Can a Metastatic Gene Expression Profile Outperform Tumor Size as a Predictor of Occult Lymph Node Metastasis in Oral Cancer Patients?

Abstract

To determine the differential gene expression between oral squamous cell carcinoma (OSCC) with and without metastasis to cervical lymph nodes and to assess prediction of nodal metastasis by using molecular features. We used Affymetrix U133 2.0 plus arrays to compare the tumor genome-wide gene expression of 73 node-positive OSCCs with 40 node-negative OSCCs (≥ 18 months). Multivariate linear regression was used to estimate the association between gene expression and nodal metastasis. Stepwise logistic regression and receiver operating characteristics (ROC) analysis were used to generate predictive models and to compare these with models by using tumor size alone. We identified five genes differentially expressed between node-positive and node-negative OSCCs after adjusting for tumor size and human papillomavirus status: REEP1, RNF145, CTONG2002744, MYO5A, and FBXO32. Stepwise regression identified a four-gene model (MYO5A, RFN145, FBXO32, and CTONG2002744) as the most predictive of nodal metastasis. A leave-one-out ROC analysis revealed that our model had a higher area under the curve (AUC) for identifying occult nodal metastasis compared with that of a model by tumor size alone (respective AUC: 0.85 and 0.61; P = 0.011). A model combining tumor size and gene expression did not further improve the prediction of occult metastasis. Independent validation using 31 metastatic and 13 nonmetastatic cases revealed a significant underexpression of CTONG2002744 (P = 0.0004). These results suggest that our gene expression markers of OSCC metastasis hold promise for improving current clinical practice. Confirmation by others and functional studies of CTONG2002744 is warranted.