Abstract
In the acute myeloid leukemia (AML) setting, research has extensively investigated the existence and relevance of molecular biomarkers, in order to better tailor therapy with newly developed agents and hence improve outcomes and/or save the patient from poorly effective therapies. In particular, in patients with AML, residual disease after therapy does reflect the sum of the contributions of all factors associated with diagnosis and post-diagnosis resistance. The evaluation of minimal/measurable residual disease (MRD) can be considered as a key tool to guide patient’s management and a promising endpoint for clinical trials. In this narrative review, we discuss MRD evaluation as biomarker for tailored therapy in AML patients; we briefly report current evidence on the use of MRD in clinical practice, and comment on the potential ability of MRD in the assessment of the efficacy of new molecules.
Highlights
By definition, biomarkers are biological variables associated with the outcome of a given disease
Demonstrated excellent sensitivity and agreement with RQ-PCR, allowing for the detection of a variety of rare NPM1 mutation subtypes [18,19]. These results suggest that Digital droplet PCR (ddPCR) can effectively quantify NPM1m measurable residual disease (MRD), reducing the potential difficulties associated with NPM1 quantification, in patients with unknown or rare mutant sequences
MRD monitoring was able to identify the majority of patients who were subject to relapse and was shown to be the most powerful predictor of relapse-free survival (RFS) at multivariable analysis (HR, 17.87; 95% CI, 6.88–46.41; p < 0.0001)
Summary
Biomarkers are biological variables associated with the outcome of a given disease. In acute myeloid leukemia (AML), multiple biomarkers have extensively been studied for their potential to predict outcomes with the goal to guide patients to tailored therapies with novel agents and to reduce chemotherapy-related toxicities [2,3]. In this context, a recent study by Gerstung et al, analyzed genomic and clinical datasets of 1540 patients by using multistage statistical models. Cancers 2019, 11, 1417 biomarker useful to guide the patient’s management and a potential surrogate endpoint for relapse-free survival (RFS) in clinical trials [4,5]. We further comment on the potential ability of MRD technologies in the assessment of the antileukemic activity of novel agents
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