Molecular classification of lymph node metastases subtypes predict for survival in head and neck cancer

Purpose: In advanced stage head and neck squamous cell cancers (HNSCC), approximately half of the patients with lymph node metastases (LNM) are not cured. Given the heterogeneous outcomes in these patients, we profiled the expression patterns of LNMs to identify the biological factors associated with patient outcomes. Experimental Design: We performed mRNAseq and miRNAseq on 72 LNMs and 29 matched primary tumors from 34 patients with HNSCC. Clustering identified molecular subtypes in LNMs and in primary tumors. Prediction Analysis of Microarrays algorithm identified a 73-gene classifier that distinguished LNM subtypes. Gene-set enrichment analysis identified pathways upregulated in LNM subtypes. Results: Integrative clustering identified three distinct LNM subtypes: (i) an immune subtype (Group 1), (ii) an invasive subtype (Group 2), and (iii) a metabolic/proliferative subtype (Group 3). Group 2 subtype was associated with significantly worse locoregional control and survival. LNM-specific subtypes were not observed in matched primary tumor specimens. In HNSCCs, breast cancers, and melanomas, a 73-gene classifier identified similar Group 2 LNM subtypes that were associated with worse disease control and survival only when applied to lymph node sites, but not when applied to other primary tumors or metastatic sites. Similarly, previously proposed prognostic classifiers better distinguished patients with worse outcomes when applied to the transcriptional profiles of LNMs, but not the profiles of primary tumors. Conclusions: The transcriptional profiles of LNMs better predict outcomes than transcriptional profiles of primary tumors. The LNMs display site-specific subtypes associated with worse disease control and survival across multiple cancer types.