Immune checkpoint blocking antibodies are a cornerstone in cancer treatment; however, they benefit only a subset of patients and biomarkers to guide immune checkpoint blockade (ICB) treatment choices are lacking. We designed this study to identify blood-based correlates of clinical outcome in ICB-treated patients. We performed immune profiling of 188 ICB-treated patients with melanoma using multiparametric flow cytometry to characterize immune cells in pretreatment peripheral blood. A supervised statistical learning approach was applied to a discovery cohort to classify phenotypes and determine their association with survival and treatment response. We identified three distinct immune phenotypes (immunotypes), defined in part by the presence of a LAG-3CD8 T cell population. Patients with melanoma with a LAG immunotype had poorer outcomes after ICB with a median survival of 22.2 months compared to 75.8 months for those with the LAG immunotype ( = 0.031). An independent cohort of 94 ICB-treated patients with urothelial carcinoma was used for validation where LAG immunotype was significantly associated with response ( = 0.007), survival ( < 0.001), and progression-free survival ( = 0.004). Multivariate Cox regression and stratified analyses further showed that the LAG immunotype was an independent marker of outcome when compared to known clinical prognostic markers and previously described markers for the clinical activity of ICB, PD-L1, and tumor mutation burden. The pretreatment peripheral blood LAG immunotype detects patients who are less likely to benefit from ICB and suggests a strategy for identifying actionable immune targets for further investigation.
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http://dx.doi.org/10.1126/scitranslmed.abf5107 | DOI Listing |
Adv Sci (Weinh)
January 2025
Center for Molecular Imaging and Nuclear Medicine, State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD-X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou, 215123, China.
Immunotherapy has significantly improved cancer patient survival, while its efficacy remains limited due to the reliance on a single marker like PD-L1 as well as its spatiotemporal heterogeneity. To address this issue, combining lymphocyte activation gene-3 (LAG-3) with PD-L1 is proposed for identifying immunotypes and monitoring immunotherapy through nuclear imaging. In short, Tc-HYNIC-αLAG-3 and Tc-HYNIC-αPD-L1 probes are synthesized using anti-human LAG-3 and PD-L1 antibodies, respectively.
View Article and Find Full Text PDFCell Rep Methods
August 2023
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
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).
View Article and Find Full Text PDFSci Transl Med
August 2021
Department of Medicine, Memorial Sloan Kettering Cancer Center New York, NY 10065, USA.
Immune checkpoint blocking antibodies are a cornerstone in cancer treatment; however, they benefit only a subset of patients and biomarkers to guide immune checkpoint blockade (ICB) treatment choices are lacking. We designed this study to identify blood-based correlates of clinical outcome in ICB-treated patients. We performed immune profiling of 188 ICB-treated patients with melanoma using multiparametric flow cytometry to characterize immune cells in pretreatment peripheral blood.
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