Dataset Information

Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.

ABSTRACT: BACKGROUND: An estimated 12% of females in the United States will develop breast cancer in their lifetime. Although, there are advances in treatment options including surgery and chemotherapy, breast cancer is still the second most lethal cancer in women. Thus, there is a clear need for better methods to predict prognosis for each breast cancer patient. With the advent of large genetic databases and the reduction in cost for the experiments, researchers are faced with choosing from a large pool of potential prognostic markers from numerous breast cancer gene expression profile studies. METHODS: Five microarray datasets related to breast cancer were examined using gene set analysis and the cancers were categorized into different subtypes using a scoring system based on genetic pathway activity. RESULTS: We have observed that significant genes in the individual studies show little reproducibility across the datasets. From our comparative analysis, using gene pathways with clinical variables is more reliable across studies and shows promise in assessing a patient's prognosis. CONCLUSIONS: This study concludes that, in light of clinical variables, there are significant gene pathways in common across the datasets. Specifically, several pathways can further significantly stratify patients for survival. These candidate pathways should help to develop a panel of significant biomarkers for the prognosis of breast cancer patients in a clinical setting.

SUBMITTER: Miecznikowski JC

PROVIDER: S-EPMC2972286 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.

Miecznikowski Jeffrey C JC Wang Dan D Liu Song S Sucheston Lara L Gold David D

BMC cancer 20101021

<h4>Background</h4>An estimated 12% of females in the United States will develop breast cancer in their lifetime. Although, there are advances in treatment options including surgery and chemotherapy, breast cancer is still the second most lethal cancer in women. Thus, there is a clear need for better methods to predict prognosis for each breast cancer patient. With the advent of large genetic databases and the reduction in cost for the experiments, researchers are faced with choosing from a larg ...[more]

PMID: 20964848

Similar Datasets

Project description:Using array comparative genomic hybridization (aCGH), a large number of deleted genomic regions have been identified in human cancers. However, subsequent efforts to identify target genes selected for inactivation in these regions have often been challenging. We integrated here genome-wide copy number data with gene expression data and non-sense mediated mRNA decay rates in breast cancer cell lines to prioritize gene candidates that are likely to be tumour suppressor genes inactivated by bi-allelic genetic events. The candidates were sequenced to identify potential mutations. This integrated genomic approach led to the identification of RIC8A at 11p15 as a putative candidate target gene for the genomic deletion in the ZR-75-1 breast cancer cell line. We identified a truncating mutation in this cell line, leading to loss of expression and rapid decay of the transcript. We screened 127 breast cancers for RIC8A mutations, but did not find any pathogenic mutations. No promoter hypermethylation in these tumours was detected either. However, analysis of gene expression data from breast tumours identified a small group of aggressive tumours that displayed low levels of RIC8A transcripts. Real-time PCR analysis of 38 breast tumours showed a strong association between low RIC8A expression and the presence of TP53 mutations (P=0.006). We demonstrate a data integration strategy leading to the identification of RIC8A as a gene undergoing a classical double-hit genetic inactivation in a breast cancer cell line, as well as in vivo evidence of loss of RIC8A expression in a subgroup of aggressive TP53 mutant breast cancers. Gene expression data: Samples GSM388181-GSM388198. The experiment utilized six breast cancer cell lines: MDA-MB-468, MDA-MB-231, ZR-75-1, MCF7, BT-474 and T-47D, and three non-malignant cell lines: HMECs (non-malignant human mammary epithelial cells), IMR90 (normal lung fibroblasts) and WS1 (normal skin fibroblasts). All cell lines were obtained from American Type Culture Collection and grown in accordance with the distributor's instructions. Both malignant and non-malignant cell lines were treated with the translation inhibitor emetine dihydrochloride hydrate. For each cell line, parallel cell cultures were grown in 175 cm2 flasks until 70-80 % confluence. Half of the subconfluent cultures were treated with 100 μg ml-1 of emetine dihydrochloride hydrate while the other half were left as untreated controls. Genome-wide copy number data: Samples GSM388211-GSM388216. The experiment utilized six breast cancer cell lines; MDA-MB-468, MDA-MB-231, ZR-75-1, MCF7, BT-474 and T-47D. All cell lines were obtained from American Type Culture Collection and grown in accordance with the distributor's instructions. All samples were hybridized once on 44k Agilent Human Genome CGH microarrays according to manufacturers instructions. Genomic DNA pooled from healthy female donors was used as a reference in all hybridizations. DNA from cell line samples were labeled with Cy5 and DNA from reference were labeled with Cy3.

Project description:BackgroundShigella flexneri inhibits apoptosis in infected epithelial cells. In order to understand the pro-survival effects induced by the bacteria, we utilized apoptosis-specific microarrays to analyze the changes in eukaryotic gene expression in both infected and uninfected cells in the presence and absence of staurosporine, a chemical inducer of the intrinsic pathway of apoptosis. The goal of this research was to identify host factors that contribute to apoptosis inhibition in infected cells.ResultsThe microarray analysis revealed distinct expression profiles in uninfected and infected cells, and these changes were altered in the presence of staurosporine. These profiles allowed us to make comparisons between the treatment groups. Compared to uninfected cells, Shigella-infected epithelial cells, both in the presence and absence of staurosporine, showed significant induced expression of JUN, several members of the inhibitor of apoptosis gene family, nuclear factor kappaB and related genes, genes involving tumor protein 53 and the retinoblastoma protein, and surprisingly, genes important for the inhibition of the extrinsic pathway of apoptosis. We confirmed the microarray results for a selection of genes using in situ hybridization analysis.ConclusionInfection of epithelial cells with S. flexneri induces a pro-survival state in the cell that results in apoptosis inhibition in the presence and absence of staurosporine. The bacteria may target these host factors directly while some induced genes may represent downstream effects due to the presence of the bacteria. Our results indicate that the bacteria block apoptosis at multiple checkpoints along both pathways so that even if a cell fails to prevent apoptosis at an early step, Shigella will block apoptosis at the level of caspase-3. Apoptosis inhibition is most likely vital to the survival of the bacteria in vivo. Future characterization of these host factors is required to fully understand how S. flexneri inhibits apoptosis in epithelial cells.

Dataset Information

Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.

Publications

Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets