Summary
Checkpoint inhibitors have significantly accelerated cancer treatment but still a majority of patients do not respond. Biomarker driven patient stratification early to the right immunotherapeutic might enhance response and patient survival. Here we used high-dimensional mass cytometry (CyTOF) combined with machine-learning bioinformatics for the in-depth characterization of immune responses before and during anti-PD-1 immunotherapy. CyTOF allows us to monitor protein expression of 34 markers on a single cell while running 20 samples simultaneously. The analysis is data driven, can be adapted to high throughput approaches and can model arbitrary trial designs such as batch effects and paired designs and is quantitative over millions of events. Using CyTOF as a precision medicine tool we cou
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.