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  • Original Paper
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Identification of genes associated with tumorigenesis and metastatic potential of hypopharyngeal cancer by microarray analysis

Abstract

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer among men in the developed world. There is a need, for both clinical and scientific reasons, to find markers to identify patients with aggressive disease as early as possible, and to understand the events leading to malignant transformation and susceptibility to metastasis. We report the first large-scale gene expression analysis of a unique HNSCC location, the hypopharynx. Four normal and 34 tumour samples were analysed with 12 600 gene microarrays. Clusters of differentially expressed genes were identified in the chromosomal regions 3q27.3, 17q21.2–q21.31, 7q11.22–q22.1 and 11q13.1–q13.3, which, interestingly, have already been identified by comparative genomic hybridization (CGH) as major regions of gene amplification. We showed that six overexpressed genes (EIF4G1, DVL3, EPHB4, MCM7, BRMS1 and SART1) located in these regions are indeed amplified. We report 119 genes that are highly differentially expressed between ‘early’ tumours and normal samples. Of these, we validated by quantitative PCR six novel poorly characterized genes. These genes are potential new markers of HNSCC. Comparing patients with relatively nonaggressive and aggressive tumours (without or with clinical evidence of metastasis 3 years after surgery), we identified 164 differentially expressed genes potentially involved in the acquisition of metastatic potential. This study contributes to the understanding of HNSCC, staging patients into prognostic groups and identifying high-risk patients who may benefit from more aggressive treatment.

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Acknowledgements

We thank (a) Diemunsch F. for technical assistance; (b) the IGBMC core facilities; (c) the Ligue Regionale contre le Cancer, the Association pour la Recherche sur le Cancer, the Ministère de la Recherche et de la Technologie, and the Fondation pour la Recherche Médicale for fellowships to A Cromer, A Carles, G Ganguli, F Lemaire and J Young; (c) the Ligue Régionale (Bas-Rhin/Haut-Rhin) contre le Cancer for funding for an RT-QPCR machine; (d) The Ministère de la Recherche for the purchase of the Affymetrix arrays; and (e)ARERS Verre Espoir (no. 138.02), Aventis, the Centre National de la Recherche Scientifique, the Institut National de la Santé et de la Recherche Médicale, the Hôpital Universitaire de Strasbourg, the Association pour la Recherche sur le Cancer, the Fondation pour la Recherche Médicale, the Ligue Nationale Française contre le Cancer (Equipe labellisée), the Ligue Régionale (Haut-Rhin) contre le Cancer, the Ligue Régionale (Bas-Rhin) contre le Cancer, the European Union (FP5 project QLK6-2000-00159) and the Ministère de la Recherche (Décisions 99H0161 and 98C0372) for financial assistance.

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Correspondence to Bohdan Wasylyk.

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Supplementary Information accompanies the paper on Oncogene website (http://www.nature.com/onc).

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Supplementary figure

Increasing the number of training samples increases the accuracy of prediction of tumour outcome. MAS 5.0 Signal was used to select the gene-set that was then used to predict the tumour subtype of the other samples in a blinded manner. (A). The selection was performed on the first batch (5 M and 5 NM samples) to predict the second batch samples by PAM cross-validation. The 384 selected probe sets correctly predicted 7/10 M, 3/6 NM (62% correctly predicted). (B). The converse experiment was performed. The 320 selected probe sets correctly predicted 4/5 M and 4/5 NM (80% correct prediction). (C). The selection was performed on all the 26 microarrays normalised by SVD. PAM cross-validation using the 121 selected probe sets (118 unique genes) correctly predicted 14/15 M and 10/11 NM (92.3% correctly classified).Materials and Methods: The genes that exhibit a signal ratio of more than 1.5 between at least half of the samples of one subtype and the average of the opposite tumour subtype, and never in the opposite subtype, were selected. The cross-validations were performed using values normalised for batch variation by SVD. The dataset were analysed by Prediction Analysis for Microarrays (PAM: (Tibshirani et al., 2002); http://www-stat.stanford.edu/~tibs/PAM/index.html). The graphs represent the cross-validation part of PAM that gives an estimation of prediction error (threshold 0) (TIF 3879 kb)

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Cromer, A., Carles, A., Millon, R. et al. Identification of genes associated with tumorigenesis and metastatic potential of hypopharyngeal cancer by microarray analysis. Oncogene 23, 2484–2498 (2004). https://doi.org/10.1038/sj.onc.1207345

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