Immunophenotypes of Acute Myeloid Leukemia From Flow Cytometry Data Using Templates

TL;DR

This paper demonstrates that a template-based classification pipeline using flow cytometry data can accurately identify and classify immunophenotypes of Acute Myeloid Leukemia subtypes, including APL, with high confidence.

Contribution

The study introduces a pipeline that effectively summarizes AML classes with templates and accurately classifies subtypes, improving upon previous methods.

Findings

All AML samples in the test set were classified correctly with high confidence.

The pipeline effectively captures heterogeneity in AML data.

Templates successfully distinguish various AML subtypes, including APL.

Abstract

Motivation: We investigate whether a template-based classification pipeline could be used to identify immunophenotypes in (and thereby classify) a heterogeneous disease with many subtypes. The disease we consider here is Acute Myeloid Leukemia, which is heterogeneous at the morphologic, cytogenetic and molecular levels, with several known subtypes. The prognosis and treatment for AML depends on the subtype. Results: We apply flowMatch, an algorithmic pipeline for flow cytometry data created in earlier work, to compute templates succinctly summarizing classes of AML and healthy samples. We develop a scoring function that accounts for features of the AML data such as heterogeneity to identify immunophenotypes corresponding to various AML subtypes, including APL. All of the AML samples in the test set are classified correctly with high confidence. Availability: flowMatch is available at www.bioconductor.org/packages/devel/bioc/html/flowMatch.html; programs specific to immunophenotyping AML are at www.cs.purdue.edu/homes/aazad/software.html.