bioRxivImmunologyPreprint
Predicting efficacy of immunotherapy in mice with triple negative breast cancer using a cholesterol PET radiotracer
N. G. Ciavattone, J. Guan, A. Farfel, T. Desmond, B. L. Viglianti, P. J. Scott, A. F. Brooks, G. D. Luker
Abstract
Predicting the response to cancer immunotherapy remains an unmet challenge in triple-negative breast cancer (TNBC) and other malignancies. T cells, the major target of current checkpoint inhibitor immunotherapies, accumulate cholesterol during activation to support proliferation and signaling. The requirement of cholesterol for anti-tumor functions of T cells led us to hypothesize that quantifying cellular accumulation of this molecule could distinguish successful from ineffective checkpoint immunotherapy. To analyze accumulation of cholesterol by T cells in the immune microenvironment of breast cancer, we leveraged a novel positron emission tomography (PET) radiotracer, FNP-59. FNP-59 is an analog of cholesterol that our group has validated as an imaging biomarker for cholesterol uptake in pre-clinical models and initial human studies. In immunocompetent mouse models of TNBC, we found that elevated uptake of exogenous labeled cholesterol analogs functions as a marker for T cell activation. When comparing immune checkpoint inhibitor (ICI)-responsive EO771 tumors to non-responsive AT-3 tumors, we found significantly higher uptake of a fluorescent cholesterol analog in T cells of the ICI-responsive tumors both in vitro and in vivo. Using the FNP-59 radiotracer, we discovered that accumulation of cholesterol by T cells increased further in ICI-responding tumors that received ant-PD-1 checkpoint immunotherapy. We verified these data by mining single cell sequencing data from patients with TNBC. Patients with tumors containing cycling T cells showed gene expression signatures of cholesterol uptake and trafficking. These results suggest that uptake of exogenous cholesterol analogs by tumor-infiltrating T cells predict T cell activation and success of ICI therapy.
- organism: mouse
- assay: spatial transcriptomics
- assay: imaging
- research focus: host-pathogen & immune response
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- approach: statistical model
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