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Optimization of the cytokine secretion assay for human IL-2 in single and combination assays.

ABSTRACT: The cytokine secretion assay identifies live cytokine-secreting cells by capturing the secreted cytokine on a surface-bound capture antibody in dilute suspension culture, followed by detection with a fluorescent anti-cytokine antibody. However, examining the kinetics of cytokine detection revealed that IL-2 staining reached a maximum at early times and then declined, whereas staining for other cytokines including interferon (IFN?) increased for up to 90 min. The decline in IL-2 staining could have been due to rapid cessation of cytokine synthesis, coupled with internalization of cytokine/antibody complexes from the cell surface. Consistent with this model, addition of the anti-IL-2 detection antibody during the cytokine secretion step resulted in higher and more sustained staining. This modified method enhanced staining of IL-2 and IL-4, but not IFN?, tumor necrosis factor alpha (TNF?), or IL-5. However, the longer secretion times possible in the modified assay also improved detection of other cytokines in multi-cytokine combinations.

SUBMITTER: Deng N

PROVIDER: S-EPMC4759652 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Optimization of the cytokine secretion assay for human IL-2 in single and combination assays.

Deng Nan N Mosmann Tim R TR

Cytometry. Part A : the journal of the International Society for Analytical Cytology 20150428 8

The cytokine secretion assay identifies live cytokine-secreting cells by capturing the secreted cytokine on a surface-bound capture antibody in dilute suspension culture, followed by detection with a fluorescent anti-cytokine antibody. However, examining the kinetics of cytokine detection revealed that IL-2 staining reached a maximum at early times and then declined, whereas staining for other cytokines including interferon (IFNγ) increased for up to 90 min. The decline in IL-2 staining could ha ...[more]

PMID: 25919308

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Project description:BackgroundThe precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.MethodsHere, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.ResultsWe apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.ConclusionsOverall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Dataset Information

Optimization of the cytokine secretion assay for human IL-2 in single and combination assays.

Publications

Optimization of the cytokine secretion assay for human IL-2 in single and combination assays.

Similar Datasets

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