Abstract

Abstract FMS-like tyrosine kinase-3 (FLT3) mutations are often linked with poor prognosis in Acute myeloid leukemia (AML). Despite increasing availability of targeted therapy, such as FLT3 inhibitors (FLT3i), remission is often short-term and followed by relapse and drug resistance. With varying response rates to standard treatments, the need to understand the molecular mechanisms driving drug resistance and accurately predict responses to treatment is crucial. Here, we present the ability of Quadratic phenotypic optimization platform (QPOP), in accurately identifying potential responders to possible combination therapies in AML. AML cell lines and AML patient samples were treated with a set panel of drugs including FLT3i. QPOP drug combination scores and ranking were derived from cell viability response following treatment. 40 patients were recruited for the study, of which 20 patients were evaluated for their clinical concordance. RNA sequencing and molecular analysis was further conducted to determine the accuracy of QPOP predicted response and to determine mechanism of resistance to FLT3i. QPOP predicted response was concordant to patient treatment outcome with 80% sensitivity and specificity. QPOP analysis on AML cell lines accurately identified responders to FLT3i including the differential response between a FLT3- ITD isogenic parental and FLT3i resistant cell line. Serial QPOP analysis in a FLT3 mutant patient sample indicated a decrease in FLT3i sensitivity concordant with an increasing FLT3 allelic burden and the development of resistance. The development of resistance to FLT3i based combinations was correlated to an increase in phosphorylated AKT expression. Activation of AKT is associated with the upregulation of Forkhead box M1 (FoxM1) in the resistant cell line. Co-treatment with an AKT inhibitor restored sensitivity to FLT3i treatment in the resistant cells. We demonstrate that QPOP analysis accurately predicts sensitivity to drug-combinations and can be used as a tool to identify sensitivity to FLT3i-based combination therapy in AML. Citation Format: Noor Rashidha Bte Meera Sahib, Jen Wei Ying, Melissa Ooi, Yen Lin Chee, Jayalakshmi, Jameelah Bte Sheik Mohamed, Masturah Rashid, Edward KH Chow. AN EX-VIVO COMBINATION DRUG SENSITIVITY PLATFORM FOR PREDICTING SENSITIVITY TO FLT3 INHIBITOR-BASED COMBINATION IN ACUTE MYELOID LEUKEMIA [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P09.

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