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Acute myeloid leukemia (AML) encompasses a large number of morphologically similar but molecularly distinct variants. Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value. However, despite recent successes in detecting novel molecular markers like FLT3 (fms-related tyrosine kinase 3) mutation, treatment stratification is still difficult, especially for the 40–45% of patients with intermediate-risk, normal karyotype disease. To better characterize AML at the molecular level, and to address the need for improved risk stratification, we recently profiled gene expression in a large series of adult AML patients (Bullinger et al., N Engl J Med350:1605, 2004). By unsupervised analysis we identified new prognostically-relevant AML subgroups, and using a supervised learning algorithm we constructed a gene-expression based outcome predictor, which accurately predicted overall survival across all patients, including for the subset of AML cases normal karyotype. Having demonstrated the presence at diagnosis of normal karyotype signatures correlating with clinical outcome, we have now sought to refine a prognostic signature specific for normal karyotype disease. Towards this goal, we have now profiled 119 samples of adult AML patients with normal karyotype using 42k cDNA microarrays from the Stanford Functional Genomics Facility. By semi-supervised analysis using the supervised principal component method (Bair et al., PLoS Biology2:511, 2004), we built a cross-validated gene-expression based outcome predictor in a randomly partitioned training set (n=60 samples). This outcome signature, comprising only 16 genes, significantly predicted outcome class for normal karyotype samples in the independent test set (n=59 samples; P=0.001). In multivariate analysis, the 16-gene signature was a strong [odds ratio=0.35 (0.13 to 0.91); P=0.01] factor in predicting overall survival, independent of known prognostic factors including FLT3 mutations and preceeding malignancy. Our findings support the utility of expression profiling for improved risk stratification and clinical management of the clinically important subclass of AML patients with normal karyotype disease.

Recurrent cytogenetic aberrations have been shown to constitute markers of diagnostic and prognostic value in acute myeloid leukemia (AML). However, even within the well-defined cytogenetic AML subgroup with an inv(16) we see substantial biological and clinical heterogeneity which is not fully reflected by the current classification system. To better characterize this cytogenetic group on the molecular level we profiled gene expression in a series of adult AML patients (n=26) with inv(16) using 42k cDNA microarrays. By unsupervised hierarchical clustering we observed that samples with inv(16) separated primarily into two different subgroups. These showed no significant differences regarding known risk factors like age, WBC, LDH, etc. However, these newly defined inv(16)-subgroups were characterized by distinct clinical behavior. There was a strong trend towards unfavorable outcome with shorter overall survival times in one group (P=0.09, log rank test). Since the primary translocation/inversion events themselves are not sufficient for leukemogenesis, distinct patterns of gene expression found within each of these cytogenetic groups may suggest alternative cooperating mutations and deregulated pathways leading to transformation. Therefore, we performed a supervised analysis to determine the characteristic gene expression patterns underlying the cluster-defined subgroups. This Significance Analysis of Microarrays (SAM) method identified 260 genes significantly differentially expressed between the two newly defined inv(16)-subgroups (false discovery rate = 0.002). High expression levels of JUN, JUNB, JUND, FOS and FOSB characterized the first inv(16) subgroup (having less favorable prognosis). FOS gene family members can dimerize with proteins of the JUN family, forming the transcription factor complex AP-1 which has been implicated in the regulation of cell proliferation, differentiation, and transformation. Among the second subgroup, the proto-oncogene ETS1,displayed elevated expression, possibly resulting from aberrant MEK/ERK pathway activation as these cases also showed an over-expression of MAP3K1 and MAP3K2. In conclusion, both supervised and unsupervised methods provide numerous insights into the pathogenesis of AML with inv(16), identifying clinically significant patterns of gene expression, as well as candidate target genes involved in leukemogenesis.