CELLector: genomics-guided selection of cancer in vitro models
Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-g...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
20 May 2020
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| In: |
Cell systems
Year: 2020, Jahrgang: 10, Heft: 5, Pages: 424-432.e6 |
| ISSN: | 2405-4720 |
| DOI: | 10.1016/j.cels.2020.04.007 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.cels.2020.04.007 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S2405471220301502 
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| Verfasserangaben: | Hanna Najgebauer, Mi Yang, Hayley E. Francies, Clare Pacini, Euan A. Stronach, Mathew J. Garnett, Julio Saez-Rodriguez, and Francesco Iorio |
| Zusammenfassung: | Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-guided fashion. CELLector leverages tumor genomics to identify recurrent subtypes with associated genomic signatures. It then evaluates these signatures in cancer cell lines to prioritize their selection. This enables users to choose appropriate in vitro models for inclusion or exclusion in retrospective analyses and future studies. Moreover, this allows bridging outcomes from cancer cell line screens to precisely defined sub-cohorts of primary tumors. Here, we demonstrate the usefulness and applicability of CELLector, showing how it can aid prioritization of in vitro models for future development and unveil patient-derived multivariate prognostic and therapeutic markers. CELLector is freely available at https://ot-cellector.shinyapps.io/CELLector_App/ (code at https://github.com/francescojm/CELLector and https://github.com/francescojm/CELLector_App). |
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| Beschreibung: | Gesehen am 13.08.2020 |
| Beschreibung: | Online Resource |
| ISSN: | 2405-4720 |
| DOI: | 10.1016/j.cels.2020.04.007 |