AbstractSeveral gene expression profiles with a strong correlation with patient outcomes have been previously described in chronic lymphocytic leukemia (CLL), although their applicability as biomarkers in clinical practice has been particularly limited. Here we describe the training and validation of a gene expression signature for predicting early progression in patients with CLL based on the analysis of 200 genes related to microenvironment signaling on the NanoString platform. In the training cohort (n = 154), the CLL15 assay containing a 15-gene signature was associated with the time to first treatment (TtFT) (hazard ratio [HR], 2.83; 95% CI, 2.17-3.68; P < .001). The prognostic value of the CLL15 score (HR, 1.71; 95% CI, 1.15-2.52; P = .007) was further confirmed in an external independent validation cohort (n = 112). Notably, the CLL15 score improved the prognostic capacity over IGHV mutational status and the International Prognostic Score for asymptomatic early-stage (IPS-E) CLL. In multivariate analysis, the CLL15 score (HR, 1.83; 95% CI, 1.32-2.56; P < .001) and the IPS-E CLL (HR, 2.23; 95% CI, 1.59-3.12; P < .001) were independently associated with TtFT. The newly developed and validated CLL15 assay successfully translated previous gene signatures such as the microenvironment signaling into a new gene expression–based assay with prognostic implications in CLL.