A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia

• Published in: Nature communications Vol. 12; no. 1; p. 2474
• Main Authors: Docking, T. Roderick, Parker, Jeremy D. K., Jädersten, Martin, Duns, Gerben, Chang, Linda, Jiang, Jihong, Pilsworth, Jessica A., Swanson, Lucas A., Chan, Simon K., Chiu, Readman, Nip, Ka Ming, Mar, Samantha, Mo, Angela, Wang, Xuan, Martinez-Høyer, Sergio, Stubbins, Ryan J., Mungall, Karen L., Mungall, Andrew J., Moore, Richard A., Jones, Steven J. M., Birol, İnanç, Marra, Marco A., Hogge, Donna, Karsan, Aly
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 30.04.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 38/1; 38/22; 38/39; 38/91; 45/100; 49/23; 49/90; 631/67/1990; 631/67/2322; 631/67/68; 631/67/69; 692/4028/67/1990/283/1897; 82/80; Acute myeloid leukemia; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cell Line, Tumor; Cohort Studies; Core Binding Factor Alpha 2 Subunit - genetics; Core Binding Factor Alpha 2 Subunit - metabolism; Female; Focal adhesion kinase; Gene deletion; Gene expression; Gene Expression Regulation, Neoplastic - genetics; Gene Fusion; Gene sequencing; Genetic screening; Genomics; Humanities and Social Sciences; Humans; INDEL Mutation; Insertion; Integrins - genetics; Integrins - metabolism; Kinases; Leukemia; Leukemia, Myeloid, Acute - diagnosis; Leukemia, Myeloid, Acute - genetics; Leukemia, Myeloid, Acute - metabolism; Male; Malignancy; Medicin och hälsovetenskap; multidisciplinary; Mutation; Myeloid leukemia; Nucleotides; p53 Protein; Patients; Polymorphism, Single Nucleotide; Prognosis; Prospective Studies; Ribonucleic acid; Risk; Risk Factors; Risk groups; RNA; RNA-Seq; Runx1 protein; Science; Science (multidisciplinary); Signal Transduction - genetics; Subgroups; Survival Analysis; Therapy; Transcriptome; Transcriptomes; Tumor Suppressor Protein p53 - genetics; Tumor Suppressor Protein p53 - metabolism; Whole Exome Sequencing; Whole Genome Sequencing
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-22625-y

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 develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows 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 identify 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, encoded by PTK2 , demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy. Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.