Project description:Primary bone diffuse large B-cell lymphoma (PB-DLBCL) is a rare extranodal lymphoma subtype. This retrospective study elucidates the currently unknown genetic background of a large clinically well-annotated cohort of DLBCL with osseous localizations (O-DLBCL), including PB-DLBCL. 103 O-DLBCL patients were included and compared with 63 (extra)nodal non-osseous (NO)-DLBCLs with germinal center B-cell phenotype (NO-DLBCL-GCB). Cell-of-origin (COO) was determined by immunohistochemistry and gene-expression-profiling (GEP) using (extended)-NanoString/Lymph2Cx. Mutational profiles were identified with targeted next-generation deep-sequencing, including 52 B-cell lymphoma-relevant genes. O-DLBCLs, including 34 PB-DLBCL, were predominantly classified as GCB-phenotype based on immunohistochemistry (74%) and NanoString analysis (88%). Unsupervised hierarchical clustering of an extended-NanoString/Lymph2Cx demonstrated significantly different GEP-clusters for PB-DLBCL as opposed to NO-DLBCL-GCB (P<0.001). Expression levels of 23 genes of two different targeted GEP-panels, indicated a centrocyte–like phenotype for PB-DLBCL, whereas NO-DLBCL-GCB showed a centroblast-like constitution. PB-DLBCL had significantly more frequent mutations in four GCB-associated genes, i.e. B2M, EZH2, IRF8, and TNFRSF14, compared to NO-DLBCL-GCB (P=0.031, P=0.010, P=0.047, and P=0.003). PB-DLBCL with its corresponding specific mutational profile were significantly associated with a superior overall survival compared to equivalent Ann Arbor limited-stage I/II NO-DLBCL-GCB (P=0.011). This study is the first to demonstrate that PB-DLBCL is characterized by a GCB-phenotype, with a centrocyte-like GEP-pattern and a GCB-associated mutational profile (both involved in immune surveillance) and a favorable prognosis. These novel biology-associated features provide evidence that PB-DLBCL represents a distinct extranodal DLBCL entity and its specific mutational landscape holds potential for targeted therapies (e.g. EZH2-inhibitors). The NanoString analsyis consisted out of 219 probes for Lymph2Cx classifier (COO), MYC-activity GEP score, CNV-associated GEP signature, consensus clustering, and immune-ratio signature. This custome probeset was used to differentiate GEPs between osseous and non-osseos DLBCL of the GCB-phenotype.

Project description:The mTOR (mammalian Target of Rapamycin) pathway is constitutively activated in Diffuse Large B-Cell Lymphoma (DLBCL). mTOR inhibition has been shown to have clinical activity in patients with DLBCL, although overall response rates remain low. We therefore evaluated differences in the transcriptome between DLBCL cell lines with differential sensitivity to the mTOR inhibitor Rapamycin, to (A) identify gene-expression patterns(GEP) capable of identifying sensitivity to Rapamycin, (B) understand the underlying mechanisms of resistance to Rapamycin in DLBCL and (C) identify bioactive molecules likely to synergize with mTOR inhibitors. Using Affymetrix HuGene ST 1.0 microarrays, we were able to identify a gene expression signature capable of accurately predicting sensitivity and resistance to Rapamycin in DLBCL cell lines. Pathway analysis identified the serine/threonine kinase Akt as central to the differentially-expressed gene network. Connectivity mapping of our datasets identified compounds targeting the AKT pathway with a high likelihood of reversing the GEP associated with resistance to Rapamycin. Specifically, we evaluated the HIV protease inhibitor (PI) Nelfinavir, which is known to have anti-cancer and Akt-inhibitory properties, as well as the small molecule Akt inhibitor MK-2206, for their potential to synergize with to Rapamycin in DLBCL. Nelfinavir and MK-2206 caused profound inhibition of cell viability in combination with Rapamycin in DLBCL cell lines. Low nanomolar concentrations of Rapamycin inhibited phosphorylation of Akt and also downstream targets of activated mTOR when used in combination with these Akt inhibitors. These findings have the potential to significantly improve patient selection for mTOR inhibitor therapy, and to improve rates and depths of response. More broadly, they support the use of global RNA expression and connectivity mapping to improve patient selection and identify synergistic drug combinations for cancer therapy.

Project description:The mTOR (mammalian Target of Rapamycin) pathway is constitutively activated in Diffuse Large B-Cell Lymphoma (DLBCL). mTOR inhibition has been shown to have clinical activity in patients with DLBCL, although overall response rates remain low. We therefore evaluated differences in the transcriptome between DLBCL cell lines with differential sensitivity to the mTOR inhibitor Rapamycin, to (A) identify gene-expression patterns(GEP) capable of identifying sensitivity to Rapamycin, (B) understand the underlying mechanisms of resistance to Rapamycin in DLBCL and (C) identify bioactive molecules likely to synergize with mTOR inhibitors. Using Affymetrix HuGene ST 1.0 microarrays, we were able to identify a gene expression signature capable of accurately predicting sensitivity and resistance to Rapamycin in DLBCL cell lines. Pathway analysis identified the serine/threonine kinase Akt as central to the differentially-expressed gene network. Connectivity mapping of our datasets identified compounds targeting the AKT pathway with a high likelihood of reversing the GEP associated with resistance to Rapamycin. Specifically, we evaluated the HIV protease inhibitor (PI) Nelfinavir, which is known to have anti-cancer and Akt-inhibitory properties, as well as the small molecule Akt inhibitor MK-2206, for their potential to synergize with to Rapamycin in DLBCL. Nelfinavir and MK-2206 caused profound inhibition of cell viability in combination with Rapamycin in DLBCL cell lines. Low nanomolar concentrations of Rapamycin inhibited phosphorylation of Akt and also downstream targets of activated mTOR when used in combination with these Akt inhibitors. These findings have the potential to significantly improve patient selection for mTOR inhibitor therapy, and to improve rates and depths of response. More broadly, they support the use of global RNA expression and connectivity mapping to improve patient selection and identify synergistic drug combinations for cancer therapy. DLBCL cell lines were tested for Rapamycin sensitivity and classified as "sensitive" or "resistant." Genome-wide analysis of all cell lines were performed using the Affymetrix HuGene ST 1.0 Array Platform. Genes with differential expression between sensitive and resistant cell lines were analyzed using Statistical Analysis of Microarrays (SAM) software, and a signature of genes determnined. This signature was found to accurately predict sensitivity or resistance of other DLBCL cell lines, and to identify the protein kinase Akt as central to resistance.

Dataset Information

Gene expression profile in DLBCL cases according to response to R-CHOP

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