Clinical Research Papers:

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

Loris De Cecco _, Monica Nicolau, Marco Giannoccaro, Maria Grazia Daidone, Paolo Bossi, Laura Locati, Lisa Licitra and Silvana Canevari

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Oncotarget. 2015; 6:9627-9642. https://doi.org/10.18632/oncotarget.3301

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Loris De Cecco1, Monica Nicolau2, Marco Giannoccaro1, Maria Grazia Daidone3, Paolo Bossi4, Laura Locati4, Lisa Licitra4, Silvana Canevari1

1Functional Genomics and Bioinformatics, Dept. of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

2Department of Mathematics, Stanford University, Stanford, CA, USA

3Dept. of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

4Head and Neck Medical Oncology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

Correspondence to:

Loris De Cecco, e-mail: [email protected]

Silvana Canevari, e-mail: [email protected]

Keywords: tumor subtypes, gene expression, HNSCC, microarray, meta-analysis

Received: January 26, 2015     Accepted: February 08, 2015     Published: March 20, 2015


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.

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