CytoGPNet: Enhancing Clinical Outcome Prediction Accuracy Using Longitudinal Cytometry Data in Small Cohort Studies.

ABSTRACT: Cytometry data, including flow cytometry and mass cytometry, are now standard in numerous immunological studies, such as cancer immunotherapy and vaccine trials. These data enable the monitoring of an individual's peripheral immune status over time, providing detailed insights into immune cells and their role in clinical outcomes. However, traditional analyses relying on summary statistics, such as cell subset proportions and mean fluorescence intensity, may overlook critical single-cell information. To address this limitation, we introduce cytoGPNet, a novel approach that harnesses extensive cytometry data to predict individual-level outcomes. cytoGPNet is designed to address four key challenges: (1) accommodating varying numbers of cells per sample; (2) analyzing the longitudinal cytomet

SUBMITTER: Zhang J 

PROVIDER: S-EPMC12247962 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature