Project description:Genomic profiles of DLBCL (Diffuse Large B-cell Lymphoma) patients 20 DLBCL patients were selected for detection of genomic aberrations
Project description:Genomic profiles of DLBCL (Diffuse Large B-cell Lymphoma) patients 20 DLBCL patients were selected for detection of genomic aberrations Patient's DNA were hybridized against Promega control on Agilent G4410B arrays and scanned with the Agilent G2505B scanner.
Project description:RNA extracted from diagnostic tumor samples of 52 patients affected by DLBCL was analyzed on the nCounter system using the PanCancer Immune Profiling Panel.
Project description:Diffuse large B-cell lymphoma (DLBCL) is currently divided into three main molecular subtypes, defined by gene expression profiling (GEP): Germinal Center B-cell like (GCB), Activated B-Cell like (ABC), and Primary Mediastinal B-cell Lymphoma (PMBL). DLBCL subtypes were determined according to patients' gene expression profiles.
Project description: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.
Project description:The main purpose of the study was to identify biological prognostic factors that could be used to define poor risk diffuse large B-cell lymphoma (DLBCL) patients. We used exon array profiling to screen differentially expressed genes and splicing variants between clinically high risk patients, who have relapsed or remained in remission in response to dose dense chemoimmunotherapy. Study population consisted of 43 high-risk DLBCL/FL grade 3 patients less than 65 years old. The patients were treated in the Nordic phase II protocol with six courses of R-CHOEP14 followed by systemic central nervous system prophylaxis with one course of high dose methotrexate and one course of high dose cytarabine.
Project description:Diffuse large B-cell lymphoma (DLBCL) is the most common form of lymphoma in adults. The disease exhibits a striking heterogeneity in gene expression profiles and clinical outcomes, but its genetic causes remain to be fully defined. Through whole genome and exome sequencing, we characterized the genetic diversity of DLBCL. In all, we sequenced 73 DLBCL primary tumors (34 with matched normal DNA). Separately, we sequenced the exomes of 21 DLBCL cell lines. We identified 322 DLBCL cancer genes that were recurrently mutated in primary DLBCLs. We identified recurrent mutations implicating a number of known and not previously identified genes and pathways in DLBCL including those related to chromatin modification (ARID1A and MEF2B), NF-κB (CARD11 and TNFAIP3), PI3 kinase (PIK3CD, PIK3R1, and MTOR), B-cell lineage (IRF8, POU2F2, and GNA13), and WNT signaling (WIF1). We also experimentally validated a mutation in PIK3CD, a gene not previously implicated in lymphomas. The patterns of mutation demonstrated a classic long tail distribution with substantial variation of mutated genes from patient to patient and also between published studies. Thus, our study reveals the tremendous genetic heterogeneity that underlies lymphomas and highlights the need for personalized medicine approaches to treating these patients. 21 DLBCL cell lines and 70 DLBCL patient samples.
Project description:We performed exon-based transcrition profiling with Affymetrix Human 1.0 ST Exon Array from pairwise tissue samples of 8 DLBCL/FL3B patients. Paired biopsies were taken at diagnosis and 1-2 days after the first cycle of chemoimmunotherapy (R-CHOP).
Project description:Diffuse large B-cell lymphoma (DLBCL) has striking clinical and molecular variability. Although a more precise identification of the multiple determinants of this variability is still under investigation, there is a consensus that high-clinical-risk DLBCL cases require a risk-adapted therapy, since intensification of chemotherapy with autologous stem-cell transplantation (ASCT) has been shown to improve the prognosis for high-risk patients in randomised clinical trials. In spite of this, the protocols used for these patients have a high morbidity, associated with ASCT and the use of multiple drugs. This makes it important to identify patients that may take benefit from risk-adapted therapies, through the recognition of biological markers that provide information about both the tumoral cells and the microenvironment. Unfortunately, many of the studies so far performed have relied on heterogeneous series of patients, staged or treated with different protocols. For instance, some of the variability in DLBCL arises from the fact that this diagnosis is applied to de novo and secondary tumours, nodal and extranodal, irrespective of clinical stage, patient age and associated infections. Additionally, DLBCL includes some specific variants, such as mediastinal DLBCL and T/HRBCL, with specific prognostic parameters. This could prevent the identification of potential predictive biomarkers, because the results of many studies show that the search for predictive biomarkers should be promoted in the context of samples of clinically homogeneous patients enrolled in clinical trials. A further source of variability is the dependence of some predictive markers on specific therapeutic approaches, as is the case for the Bcl6 expression in DLBCL, since Bcl-6+ cases have been shown not to benefit from the addition of R to CHOP. Here we have analysed a series of high-clinical-risk DLBCLs by a two-stage approach, first identifying functional signatures by expression analysis, then analysing surrogate biomarkers using tissue microarrays (TMAs). This eclectic approach could reveal new aspects of the relationship between the neoplastic cells and the microenvironment, leading to the identification of previously unknown prognostic markers. At the same time, the use of functional signatures to analyse expression-profiling data avoids the poor reproducibility of the data obtained from gene-by-gene analysis, and benefits from the existence of a growing body of data concerning the major pathways deregulated in DLBCL. To avoid the bias of semiquantitative scoring, in this study we have quantified the markers included in the multivariate analysis. Keywords: new biological variables, risk-adapted therapies