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Open Access Research

Microenvironmental genomic alterations reveal signaling networks for head and neck squamous cell carcinoma

Gurkan Bebek134, Mohammed Orloff12 and Charis Eng1245*

Author Affiliations

1 Genomic Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Mailstop NE-50 Cleveland, OH 44195, USA

2 Taussig Cancer Institute, Cleveland Clinic, 9500 Euclid Avenue, Mailstop NE-50 Cleveland, OH 44195, USA

3 Case Center for Proteomics and Bioinformatics, Case Western Reserve University, 10900 Euclid Ave. Cleveland OH 44106, USA

4 Case Comprehensive Cancer Center, Case Western Reserve University, 10900 Euclid Ave. Cleveland OH 44106, USA

5 Department of Genetics, Case Western Reserve University, 10900 Euclid Ave. Cleveland OH 44106, USA

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Journal of Clinical Bioinformatics 2011, 1:21  doi:10.1186/2043-9113-1-21

Published: 2 August 2011

Abstract

Background

Advanced stage head and neck squamous cell carcinoma (HNSCC) is an aggressive cancer with low survival rates. Loss-of-heterozygosity/allelic imbalance (LOH/AI) analysis has been widely used to identify genomic alterations in solid tumors and the tumor microenvironment (stroma). We hypothesize that these identified alterations can point to signaling networks functioning in HNSCC epithelial-tumor and surrounding stroma (tumor microenvironment).

Results

Under the assumption that genes in proximity to identified LOH/AI regions are correlated with the tumorigenic phenotype, we mined publicly available biological information to identify pathway segments (signaling proteins connected to each other in a network) and identify the role of tumor microenvironment in HNSCC. Across both neoplastic epithelial cells and the surrounding stromal cells, genetic alterations in HNSCC were successfully identified, and 75 markers were observed to have significantly different LOH/AI frequencies in these compartments (p < 0.026). We applied a network identification approach to the genes in proximity to these 75 markers in cancer epithelium and stroma in order to identify biological networks that can describe functional associations amongst these marker-associated genes.

Conclusions

We verified the involvement of T-cell receptor signaling pathways in HNSCC as well as associated oncogenes such as LCK and PLCB1, and tumor suppressors such as STAT5A, PTPN6, PARK2. We identified expression levels of genes within significant LOH/AI regions specific to stroma networks that correlate with better outcome in radiation therapy. By integrating various levels of high-throughput data, we were able to precisely focus on specific proteins and genes that are germane to HNSCC.