Reference : Long noncoding RNA expression in lymphoma
Scientific congresses and symposiums : Poster
Human health sciences : Multidisciplinary, general & others
http://hdl.handle.net/2268/218634
Long noncoding RNA expression in lymphoma
English
O'Grady, Tina mailto [Université de Liège - ULiège > Département des sciences de la vie > Génétique et biologie moléculaires animales >]
Flemington, Erik K. []
2013
Yes
International
Noncoding RNAs in Development and Cancer Keystone Symposium
January 20-25, 2013
[en] Diffuse large B cell lymphoma (DLBCL), the most common non-Hodgkin’s lymphoma, is an aggressive lymphoma that affects patients worldwide. Although it is curable in some cases, many patients remain refractory to treatment and a better understanding of disease mechanisms could lead to improved therapies. Using expression data from protein-coding genes DLBCL can be classified into the activated B cell (ABC) and germinal centre B cell (GCB) subtypes (1), which are predictive of different outcomes (2). However, many tumours remain unclassifiable with this data. Furthermore, DLBCL can be difficult to distinguish from the more easily treatable Burkitt’s Lymphoma (BL) using histology and even protein-coding gene expression (3). The proliferation of publicly available datasets and lncRNA annotation offers the opportunity to re-examine this clinically important problem. We are using RNA-Seq datasets from DLBCL and BL available from the NCBI’s Sequence Read Archive (4, 5) in conjunction with the transcript assembler Cufflinks and noncoding RNA catalogs from the ENCODE project and John Rinn’s laboratory (6) to detect and quantify novel and known long noncoding transcripts in these tumours. Using hierarchical clustering and differential expression analysis we are characterizing lncRNA expression profiles in both established and lncRNA-defined subtypes.
In addition, both DLBCL and BL are known in some cases to be driven by Epstein-Barr Virus (EBV), a factor that is potentially confounding to attempts to classify tumours and characterize pathways. Using the RNA Comprehensive Multi-Processor Analysis System for Sequencing (RNA CoMPASS) developed in our laboratory (7), we are able to sensitively detect and quantify EBV RNA expression in RNA-Seq datasets. LncRNA expression in different tumours can then be analyzed in this context, and
http://hdl.handle.net/2268/218634

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