In the context of tumor analysis, the implementation of precision medicine requires on-time clinical measurements, which requires rapid large-scale single-cell screening that obtains cell population distributions and functions in tumors to determine disease progression for therapeutics. In this study, a high-throughput screening (HTS) platform integrating optical fluorescence detectors and a computational method was developed as a droplet-based microfluidic flow cytometer (Droplet-μFC) to comprehensively analyze multiple proteolytic activities of a patient-derived tumor (with ∼0.5-2 M cells) at single-cell resolution within 2 h. The data-driven analytical method identified distinct cell types and status through protease profiling with high precision. Multiple protease activities of single cells harvested from a tumor were thus determined with a throughput of ∼100 cells per second. This platform was used to screen protease activities of a wide range of cell types, forming a library. With the development of advanced computational clustering and cell mapping, rapid quantitative tumor profiling with a comprehensive description of cell population distributions and functions could be obtained for clinical treatments.