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Acute lymphoblastic leukemia

A 9-gene score for risk stratification in B-cell acute lymphoblastic leukemia

Leukemia volume 34, pages 3070–3074 (2020)Cite this article

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B-cell acute lymphoblastic leukemia (B-ALL), the most common malignancy in children, has an age-dependent prognosis with survival of more than 90% in young children but decreasing to <20% in older adults [1, 2]. Assessment of prognosis at the time of presentation is a key component of management, especially in children, which allows the physician to minimize therapeutic toxicity for favorable risk patients and maximize therapeutic intensity for high-risk patients. Genomic abnormalities are one of the best predictors of outcome, with high hyperdiploidy and t(12;21)/ETV6-RUNX1 predicting a favorable outcome whilst BCR-ABL1, KMT2A translocations, hypodiploidy, iAMP21, and IKZF1 deletions predicting a poor outcome. However, up to 50% of patients have non-informative cytogenetic analyses and are therefore considered standard risk [3]. Detection of minimal residual disease (MRD) during induction therapy provides additional prognostic information that is used to tailor therapy [4].

Relapse arising from chemo-resistant leukemia cells remains the major cause of death. For acute myeloid leukemia (AML), relapse may arise from the survival of leukemia stem cells (LSCs), which have stem cell-like properties including dormancy and chemo-resistance [5]. In this context, based on gene expression profiling of LSCs, a 17-gene LSC score and more recently a 6-gene LSC score could provide prognostic information independent of cytogenetic risk in adult and pediatric AML, respectively [6, 7]. In B-ALL, a rare subpopulation of leukemia cells with dormancy and chemo-resistance was recently identified [8]. Here, we have used the gene signature from these chemo-resistant cells to generate a model that enables prediction of survival outcomes and relapse risk using mRNA expression from primary B-ALL diagnosis samples.

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Fig. 1: Identification of a 9-gene LRC score using genes expressed in chemo-resistant B-ALL cells.
Fig. 2: Performance of 9-gene LRC scores in three test datasets.

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Acknowledgements

FY is supported by a Monash Graduate Scholarship and Monash International Postgraduate Research Scholarship and DJC is supported by a National Health and Medical Research Council Senior Research Fellowship (APP1139466).

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Authors and Affiliations

  1. Australian Centre for Blood Diseases, Central Clinical School, Monash University, Melbourne, VIC, Australia

    Feng Yan, Nicholas C. Wong & David J. Curtis

  2. Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia

    Nicholas C. Wong & David R. Powell

  3. Department of Clinical Haematology, Alfred Health, Melbourne, VIC, Australia

    David J. Curtis

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  1. Feng Yan
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  2. Nicholas C. Wong
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Contributions

FY designed the project and performed all the data analysis including data extraction, cleaning, modeling and validation, and wrote the manuscript. DJC outlined the project. DJC, NCW, and DRP supervised the project, reviewed, and revised the manuscript.

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Correspondence to David J. Curtis.

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Yan, F., Wong, N.C., Powell, D.R. et al. A 9-gene score for risk stratification in B-cell acute lymphoblastic leukemia. Leukemia 34, 3070–3074 (2020). https://doi.org/10.1038/s41375-020-0888-8

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