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Copy number abnormality, MYC activity and the genetic fingerprint of normal B-cells and the microRNA profile of DLBCL-77

ABSTRACT: A better understanding of the pathogenesis of diffuse large B-cell lymphoma (DLBCL) has clarified its relationship to normal B-cells, pointed to distinct mechanisms of cell transformation, and facilitated the design of novel treatments. However, these data derive from mRNA genes studies, whereas genome-wide integrative investigations of the role of microRNAs (miRNAs) in DLBCL are still unavailable. We used array-CGH and microarray-based expression analyses to map the abnormalities targeting miRNAs in DLBCLs (n=86). Using training and validation DLBCL cohorts, we defined a collection of miRNAs that robustly segregates these tumors in three unique subsets. This miRNA-driven substructure appears to influence disease outcome, is independent of other mRNA-based DLBCL classifications, and stems from copy number changes targeting the miRNA genome, MYC activity, and the miRNA fingerprints of mature normal B-cells. Our data have uncovered clinically relevant additional molecular complexity in DLBCL and have established a blueprint for the detailed characterizations of miRNAs that are pertinent to B-cell lymphoma biology.

ORGANISM(S): Homo sapiens

PROVIDER: GSE15177 | GEO | 2009/03/16

SECONDARY ACCESSION(S): PRJNA123131

REPOSITORIES: GEO

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Project description:A better understanding of the pathogenesis of diffuse large B-cell lymphoma (DLBCL) has clarified its relationship to normal B-cells, pointed to distinct mechanisms of cell transformation, and facilitated the design of novel treatments. However, these data derive from mRNA genes studies, whereas genome-wide integrative investigations of the role of microRNAs (miRNAs) in DLBCL are still unavailable. We used array-CGH and microarray-based expression analyses to map the abnormalities targeting miRNAs in DLBCLs (n=86). Using training and validation DLBCL cohorts, we defined a collection of miRNAs that robustly segregates these tumors in three unique subsets. This miRNA-driven substructure appears to influence disease outcome, is independent of other mRNA-based DLBCL classifications, and stems from copy number changes targeting the miRNA genome, MYC activity, and the miRNA fingerprints of mature normal B-cells. Our data have uncovered clinically relevant additional molecular complexity in DLBCL and have established a blueprint for the detailed characterizations of miRNAs that are pertinent to B-cell lymphoma biology. Fifty-nine primary DLBCL samples obtained from our Cancer Center tumor bank and 27 cell lines (26 DLBCL and 1 mediastinal B-cell lymphoma) were included in this study for copy number analysis. The clinical and pathological features of this collection are described in the paper. All tumors were reviewed for diagnostic accuracy by a hematopathologist (R.R.) and the categorization in germinal center B-cell-like (GCB) or non-germinal center B-cell-like (non-GCB) was performed according to the algorithm described by Hans et al. The extent of normal cells infiltration in the DLBCL was determined by semi-quantitative measurement of CD3 (T-cells) and CD68 (macrophages) staining. Four normal control hybridizations are also included. Even though we started off with 90 samples total, we inspected the sample quality visually according the log2 ratio curves and excluded 13 samples with noisy or very low signals throughout the genome. The 77 remaining samples were used in the following analyses.

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Copy number abnormality, MYC activity and the genetic fingerprint of normal B-cells and the microRNA profile of DLBCL-77

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