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Acute myeloid leukemia

Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling

Leukemia volume 31, pages 2029–2036 (2017)Cite this article

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Abstract

Risk stratification of acute myeloid leukemia (AML) patients needs improvement. Several AML risk classification models based on somatic mutations or gene-expression profiling have been proposed. However, systematic and independent validation of these models is required for future clinical implementation. We performed whole-transcriptome RNA-sequencing and panel-based deep DNA sequencing of 23 genes in 274 intensively treated AML patients (Clinseq-AML). We also utilized the The Cancer Genome Atlas (TCGA)-AML study (N=142) as a second validation cohort. We evaluated six previously proposed molecular-based models for AML risk stratification and two revised risk classification systems combining molecular- and clinical data. Risk groups stratified by five out of six models showed different overall survival in cytogenetic normal-AML patients in the Clinseq-AML cohort (P-value<0.05; concordance index >0.5). Risk classification systems integrating mutational or gene-expression data were found to add prognostic value to the current European Leukemia Net (ELN) risk classification. The prognostic value varied between models and across cohorts, highlighting the importance of independent validation to establish evidence of efficacy and general applicability. All but one model replicated in the Clinseq-AML cohort, indicating the potential for molecular-based AML risk models. Risk classification based on a combination of molecular and clinical data holds promise for improved AML patient stratification in the future.

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Acknowledgements

We acknowledge funding from Swedish Cancer Society (Cancerfonden), Swedish e-Science Research Centre (SERC)–‘e-Science for Cancer Prevention and Control (ecpc)’, the Swedish Research Council (Vetenskapsrådet), the Strategic Research Programme in Cancer (StratCan) in Karolinska Institutet and the Stockholm County Council.

Author contributions

MW, JL and MR developed the concept and designed the study, analyzed data and wrote the paper. DK analyzed the data. CN collected and assembled the data. ASM analyzed the data. SL developed the concept and designed the research and wrote the paper. HG developed the concept and designed the research.

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Author notes

  1. M Wang and J Lindberg: These authors contributed equally as the first authors.

  2. M Rantalainen, S Lehmann and H Grönberg: These authors contributed equally as the last authors.

Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    M Wang, D Klevebring, A S Mer, M Rantalainen & H Grönberg

  2. Department of Medical Epidemiology and Biostatistics, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden

    J Lindberg

  3. Karolinska University Hospital and Department of Medicine, Hematology Centre, Karolinska Institutet, Huddinge, Stockholm, Sweden

    C Nilsson & S Lehmann

  4. Department of Medical Sciences, Uppsala University, Uppsala, Sweden

    S Lehmann

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  1. M Wang
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Correspondence to H Grönberg.

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The authors declare no conflict of interest.

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Supplementary Information accompanies this paper on the Leukemia website .

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Wang, M., Lindberg, J., Klevebring, D. et al. Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling. Leukemia 31, 2029–2036 (2017). https://doi.org/10.1038/leu.2017.48

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