Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression profiles in resistant acute lymphoblastic leukemia

ABSTRACT: Treatment resistance as indicated by the presence of high levels of minimal residual disease (MRD) after induction therapy and induction consolidation is associated with a poor prognosis in childhood acute lymphoblastic leukemia (ALL). We hypothesized that treatment resistance is an intrinsic feature of ALL cells, which is reflected in the gene expression pattern, and that resistance to chemotherapy can be predicted prior to treatment. To test these hypotheses, gene expression signatures of ALL samples with a high MRD load (MRD-HR) were compared to those of samples without measurable MRD (MRD-SR) during treatment. We identified 54 genes that clearly distinguished resistant from sensitive ALL samples. Genes low expressed in resistant samples were predominantly associated with cell cycle progression and apoptosis, suggesting that impaired cell proliferation and apoptosis are involved in treatment resistance. Prediction analysis using randomly selected samples as a training set and the remaining samples as a test set revealed an accuracy of 84%. We conclude that resistance to chemotherapy seems at least in part to be an intrinsic feature of ALL cells. As treatment response could be predicted with a high accuracy, gene expression profiling could become a clinically relevant tool for treatment stratification in the early course of childhood ALL. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Keywords: disease_state_design Using regression correlation

ORGANISM(S): Homo sapiens

SUBMITTER: Gunnar Cario

PROVIDER: E-GEOD-4057 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemia.

Cario Gunnar G Stanulla Martin M Fine Bernard M BM Teuffel Oliver O Neuhoff Nils V NV Schrauder André A Flohr Thomas T Schäfer Beat W BW Bartram Claus R CR Welte Karl K Schlegelberger Brigitte B Schrappe Martin M

Blood 20040923 2

Treatment resistance, as indicated by the presence of high levels of minimal residual disease (MRD) after induction therapy and induction consolidation, is associated with a poor prognosis in childhood acute lymphoblastic leukemia (ALL). We hypothesized that treatment resistance is an intrinsic feature of ALL cells reflected in the gene expression pattern and that resistance to chemotherapy can be predicted before treatment. To test these hypotheses, gene expression signatures of ALL samples wit ...[more]

PMID: 15388585

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:The first goal of the study was to find the genes that explain the difference in progression of age-related retinal degeneration (ageRD) between the inbred strains C57BL/6J-c2J (B6a) and BALB/cByJ (C). The specific goal was to find the candidate genes that explain the chromosome 6 and chromosome 10 quantitative trait loci (QTL) found in a previous study. Genes differentially expressed in retina between both strains and that map to the QTL are candidate genes. By integrating different approaches: microarray study, knowledge-based candidate gene search and screening of genetic variants, we found 35 candidate genes for chromosome 6 QTL and 14 candidate genes for chromosome 10 QTL. Five genes for each QTL were selected for sequencing and qPCR analysis. One gene, Tnfaip3 was selected for phenotypic testing and was excluded as the quantitative trait gene for chr10 QTL. The second goal of the study was to find biological processes and pathways associated with ageRD by Gene Ontology analysis of the microarray data. We concentrated on GO terms overrepresented in either strain at 8 months; the age when there is a difference in the phenotype (outer nuclear layer thickness). The GO analysis revealed that transcripts associated with inflammation, mitochondrial envelope, DNA repairing and oxidative stress were increased in the ageRD sensitive C strain with age (8 months). In the ageRD resistant B6a strain transcripts associated with antioxidant response, regulation of blood vessel size and growth factor activity were increased with age. Transcripts associated with cell remodeling and lipid metabolism were increased in either strain with age. This study aims to identify gene expression differences in posterior eyecups between the strains C and B6a at 4 months and at 8 months. Twelve animals were used per strain and time point for a total of 48 mice. Total RNA for 3 animals (6 eyes) were pooled giving a total of 4 biological replicates per strain and time point. The 4-month C samples labeled with Cy5 were hybridized with the 4-month B6a samples labeled with Cy3 (4 biological replicates); the 8-month C samples labeled with Cy5 were hybridized with the 8-month B6a samples labeled with Cy3, for 8 arrays (4 biological replicates). A second set of eight arrays were used to analyzed the same RNA samples but with the dye orientation reversed, yielding a total of 16 arrays in the experiment. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc.

Dataset Information

Gene expression profiles in resistant acute lymphoblastic leukemia

Publications

Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets