Integrated profiling of diffuse large B‐cell lymphoma with 7q gain

To characterize diffuse large B‐cell lymphoma (DLBCL) with chromosome 7 gains, we combined clinical data with genomic, RNA and miRNA profiling. Gains were associated with age >60 years, female gender, a trend for higher complete response rate, lower death rate, and better overall survival in patients treated with R‐CHOP. Lesions were inversely associated with bone marrow involvement and number of extra‐nodal sites. Differentially expressed transcripts were enriched of genes belonging to specific pathways and miRNAs targets. MIR96, MIR182, MIR589, MIR25 were shown significantly up‐regulated in 7q+ DLBCL by real‐time PCR.

[1]  W. Chan,et al.  Diffuse large B‐cell lymphoma with concordant bone marrow involvement has peculiar genomic profile and poor clinical outcome , 2011, Hematological oncology.

[2]  W. Chan,et al.  Genomic lesions associated with a different clinical outcome in diffuse large B‐Cell lymphoma treated with R‐CHOP‐21 , 2010, British journal of haematology.

[3]  J. Cigudosa,et al.  Mantle cell lymphoma: transcriptional regulation by microRNAs , 2010, Leukemia.

[4]  Lara J. Monteiro,et al.  Definition of microRNAs that repress expression of the tumor suppressor gene FOXO1 in endometrial cancer. , 2009, Cancer research.

[5]  H. Tagawa,et al.  The potential of copy number gains and losses, detected by array-based comparative genomic hybridization, for computational differential diagnosis of B-cell lymphomas and genetic regions involved in lymphomagenesis , 2009, Haematologica.

[6]  L. Staudt,et al.  Molecular subtypes of diffuse large B-cell lymphoma arise by distinct genetic pathways , 2008, Proceedings of the National Academy of Sciences.

[7]  A. Ng,et al.  Diffuse large B-cell lymphoma. , 2007, Seminars in radiation oncology.

[8]  F. Nielsen,et al.  Prognostic significance of metallothionein in B-cell lymphomas. , 2006, Blood.

[9]  L. Staudt,et al.  Diffuse large B-cell lymphoma subgroups have distinct genetic profiles that influence tumor biology and improve gene-expression-based survival prediction. , 2005, Blood.

[10]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[11]  H. Tagawa,et al.  Comparison of genome profiles for identification of distinct subgroups of diffuse large B-cell lymphoma. , 2005, Blood.

[12]  Mattias Höglund,et al.  Identification of cytogenetic subgroups and karyotypic pathways of clonal evolution in follicular lymphomas , 2004, Genes, chromosomes & cancer.

[13]  Ash A. Alizadeh,et al.  Transformation of follicular lymphoma to diffuse large cell lymphoma is associated with a heterogeneous set of DNA copy number and gene expression alterations. , 2003, Blood.

[14]  David Botstein,et al.  Transformation of follicular lymphoma to diffuse large-cell lymphoma: Alternative patterns with increased or decreased expression of c-myc and its regulated genes , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[15]  L. Staudt,et al.  Mechanisms of Disease , 2010 .

[16]  Todd,et al.  Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.