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Prediction of lymph node metastasis in oral squamous cell carcinoma based on protein profile

dataset
posted on 06.03.2019, 13:43 by Binbin Yu, Wei Cao, Chenping Zhang, Ronghui Xia, Jinlin Liu, Ming Yan, Wantao Chen

Objective: Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3).

Methods: We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage.

Results: We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC.

Conclusions: Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.

Funding

This paper was funded by the National Program on Key Research Project of China, [grant number: 2016YFC0902700], the National Natural Science Foundation of China, [grant number: 81672829]; Shanghai Municipal Science and Technology Commission Funded Projects: [18DZ2291500, 16140903300]; .

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