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

[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 w...

Descripción completa

Detalles Bibliográficos
Autor: Garrido Garcia, Alícia
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/192108
Acceso en línea:https://hdl.handle.net/2445/192108
http://hdl.handle.net/10803/687394
Access Level:acceso abierto
Palabra clave:Oncologia pediàtrica
Epigenètica
Metilació
ADN
Aprenentatge automàtic
Tumors in children
Epigenetics
Methylation
DNA
Machine learning
id ES_9a86fc0000e2cae494542e6abfe9fe7d
oai_identifier_str oai:diposit.ub.edu:2445/192108
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
title Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
spellingShingle Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
Garrido Garcia, Alícia
Oncologia pediàtrica
Epigenètica
Metilació
ADN
Aprenentatge automàtic
Tumors in children
Epigenetics
Methylation
DNA
Machine learning
title_short Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
title_full Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
title_fullStr Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
title_full_unstemmed Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
title_sort Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classification
dc.creator.none.fl_str_mv Garrido Garcia, Alícia
author Garrido Garcia, Alícia
author_facet Garrido Garcia, Alícia
author_role author
dc.contributor.none.fl_str_mv Lavarino, Cinzia
Universitat de Barcelona. Facultat de Biologia
dc.subject.none.fl_str_mv Oncologia pediàtrica
Epigenètica
Metilació
ADN
Aprenentatge automàtic
Tumors in children
Epigenetics
Methylation
DNA
Machine learning
topic Oncologia pediàtrica
Epigenètica
Metilació
ADN
Aprenentatge automàtic
Tumors in children
Epigenetics
Methylation
DNA
Machine learning
description [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.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/doctoralThesis
info:eu-repo/semantics/publishedVersion
format doctoralThesis
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/192108
http://hdl.handle.net/10803/687394
url https://hdl.handle.net/2445/192108
http://hdl.handle.net/10803/687394
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv cc by (c) Garrido Garcia, Alícia, 2023
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc by (c) Garrido Garcia, Alícia, 2023
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat de Barcelona
publisher.none.fl_str_mv Universitat de Barcelona
dc.source.none.fl_str_mv Tesis Doctorals - Facultat - Biologia
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869414411604590592
spelling Molecular characterization of High Risk Neuroblastoma. Potential biomarkers for high-risk neuroblastoma classificationGarrido Garcia, AlíciaOncologia pediàtricaEpigenèticaMetilacióADNAprenentatge automàticTumors in childrenEpigeneticsMethylationDNAMachine learning[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.[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.Universitat de BarcelonaLavarino, CinziaUniversitat de Barcelona. Facultat de Biologia2022info:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/192108http://hdl.handle.net/10803/687394Tesis Doctorals - Facultat - Biologiareponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaIngléscc by (c) Garrido Garcia, Alícia, 2023http://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1921082026-05-27T06:46:51Z
score 15.300724

Similares en LA Referencia