The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods.

A comprehensive functional analysis of tissue specificity of human gene expression.

Background: In recent years, the maturation of microarray technology has allowed the genome-wide analysis of gene expression patterns to identify tissue-specific and ubiquitously expressed ('housekeeping') genes. We have performed a functional and topological analysis of housekeeping and tissue-specific networks to identify universally necessary biological processes, and those unique to or characteristic of particular tissues.

Results: We measured whole genome expression in 31 human tissues, identifying 2374 housekeeping genes expressed in all tissues, and genes uniquely expressed in each tissue.

Genome-wide functional synergy between amplified and mutated genes in human breast cancer.

A single cancer cell contains large numbers of genetic alterations that in combination create the malignant phenotype. However, whether amplified and mutated genes form functional and physical interaction networks that could explain the selection for cells with combined alterations is unknown. To investigate this issue, we characterized copy number alterations in 191 breast tumors using dense single nucleotide polymorphism arrays and identified 1,747 genes with copy number gain organized into 30 amplicons.