Abstract
Background and aim: Treatment of acute myeloid leukemia (AML) remains a considerable therapeutic challenge. Complete response (CR) after induction therapy is the first treatment goal in these leukemic patients. A few combinations, based mostly on empirical observations with drugs already known to be more or less effective, are frequently used in the treatment of AML. Because of this, many patients who do not respond to standard chemotherapy need to enter in clinical trials and the use of predictive assays prior to patient treatment represents the ideal scenario to guide or help in treatment decisions. We have now developed an ex vivo test where a initial clinical validation has been achieved in an observational clinical trial in 123 AML patients on single-treatment, 1st-line cytarabine (CYT) plus idarubicin (IDA), achieving 85% clinical correlation. The aim of this study is to provide actionable data to improve disease management in the context of a clinical trial, and provide key information for Precision Medicine (PM) to guide the hematologist among the more sensitive treatments to achieve a CR.
Methods: AML bone marrow (BM) samples from adult patients are received at the laboratory within 24 hours from extraction and incubated for 48 hours in 96-well plates containing the single drugs or combinations. The analysis is performed in the automated flow cytometry PharmaFlow platform and 72 hours after the extraction of the sample, an encrypted report is sent to the hematologist before the patient begins treatment. Pharmacologic responses were calculated using pharmacokinetic population models. Induction response was assessed according to the Cheson criteria (2003). Patients attaining a CR/CRi were classified as responders and the remaining as resistant, excluding early deaths. Final scores and treatments ranking are based on a therapeutic algorithm that integrates ex vivo activity; monotherapy dose responses are quantified by the area under the curve (AUC) with limits such as Cmax values, and synergism calculated measuring 8 concentration ratios, requiring consistency in their results in a 3D surface (so-called alpha factor synergism). The PM test attempts to identify the best treatment for predicting sensitivity for each patient.
Results: The scoring method was tested using ex vivo results from samples obtained in an observational clinical trial with Spain's PETHEMA group from a cohort of 123 samples from de novo diagnosed AML patients, treated with the standard PETHEMA 1st-line guideline 3+7 with CYT+IDA. The score predicts sensitive patients with 90% accuracy. This accuracy can be compared with an independently derived 92% accuracy in identifying sensitive patients in a statistically significant clinical correlation study. The score is a simplified version of such correlation algorithm. Both methods identify a similar % of all clinically sensitive patients (67% vs 71%). However, the correlation is only valid for CYT-IDA while the PM test can be applied to any treatment. Moreover, for CYT+IDA treatment, the PM test predicts a 3-year overall survival with 75% accuracy.
Conclusion: We have developed a novel ex vivo PM test for induction treatment in AML patients to guide hematologists selecting the right treatment to achieve CR in individual patients. Assuming a similar response rate for all these treatments, our test could estimate a net prediction for sensibility to AML treatment higher than 80% in 1st line. This PM test can be used in an Investigator Sponsored Trial as a Companion Diagnostic selecting sensitive patients with higher response rates and survival.
Citation Format: Joan Ballesteros, Pau Montesinos, David Martinez-Cuadron, Joaquin Martinez-Lopez, Julian Gorrochategui, Jose Luis Rojas, Cristina Gomez, Pilar Hernandez, Alicia Robles. A new precision medicine test to guide personalized treatments decision for acute myeloid leukemia patients [abstract]. In: Proceedings of the Second AACR Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; May 6-9, 2017; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(24_Suppl):Abstract nr 22.