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Updated: Sep 22, 2025
Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
Published on: June 26, 2018
Multidimensional Immune Profiling of Cutaneous Lupus Erythematosus In Vivo Stratified by Patient Response to
Jay Patel1, Thomas Vazquez1, Felix Chin1
1Corporal Michael J. Crescenz Veterans Affairs Medical Center and University of Pennsylvania, Philadelphia.
Objective:
The pathogenesis of cutaneous lupus erythematosus (CLE) is multifactorial, and CLE is difficult to treat due to the heterogeneity of inflammatory processes among patients. Antimalarials such as hydroxychloroquine (HCQ) and quinacrine (QC) have long been used as first-line systemic therapy; however, many patients do not respond to treatment with antimalarials and require systemic immunosuppressants that produce undesirable side effects. Given the complexity and the unpredictability of responses to antimalarial treatments in CLE patients, we sought to characterize the immunologic profile of patients with CLE stratified by subsequent treatment outcomes to identify potential biomarkers of inducible response.
Methods:
We performed mass cytometry imaging of multiple immune cell types and inflammation markers in treatment-naive skin biopsy samples from 48 patients with CLE to identify baseline immunophenotypes that may predict the response to antimalarial therapy. Patients were stratified according to their response to treatment with antimalarials, as HCQ responders, QC responders, or nonresponders.
Results:
HCQ responders demonstrated increased CD4+ T cells compared to the QC responder group. Patients in the nonresponder group were found to have decreased Treg cells compared to QC responders and increased central memory T cells compared to HCQ responders. QC responders expressed increased phosphorylated stimulator of interferon genes (pSTING) and interferon-κ (IFNκ) compared to HCQ responders. Phosphorylated STING and IFNκ were found to be localized to conventional dendritic cells (cDCs), and the intensity of pSTING and IFNκ staining was positively correlated with the number of cDCs on a tissue and cellular level. Neighborhood analysis revealed decreased regulatory cell interactions in nonresponder patients. Hierarchical clustering revealed that nonresponder patients could be further differentiated based on expression of pSTAT2, pSTAT3, pSTAT4, pSTAT5, phosphorylated interferon regulatory factor 3 (pIRF3), granzyme B, pJAK2, interleukin-4 (IL-4), IL-17, and IFNγ.
Conclusion:
These findings indicate differential immune cell compositions between patients with CLE, offering guidance for future research on precision-based medicine and treatment response.
