A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy.

ABSTRACT: We present TopicFlow, a computational framework for flow cytometry data analysis of patient blood samples for the identification of functional and dynamic topics in circulating T cell population. This framework applies a Latent Dirichlet Allocation (LDA) model, adapting the concept of topic modeling in text mining to flow cytometry. To demonstrate the utility of our method, we conducted an analysis of ∼17 million T cells collected from 138 peripheral blood samples in 51 patients with melanoma undergoing treatment with immune checkpoint inhibitors (ICIs). Our study highlights three latent dynamic topics identified by LDA: a T cell exhaustion topic that independently recapitulates the previously identified LAG-3⁺ immunotype associated with ICI resistance, a naive topic and its ass

SUBMITTER: Peng X 

PROVIDER: S-EPMC10475788 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature