Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data

Abstract

Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40–50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets.Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes.To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.

Functional Genomics Uncover the Biology behind the Responsiveness of Head and Neck Squamous Cell Cancer Patients to Cetuximab

“…Graphical representation of GSEA findings was provided by GOCircle plot function of GOplot R package (11), displaying information about the significance of the enrichment (Àlog 10 adjusted P) and the z-score of each gene set. To better disclose the biology underlying long-and short-PFS, we applied the Prediction Analysis for Microarrays (PAM) subtype classifier described in De Cecco and colleagues (12) and the centroid supergroup classification described in Keck and colleagues (13). Subsequently, a score was determined according to the Pearson correlation between the gene expression profile of each sample of our case material and the centroids for Cl3 and Basal subtypes of De Cecco and Keck classification, respectively.…”

Heads Up! Predictive Gene Signatures in Head and Neck Cancer May Be Coming Soon

“…The gene expression signature by Bossi and colleagues was able to classify metastatic colorectal cancer cases according to PFS, and among HNSCC patients, long cetuximabchemotherapy-PFS correlated with high scores in 3 of 5 of the HNSCC prognostic signatures. Further molecular subtype analysis revealed that gene expression patterns derived from the long cetuximab-chemotherapy-PFS patients appeared to be correlated with previously described basal and hypoxia molecular subtypes of HNSCC (4,5), and enriched for gene sets related to bCAT, E2F3, MYC, and p53. Additional drug sensitivity studies in this report showed that the GEP of long cetuximab-chemotherapy-PFS patients appeared to select for cell lines sensitive to EGFR tyrosine kinase inhibitors (afatinib, gefitinib, erlotinib, lapatinib), whereas GEP of short cetuximab-chemotherapy-PFS patients selected for gemcitabine sensitivity.…”

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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“…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.…”