Metabolomics analysis of oral mucosa reveals profile perturbation in reticular oral lichen planus

An improved scoring system for monitoring oral lichen planus: A preliminary clinical study

OBJECTIVES

To design an improved oral lichen planus (OLP) scoring system, which can be widely applied.

SUBJECTS AND METHODS

A new scoring system that took reticulation, hyperemia and ulceration (RHU) into account, named as RHU scoring system, was designed for OLP patients' management. The patients were also scored for the reticulation/erythema/ulcer (REU) scoring system, physician global assessment (PGA), numerical rating scale (NRS) and Oral Health Impact Profile-14 (OHIP-14). The reliability and validity analyses were utilized to assess the RHU scoring system. We further applied the RHU scoring system to examine the treatment outcomes of topical dexamethasone sodium phosphate and general hydroxychloroquine hydrochloride among OLP patients.

RESULTS

Forty-eight OLP patients from two medical centers were recruited. This new scoring system has reliability with an internal consistency index Cronbach α 0.49. The Pearson correlation of RHU score with PGA and REU score were 0.891 and 0.675 (p < 0.05) respectively, reflecting satisfactory standard validity. A 10% change in RHU score was used as the disease condition evaluation standard, reflecting satisfactory discriminating validity (t = -5.821, p < 0.001). During follow-ups, scores of all scales decreased at each re-visit. The drop between each visit of OHIP-14 fluctuated compared with the RHU system and NRS.

CONCLUSIONS

As a semi-quantitative score system, the RHU scoring system can reflect the severity of OLP patients with hyperemia and ulceration lesions more accurately and sensitively compared with other score systems, which provides the potential to be widely used.

Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus

Objective

To explore metabolic biomarkers related to erosive and reticulated oral lichen planus (OLP) by non-targeted metabolomics methods and correlate metabolites with gene expression, and to investigate the pathological network pathways of OLP from the perspective of metabolism.

Methods

A total of 153 individuals were enrolled in this study, including 50 patients with erosive oral lichen planus (EOLP), 51 patients with reticulated oral lichen planus (ROLP), and 52 healthy controls (HC). The ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS) was used to analyze the metabolites of 40 EOLP, 40 ROLP, and 40 HC samples, and the differential metabolic biomarkers were screened and identified. The regulatory genes were further screened through the shared metabolites between EOLP and ROLP, and cross-correlated with the OLP-related differential genes in the network database. A “gene-metabolite” network was constructed after finding the key differential genes. Finally, the diagnostic efficiency of the biomarkers was verified in the validation set and a diagnostic model was constructed.

Result

Compared with HC group, a total of 19 and 25 differential metabolites were identified in the EOLP group and the ROLP group, respectively. A total of 14 different metabolites were identified between EOLP and ROLP. Two diagnostic models were constructed based on these differential metabolites. There are 14 differential metabolites shared by EOLP and ROLP. The transcriptomics data showed 756 differentially expressed genes, and the final crossover network showed that 19 differential genes were associated with 12 metabolites. Enrichment analysis showed that alanine, aspartate and glutamate metabolism were closely associated with the pathogenesis of OLP.

Conclusion

The metabolic change of different types of OLP were clarified. The potential gene perturbation of OLP was provided. This study provided a strong support for further exploration of the pathogenic mechanism of OLP.

Integrative Analysis of Metabolomics and Transcriptomics Data Identifies Prognostic Biomarkers Associated With Oral Squamous Cell Carcinoma

Background

Oral squamous cell carcinoma (OSCC) is the most malignant neoplasm in oral cancer. There is growing evidence that its progression involves altered metabolism. The current method of evaluating prognosis is very limited, and metabolomics may provide a new approach for quantitative evaluation. The aim of the study is to evaluate the use of metabolomics as prognostic markers for patients with OSCC.

Methods

An analytical platform, Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS), was used to acquire the serum fingerprinting profiles from a total of 103 patients of OSCC before and after the operation. In total, 103 OSCC patients were assigned to either a training set (n = 73) or a test set (n = 30). The potential biomarkers and the changes of serum metabolites were profiled and correlated with the clinicopathological parameters and survival of the patients by statistical analysis. To further verify our results, we linked them to gene expression using data from the Kyoto Encyclopedia of Genes and Genomes (KEGG).

Results

In total, 14 differential metabolites and five disturbed pathways were identified between the preoperative group and postoperative group. Succinic acid change-low, hypoxanthine change-high tumor grade, and tumor stage indicated a trend towards improved recurrence-free survival (RFS), whether in a training set or a test set. In addition, succinic acid change-low, hypoxanthine change-high, and tumor grade provided the highest predictive accuracy of the patients with OSCC. KEGG enrichment analysis showed that the imbalance in the amino acid and purine metabolic pathway may affect the prognosis of OSCC.

Conclusions

The changes of metabolites before and after operation may be related to the prognosis of OSCC patients. UHPLC-Q-Orbitrap HRMS serum metabolomics analysis could be used to further stratify the prognosis of patients with OSCC. These results can better understand the mechanisms related to early recurrence and help develop more effective therapeutic targets.

