Integrating Proteomics and Transcriptomics for Systematic Combinatorial Chimeric Antigen Receptor Therapy of AML

Abstract

Chimeric antigen receptor (CAR) therapy targeting CD19 has yielded remarkable outcomes in patients with acute lymphoblastic leukemia. To identify potential CAR targets in acute myeloid leukemia (AML), we probed the AML surfaceome for overexpressed molecules with tolerable systemic expression. We integrated large transcriptomics and proteomics datasets from malignant and normal tissues, and developed an algorithm to identify potential targets expressed in leukemia stem cells, but not in normal CD34+CD38− hematopoietic cells, T cells, or vital tissues. As these investigations did not uncover candidate targets with a profile as favorable as CD19, we developed a generalizable combinatorial targeting strategy fulfilling stringent efficacy and safety criteria. Our findings indicate that several target pairings hold great promise for CAR therapy of AML. Perna et al. search for optimal chimeric antigen receptor targets in acute myeloid leukemia using extensive proteomics and transcriptomics. In the absence of a target as favorable as CD19, they develop a generalizable combinatorial targeting strategy identifying several promising target pairings.