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Improving the prediction of acute myeloid leukaemia outcomes by complementing mutational profiling withex vivochemosensitivity

Authors :
Joaquin Martinez-Lopez
Rosa Ayala
Julian Gorrochategui
Jaime Pérez-Oteyza
Inmaculada Rapado
Joan Ballesteros
Eva Barragán
Pau Montesinos
José Luis Rojas
David Martínez-Cuadrón
Esther Onecha
María Linares
Elena Magro
Blanca Boluda
Pilar Martínez-Sánchez
Claudia Sargas
Yanira Ruiz-Heredia
Jesús Villoria
Pilar Herrera
Source :
British Journal of Haematology. 189:672-683
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Refractoriness to induction therapy and relapse after complete remission are the leading causes of death in patients with acute myeloid leukaemia (AML). This study focussed on the prediction of response to standard induction therapy and outcome of patients with AML using a combined strategy of mutational profiling by next-generation sequencing (NGS, n = 190) and ex vivo PharmaFlow testing (n = 74) for the 10 most widely used drugs for AML induction therapy, in a cohort of adult patients uniformly treated according to Spanish PETHEMA guidelines. We identified an adverse mutational profile (EZH2, KMT2A, U2AF1 and/or TP53 mutations) that carries a greater risk of death [hazard ratio (HR): 3·29, P < 0·0001]. A high correlation was found between the ex vivo PharmaFlow results and clinical induction response (69%). Clinical correlation analysis showed that the pattern of multiresistance revealed by ex vivo PharmaFlow identified patients with a high risk of death (HR: 2·58). Patients with mutation status also ran a high risk (HR 4·19), and the risk was increased further in patients with both adverse profiles (HR 4·82). We have developed a new score based on NGS and ex vivo drug testing for AML patients that improves upon current prognostic risk stratification and allows clinicians to tailor treatments to minimise drug resistance.

Details

ISSN :
13652141 and 00071048
Volume :
189
Database :
OpenAIRE
Journal :
British Journal of Haematology
Accession number :
edsair.doi.dedup.....1044ded09a0ed2a99538c38aeb624a1c