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Single-cell mass cytometry and machine learning predict relapse in childhood leukemia

Jolanda Sarno1, Kara L Davis1

  • 1Department of Pediatrics, Bass Center for Childhood Cancer and Blood Disorders, Stanford University, Stanford, CA, USA.

Molecular & Cellular Oncology
|September 29, 2018
PubMed
Summary

A single-cell study of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) identified unique cell signaling states linked to treatment failure. Understanding these hidden developmental states can improve patient outcomes in BCP-ALL.

Keywords:
Childhood leukemiacell signalinginnovative methods in molecular and cellular oncologymachine learningmass cytometrymechanisms of oncogenesis and tumor progressionmechanisms of resistance to therapynovel therapeutic targetsprognostic and predictive biomarkersrelapse prediction

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