Abstract
The surfaceome is critical because surface proteins provide a gateway for internal signals and transfer of molecules into cells, and surfaceome differences can influence therapy response. We have used a surfaceome analysis method, based on comparing RNA-seq data between normal and abnormal cells (Surfaceome DataBase Mining or Surfaceome DBM), to identify sets of upregulated cell surface protein mRNAs in an LMO2-mediated T-ALL mouse model and corroborated by protein detection using antibodies. In this model the leukemia initiating cells (LICs) comprise pre-leukaemic, differentiation inhibited thymocytes allowing us to provide a profile of the LIC surfaceome in which GPR56, CD53 and CD59a are co-expressed with CD25. Implementation of cell surface interaction assays demonstrates fluid interaction of surface proteins and CD25 is only internalized when co-localized with other proteins. The Surfaceome DBM approach to analyse cancer cell surfaceomes is a way to find targetable surface biomarkers for clinical conditions where RNA-seq data from normal and abnormal cell are available.