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Early response evaluation by single cell signaling profiling in acute myeloid leukemia

Benedicte Sjo Tislevoll, Monica Hellesøy, Oda Helen Eck Fagerholt, Stein‐Erik Gullaksen, Aashish Srivastava, Even Birkeland, Dimitrios Kleftogiannis, Pilar Ayuda‐Durán, Laure Piechaczyk, Dagim Shiferaw Tadele, Jørn Skavland, Panagotis Baliakas, Randi Hovland, Vibeke Andresen, Ole Morten Seternes, Tor Henrik Anderson Tvedt, Nima Aghaeepour, Sonia Gavasso, Kimmo Porkka, Inge Jonassen, Yngvar Fløisand, Jorrit M. Enserink, Nello Blaser, Bjørn Tore Gjertsen

2023Nature Communications30 citationsDOIOpen Access PDF

Abstract

Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of extracellular-signal-regulated kinase (ERK) 1/2 and p38 mitogen-activated protein kinase (MAPK) phosphorylation in the myeloid cell compartment 24 h post-chemotherapy is a significant predictor of patient 5-year overall survival in this cohort. Validation by RNA sequencing shows induction of MAPK target gene expression in patients with high phospho-ERK1/2 24 h post-chemotherapy, while proteomics confirm an increase of the p38 prime target MAPK activated protein kinase 2 (MAPKAPK2). In this study, we demonstrate that mass cytometry can be a valuable tool for early response evaluation in AML and elucidate the potential of functional signaling analyses in precision oncology diagnostics.

Topics & Concepts

Myeloid leukemiaMass cytometryMAPK/ERK pathwayCancer researchSignal transductionKinaseMyeloidMedicineInduction chemotherapyp38 mitogen-activated protein kinasesProtein kinase AChemotherapyBiologyOncologyCell biologyInternal medicineGeneGeneticsPhenotypeSingle-cell and spatial transcriptomicsAcute Myeloid Leukemia ResearchCancer Genomics and Diagnostics