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Palabras clave – provistas por la editorial

neurofibromatosis type 1; nerve sheath tumor; cancer; latent variables; machine learning; supervised learning; transfer learning; random forest; metaVIPER; tumor deconvolution; neurofibromatosis; malignant peripheral nerve sheath tumor; MPNST; polycomb repressive complex; PRC2; NF1; kinase; kinome adaptation; kinome reprogramming; MET; MEK; doxorubicin; capmatinib; tram; genomics; tumor evolution; pathology; next generation sequencing; clinical genetics; malignant peripheral nerve sheath tumors; plexiform neurofibromas; Schwann cells; neurofibromatosis type 1 syndrome; neurofibromin 1; genetically engineered mouse models; heterogeneity; CRISPR/Cas9; mouse models; sarcoma; tumor microenvironment; neurofibromatosis 1 (NF1); mebendazole (MBZ); COX-2 inhibitor; malignancy; chemoprevention; nerve sheath tumors