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Updated: May 15, 2025

Th17 Inflammation Model of Oropharyngeal Candidiasis in Immunodeficient Mice
Published on: February 18, 2015
Variable innate lymphoid cells predominancy in oral lichen planus latently led to diverse clinical outcomes: a
Xi-Ye Li1,2,3, Lei Pan4, Yi-Wen Deng1,2,3
1Department of Oral Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objectives:
To search for a new classification scheme for oral lichen planus (OLP) and oral lichenoid lesions (OLL) based on innate lymphoid cells (ILCs) and to evaluate the clinical significance of this classification for diagnosis and treatment.
Subjects And Methods:
This study was based on a clinical cohort and applied flow cytometry to prospectively analyze the ILC subgroups and proportions in OLP and OLL lesions using SPSS software (version 26.0) to attempt cluster analysis to classify diseases at the cellular level based on the phenotype and quantity of ILCs cells, analyze the correlation between the new classification of diseases and clinical risk factors based on the patient's clinical background information and classification results, and evaluate the differences in therapeutic effects among patients in different groups in corresponding clinical cohorts.
Results:
In the OLP and OLL groups, the ILC compartment consisted mainly of ILC1 (75.02% ± 27.55% and 72.99% ± 25.23%, respectively), ILC2 (1.49% ± 4.12% and 1.72% ± 3.18%, respectively), and ILC3 (16.52% ± 19.47% and 18.77% ± 18.12%, respectively). Using k-means clustering and two-step clustering, patients could be clustered into three groups that did not respond equally to the same treatment. Using k-means clustering, there was a statistically significant difference in REU scores between the ILC1 advantage group and the OLL subgroup before and after treatment (P = 0.02), which was not observed in two-step clustering. This indicates that k-means clustering may have greater value in the clinical application of OLL. In the ILC1 absolute advantage group, using HCQ + TGP for one month could effectively treat the patients regardless of the use of k-means clustering or two-step clustering (P ≤0.001), whereas the other groups did not.
Conclusions:
This study provides a preliminary OLP and OLL classification method based on ILC subgroups that can guide the cytological classification of diseases to a certain extent. Further clinical application values should be verified in subsequent cohort studies.
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