The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

BACKGROUND: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses. RESULTS: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics. CONCLUSION: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power

Co-regulation of a large and rapidly evolving repertoire of odorant receptor genes

The olfactory system meets niche- and species-specific demands by an accelerated evolution of its odorant receptor repertoires. In this review, we describe evolutionary processes that have shaped olfactory and vomeronasal receptor gene families in vertebrate genomes. We emphasize three important periods in the evolution of the olfactory system evident by comparative genomics: the adaptation to land in amphibian ancestors, the decline of olfaction in primates, and the delineation of putative pheromone receptors concurrent with rodent speciation. The rapid evolution of odorant receptor genes, the sheer size of the repertoire, as well as their wide distribution in the genome, presents a developmental challenge: how are these ever-changing odorant receptor repertoires coordinated within the olfactory system? A central organizing principle in olfaction is the specialization of sensory neurons resulting from each sensory neuron expressing only ~one odorant receptor allele. In this review, we also discuss this mutually exclusive expression of odorant receptor genes. We have considered several models to account for co-regulation of odorant receptor repertoires, as well as discussed a new hypothesis that invokes important epigenetic properties of the system

Loss of the Urothelial Differentiation Marker FOXA1 Is Associated with High Grade, Late Stage Bladder Cancer and Increased Tumor Proliferation

Approximately 50% of patients with muscle-invasive bladder cancer (MIBC) develop metastatic disease, which is almost invariably lethal. However, our understanding of pathways that drive aggressive behavior of MIBC is incomplete. Members of the FOXA subfamily of transcription factors are implicated in normal urogenital development and urologic malignancies. FOXA proteins are implicated in normal urothelial differentiation, but their role in bladder cancer is unknown. We examined FOXA expression in commonly used in vitro models of bladder cancer and in human bladder cancer specimens, and used a novel in vivo tissue recombination system to determine the functional significance of FOXA1 expression in bladder cancer. Logistic regression analysis showed decreased FOXA1 expression is associated with increasing tumor stage (p<0.001), and loss of FOXA1 is associated with high histologic grade (p<0.001). Also, we found that bladder urothelium that has undergone keratinizing squamous metaplasia, a precursor to the development of squamous cell carcinoma (SCC) exhibited loss of FOXA1 expression. Furthermore, 81% of cases of SCC of the bladder were negative for FOXA1 staining compared to only 40% of urothelial cell carcinomas. In addition, we showed that a subpopulation of FOXA1 negative urothelial tumor cells are highly proliferative. Knockdown of FOXA1 in RT4 bladder cancer cells resulted in increased expression of UPK1B, UPK2, UPK3A, and UPK3B, decreased E-cadherin expression and significantly increased cell proliferation, while overexpression of FOXA1 in T24 cells increased E-cadherin expression and significantly decreased cell growth and invasion. In vivo recombination of bladder cancer cells engineered to exhibit reduced FOXA1 expression with embryonic rat bladder mesenchyme and subsequent renal capsule engraftment resulted in enhanced tumor proliferation. These findings provide the first evidence linking loss of FOXA1 expression with histological subtypes of MIBC and urothelial cell proliferation, and suggest an important role for FOXA1 in the malignant phenotype of MIBC