ABSTRACT
Lymph nodal disease (LN+) is the most significant prognostic factor of oral squamous cell carcinoma (OSCC). Current risk indicator(s) for guiding elective neck dissection (END) is insufficient for clinically node-negative (cN0) patients, resulting in under- or overtreatment. While the role of immunological events in tumorigenesis and metastasis is evident, the prognostic implication in OSCC remains unclear. The study objective was to investigate large-scale immune-related gene expression and determine its prognostic value on node-free survival (NFS). We analyzed patients who received intent-to-cure surgery with at least 3 y of follow-up and known outcome of LN through a pan-Canadian surgical trial. Total RNA was extracted from surgical tissues with >70% tumor content and analyzed on a 730-gene panel (NanoString nCounter® PanCancer Immune Panel). We first profiled gene expression in a fresh-frozen (FF) discovery set to identify differentially expressed (DE) genes, which were then used in unsupervised clustering analysis to identify patient subgroups. The prognostic value of the identified DE genes was then validated on formalin-fixed, paraffin-embedded (FFPE) samples. A total of 177 RNA samples were derived from 89 FF and 88 FFPE surgical tissues, of which 45 (51%) and 40 (45%), respectively, were from patients who developed LN+. We identified 6 DE genes overexpressed in LN+ tumors (false discovery rate <0.001; log2 fold change >1). Clustering analysis separated the patients into 2 subgroups (CM1, CM2), with CM2 exhibiting significantly increased expression and worse 5-y NFS rate (28%; P < 0.001). The prognostic value of these 6 candidate genes was validated on FFPE samples, which were also separated into 2 distinct prognostic groups, confirming the association between increased gene expression and poor 5-y NFS (CM1, 70.3%; CM2, 43.3%; P = 0.01). This is the first study identifying a panel of immune-related genes associated with NFS that can potentially be used clinically stratifying the risk of LN+ at the time of OSCC diagnosis.
