Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Large scale screening for known fusion genes in cancer cell lines

ABSTRACT: We have utilized a version 2.0 of our Fusion gene microarray (version 1.0 described by PMID: 19152679 and GEO, GPL8078) to screen cancer cell lines for known fusion genes We assembled a comprehensive database of published fusion genes, including those which have been reported only in individual studies and samples, and fusion genes resulting from deep sequencing of cancer genomes and transcriptomes. From the total set of 548 fusion genes, we designed 197,846 unique oligonucleotides, targeting both chimeric transcript junctions as well as sequences internal to each of the fusion gene partners. We investigated the presence of fusion genes in a series of 67 cell lines originating from 15 different cancer types. Data from ten leukaemia cell lines with known fusion gene status were used to evaluate and calibrate an automated scoring algorithm. In five out of ten cell lines the correct fusion gene was the top most scoring hit, and one came second, all six passing a cut-off of 50 percent of theoretical maximum-score. Two additional fusion genes, BCAS4-BCAS3 from the MCF-7 breast cancer cell line and CCDC6-RET from the TPC-1 thyroid cancer cell line were validated as true positive fusion transcripts from the remaining 57 cell lines. A total of 67 cell lines from various cancer types were analysed for presence of known fusion genes

ORGANISM(S): Homo sapiens

SUBMITTER: Gard Thomassen

PROVIDER: E-GEOD-24737 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Fusion gene microarray reveals cancer type-specificity among fusion genes.

Løvf Marthe M Thomassen Gard O S GO Bakken Anne Cathrine AC Celestino Ricardo R Fioretos Thoas T Lind Guro E GE Lothe Ragnhild A RA Skotheim Rolf I RI

Genes, chromosomes & cancer 20110208 5

Detection of fusion genes for diagnostic purposes and as a guide to treatment is well-established in hematological malignancies, and the prevalence of fusion genes in epithelial cancers is also increasingly appreciated. To study whether established fusion genes are present within additional cancer types, we have used an updated version of our fusion gene microarray in a systematic survey of reported fusion genes in multiple cancer types. We assembled a comprehensive database of published fusion ...[more]

PMID: 21305644

Similar Datasets

Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.

Project description:This is the experiment set used for a paper written in collaboration with Hopkins. It compares genes that are differentially expressed between normal pancreas, pancreatic cell lines and pancreatic adenocarcinoma. Pancreatic cancer is the fifth leading cause of cancer death in the United States. We used cDNA microarrays to analyze global gene expression patterns in 14 pancreatic cancer cell lines, 17 resected infiltrating pancreatic cancer tissues, and 5 samples of normal pancreas to identify genes that are differentially expressed in pancreatic cancer. We found more than 400 cDNAs corresponding to genes that were differentially expressed in the pancreatic cancer tissues and cell lines as compared to normal pancreas. These genes that tended to be expressed at higher levels in pancreatic cancers were associated with a variety of processes, including cell-cell and cell-matrix interactions, cytoskeletal remodeling, proteolytic activity, and Ca(++) homeostasis. Two prominent clusters of genes were related to the high rates of cellular proliferation in pancreatic cancer cell lines and the host desmoplastic response in the resected pancreatic cancer tissues. Of 149 genes identified as more highly expressed in the pancreatic cancers compared with normal pancreas, 103 genes have not been previously reported in association with pancreatic cancer. The expression patterns of 14 of these highly expressed genes were validated by either immunohistochemistry or reverse transcriptase-polymerase chain reaction as being expressed in pancreatic cancer. The overexpression of one gene in particular, 14-3-3 sigma, was found to be associated with aberrant hypomethylation in the majority of pancreatic cancers analyzed. The genes and expressed sequence tags presented in this study provide clues to the pathobiology of pancreatic cancer and implicate a large number of potentially new molecular markers for the detection and treatment of pancreatic cancer. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Using regression correlation

Dataset Information

Large scale screening for known fusion genes in cancer cell lines

Publications

Fusion gene microarray reveals cancer type-specificity among fusion genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure