Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Finding new Chimeric RNAs in RNA-seq data, a test study in Acute Myeloid Leukemia patient cells

ABSTRACT: In this strudy, we seek out new chimeric RNA in RNA-seq data from acute myeloid leukemia (AML) patient cells as new biomarkers to improve diagnosis and prognosis in cancer. Total RNA were extracted from bone marrow or peripheral blood mononuclear cells in three AML patients. polyA+ cDNAs were sequenced to generate stranded paired-end reads. RNA-seq analyses were performed using Crac and CracTools software. In particular using these tools, we classified chimeric RNA in four classes, finding new chimeric RNAs. By analysis a larger cohort by qPCR, we were able to define new chimeric RNA as new biomarkers in AML patients.

INSTRUMENT(S): Illumina protocol, Illumina HiSeq 2000

ORGANISM(S): Homo sapiens

SUBMITTER: Anthony Boureux

PROVIDER: E-MTAB-5767 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

New chimeric RNAs in acute myeloid leukemia.

Rufflé Florence F Audoux Jerome J Boureux Anthony A Beaumeunier Sacha S Gaillard Jean-Baptiste JB Bou Samra Elias E Megarbane Andre A Cassinat Bruno B Chomienne Christine C Alves Ronnie R Riquier Sebastien S Gilbert Nicolas N Lemaitre Jean-Marc JM Bacq-Daian Delphine D Bougé Anne Laure AL Philippe Nicolas N Commes Therese T

F1000Research 20170802

<b>Background:</b> High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric ...[more]

PMID: 29623188

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Project description:Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARalpha], t(8;21)[AML1-ETO], inv(16) [CBFbeta-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation. All the gene expression arrays are available through http://www.stjuderesearch.org/site/data/AML1/ in the original study (PMID:15226186). To study the RAS gene expression in the human AML patients, a total of 104 AML cases with known KRAS and NRAS status (including 72 gene expression arrays in the original study and 32 additional arrays acquired later on), as well as 4 CD34+ normal bone marrow cases deposited in GEO GSE33315, were including in this depository. Gene expression profiling was performed on 104 single diagnosis tumor samples and 4 CD34+ normal bone marrow samples

Dataset Information

Finding new Chimeric RNAs in RNA-seq data, a test study in Acute Myeloid Leukemia patient cells

Publications

New chimeric RNAs in acute myeloid leukemia.

Similar Datasets

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