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Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in
Federico E Turkheimer1, Federico Roncaroli, Benoit Hennuy
1Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk
BMC Bioinformatics
|December 5, 2006
Summary
A new mathematical method, CHROMOWAVE, identifies gene expression patterns on chromosomes linked to glioma patient outcomes. This technique reveals low expression in specific chromosomal regions, predicting favorable prognosis and aiding in identifying clinically relevant gene expression changes.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Gene expression microarrays allow simultaneous investigation of thousands of genes.
- Gene location on chromosomes influences coordinated expression, necessitating advanced analytical methods.
- Understanding gene positional effects is crucial for analyzing gene expression data.
Purpose of the Study:
- To develop and apply a novel mathematical technique (CHROMOWAVE) for analyzing gene expression data based on chromosomal location.
- To identify multi-chromosomal expression patterns in gliomas and assess their clinical relevance.
- To investigate the relationship between identified expression patterns and chromosomal abnormalities.
Main Methods:
- Development of CHROMOWAVE, a novel mathematical technique utilizing the Haar wavelet transform.
- Application of CHROMOWAVE to Affymetrix HG-U133_Plus_2 expression data from 27 gliomas.
- Validation of findings using FISH (fluorescence in situ hybridization) analysis and replication on an independent dataset.
Main Results:
- CHROMOWAVE identified a multi-chromosomal pattern of low gene expression in specific regions (1p, 4, 9q, 13, 18, 19q) in gliomas.
- This expression pattern was statistically robust and significantly predicted favorable patient outcomes.
- FISH analysis revealed frequent monosomy 1p and 19q in tumors with the CHROMOWAVE pattern, but less frequent allelic loss on other affected chromosomes.
Conclusions:
- CHROMOWAVE is a valuable screening tool for detecting clinically relevant regional gene expression changes.
- Monosomy of chromosomes 1p and 19q is associated with diffuse low gene expression in gliomas.
- Further studies (CGH, polymorphism, methylation) are ongoing to elucidate the mechanisms behind this multi-chromosomal expression pattern.
