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Imbalance between genomic gain and loss identifies high-risk neuroblastoma patients with worse outcomes

Survival in high-risk neuroblastoma (HR-NB) patients remains poor despite multimodal treatment. We aimed to identify HR-NB patients with worse outcomes by analyzing the genomic instability derived from segmental chromosomal aberrations. We calculated 3 genomic instability indexes for primary tumor S...

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Detalles Bibliográficos
Autores principales: Fernández-Blanco, Beatriz, Berbegall, Ana Pilar, Martin-Vañó, Susana, Castel, Victoria, Navarro, Samuel, Noguera, Rosa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674617/
https://www.ncbi.nlm.nih.gov/pubmed/33190090
http://dx.doi.org/10.1016/j.neo.2020.11.001
Descripción
Sumario:Survival in high-risk neuroblastoma (HR-NB) patients remains poor despite multimodal treatment. We aimed to identify HR-NB patients with worse outcomes by analyzing the genomic instability derived from segmental chromosomal aberrations. We calculated 3 genomic instability indexes for primary tumor SNP array profiles from 127 HR-NB patients: (1) Copy number aberration burden (%gains(length)+%losses(length)), (2) copy number load (CNL) (%gains(length)-%losses(length)) and (3) net genomic load (NGL) (%gains(amount)-%losses(amount)). Tumors were classified according to positive or negative CNL and NGL genomic subtypes. The impact of the genomic instability indexes on overall survival (OS) was assessed with Cox regression. We identified 38% of HR-NB patients with poor 5-year OS. A negative CNL genomic background was related to poor prognosis in patients ≥18 months showing tumors with homogeneous MYCN amplification (9.5% survival probability, P < 0.05) and patients with non-MYCN amplified NB (18.8% survival probability related to >2.4% CNL, P < 0.01). A positive CNL genomic background was associated with worse outcome in patients with heterogeneous MYCN amplification (22.5% survival probability, P < 0.05). We conclude that characterizing a tumor genomic background according to predominance of genome gained or lost contributes toward improved outcome prediction and brings greater insight into the tumor biology of HR-NB patients.