Cancer predictive studies

Author:

Amelio IvanoORCID,Bertolo RiccardoORCID,Bove PierluigiORCID,Candi EleonoraORCID,Chiocchi MarcelloORCID,Cipriani ChiaraORCID,Di Daniele NicolaORCID,Ganini CarloORCID,Juhl Hartmut,Mauriello AlessandroORCID,Marani CarlaORCID,Marshall John,Montanaro ManuelaORCID,Palmieri GiampieroORCID,Piacentini MauroORCID,Sica GiuseppeORCID,Tesauro ManfrediORCID,Rovella ValentinaORCID,Tisone GiuseppeORCID,Shi YufangORCID,Wang YingORCID,Melino GerryORCID

Abstract

AbstractThe identification of individual or clusters of predictive genetic alterations might help in defining the outcome of cancer treatment, allowing for the stratification of patients into distinct cohorts for selective therapeutic protocols. Neuroblastoma (NB) is the most common extracranial childhood tumour, clinically defined in five distinct stages (1–4 & 4S), where stages 3–4 define chemotherapy-resistant, highly aggressive disease phases. NB is a model for geneticists and molecular biologists to classify genetic abnormalities and identify causative disease genes. Despite highly intensive basic research, improvements on clinical outcome have been predominantly observed for less aggressive cancers, that is stages 1,2 and 4S. Therefore, stages 3–4 NB are still complicated at the therapeutic level and require more intense fundamental research. Using neuroblastoma as a model system, here we herein outline how cancer prediction studies can help at steering preclinical and clinical research toward the identification and exploitation of specific genetic landscape. This might result in maximising the therapeutic success and minimizing harmful effects in cancer patients.

Funder

Associazione Italiana per la Ricerca sul Cancro

Ministero della Salute

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Immunology

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