Aptamer-Based Cell-Surface Profiling with Single-Cell Resolution Enables Precise Cancer Characterization

Molecular profiling of cell-surface proteins is a powerful strategy for precise cancer diagnosis. While mass cytometry (MC) enables synchronous detection of over 40 cellular parameters, its full potential in disease classification is challenged by the limited types of recognition probes currently available. In this work, we synthesize a panel of heavy isotope conjugated aptamers to profile cancer-associated signatures on the surface of hematological malignancy (HM) cells. Based on 15 molecular signatures, we performed cell-surface profiling that allowed the precise classification of 8 HM cell lines. Combined with machine-learning technology, this aptamer-based MC platform also achieved multiclass identification of HM subtypes in clinical samples with 100% accuracy in the training cohort and 80% accuracy in the test cohort. Therefore, we report an effective and practical strategy for precise cancer classification at the single cell level, paving the way for its clinical use in the near future.