Molecular Subtypes in Head and Neck Cancer Exhibit Distinct Patterns of Chromosomal Gain and Loss of Canonical Cancer Genes

Abstract

Head and neck squamous cell carcinoma (HNSCC) is a frequently fatal heterogeneous disease. Beyond the role of human papilloma virus (HPV), no validated molecular characterization of the disease has been established. Using an integrated genomic analysis and validation methodology we confirm four molecular classes of HNSCC (basal, mesenchymal, atypical, and classical) consistent with signatures established for squamous carcinoma of the lung, including deregulation of the KEAP1/NFE2L2 oxidative stress pathway, differential utilization of the lineage markers SOX2 and TP63, and preference for the oncogenes PIK3CA and EGFR. For potential clinical use the signatures are complimentary to classification by HPV infection status as well as the putative high risk marker CCND1 copy number gain. A molecular etiology for the subtypes is suggested by statistically significant chromosomal gains and losses and differential cell of origin expression patterns. Model systems representative of each of the four subtypes are also presented.

Immunological and classical subtypes of oral premalignant lesions

“…Conversely, cluster 2 was characterized by a moderate enrichment of pathways involved in xenobiotic metabolism as well as EGFR signaling and was therefore named ‘classical’ by analogy with the classical subtype of head neck cancers. 18,21 Of note, EGFR gene expression was significantly higher in the classical subtype compared to the immunological subtype of OPL (P < 0.0001; Supplementary Figure 3).

10.1080/2162402X.2018.1496880-F0003Figure 3. Integrative network of miRNAs and target genes differentially expressed between the two subtypes . In the discovery set, we identified a set of 31 miRNAs differentially expressed between the immunological and classical subtypes (Q-value< 0.05, |FC|> 2) and connected with 970 target genes (miRNet tool) which were also differentially expressed between the two subtypes (Q-value< 0.05).

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“…18 Two main clusters, including 42 (cluster 1) and 44 (cluster 2) OPLs, respectively, were identified based on the heatmap of the consensus matrix (Figure 1A) and plots (Supplementary Figure 1) produced by the ConsensusClusterPlus R package, as well as on the heatmap of hierarchical clustering using ArrayStudio software (Supplementary Figure 2).

10.1080/2162402X.2018.1496880-F0001Figure 1. Identification of two gene expression-based subtypes, “classical” and “immunological”, in the discovery dataset of 86 OPL . To identify gene expression subtypes, we ran the ConsensusClusterPlus R package 55 with the 2,500 most variable genes, which were selected using the median absolute deviation, as previously described 18 . (A) Heatmap of the consensus matrix for k = 2 clusters, with samples in rows and columns, and consensus values ranging from 0 (never clustered together) to 1 (always clustered together) and marked by white to dark blue.

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“…To identify gene expression subtypes, we ran the ConsensusClusterPlus R package 55 with the 2,500 most variable genes, which were selected using the median absolute deviation, as previously described 18 . (A) Heatmap of the consensus matrix for k = 2 clusters, with samples in rows and columns, and consensus values ranging from 0 (never clustered together) to 1 (always clustered together) and marked by white to dark blue.…”

“…Large-scale programs have provided important biological insights into HNSCC and allowed for the identification of four gene expression-based subtypes 18,19 that have been associated with different patterns of drug sensitivity 21 and response to radiation therapy. 22 A pre-cancer atlas is the next step for elucidating the molecular heterogeneity at the early steps of head and neck tumorigenesis and help designing next generation prevention interventions.…”

“…18–21 Interestingly, some of these molecular subtypes present different drug sensitivity patterns 21 as well as different levels of radioresistance, 22 suggesting their potential relevance to define personalized-based therapy in head neck cancers.…”