Models of bladder tumor progression have suggested that genetic alterations may determine both phenotype and clinical course.We have applied expression microarray analysis to a divergent set of bladder tumors to further elucidate the course of disease progression and to classify tumors into more homogeneous and clinically relevant subgroups. cDNA microarrays containing 10,368 human gene elements were used to characterize the global gene expression patterns in 80 bladder tumors, 9 bladder cancer cell lines, and 3 normal bladder samples. Robust statistical approaches accounting for the multiple testing problem were used to identify differentially expressed genes. Unsupervised hierarchical clustering successfully separated the samples into two subgroups containing superficial (pT a and pT 1 ) versus muscle-invasive (pT 2 -pT 4 ) tumors. Supervised classification had a 90.5% success rate separating superficial from muscle-invasive tumors based on a limited subset of genes. Tumors could also be classified into transitional versus squamous subtypes (89% success rate) and good versus bad prognosis (78% success rate). The performance of our stage classifiers was confirmed in silico using data from an independent tumor set. Validation of differential expression was done using immunohistochemistry on tissue microarrays for cathepsin E, cyclin A2, and parathyroid hormone^related protein. Genes driving the separation between tumor subsets may prove to be important biomarkers for bladder cancer development and progression and eventually candidates for therapeutic targeting.

Asexual development in Toxoplasma gondii is a vital aspect of the parasite's life cycle, allowing transmission and avoidance of the host immune response. Differentiation of rapidly dividing tachyzoites into slowly growing, encysted bradyzoites involves significant changes in both physiology and morphology. We generated microarrays of ϳ4,400 Toxoplasma cDNAs, representing a minimum of ϳ600 genes (based on partial sequencing), and used these microarrays to study changes in transcript levels during tachyzoite-to-bradyzoite differentiation. This approach has allowed us to (i) determine expression profiles of previously described developmentally regulated genes, (ii) identify novel developmentally regulated genes, and (iii) identify distinct classes of genes based on the timing and magnitude of changes in transcript levels. Whereas microarray analysis typically involves comparisons of mRNA levels at different time points, we have developed a method to measure relative transcript abundance between genes at a given time point. This method was used to determine transcript levels in parasites prior to differentiation and to further classify bradyzoite-induced genes, thus allowing a more comprehensive view of changes in gene expression than is provided by standard expression profiles. Newly identified developmentally regulated genes include putative surface proteins (a SAG1-related protein, SRS9, and a mucin-domain containing protein), regulatory and metabolic enzymes (methionine aminopeptidase, oligopeptidase, aminotransferase, and glucose-6-phosphate dehydrogenase homologues), and a subset of genes encoding secretory organelle proteins (MIC1, ROP1, ROP2, ROP4, GRA1, GRA5, and GRA8). This analysis permits the first in-depth look at changes in gene expression during development of this complex protozoan parasite.Toxoplasma gondii is a ubiquitous protozoan parasite able to infect a broad range of warm-blooded animals, including humans (12,21). This parasite is a member of the Apicomplexa family, which includes the causative agents of malaria (Plasmodium spp.) and chicken coccidiosis (Eimeria spp.). Toxoplasma is distributed worldwide, with human infection rates ranging from 15 to 85% depending on the country. The prevalence of this parasite is due to its effective means of dissemination and ability to resist immune system clearance. Both properties depend on the complex developmental biology of this single-celled eukaryote. For example, one form of dissemination is through the sexual cycle, which occurs only in felines.

Summary Developmental switching in Toxoplasma gondii, from the virulent tachyzoite to the relatively quiescent bradyzoite stage, is responsible for disease propagation and reactivation. We have generated tachyzoite to bradyzoite differentiation (Tbd−) mutants in T. gondii and used these in combination with a cDNA microarray to identify developmental pathways in bradyzoite formation. Four independently generated Tbd− mutants were analysed and had defects in bradyzoite development in response to multiple bradyzoite‐inducing conditions, a stable phenotype after in vivo passages and a markedly reduced brain cyst burden in a murine model of chronic infection. Transcriptional profiles of mutant and wild‐type parasites, growing under bradyzoite conditions, revealed a hierarchy of developmentally regulated genes, including many bradyzoite‐induced genes whose transcripts were reduced in all mutants. A set of non‐developmentally regulated genes whose transcripts were less abundant in Tbd− mutants were also identified. These may represent genes that mediate downstream effects and/or whose expression is dependent on the same transcription factors as the bradyzoite‐induced set. Using these data, we have generated a model of transcription regulation during bradyzoite development in T. gondii. Our approach shows the utility of this system as a model to study developmental biology in single‐celled eukaryotes including protozoa and fungi.

Purpose: Bladder carcinogenesis is believed to follow alternative pathways of disease progression driven by an accumulation of genetic alterations. The purpose of this study was to evaluate associations between measures of genomic instability and bladder cancer clinical phenotype. Experimental Design: Genome-wide copy number profiles were obtained for 98 bladder tumors of diverse stages (29 pT a , 14 pT 1 , 55 pT 2-4 ) and grades (21 low-grade and 8 high-grade superficial tumors) by array-based comparative genomic hybridization (CGH). Each array contained 2,464 bacterial artificial chromosome and P1 clones, providing an average resolution of 1.5 Mb across the genome. A total of 54 muscle-invasive cases had follow-up information available. Overall outcome analysis was done for patients with muscle-invasive tumors having ''good'' (alive >2 years) versus ''bad'' (dead in <2 years) prognosis.Results: Array CGH analysis showed significant increases in copy number alterations and genomic instability with increasing stage and with outcome. The fraction of genome altered (FGA) was significantly different between tumors of different stages (pT a versus pT 1 , P = 0.0003; pT a versus pT 2-4 , P = 0.02; and pT 1 versus pT 2-4 , P = 0.03). Individual clones that differed significantly between different tumor stages were identified after adjustment for multiple comparisons (false discovery rate < 0.05). For muscle-invasive tumors, the FGA was associated with patient outcome (bad versus good prognosis patients, P = 0.002) and was identified as the only independent predictor of overall outcome based on a multivariate Cox proportional hazards method. Unsupervised hierarchical clustering separated ''good'' and ''bad'' prognosis muscle-invasive tumors into clusters that showed significant association with FGA and survival (Kaplan-Meier, P = 0.019). Supervised tumor classification (prediction analysis for microarrays) had a 71% classification success rate based on 102 unique clones. Conclusions: Array-based CGH identified quantitative and qualitative differences in DNA copy number alterations at high resolution according to tumor stage and grade. Fraction genome altered was associated with worse outcome in muscle-invasive tumors, independent of other clinicopathologic parameters. Measures of genomic instability add independent power to outcome prediction of bladder tumors.

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