users can query the SIGNOR dataset with (i) single or multiple entity name(s) or identifier(s) and optionally they may require to include in the output network their interacting partners, (ii) browse pathways that are annotated in the SIGNOR resource and (iii) extract the entire causal interactome. The app offers two visualizations modes: one only displaying entity interactions and a second emphasizing the post-translational modifications occurring as a consequence of the interaction. In addition, users can click on nodes and edges to access entity and interaction annotations. Causal information is available for three model organisms: Homo sapiens, Mus musculus and Rattus norvegicus. AVAILABILITY AND IMPLEMENTATION SIGNORApp has been developed for Cytoscape 3 (3.8 and later) in the Java programming language. The latest source code and the plugin can be found at: https://github.com/SIGNORcysAPP/signor-app and https://apps.cytoscape.org/apps/signorapp, respectively. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ilaria De Marinis
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Prisca Lo Surdo
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.,Department of Biology, Fondazione Human Technopole, 20157 Milan, Italy
| | - Gianni Cesareni
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Livia Perfetto
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy.,Department of Biology, Fondazione Human Technopole, 20157 Milan, Italy
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