Potential Metabolic Biomarkers for Early Detection of Oral Lichen Planus, a Precancerous Lesion

Background: Oral lichen planus (OLP) is a T-cell-mediated chronic inflammatory disorder and precancerous oral lesion with high incidence. The current diagnostic method of OLP is very limited and metabolomics may provide a new approach for quantitative evaluation.

Methods: The Ultra-Performance Liquid Chromatography-Quadrupole/Orbitrap High Resolution Mass Spectrometry (UHPLC-Q-Orbitrap HRMS) was applied to analyze the change of metabolites in serum of patients with OLP. A total of 115 OLP patients and 124 healthy controls were assigned to either a training set (n = 160) or a test set (n = 79). The potential biomarkers and the change of serum metabolites were profiled and evaluated by multivariate analysis.

Results: Totally, 23 differential metabolites were identified in the training set between OLP group and healthy group. Three prominent metabolites in receiver operating characteristic (ROC) were selected as a panel to distinguish OLP or healthy individuals in the test set, and the diagnostic accuracy was 86.1%.

Conclusions: This study established a new method for the early detection of OLP by analyzing serum metabolomics using UHPLC-Q-Orbitrap HRMS, which will help in understanding the pathological processes of OLP and identifying precancerous lesions in oral cavity.

Urinary metabolomic signatures in reticular oral lichen planus

Oral lichen planus (OLP) is a chronic inflammatory disease. Among all the clinical forms in OLP, reticular type has the highest incidence rate. Previous studies have applied metabolomics to investigate the metabolic changes of oral mucosa and blood samples from reticular OLP patients. Urinary metabolomic signatures is also useful in analyzing the pathological changes of the patients, which was a complement to the previous studies. Through these researches, we may have a more comprehensive understanding of the disease. Metabolic profiles of urinary samples from OLP patients and control subjects were analyzed by liquid chromatography (LC)-mass spectrometry (MS) system. Differentially expressed metabolites were identified via OSI/SMMS software for the pathology analysis. Totally, 30 differentially expressed metabolites were identified. Pathological network showed that these metabolites participated in 8 pathological processes, that is, DNA damage and repair disorder, apoptosis process, inflammatory lesion, oxidative stress injury, carbohydrate metabolism disorder, mood dysfunction, abnormal energy expenditure, and other pathological process. These findings demonstrated that the analysis of human urine metabolome might be conducive to the achievement of the objectives of this study.

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of Aconitum carmichaeli with Ampelopsis japonica Extract on Collagen-Induced Arthritis in Rats

Aconitum carmichaeli with Ampelopsis japonica (AA) is a classical traditional Chinese medicine (TCM) formula. There are a lot of examples showing that AA can be used to treat rheumatoid arthritis, but its mechanism of action is still not completely clear. In this research, collagen-induced arthritis (CIA) was chosen as a rheumatoid arthritis (RA) model. Rats of treated groups were continuously administered Aconitum carmichaeli (AC), Ampelopsis japonica (AJ) and Aconitum carmichaeli + Ampelopsis japonica (AA) orally once a day from the day after the onset of arthritis (day 7) until day 42. The results showed that AA not only significantly reduced paw swelling, but also improved the levels of TNF-α and IL-6 in serum. GC-MS-based urine metabonomics was established to analysis metabolic profiles and 21 biomarkers of RA rats were identified by the Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) methods. The prediction rate of the SVM method for the 21 biomarkers was 100%. Twenty of 21 biomarkers, including D-galactose, inositol and glycerol, gradually returned to normal levels after administration of AA. Metabolomic Pathway Analysis (MetPA) generated three related metabolic pathways-galactose metabolism, glycerolipid metabolism and inositol phosphate metabolism-which explain the mechanism of AA treatment of rheumatoid arthritis. This research provides a better understanding of the therapeutic effects and possible therapeutic mechanism of action of a complex TCM (AA) on rheumatoid arthritis.

Serum-based metabolomics characterization of patients with reticular oral lichen planus

OBJECTIVE

Oral lichen planus (OLP) is a chronic inflammatory mucosal lesion and systemic disease. In OLP, reticular type is the most common presentation of the disease. However, little is known about it. The aim of this study was to analyze the pathogenesis of reticular OLP and its possible associations with the pathological changes in other organ systems through serum-based metabolomics.

METHODS

Blood samples were obtained from 16 reticular OLP patients and 24 control subjects. Liquid chromatography (LC)-mass spectrometry (MS) system was used to identify differentially expressed metabolites. The pathways analysis was performed by MetaboAnalyst. Pathological network was constructed by Cytoscape software.

RESULTS

Totally, 31 modulated metabolites were identified, whose dysregulations affected 25 metabolic pathways and 7 pathological processes in the disease. Through an impact-value screen (impact-value＞0.1), 6 pathways were selected as the significantly dysregulated pathways. Pathological network showed that these metabolites participated in 7 pathological processes, that is, apoptosis process, DNA damage and repair disorder, oxidative stress injury, carbohydrate metabolism disorder, mood dysfunction, inflammatory lesion, and other pathological process.

CONCLUSION

The study demonstrated that reticular OLP could cause the dysregulations of the metabolites in serum, which might be also further linked to other organ and systemic diseases through the blood system, such as diabetes, sleep disorders, and depression, etc.