Gene Expression Signature Predicts Relapse in Adult Patients with Cytogenetically Normal Acute Myeloid Leukemia

Although approximately 80% of adult patients with cytogenetically normal acute myeloid leukemia (CN-AML) achieve a complete remission (CR), over half of them relapse. Better identification of patients who are likely to relapse can help inform clinical decisions. We performed RNA sequencing on pretreatment samples from 268 adults with de novo CN-AML younger than 60 years who achieved a CR after induction treatment with standard “7+3” chemotherapy. After filtering for genes whose expressions were associated with gene mutations known to impact on outcome (i.e., CEBPA, NPM1, and FLT3-internal tandem duplication [FLT3-ITD]), we identified a 10-gene signature strongly predictive of patient relapse (area under the curve [AUC]=0.81). The signature consisted of seven coding genes: GAS6, PSD3, PLCB4, DEXI, JMY, NRP1, C10orf55, and three long non-coding RNAs. In multivariable analysis, the 10-gene signature was strongly associated with relapse (P<.001), after adjustment for the FLT3-ITD, CEBPA and NPM1 mutational status. Validation of the expression signature in an independent patient set from The Cancer Genome Atlas showed the signature’s strong predictive value with AUC=0.78. Implementation of the 10-gene signature into clinical prognostic stratification could be useful for identifying patients likely to relapse. Total transcriptome RNA sequencing (RNAseq) was performed using pretreatment blood or bone marrow samples from 268 adult CN-AML patients younger than 60 years, who were similarly treated with intensive chemotherapy on Cancer and Leukemia Group B (CALGB) (now part of Alliance for Clinical Trials in Oncology [Alliance]) therapeutic trials (see Supplementary Methods), and who achieved a CR. The patient cohort did not include patients with AML secondary to antecedent hematologic disorder or patients with therapy-related AML. RNAseq reads were aligned to hg38 using HISAT2, and gene counts were obtained using featureCounts. Normalization was performed with DeSeq2, which divides counts by sample-specific size factors determined by median ratio of gene counts relative to geometric mean per gene. Note from submitter: we were advised that submission of fastq or bam files would raise concerns about the privacy of these patients and their consent.