Genome wide DNA methylation analysis identifies novel molecular subgroups and predicts survival in neuroblastoma

Lalchungnunga, H., Hao, Wen, Maris, John M., Asgharzadeh, Shahab, Henrich, Kai-Oliver, Westermann, Frank, Tweddle, Deborah A., Schwalbe, Ed and Strathdee, Gordon (2022) Genome wide DNA methylation analysis identifies novel molecular subgroups and predicts survival in neuroblastoma. British Journal of Cancer, 127 (11). pp. 2006-2015. ISSN 0007-0920

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Background: Neuroblastoma is the most common malignancy in infancy, accounting for 15% of childhood cancer deaths. Outcome for the high-risk disease remains poor. DNA-methylation patterns are significantly altered in all cancer types and can be utilised for disease stratification. Methods: Genome-wide DNA methylation (n = 223), gene expression (n = 130), genetic/clinical data (n = 213), whole-exome sequencing (n = 130) was derived from the TARGET study. Methylation data were derived from HumanMethylation450 BeadChip arrays. t-SNE was used for the segregation of molecular subgroups. A separate validation cohort of 105 cases was studied. Results: Five distinct neuroblastoma molecular subgroups were identified, based on genome-wide DNA-methylation patterns, with unique features in each, including three subgroups associated with known prognostic features and two novel subgroups. As expected, Cluster-4 (infant diagnosis) had significantly better 5-year progression-free survival (PFS) than the four other clusters. However, in addition, the molecular subgrouping identified multiple patient subsets with highly increased risk, most notably infant patients that do not map to Cluster-4 (PFS 50% vs 80% for Cluster-4 infants, P = 0.005), and allowed identification of subgroup-specific methylation differences that may reflect important biological differences within neuroblastoma. Conclusions: Methylation-based clustering of neuroblastoma reveals novel molecular subgroups, with distinct molecular/clinical characteristics and identifies a subgroup of higher-risk infant patients.

Item Type: Article
Additional Information: Funding information: This work was funded by project grants from Kidscan (GS, LH), R35 CA220500 (JMM), and P01 CA217959 (JMM, SA) from the National Institute of Health, funding from US National Institutes of Health grants RC1MD004418 to the TARGET consortium and CA98543 and CA98413 to the Children’s Oncology Group and funding by the EU as part of the EraCoSysMed initiative (Infer-NB to FW).
Subjects: B100 Anatomy, Physiology and Pathology
C400 Genetics
C500 Microbiology
Department: Faculties > Health and Life Sciences > Applied Sciences
Depositing User: Elena Carlaw
Date Deposited: 25 Nov 2022 15:35
Last Modified: 25 Nov 2022 15:45

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