Exon array analysis of head and neck cancers identifies a hypoxia related splice variant of LAMA3 associated with a poor prognosis.

PLoS Comput Biol

Applied Computational Biology and Bioinformatics Group, Cancer Research UK Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital, Manchester, United Kingdom.

Published: November 2009


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Article Abstract

The identification of alternatively spliced transcript variants specific to particular biological processes in tumours should increase our understanding of cancer. Hypoxia is an important factor in cancer biology, and associated splice variants may present new markers to help with planning treatment. A method was developed to analyse alternative splicing in exon array data, using probeset multiplicity to identify genes with changes in expression across their loci, and a combination of the splicing index and a new metric based on the variation of reliability weighted fold changes to detect changes in the splicing patterns. The approach was validated on a cancer/normal sample dataset in which alternative splicing events had been confirmed using RT-PCR. We then analysed ten head and neck squamous cell carcinomas using exon arrays and identified differentially expressed splice variants in five samples with high versus five with low levels of hypoxia-associated genes. The analysis identified a splice variant of LAMA3 (Laminin alpha 3), LAMA3-A, known to be involved in tumour cell invasion and progression. The full-length transcript of the gene (LAMA3-B) did not appear to be hypoxia-associated. The results were confirmed using qualitative RT-PCR. In a series of 59 prospectively collected head and neck tumours, expression of LAMA3-A had prognostic significance whereas LAMA3-B did not. This work illustrates the potential for alternatively spliced transcripts to act as biomarkers of disease prognosis with improved specificity for particular tissues or conditions over assays which do not discriminate between splice variants.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2773424PMC
http://dx.doi.org/10.1371/journal.pcbi.1000571DOI Listing

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