British Journal of Cancer · 2021 · 26 citations · 53 references
MedicineBioinformaticsOncologyDrug DiscoveryMetastasisMolecular OncologyCancer BiomarkersMalignant NeoplasmsMelanocytic TumorsMelanoma PharmacotherapyMetastatic Disease TreatmentMetastatic Signaling PathwaysCancer Metastasis MechanismsCell InvasionCell Morphology AnalysisDrug Target ValidationDruggable Target DiscoveryMetastasis ModelsMetastatic Melanoma TreatmentMurine Models
BACKGROUND: Metastasis is a hallmark of cancer and responsible for most cancer deaths. Migrastatics were defined as drugs interfering with all modes of cancer cell invasion and thus cancers' ability to metastasise. First anti-metastatic treatments have recently been approved. METHODS: We used bioinformatic analyses of publicly available melanoma databases. Experimentally, we performed in vitro target validation (including 2.5D cell morphology analysis and mass spectrometric analysis of RhoA binding partners), developed a new traceable spontaneously metastasising murine melanoma model for in vivo validation, and employed histology (haematoxylin/eosin and phospho-myosin II staining) to confirm drug action in harvested tumour tissues. RESULTS: Unbiased and targeted bioinformatic analyses identified the Rho kinase (ROCK)-myosin II pathway and its various components as potentially relevant targets in melanoma. In vitro validation demonstrated redundancy of several RhoGEFs upstream of RhoA and confirmed ROCK as a druggable target downstream of RhoA. The anti-metastatic effects of two ROCK inhibitors were demonstrated through in vivo melanoma metastasis tracking and inhibitor effects also confirmed ex vivo by digital pathology. CONCLUSIONS: We proposed a migrastatic drug development pipeline. As part of the pipeline, we provide a new traceable spontaneous melanoma metastasis model for in vivo quantification of metastasis and anti-metastatic effects by non-invasive imaging.
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Ethan Cerami, Jianjiong Gao, Uğur Doğrusöz et al. · Cancer Discovery · 2012 · 18.4K citations · Full text
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Jianjiong Gao, Bülent Arman Aksoy, Uğur Doğrusöz et al. · Science Signaling · 2013 · 15.9K citations · Full text
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