A novel risk classification scheme based on expression of 36 micro-RNA samples was able to identify pediatric patients with acute myeloid leukemia at high or low risk of experiencing treatment failure, according to a new analysis.
A novel risk classification scheme based on expression of 36 micro-RNA samples (miRNA) was able to identify pediatric patients with acute myeloid leukemia (AML) at high or low risk of experiencing treatment failure, according to a new analysis.
Pediatric AML patients can often be separated into risk categories based on mutation status of FLT3, NPM1, and CEBPA, but a substantial percentage of patients lack actionable mutation profiles. “Therefore, the identification of additional biomarkers and therapeutic targets may enhance existing risk-based therapy schemas,” wrote study authors led by Marco A. Marra, PhD, of the BC Cancer Agency in Vancouver, Canada.
The researchers conducted a comprehensive miRNA analysis of samples from 654 patients enrolled in one of three AML studies, as well as 666 other cases from a separate trial for validation purposes. These included 1,303 primary samples, 22 refractory samples, and 37 relapse samples. Results of the analysis were published online ahead of print in the Journal of Clinical Oncology.
Based on those analyses, they created a risk model named AMLmiR36 that included 36 specific miRNAs that were significantly associated with outcomes. Patients with high AMLmiR36 scores had poorer event-free survival (EFS) outcomes, with a hazard ratio (HR) of 3.659 (95% CI, 2.77–4.83; P < .001). They had a 5-year EFS of 9.26%, and a 5-year overall survival of 29.6%.
In contrast, patients with low AMLmiR36 scores had substantially improved EFS outcomes, with an HR of 0.265 (95% CI, 0.16–0.43; P < .001), and 5-year EFS and OS of 84.4% and 90.3%, respectively. This was validated in both the discovery group of patients and in the separate validation cohort.
Though there was some “enrichment” for patients who had other poor prognostic indicators including high-risk cytogenetic profiles, the AMLmiR36 score was independent of those other factors. Also, the full risk score was found to be a better predictor of EFS than any of four individual miRNAs known to be associated with survival.
The risk score could identify patients that otherwise would not be considered high risk as well. In the validation cohort, there were 88 AMLmiR36 high-risk patients with a 13.6% 3-year EFS rate, compared with intermediate-risk patients who had a 42.7% 3-year EFS rate (P < .001). Of those, 82 patients were classified as low or standard/conventional risk.
“Ideally, a robust prognostic biomarker of treatment outcomes would identify a group of patients who were at sufficiently high risk of relapse and treatment resistance early enough in the course of treatment to justify consideration of alternate therapies,” the authors wrote. “Of importance, AMLmiR36 was able to identify groups of high-risk patients from different clinical trials, independently of established indicators of outcome.”