Dataset Information

A multiomics approach in refractory DLBCL

ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is the most frequent entity among non-Hodgkin lymphoma (NHL). It is a clinically and biologically heterogeneous disease regarding treatment response and long-term outcome. The anthracycline-based regimen R-CHOP is still considered as the standard of care for first-line treatment allowing achieving a complete response for approximately 60% of the patients. The prognosis of patients with primary refractory or relapsed (R/R) disease is particularly poor with a median overall survival below one year. Only a fraction of R/R patients can be cured with salvage therapies due to the acquisition of chemoresistance. We conducted a large-scale and deep proteomic investigation of the proteome profiles of R/R DLBCL patients compared to chemosensitive patients in order to identify new potential biomarkers related to resistance to treatment and to better understand the biological mechanisms underlying chemoresistance.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lymph Node

DISEASE(S): Lymphoma

SUBMITTER: Luc FORNECKER

LAB HEAD: Sarah Cianférani

PROVIDER: PXD009089 | Pride | 2019-03-04

REPOSITORIES: Pride

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Publications

Multi-omics dataset to decipher the complexity of drug resistance in diffuse large B-cell lymphoma.

Fornecker Luc-Matthieu LM Muller Leslie L Bertrand Frédéric F Paul Nicodème N Pichot Angélique A Herbrecht Raoul R Chenard Marie-Pierre MP Mauvieux Laurent L Vallat Laurent L Bahram Seiamak S Cianférani Sarah S Carapito Raphaël R Carapito Christine C

Scientific reports 20190129 1

The prognosis of patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) remains unsatisfactory and, despite major advances in genomic studies, the biological mechanisms underlying chemoresistance are still poorly understood. We conducted for the first time a large-scale differential multi-omics investigation on DLBCL patient's samples in order to identify new biomarkers that could early identify patients at risk of R/R disease and to identify new targets that could determi ...[more]

PMID: 30696890

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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.

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.

Dataset Information

A multiomics approach in refractory DLBCL

Publications

Multi-omics dataset to decipher the complexity of drug resistance in diffuse large B-cell lymphoma.

Similar Datasets

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