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Lookup NU author(s): Dr Peixun Zhou, Dr Amir EnshaeiORCiD, Alex Newman, Dr Amy Erhorn, Amy Barnard, Dr Rachel CrosslandORCiD, Sara Wilkinson, Professor Anthony MoormanORCiD, Karl Wood, Dr Despoina Televantou, Dr Peter Carey, Dr Simon BomkenORCiD, Dr Christopher BaconORCiD, Professor Simon BaileyORCiD, Professor ELizabeth Molyneux, Dr Vikki Rand
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Background/Objectives: Despite excellent outcomes for Burkitt lymphoma (BL) in high-income settings, the delivery of intensive multi-agent chemo-immunotherapy is prevented in low-income countries by high costs and insufficient access to supportive care facilities. Consequently, patient outcome remains unsatisfactory and new therapeutic approaches are urgently needed to improve survival. Using genomic profiling we aimed to identify abnormalities that stratify patients based on response to current protocols and define potential therapeutic targets. Design/Methods: We collected 113 diagnostic samples from the Queen Elizabeth Central Hospital, Malawi and the Children’s Cancer and Leukaemia Group (CCLG), UK. High-resolution copy number profiling data was generated using Affymetrix Oncoscan and Cytoscan arrays. Survival analysis examined the association of clinico-molecular factors with risk of relapse. Multivariate Cox regression modelling was applied to develop a risk stratification model. Results: Thirty recurrent focal copy number abnormalities were detected in 63 endemic BL cases using GISTIC2.0. Regions of gain contained known cancer-related genes, MCL1, EBF1, BCL6, BACH2, MAP3K7, BTG4, MDM2 and FOXO1. Large genomic alterations included gain of 1q, 7q and 12q. Survival analysis identified abnormalities involving chromosomes 1 and 13 to be associated with an increased risk of relapse. Gain of either abnormality identified one third of patients with a high-risk of relapse (77%) compared to the low-risk group (25%) (hazard ratio 4.32 (CI 95% 1.46-12.83), p=0.008). Despite differences in treatment intensity, there was no difference in outcome for endemic and sporadic patients identified as low-risk by this model. However, outcome for high-risk patients was significantly different (RR 77% versus 13%, p=0.0007 for endemic and sporadic BL respectively). Conclusion: We have developed the first risk stratification model for endemic BL which identifies patients at a high-risk of relapse who may benefit from stratified increase in treatment intensity. In contrast, low-risk patients may be candidates for treatment de-intensification to reduce toxicity-related side-effects in other healthcare settings.
Author(s): Zhou P, Enshaei A, Newman AM, Chagaluka G, Lampert I, Van Noorden S, Erhorn A, Barnard A, Crossland RE, Wilkinson S, Nakang S, Moorman AV, Wood K, Televantou D, Carey P, Bomken S, Bacon CM, Bailey S, Molyneux E, Rand V
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 50th Congress of the International Society of Paediatric Oncology (SIOP)
Year of Conference: 2018
Print publication date: 20/09/2018
Online publication date: 20/09/2018
Acceptance date: 20/09/2018
ISSN: 1545-5017
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1002/pbc.27455
DOI: 10.1002/pbc.27455
PubMed id: 30240102
Series Title: Pediatric Blood and Cancer
