Oral diseases · 2023
Humoral immune disorders affect clinical outcomes of oral lichen planus.
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Qing Maofeng, Yang Dan, Shang Qianhui, Li Weiqi, Zhou Yu, Xu Hao, Chen Qianming
Аннотация
OBJECTIVES: The molecular characteristics of oral lichen planus (OLP) are still unclear, and it is not possible to distinguish the clinical outcome of OLP patients in a short period of time for follow-up. Here, we investigate the molecular characteristics of lesions in patients with stable lichen planus (SOLP) and recalcitrant erosive oral lichen planus (REOLP).
METHODS: Our clinical follow-up cohort was split into SOLP and REOLP groups based on the follow-up clinical data. The core modules associated with the clinical information were identified by weighted gene co-expression network analysis (WGCNA). The OLP cohort samples were divided into two groups by molecular typing, and a prediction model for OLP was created by training neural networks with the neuralnet package.
RESULTS: We screened 546 genes in five modules. After doing a molecular type of OLP, it was determined that B cells might have a significant impact on the clinical outcome of OLP. In addition, by means of machine learning, a prediction model was developed to predict the clinical regression of OLP with greater accuracy than the existing clinical diagnostic.
CONCLUSIONS: Our study revealed humoral immune disorders may make an important contribution to the clinical outcome of OLP.
METHODS: Our clinical follow-up cohort was split into SOLP and REOLP groups based on the follow-up clinical data. The core modules associated with the clinical information were identified by weighted gene co-expression network analysis (WGCNA). The OLP cohort samples were divided into two groups by molecular typing, and a prediction model for OLP was created by training neural networks with the neuralnet package.
RESULTS: We screened 546 genes in five modules. After doing a molecular type of OLP, it was determined that B cells might have a significant impact on the clinical outcome of OLP. In addition, by means of machine learning, a prediction model was developed to predict the clinical regression of OLP with greater accuracy than the existing clinical diagnostic.
CONCLUSIONS: Our study revealed humoral immune disorders may make an important contribution to the clinical outcome of OLP.