Molecular classification of tumour cells in a patient with intravascular large B-cell lymphoma
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ABSTRACT:
PROVIDER: PRJNA418304 | ENA |
REPOSITORIES: ENA
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Project description:Intravascular large B-cell lymphoma (IVLBCL) is a rare type of extranodal LBCL. It is characterized by the proliferation of tumour cells exclusively intraluminally in small blood vessels of different organs. We used microarray-based analysis of gene expression of tumour cells isolated from a patient with primary manifestation of the lymphoma in the skin and compared it with various other diffuse LBCLs (DLBCLs) as well as a previously published DLBCL classifier.
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Project description:Intravascular large B-cell lymphoma (IVLBCL) is a unique form of diffuse large B-cell lymphoma (DLBCL) characterized by extranodal cell growth especially in small vessels without systemic lymphadenopathy. The limitation in obtaining sufficient tumor materials hampers understanding the molecular pathogenesis of IVLBCL. We performed whole-exome sequencing of IVLBCL using plasma-derived cell-free DNA (cfDNA) and patient-derived xenograft (PDX) samples.
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Project description:Intra-tumour heterogeneity in lymphoid malignancies encompasses selection of genetic events and epigenetic regulation of transcriptional programs. Clonal-related neoplastic cell populations are unsteadily subjected to immune editing and metabolic adaptations within different tissue microenvironments. How tissue-specific mesenchymal cells impact on the diversification of aggressive lymphoma clones is still unknown. We investigated the intra-tumour heterogeneity and the specific mesenchymal modifications that are associated with A20 diffuse large B-cell lymphoma (DLBCL) cells seeding of different tissue microenvironments. We found that the tissue microenvironment casts a relevant influence over A20 transcriptional landscape also impacting on Myc and DNA damage response programs. Extending the investigation to mice deficient for the matricellular protein SPARC, a stromal prognostic factor in human DLBCL, we demonstrated a different immune imprint on A20 cells according to stromal Sparc proficiency.
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Project description:Gene expression profiling and array CGH analysis for intravascular large B-cell lymphoma (IVLBCL)
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Project description:Correct classification of cancer patients into subtypes is a prerequisite for acute diagnosis and effective treatment. Currently this classification relies mainly on histological assessment, but gene expression analysis bymicroarrays has shown great promise. Here we show that high accuracy, quantitative proteomics can robustly segregate cancer subtypes directly at the level of expressed proteins. We investigated two histologically indistinguishable subtypes of diffuse large B-cell lymphoma (DLBCL): activated Bcell- like (ABC) and germinal-center B-cell-like (GCB) subtypes, by first developing a general lymphoma stable isotope labeling with amino acids in cell culture (SILAC) mix from heavy stable isotope-labeled cell lines. This super- SILAC mix was combined with cell lysates from five ABCDLBCL and five GCB-DLBCL cell lines. Shotgun proteomic analysis on a linear ion trap Orbitrap mass spectrometer with high mass accuracy at the MS and MS/MS levels yielded a proteome of more than 7,500 identified proteins. High accuracy of quantification allowed robust separation of subtypes by principal component analysis. The main contributors to the classification included proteins known to be differentially expressed between the subtypes such as the transcription factors IRF4 and SPI1/ PU.1, cell surface markers CD44 and CD27, as well as novel candidates. We extracted a signature of 55 proteins that segregated subtypes and contained proteins connected to functional differences between the ABC and GCB-DLBCL subtypes, including many NF-kappa B-regulated genes. Shortening the analysis time to single-shot analysis combined with use of the new linear quadrupole Orbitrap analyzer (Q Exactive) also clearly differentiated between the subtypes. These results show that high resolution shotgun proteomics combined with super-SILAC-based quantification is a promising new technology for tumor characterization and classification.
2015-04-24 | PXD002098 | Pride
Project description:Correct classification of cancer patients into subtypes is a prerequisite for acute diagnosis and effective treatment. Currently this classification relies mainly on histological assessment, but gene expression analysis bymicroarrays has shown great promise. Here we show that high accuracy, quantitative proteomics can robustly segregate cancer subtypes directly at the level of expressed proteins. We investigated two histologically indistinguishable subtypes of diffuse large B-cell lymphoma (DLBCL): activated Bcell- like (ABC) and germinal-center B-cell-like (GCB) subtypes, by first developing a general lymphoma stable isotope labeling with amino acids in cell culture (SILAC) mix from heavy stable isotope-labeled cell lines. This super- SILAC mix was combined with cell lysates from five ABCDLBCL and five GCB-DLBCL cell lines. Shotgun proteomic analysis on a linear ion trap Orbitrap mass spectrometer with high mass accuracy at the MS and MS/MS levels yielded a proteome of more than 7,500 identified proteins. High accuracy of quantification allowed robust separation of subtypes by principal component analysis. The main contributors to the classification included proteins known to be differentially expressed between the subtypes such as the transcription factors IRF4 and SPI1/ PU.1, cell surface markers CD44 and CD27, as well as novel candidates. We extracted a signature of 55 proteins that segregated subtypes and contained proteins connected to functional differences between the ABC and GCB-DLBCL subtypes, including many NF-kappa B-regulated genes. Shortening the analysis time to single-shot analysis combined with use of the new linear quadrupole Orbitrap analyzer (Q Exactive) also clearly differentiated between the subtypes. These results show that high resolution shotgun proteomics combined with super-SILAC-based quantification is a promising new technology for tumor characterization and classification.
2016-03-10 | MSV000079572 | MassIVE
Project description:IVLBCL is a rare distinct disease entity of extranodal large B-cell lymphoma . The disease is characterized by selective growth of tumor cells in the lumina of small vessels and by the absence of remarkable lymphadenopathy. We have developed patient derived xenograft IVLBCL mouse models from primary patient bone marrow samples. This dataset includes the array CGH analysis of IVLBCL tumor cells from the mouse xenograft models.
2016-08-13 | GSE72027 | GEO
Project description:IVLBCL is a rare distinct disease entity of extranodal large B-cell lymphoma. The disease is characterized by selective growth of tumor cells in the lumina of small vessels and by the absence of remarkable lymphoadenopathy. We have developed patient derived xenograft IVLBCL mouse models from primary bone marrow samples. This dataset includes the gene expression profiling of IVLBCL tumor cells from the mouse xenograft models.
2016-08-13 | GSE72026 | GEO