An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

1 Dataset 2 Publications

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Dataset ID	Description	Technology	Samples
EGAD00001006701	As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.		275

Publications	Citations
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia. Docking TR, Parker JDK, Jädersten M, Duns G, Chang L, Jiang J, Pilsworth JA, Swanson LA, Chan SK, Chiu R, Nip KM, Mar S, Mo A, Wang X, Martinez-Høyer S, Stubbins RJ, Mungall KL, Mungall AJ, Moore RA, Jones SJM, Birol İ, Marra MA, Hogge D, Karsan A. Nat Commun 12: 2021 2474	62
Acute myeloid leukemia risk stratification in younger and older patients through transcriptomic machine learning models. Silva R, Riedel C, Amico M, Reboul J, Guibert B, Sennaoui C, Bessiere C, Ruffle F, Gilbert N, Boureux A, Commes T. Sci Rep 15: 2025 39821	0