RESUMEN
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
Asunto(s)
COVID-19/inmunología , Biología Computacional/métodos , Bases de Datos Factuales , SARS-CoV-2/inmunología , Programas Informáticos , Antivirales/uso terapéutico , COVID-19/genética , COVID-19/virología , Gráficos por Computador , Citocinas/genética , Citocinas/inmunología , Minería de Datos/estadística & datos numéricos , Regulación de la Expresión Génica , Interacciones Microbiota-Huesped/genética , Interacciones Microbiota-Huesped/inmunología , Humanos , Inmunidad Celular/efectos de los fármacos , Inmunidad Humoral/efectos de los fármacos , Inmunidad Innata/efectos de los fármacos , Linfocitos/efectos de los fármacos , Linfocitos/inmunología , Linfocitos/virología , Redes y Vías Metabólicas/genética , Redes y Vías Metabólicas/inmunología , Células Mieloides/efectos de los fármacos , Células Mieloides/inmunología , Células Mieloides/virología , Mapeo de Interacción de Proteínas , SARS-CoV-2/efectos de los fármacos , SARS-CoV-2/genética , SARS-CoV-2/patogenicidad , Transducción de Señal , Factores de Transcripción/genética , Factores de Transcripción/inmunología , Proteínas Virales/genética , Proteínas Virales/inmunología , Tratamiento Farmacológico de COVID-19RESUMEN
PRL-3 belongs to the PRL phosphatase family. Its physiological role remains unclear, but many studies have identified that PRL-3 is a marker of cancer progression and shown it to be associated with metastasis. Evidence implicating PRL-3 in various elements of the metastatic process, such as the cell cycle, survival, angiogenesis, adhesion, cytoskeleton remodeling, EMT, motility and invasion, has been reported. Furthermore, several molecules acting as direct or indirect substrates have been identified. However, this information was obtained in many different studies, and it remains difficult to see the larger picture. We therefore systematically collected the published information together and used it to develop a comprehensive signaling network map. By analyzing this network map, we were able to retrieve the signaling pathways via which PRL-3 governs the key steps of the metastatic process in cancer. In this review, we summarize current knowledge of the role of PRL-3 in cancer and the molecular mechanisms involved. We also provide the web-based open-source PRL-3 signaling network map, for use in further studies.