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Single nucleotide polymorphism (SNP) array-based signature of low hypodiploidy in acute lymphoblastic leukemia

Lookup NU author(s): Dr Tom Creasey, Dr Amir EnshaeiORCiD, Claire Schwab, Kathryn Watts, Gavin Cuthbert, Professor Anthony MoormanORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Low hypodiploidy (30‐39 chromosomes) is one of the most prevalent genetic subtypes among adults with ALL and is associated with a very poor outcome. Low hypodiploid clones can often undergo a chromosomal doubling generating a near‐triploid clone (60‐78 chromosomes). When cytogenetic techniques detect a near triploid clone, a diagnostic challenge may ensue in differentiating presumed duplicated low hypodiploidy from good risk high hyperdiploid ALL (51‐67 chromosomes). We used single‐nucleotide polymorphism (SNP) arrays to analyze low hypodiploid/near triploid (HoTr) (n=48) and high hyperdiploid (HeH) (n=40) cases. In addition to standard analysis, we derived log2 ratios for entire chromosomes enabling us to analyze the cohort using machine‐learning techniques. Low hypodiploid and near triploid cases clustered together and separately from high hyperdiploid samples. Using these approaches, we also identified three cases with 50‐60 chromosomes, originally called as HeH, which were, in fact, HoTr and two cases incorrectly called as HoTr. TP53 mutation analysis supported the new classification of all cases tested. Next, we constructed a classification and regression tree model for predicting ploidy status with chromosomes 1, 7 and 14 being the key discriminators. The classifier correctly identified 47/50 (94%) HoTr cases. We validated the classifier using an independent cohort of 44 cases where it correctly called 7/7 (100%) low hypodiploid cases. The results of this study suggest that HoTr is more frequent among older adults with ALL than previously estimated and that SNP array analysis should accompany cytogenetics where possible. The classifier can assist where SNP array patterns are challenging to interpret.

Publication metadata

Author(s): Creasey T, Enshaei A, Nebral K, Schwab C, Watts K, Cuthbert G, Vora A, Moppett J, Harrison CJ, Fielding AD, Haas OA, Moorman AV

Publication type: Article

Publication status: Published

Journal: Genes Chromosomes Cancer

Year: 2021

Volume: 60

Issue: 9

Pages: 604-615

Print publication date: 01/09/2021

Online publication date: 03/05/2021

Acceptance date: 26/04/2021

Date deposited: 03/08/2022

ISSN (print): 1045-2257

ISSN (electronic): 1098-2264

Publisher: Wiley


DOI: 10.1002/gcc.22956

PubMed id: 33938069


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Funder referenceFunder name
15036Bloodwise (Formerly Leukaemia and Lymphoma Research) Closed Competition
17-242Children with Cancer UK (Formerly Children with Leukaemia)
C27995/A21019Cancer Research UK CRUK (open competition)