A 7-Gene Nomogram for Predicting Cervical Lymph Node Status in cT 1-2 Oral Squamous Cell Carcinoma

Background: Around 20-30% of patients with early-stage OSCC have hidden lymph node metastases, meaning that over 70% of early-stage OSCC patients may have had unnecessary prophylactic lymph node dissection. Therefore, it is crucial to have dependable biomarkers that can forecast lymph node spread status and direct personalized treatment for initial OSCC stages. Our goal in this study was to develop a strong set of multiple genes that can accurately predict lymph node spread status in patients with cT _1/2 oral cancer. Methods： Initially, RNA-seq information for cT _1/2 OSCC individuals was obtained from The Cancer Genome Atlas (TCGA) repository, and then separated into two categories: patients with positive pathological lymph nodes (pN ⁺ ) and patients with negative pathological lymph nodes (pN ^- ). Next, a novel multi-RNA nomogram was developed using LASSO regression and stepwise multivariate logistic regression to predict lymph node status in cT _1/2 OSCC cases. Furthermore, the accuracy of the model was evaluated using C-index, ROC AUC, and calibration curve to assess prediction performance. Finally, an external validation data obtained from GEO dataset was employed to validate the prediction capability of the novel prediction model. Results： In this study, we developed a nomogram based on 7 mRNAs to predict cervical lymph node metastases status in cT _1-2 OSCC patients. The mRNAs included in the nomogram are ZFP42 , ARG1 , FRMD1 , CALB1 , ERICH5 , AMBP , and AQP4 . The ROC internal validation resulted in an AUC of 0.806, indicating the fitted model's exceptional predictive accuracy. Furthermore, the 7-gene model demonstrated excellent performance with an AUC of 0.861 when validated using the GEO dataset (GSE42743). Finally, a nomogram integrating 7 genes for predicting lymph nodal metastasis status in cT _1-2 oral squamous cell carcinoma was established. Conclusion： Our results demonstrate a novel 7-gene signature which can predict lymph node status for cT _1/2 OSCC patients accurately. The nomogram that combines 7 genes shows promise as a tool for creating personalized treatment plans for cT _1/2 oral squamous cell carcinoma (OSCC) patients.