Dataset Information

MicroRNA signatures in B-cell lymphomas.

ABSTRACT: Accurate lymphoma diagnosis, prognosis and therapy still require additional markers. We explore the potential relevance of microRNA (miRNA) expression in a large series that included all major B-cell non-Hodgkin lymphoma (NHL) types. The data generated were also used to identify miRNAs differentially expressed in Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) samples. A series of 147 NHL samples and 15 controls were hybridized on a human miRNA one-color platform containing probes for 470 human miRNAs. Each lymphoma type was compared against the entire set of NHLs. BL was also directly compared with DLBCL, and 43 preselected miRNAs were analyzed in a new series of routinely processed samples of 28 BLs and 43 DLBCLs using quantitative reverse transcription-polymerase chain reaction. A signature of 128 miRNAs enabled the characterization of lymphoma neoplasms, reflecting the lymphoma type, cell of origin and/or discrete oncogene alterations. Comparative analysis of BL and DLBCL yielded 19 differentially expressed miRNAs, which were confirmed in a second confirmation series of 71 paraffin-embedded samples. The set of differentially expressed miRNAs found here expands the range of potential diagnostic markers for lymphoma diagnosis, especially when differential diagnosis of BL and DLBCL is required.

SUBMITTER: Di Lisio L

PROVIDER: S-EPMC3288280 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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MicroRNA signatures in B-cell lymphomas.

Di Lisio L L Sánchez-Beato M M Gómez-López G G Rodríguez M E ME Montes-Moreno S S Mollejo M M Menárguez J J Martínez M A MA Alves F J FJ Pisano D G DG Piris M A MA Martínez N N

Blood cancer journal 20120217 2

Accurate lymphoma diagnosis, prognosis and therapy still require additional markers. We explore the potential relevance of microRNA (miRNA) expression in a large series that included all major B-cell non-Hodgkin lymphoma (NHL) types. The data generated were also used to identify miRNAs differentially expressed in Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) samples. A series of 147 NHL samples and 15 controls were hybridized on a human miRNA one-color platform containing probe ...[more]

PMID: 22829247

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Project description:BackgroundThe diagnosis of T-cell lymphomas is typically established through a multiparameter approach that combines clinical, morphologic, immunophenotypic, and genetic features, utilizing a variety of histopathologic and molecular techniques. However, accurate diagnosis of such lymphomas and distinguishing them from reactive lymph nodes remains challenging due to their low prevalence and heterogeneous features, hence limiting the confidence of pathologists. We investigated the use of microRNA (miRNA) expression signatures as an adjunctive tool in the diagnosis and classification of T-cell lymphomas that involve lymph nodes. This study seeks to distinguish reactive lymph nodes (RLN) from two types of frequently occurring nodal T-cell lymphomas: nodal T-follicular helper (TFH) cell lymphomas (nTFHL) and peripheral T-cell lymphomas, not otherwise specified (nPTCL).MethodsFrom the formalin-fixed paraffin-embedded (FFPE) samples from a cohort of 88 subjects, 246 miRNAs were quantified and analyzed by differential expression. Two-class logistic regression and random forest plot models were built to distinguish RLN from the nodal T-cell lymphomas. Gene set enrichment analysis was performed on the target genes of the miRNA to identify pathways and transcription factors that may be regulated by the differentially expressed miRNAs in each subtype.ResultsUsing logistic regression analysis, we identified miRNA signatures that can distinguish RLN from nodal T-cell lymphomas (AUC of 0.92 ± 0.05), from nTFHL (AUC of 0.94 ± 0.05) and from nPTCL (AUC of 0.94 ± 0.08). Random forest plot modelling was also capable of distinguishing between RLN and nodal T-cell lymphomas, but performed worse than logistic regression. However, the miRNA signatures are not able to discriminate between nTFHL and nPTCL, owing to large similarity in miRNA expression patterns. Bioinformatic analysis of the gene targets of unique miRNA expression revealed the enrichment of both known and potentially understudied signalling pathways and genes in such lymphomas.ConclusionThis study suggests that miRNA biomarkers may serve as a promising, cost-effective tool to aid the diagnosis of nodal T-cell lymphomas, which can be challenging. Bioinformatic analysis of differentially expressed miRNAs revealed both relevant or understudied signalling pathways that may contribute to the progression and development of each T-cell lymphoma entity. This may help us gain further insight into the biology of T-cell lymphomagenesis.

Dataset Information

MicroRNA signatures in B-cell lymphomas.

Publications

MicroRNA signatures in B-cell lymphomas.

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