Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human imatinib-sensitive and imatinib-resistant cells compared in the absence of imatinib

ABSTRACT: Both imatinib-sensitive and imatinib-resistant cells were compared in the absence of imatinib. The resistant cells in the presence of imatinib were compared to the sample in the absence of imatinib. The sample from the resistant cells in the presence of imatinib was labelled in duplicate to assess false-positive rates.

ORGANISM(S): Homo sapiens

DISEASE(S): Imatinib-resistant CML cell line subclone

SUBMITTER: Michael Deininger

PROVIDER: E-MEXP-21 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Comparative gene expression profile of chronic myeloid leukemia cells innately resistant to imatinib mesylate.

Tipping Alex J AJ Deininger Michael W MW Goldman John M JM Melo Junia V JV

Experimental hematology 20031101 11

<h4>Objective</h4>Resistance to imatinib mesylate monotherapy is clearly a barrier to successful treatment of chronic myeloid leukemia (CML) patients. In some patients, resistance arises due to powerful selective pressure on rare cells that carry amplified copies of the BCR-ABL fusion oncogene or point mutations in the Bcr-Abl tyrosine kinase domain that affect binding of the drug to the oncoprotein. However, in a proportion of patients neither mechanism operates, and resistance appears to be a ...[more]

PMID: 14585372

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Project description:Our objective is to decipher a miRNA expression signature associated with Chronic myeloid leukemia (CML), with or without Imatinib or Dasatinib and compared to normal blood leukocytes, and to determine potential target genes and signaling pathways affected by these signature miRNAs. Background/Aims: MicroRNAs (miRNAs) are short non-coding regulatory RNAs that control gene expression and play an important role in cancer development and progression. However, little is known about the role of miRNAs in chronic myeloid leukemia (CML). Our objective is to decipher a miRNA expression signature associated with CML and to determine potential target genes and signaling pathways affected by these signature miRNAs. Results: Using miRNA microarrays we characterized the miRNAs expression profile of K562 cells in reference to healthy blood. We also looked into the expression profile of K562 cells treated with imatinib or dasatinib. We identified a miRNA signature that distinguishes K562 cells from healthy blood that included downregulation of miRNAs such as miR-31, miR-34a, miR-143, miR-145, miR-155, miR-196b and miR-564 and upregulation of miR-128. We also identified a miRNA signature that distinguishes untreated K562 cells from the treated ones that included downregulation of miRNAs such as miR-128 and upregulation of miR-564. Results: Using miRNA microarrays we characterized the miRNAs expression profile of K562 cells in reference to healthy blood. We also looked into the expression profile of K562 cells treated with imatinib or dasatinib. We identified a miRNA signature that distinguishes K562 cells from healthy blood that included downregulation of miRNAs such as miR-31, miR-34a, miR-143, miR-145, miR-155, miR-196b and miR-564 and upregulation of miR-128. We also identified a miRNA signature that distinguishes untreated K562 cells from the treated ones that included downregulation of miRNAs such as miR-128 and upregulation of miR-564. We next analyzed predicted targets and affected pathways of the deregulated miRNAs. Reassuringly, the analysis identified CML as the main disease associated with these miRNAs. MAPK, TGF-beta and Wnt were the main molecular pathways related with these expression patterns. Utilizing Venn diagrams we found appreciable overlap between the CML-related miRNAs and the MAPK and TGF-beta signaling pathways and focal adhesion-related miRNAs. Conclusions: The miRNAs identified in this study might offer a pivotal role in CML. Nevertheless, while these data point to a central disease, the precise molecular pathway/s targeted by these miRNAs is variable implying a high level of complexity of miRNA target selection and regulation. These deregulated miRNAs highlight new candidate gene targets allowing for a better understanding of the molecular mechanism underlying the development of CML, and propose possible new avenues for therapeutic treatment. MiRNA profiling of CML: With the objective of deciphering a potential miRNA expression signature associated with CML, we analyzed the miRNAs expression profile of K562 in reference to a pool of 3 healthy blood samples using an miRNA-based microarray chip assay. In addition, to search for Bcr-Abl-dependent or Src-dependant miRNA expression patterns, K562 cells were treated or not with imatinib or with dasatinib to inhibit Bcr-Abl tyrosine kinase activity or Bcr-Abl and Src tyrosine kinase activity, respectively. In order to validate the microarray data and to ensure that the variability observed among samples was not technical, we carried out Taqman miRNA quantitative real-time PCR analysis (Applied Biosystems, USA) on miRNAs that we find to be most relevant, according to bioinformatics analysis (see below) and published data.

Dataset Information

Transcription profiling of human imatinib-sensitive and imatinib-resistant cells compared in the absence of imatinib

Publications

Comparative gene expression profile of chronic myeloid leukemia cells innately resistant to imatinib mesylate.

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