Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification

dc.contributor
Universitat de Barcelona. Facultat de Biologia
dc.contributor.author
Garrido Garcia, Alícia
dc.date.accessioned
2023-01-12T08:55:00Z
dc.date.available
2023-11-10T23:45:28Z
dc.date.issued
2022-11-10
dc.identifier.uri
http://hdl.handle.net/10803/687394
dc.description
Programa de Doctorat en Biomedicina / Tesi realitzada al Pediatric Cancer Center Barcelona
ca
dc.description.abstract
[eng] BACKGROUND: High-risk neuroblastoma (NB) represents a heterogeneous group of tumors, whereby patients can display response to treatment and long-term outcome or develop early progressive, chemoresistant disease with poor outcome. To date, high-risk NB patients are generally treated uniformly with no further stratification, as established in routinely used risk stratification systems. A revised molecular risk stratification has been proposed based on the analysis of telomere maintenance mechanisms, and RAS or TP53 pathway mutations. However, genetics underlying this aggressive subgroup is still greatly unknown and risk stratification of high-risk NB tumors is still challenging. AIM: To study high-risk NB tumors and to define a subgroup of high-risk NB patients with particularly poor outcome, with the aim of improving risk­ stratification of high-risk NB, of identifying altered biological pathways that may represent therapeutic options, and to learn more about the biology underlying this malignant pediatric tumor. METHODS: We analyzed DNA methylation microarray and gene expression data from nearly 700 high-risk NB samples obtained at diagnosis. Cox-regression models and Machine-Learning analysis were used for survival analyses. Survival curves were estimated by Kaplan-Meier method and compared by log-rank test. Pathway analysis was performed using R package KEGGREST, ConsensusPathDB-MaxPlanck and R package topGO. Pyrosequencing, phospho-kinase array, immunoblotting and immunohistochemical techniques were used for validation purposes. RESULTS: We identified distinct DNA methylation profiles within high-risk NB. Cox­ regression models and Machine Learning analysis, identified differentially methylated CpG sites that defined two subgroups of patients with substantially different overall survival (OS). Moreover, we identified methylation markers that could distinguish these clinically relevant subgroups of tumors. Integrative analysis of DNA methylation and matching gene expression data, identified differential expression of genes involved in cellular metabolism, purine biosynthesis and AKT/mTOR cell signaling. Protein expression analysis identified high levels of proteins involved in IMP metabolism and increased activation of AKT/mTOR pathways in highly aggressive NB. CONCLUSION: We have identified (epi)genetic changes underlying the heterogeneous behavior of aggressive NB, and revealed altered pathways of interest for potential therapeutic options. We identified a set of markers that enabled classification of high-risk NB into clinically relevant subgroups.
ca
dc.description.abstract
[spa] 1. OBJETIVO GLOBAL: En neuroblastoma (NB), la presencia de enfermedad diseminada en pacientes mayores de 18 meses de edad o la presencia de amplificación del oncogén MYCN a cualquier edad, define un grupo de alto-riesgo clínico con supervivencia a 5 años inferior a 50%. El NB de alto-riesgo representa un grupo heterogéneo de tumores, con comportamiento clínico diverso y diferente respuesta al tratamiento. Sin embargo, los pacientes con tumores diseminados de alto-riesgo son tratados uniformemente con tratamiento multimodal intensivo, sin ninguna estratificación adicional. En la actualidad, no existen biomarcadores que permitan identificar, de forma rápida y precisa en el momento del diagnóstico, los pacientes con NB agresivos, potencialmente refractarios, que no se benefician de los tratamientos convencionales y que necesitan nuevas estrategias terapéuticas. Numerosos estudios han demostrado que el análisis del perfil de metilación del DNA permite tipificar y clasificar de forma precisa los tumores del sistema nervioso central, demostrando ser aplicable en el contexto del diagnóstico molecular. Hasta la fecha, el metiloma del HR-NB, no ha sido estudiado en profundidad. En esta tesis doctoral, hemos estudiado el metiloma del HR-NB con el objetivo de i) identificar patrones de metilación que permitan distinguir subgrupos con diversa evolución clínica, y mejorar la estratificación de los pacientes, ii) identificar posibles vías biológicas alteradas que puedan representar nuevas opciones terapéuticas, y iii) mejorar el conocimiento de la biología subyacente al comportamiento agresivo de estos tumores. 2. OBJETIVOS ESPECÍFICOS: l. Estudiar el perfil de metilación del DNA en el neuroblastoma de alto­ riesgo. 2. Identificar potenciales biomarcadores epigenéticos asociados con supervivencia de los pacientes con neuroblastoma de alto-riesgo. 3. Caracterizar la biología del neuroblastoma de alto-riesgo.
ca
dc.format.extent
179 p.
ca
dc.language.iso
eng
ca
dc.publisher
Universitat de Barcelona
dc.rights.license
L'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by/4.0/
ca
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
*
dc.source
TDX (Tesis Doctorals en Xarxa)
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Oncologia pediàtrica
ca
dc.subject
Oncología pediátrica
ca
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Tumors in children
ca
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Epigenètica
ca
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Epigenética
ca
dc.subject
Epigenetics
ca
dc.subject
Metilació
ca
dc.subject
Metilación
ca
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Methylation
ca
dc.subject
ADN
ca
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DNA
ca
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Aprenentatge automàtic
ca
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Aprendizaje automático
ca
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Machine learning
ca
dc.subject.other
Ciències Experimentals i Matemàtiques
ca
dc.title
Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
ca
dc.type
info:eu-repo/semantics/doctoralThesis
dc.type
info:eu-repo/semantics/publishedVersion
dc.subject.udc
575
ca
dc.contributor.director
Lavarino, Cinzia
dc.contributor.tutor
Gelpi Buchaca, Josep Lluís
dc.rights.accessLevel
info:eu-repo/semantics/openAccess


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