Abstract
Objective We aimed to find biological signatures of malignant transformation using non-invasive liquid biopsy. Study Design Unstimulated tears from patients with OL (N=10), PVL (N=10), OSCC (n=14), and control patients (N=10) were collected, and submitted to discovery-based proteomics by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data were analyzed by the software MaxQuant (proteomics), Byonics (N-glycoproteomics), and PEAKS database (post-translational modifications). Differential abundance between the groups was assessed by ANOVA following the Tukey test (p<0.05). We performed analyses of biologically processed enrichment, hierarchical clustering, and clinicopathologic correlation using Pearson correlation and linear regression (R²>0.5; p<0.05). Results We identified a panel of 24 proteins with differential abundance between the groups that present potential capacity to predict malignant transformation. The innate immune system was the main biological process correlated with these proteins. Clinicopathologic correlation analyses showed several associations, such as epithelial dysplasia, lymph node metastasis, and clinical stages of the disease. In addition, we identified several proteins that are druggable and may be useful as therapeutic targets. Conclusion Liquid biopsy from tear fluids may be a powerful non-invasive tool to provide insights into the process of malignant transformation into oral cancer, guiding early diagnosis and improving the prognosis. The São Paulo Research Foundation-FAPESP (18/19922-9). We aimed to find biological signatures of malignant transformation using non-invasive liquid biopsy. Unstimulated tears from patients with OL (N=10), PVL (N=10), OSCC (n=14), and control patients (N=10) were collected, and submitted to discovery-based proteomics by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data were analyzed by the software MaxQuant (proteomics), Byonics (N-glycoproteomics), and PEAKS database (post-translational modifications). Differential abundance between the groups was assessed by ANOVA following the Tukey test (p<0.05). We performed analyses of biologically processed enrichment, hierarchical clustering, and clinicopathologic correlation using Pearson correlation and linear regression (R²>0.5; p<0.05). We identified a panel of 24 proteins with differential abundance between the groups that present potential capacity to predict malignant transformation. The innate immune system was the main biological process correlated with these proteins. Clinicopathologic correlation analyses showed several associations, such as epithelial dysplasia, lymph node metastasis, and clinical stages of the disease. In addition, we identified several proteins that are druggable and may be useful as therapeutic targets. Liquid biopsy from tear fluids may be a powerful non-invasive tool to provide insights into the process of malignant transformation into oral cancer, guiding early diagnosis and improving the prognosis.
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