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Effective Response Metric: a novel tool to predict relapse in childhood acute lymphoblastic leukaemia using time-series gene expression profiling

AE. Yeoh, Z. Li, D. Dong, Y. Lu, N. Jiang, J. Trka, AM. Tan, HP. Lin, TC. Quah, H. Ariffin, L. Wong,

. 2018 ; 181 (5) : 653-663.

Language English Country England, Great Britain

Document type Clinical Trial, Journal Article, Multicenter Study, Research Support, Non-U.S. Gov't

Accurate risk assignment in childhood acute lymphoblastic leukaemia is essential to avoid under- or over-treatment. We hypothesized that time-series gene expression profiles (GEPs) of bone marrow samples during remission-induction therapy can measure the response and be used for relapse prediction. We computed the time-series changes from diagnosis to Day 8 of remission-induction, termed Effective Response Metric (ERM-D8) and tested its ability to predict relapse against contemporary risk assignment methods, including National Cancer Institutes (NCI) criteria, genetics and minimal residual disease (MRD). ERM-D8 was trained on a set of 131 patients and validated on an independent set of 79 patients. In the independent blinded test set, unfavourable ERM-D8 patients had >3-fold increased risk of relapse compared to favourable ERM-D8 (5-year cumulative incidence of relapse 38·1% vs. 10·6%; P = 2·5 × 10-3 ). ERM-D8 remained predictive of relapse [P = 0·05; Hazard ratio 4·09, 95% confidence interval (CI) 1·03-16·23] after adjusting for NCI criteria, genetics, Day 8 peripheral response and Day 33 MRD. ERM-D8 improved risk stratification in favourable genetics subgroups (P = 0·01) and Day 33 MRD positive patients (P = 1·7 × 10-3 ). We conclude that our novel metric - ERM-D8 - based on time-series GEP after 8 days of remission-induction therapy can independently predict relapse even after adjusting for NCI risk, genetics, Day 8 peripheral blood response and MRD.

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$a Accurate risk assignment in childhood acute lymphoblastic leukaemia is essential to avoid under- or over-treatment. We hypothesized that time-series gene expression profiles (GEPs) of bone marrow samples during remission-induction therapy can measure the response and be used for relapse prediction. We computed the time-series changes from diagnosis to Day 8 of remission-induction, termed Effective Response Metric (ERM-D8) and tested its ability to predict relapse against contemporary risk assignment methods, including National Cancer Institutes (NCI) criteria, genetics and minimal residual disease (MRD). ERM-D8 was trained on a set of 131 patients and validated on an independent set of 79 patients. In the independent blinded test set, unfavourable ERM-D8 patients had >3-fold increased risk of relapse compared to favourable ERM-D8 (5-year cumulative incidence of relapse 38·1% vs. 10·6%; P = 2·5 × 10-3 ). ERM-D8 remained predictive of relapse [P = 0·05; Hazard ratio 4·09, 95% confidence interval (CI) 1·03-16·23] after adjusting for NCI criteria, genetics, Day 8 peripheral response and Day 33 MRD. ERM-D8 improved risk stratification in favourable genetics subgroups (P = 0·01) and Day 33 MRD positive patients (P = 1·7 × 10-3 ). We conclude that our novel metric - ERM-D8 - based on time-series GEP after 8 days of remission-induction therapy can independently predict relapse even after adjusting for NCI risk, genetics, Day 8 peripheral blood response and MRD.
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$a Li, Zhenhua $u Centre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. Viva-University Children's Cancer Centre, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore.
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$a Dong, Difeng $u School of Computing, National University of Singapore, Singapore.
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$a Lu, Yi $u Centre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. Viva-University Children's Cancer Centre, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore.
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$a Jiang, Nan $u Centre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. Viva-University Children's Cancer Centre, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore.
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$a Trka, Jan $u 2nd Faculty of Medicine, Charles University, Prague, Czech Republic.
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$a Tan, Ah Moy $u Department of Paediatrics, KK Women's & Children's Hospital, Singapore.
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$a Lin, Hai Peng $u Sime Darby Medical Centre, Subang Jaya, Malaysia.
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$a Quah, Thuan Chong $u Centre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. Viva-University Children's Cancer Centre, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore.
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$a Ariffin, Hany $u Faculty of Medicine, University of Malaya Cancer Research Institute, University of Malaya, Kuala Lumpur, Malaysia.
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