A proteomics and transcriptomics approach to identify leukemic stem cell (LSC) markers.

Interactions between hematopoietic stem cells and their niche are mediated by proteins within the plasma membrane (PM) and changes in these interactions might alter hematopoietic stem cell fate and ultimately result in acute myeloid leukemia (AML). Here, using nano-LC/MS/MS, we set out to analyze the PM profile of two leukemia patient samples. We identified 867 and 610 unique CD34(+) PM (-associated) proteins in these AML samples respectively, including previously described proteins such as CD47, CD44, CD135, CD96, and ITGA5, but also novel ones like CD82, CD97, CD99, PTH2R, ESAM, MET, and ITGA6. Further validation by flow cytometry and functional studies indicated that long-term self-renewing leukemic stem cells reside within the CD34(+)/ITGA6(+) fraction, at least in a subset of AML cases. Furthermore, we combined proteomics with transcriptomics approaches using a large panel of AML CD34(+) (n = 60) and normal bone marrow CD34(+) (n = 40) samples. Thus, we identified eight subgroups of AML patients based on their specific PM expression profile. GSEA analysis revealed that these eight subgroups are enriched for specific cellular processes.