Biomedical subjects

Ekaterini Blaveri

Publications and source records attributed to Ekaterini Blaveri.

3 recordsLinked to original sources

PubMed2005

Bladder cancer stage and outcome by array-based comparative genomic hybridization.

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 pT1, 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 pT1, P = 0.0003; pT(a) versus pT(2-4), P = 0.02; and pT1 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.

Chromosome Mapping↗

PubMed2005

Bladder cancer outcome and subtype classification by gene expression.

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.

Aged↗

PubMed2004

Analysis of gene expression in cancer cell lines identifies candidate markers for pancreatic tumorigenesis and metastasis.

Pancreatic cancer is a highly aggressive type of malignancy and the prognosis for disease presenting typically at a late stage is extremely poor. A comprehensive understanding of its molecular genetics is required in order to develop new approaches to clinical management. To date, serial analysis of gene expression and more recently oligo/cDNA microarray technologies have been employed in order to identify genes involved in pancreatic neoplasia that can be developed as diagnostic markers and drug targets for this dismal disease. This study describes the expression profile obtained from 20 pancreatic cell lines using cDNA microarrays containing 9,932 human gene elements. Numerous genes were identified as being differentially expressed, some of which have been previously implicated in pancreatic adenocarcinoma (S100P, S100A4, prostate stem cell antigen, lipocalin 2, claudins 3 and 4, trefoil factors 1 and 2) as well as several novel genes. The differentially expressed genes identified are involved in a variety of cellular functions, including control of transcription, regulation of the cell cycle, proteolysis, cell adhesion and signaling. Validation of our array results was performed by exploring the SAGEmap database and by immunohistochemistry for a selection of 4 genes that have not previously been studied in pancreatic cancer: anterior gradient 2 homologue (Xenopus laevis), insulin-like growth factor binding protein 3 and 4 and Forkhead box J1. Immunostaining was performed using pancreas-specific tissue microarrays containing core biopsies from 305 clinical specimens. In addition, using statistical group comparison and hierarchical clustering, a selection of genes was identified that may be linked to the site of metastasis from which these cell lines were isolated.

Biomarkers, Tumor↗