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

ABSTRACT

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.

KEYWORDS:

• lymph node metastasis
• oral squamous cell carcinoma
• prediction model

Article highlights

• Cervical lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC), but it is controversial to define the risk of occult (clinically and radiologically undetectable) lymph node metastasis.

• Invasive incisional biopsy followed by histopathology is the gold standard for oral cancer diagnosis. However, standard histopathology does not predict the observed variability in treatment response or prognosis, and the prognostic value ranged from not any to highly significant.

• Quantitative proteomics methods are increasingly used for cancer progression and possible treatment targets.

Combination of CAD, SOD2, and histopathological grade significantly enhanced the accuracy of predicting the lymph node metastasis and life status in OSCCs.

Author contribution

B. Yu carried out the experiments and contributed to the writing of the manuscript. M. Yan and W. Chen supervised the work and consulted advised on the final manuscript. W. Cao collected the patient information and analyzed the data. R. Xia provided materials for and consulted on the tissue section analysis. J. Liu assisted in the collection of patient information. C. Zhang assisted in the analysis of the data.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

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]; .