Li Xi-Ye, Pan Lei, Deng Yi-Wen, Chen Jun-Jun, Tian Zhen, Tang Guo-Yao, Ge Shu-Yun, Wang Yu-Feng
Department of Oral Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
National Center for Stomatology, National Clinical Research Center for Oral Diseases, Shanghai, China.
Front Immunol. 2025 Apr 28;16:1551311. doi: 10.3389/fimmu.2025.1551311. eCollection 2025.
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.
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.
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 ( = 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 ( ≤0.001), whereas the other groups did not.
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.
基于固有淋巴细胞（ILC）寻找口腔扁平苔藓（OLP）和口腔苔藓样病变（OLL）的新分类方案，并评估该分类在诊断和治疗方面的临床意义。
本研究基于一个临床队列，应用流式细胞术对OLP和OLL病变中的ILC亚群及其比例进行前瞻性分析，使用SPSS软件（版本26.0）尝试进行聚类分析，以便根据ILC细胞的表型和数量在细胞水平对疾病进行分类，基于患者的临床背景信息和分类结果分析疾病新分类与临床危险因素之间的相关性，并评估相应临床队列中不同组患者治疗效果的差异。
在OLP组和OLL组中，ILC区室主要由ILC1（分别为75.02%±27.55%和72.99%±25.23%）、ILC2（分别为1.49%±4.12%和1.72%±3.18%）和ILC3（分别为16.52%±19.47%和18.77%±18.12%）组成。使用k均值聚类和两步聚类法，可将患者分为三组，这三组对相同治疗的反应并不相同。使用k均值聚类时，治疗前后ILC1优势组和OLL亚组的REU评分存在统计学显著差异（ = 0.02），而在两步聚类中未观察到这种差异。这表明k均值聚类在OLL的临床应用中可能具有更大价值。在ILC1绝对优势组中，无论使用k均值聚类还是两步聚类法，使用羟氯喹（HCQ）+白芍总苷（TGP）治疗一个月均可有效治疗患者（≤0.001），而其他组则不然。
本研究提供了一种基于ILC亚群的OLP和OLL初步分类方法，可在一定程度上指导疾病的细胞学分类。后续队列研究应验证其进一步的临床应用价值。
