Development And Validation Of A Nomogram Based On Immunochemistry Molecular Biomarkers For Oral Squamous Cell Carcinoma

Background:Oral cancer is a common malignancy in head and neck cancer.Oral squamous cell carcinoma(OSCC)is the predominant histological type,accounting for approximately more than 90% of oral cancers.Although improvements in the treatment have evolved from a surgical-based treatment model to multimodal therapies,the prognosis of patients with OSCC remains poor.The current American Joint Committee on Cancer(AJCC)TNM staging system and important prognostic indicators are widely used as guidelines in the decision-making process.However,in our clinical practice,it was usually found that the survival outcomes of patients with the same TNM staging could differ greatly even if they received similar treatments,indicating that the current TNM staging system could not provide individualized prognostic information for patients,and this might be related to the tumour heterogeneity of OSCC.Therefore,a supplement to TNM staging system may assist in evaluating the tumour growth,invasiveness,and sensitivity to treatment for better predicting the prognosis of patients with OSCC.Therefore,a classifier,which combines the expression of molecular biomarkers with the TNM staging system,is urgently needed to classify patients with different risks of relapse and metastasis.We aimed to develop a prognostic nomogram based on immunohistochemistry(IHC)biomarkers of patients with oral squamous cell carcinoma(OSCC),and use statistical methods to evaluate the accuracy and clinical utility of the nomogram,thus assisting to predict the prognosis of patients with OSCC and guide the individual decision-making process.Methods:1.We retrospectively reviewed the medical records of 294 patients who had undergone surgery with or without induction chemotherapy at Tianjin Medical University Cancer Institute and Hospital between January 2010 and December2015.The basic characteristics of all patients included in the study were analyzed.We used the Kaplan–Meier survival analysis and log-rank test to estimate the OS.Univariate and multivariate analyses were performed with the Cox regression model to determine the clinicopathological characteristics which may affect the prognosis of patients with OSCC.2.Using computer-generated numbers,patients were randomly stratified into two groups at the 1:1 ratio,and tissue samples of the patients were collected.Immunohistochemical experiments were performed,and the IHC results of the 16 molecular markers of each patient were analyzed.The least absolute shrinkage and selection operator(LASSO)Cox regression model was performed to select the biomarkers and develop a combined IHC score(IHCs)classifier.The two groups were compared using the t-test for continuous variables and chi-square test for categorical variables.Receiver operating characteristic(ROC)analysis was conducted to explore the prognostic performance of the IHCs classifier.3.A nomogram was built by integrating the clinicopathological characteristics with the IHCs classifier.The calibration curve was used to compare the predicted survival rate and the true survival rate.Decision curve analysis(DCA)was carried out to evaluate the clinical utility of the nomogram.Statistical analysis was performed with R software(3.6.1)and SPSS software(version 25.0).Statistical significance was two-sided,and P <0.05 was considered statistically significant.Results:1.A total of 294 patients with oral squamous cell carcinoma who met the inclusion criteria were included in this study.The multivariate Cox analysis identified that the age≥60,poor differentiation,stage Ⅲ-Ⅳ were independent prognostic factors for OS.Among patients with TNM stage I,the 5-year survival rate of patients with G1-G2 was 61.6%,and the 5-year survival rate of patients with G3 was 25.4%,with significant statistical difference.Similarly,in patients with TNM stage Ⅱ and Ⅲ,the prognosis of patients with G3 was worse than that of patients whose tissue differentiation type were G1-G2,with statistical significance.However,there was no statistical significance between the tumor differentiation G3 and G1-G2 in patients with stages Ⅳ.2.In the training cohort,five biomarkers,specifically c-Met,Vimentin,HIF-2α,VEGFc,and Bcl-2 were extracted.Then,an IHCs classifier was developed,and patients were stratified into high-and low-IHCs groups.In the training cohort,the 5-year overall survival(OS)was 62.1% in low-IHCs group and 28.2% in high-IHCs group(P<0.001),similarly results were shown in the validation cohort.The area under the time independent ROC curve(AUROC)of the TNM stage was 0.690,while the AUROC of the combination of the IHCs classifier and TNM stage was 0.746,which showed a better performance for predicting the OS than the TNM stage alone.Similar to the results displayed in the validation cohort.3.Therefore,a nomogram was built to integrate the IHCs classifier and clinicopathological factors related to the survival outcomes of the patients with OSCC.The C-index was 0.67 and 0.76 in the training cohort and validation cohort,respectively.It is indicated that our nomogram has a good ability of discrimination.The DCA analysis shows that the nomogram has good clinical unity value in predicting the 3-and 5-year survival rate.The calibration curves showed that our nomogram had a good consistency with the ideal model for predicting the 3-and 5-year OS in the training cohort and validation cohort.Conclusions:1.Age,TNM stage,tumor cell differentiation were related factors which affected the prognosis of patients with OSCC.TNM staging cannot completely individualized predict the survival of patients with OSCC.The prognosis of patients with the same TNM staging could be different.2.The IHCs classifier was shown to be an independent predictor for the prognosis of patients with OSCC.It can be used as a supplement to the TNM staging system to help assess the prognosis of patients and increase its accuracy for predicting the prognosis of patients with oral squamous cell carcinoma.3.The nomogram which was constructed based on IHCs classifier and clinicopathological factors could effectively predict the prognosis of OSCC patients and can be used as a potential tool to guide the individualized decision-making process.As a tool for evaluating the prognosis of OSCC,the nomogram had good accuracy and clinical unity.