Diffuse Large B-Cell Lymphoma Classification System That Associates Normal B-Cell Subset Phenotypes With Prognosis
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PROVIDER: PRJNA242893 | ENA |
REPOSITORIES: ENA
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Project description:Purpose Current diagnostic tests for diffuse large B-cell lymphoma use the updated WHO criteria based on biologic, morphologic, and clinical heterogeneity. We propose a refined classification sys-tem based on subset-specific B-cell–associated gene signatures (BAGS) in the normal B-cell hierarchy, hypothesizing that it can provide new biologic insight and diagnostic and prognostic value. Patients and Methods We combined fluorescence-activated cell sorting, gene expression profiling, and statistical modeling to generate BAGS for naive, centrocyte, centroblast, memory, and plasmablast B cells from normal human tonsils. The impact of BAGS-assigned subtyping was analyzed using five clinical cohorts (treated with cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP], n _ 270; treated with rituximab plus CHOP [R-CHOP], n _ 869) gathered across geo-graphic regions, time eras, and sampling methods. The analysis estimated subtype frequencies and drug-specific resistance and included a prognostic meta-analysis of patients treated with first-line R-CHOP therapy. Results Similar BAGS subtype frequencies were assigned across 1,139 samples from five different co-horts. Among R-CHOP–treated patients, BAGS assignment was significantly associated with overall survival and progression-free survival within the germinal center B-cell–like subclass; the centrocyte subtype had a superior prognosis compared with the centroblast subtype. In agreement with the observed therapeutic outcome, centrocyte subtypes were estimated as being less resistant than the centroblast subtype to doxorubicin and vincristine. The centroblast subtype had a complex genotype, whereas the centrocyte subtype had high TP53 mutation and insertion/deletion frequencies and expressed LMO2, CD58, and stromal-1–signature and major histocompatibility complex class II–signature genes, which are known to have a positive impact on prognosis. Conclusion Further development of a diagnostic platform using BAGS-assigned subtypes may allow pathogenetic studies to improve disease management.
2015-03-24 | GSE56314 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below: GSE56313 and GSE56314 Purpose Current diagnostic tests for diffuse large B-cell lymphoma use the updated WHO criteria based on biologic, morphologic, and clinical heterogeneity. We propose a refined classification sys-tem based on subset-specific B-cell–associated gene signatures (BAGS) in the normal B-cell hierarchy, hypothesizing that it can provide new biologic insight and diagnostic and prognostic value. Patients and Methods We combined fluorescence-activated cell sorting, gene expression profiling, and statistical modeling to generate BAGS for naive, centrocyte, centroblast, memory, and plasmablast B cells from normal human tonsils. The impact of BAGS-assigned subtyping was analyzed using five clinical cohorts (treated with cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP], n _ 270; treated with rituximab plus CHOP [R-CHOP], n _ 869) gathered across geo-graphic regions, time eras, and sampling methods. The analysis estimated subtype frequencies and drug-specific resistance and included a prognostic meta-analysis of patients treated with first-line R-CHOP therapy. Results Similar BAGS subtype frequencies were assigned across 1,139 samples from five different co-horts. Among R-CHOP–treated patients, BAGS assignment was significantly associated with overall survival and progression-free survival within the germinal center B-cell–like subclass; the centrocyte subtype had a superior prognosis compared with the centroblast subtype. In agreement with the observed therapeutic outcome, centrocyte subtypes were estimated as being less resistant than the centroblast subtype to doxorubicin and vincristine. The centroblast subtype had a complex genotype, whereas the centrocyte subtype had high TP53 mutation and insertion/deletion frequencies and expressed LMO2, CD58, and stromal-1–signature and major histocompatibility complex class II–signature genes, which are known to have a positive impact on prognosis. Conclusion Further development of a diagnostic platform using BAGS-assigned subtypes may allow pathogenetic studies to improve disease management.
2015-03-24 | GSE56315 | GEO
Project description:Purpose Current diagnostic tests for diffuse large B-cell lymphoma use the updated WHO criteria based on biologic, morphologic, and clinical heterogeneity. We propose a refined classification sys-tem based on subset-specific B-cell–associated gene signatures (BAGS) in the normal B-cell hierarchy, hypothesizing that it can provide new biologic insight and diagnostic and prognostic value. Patients and Methods We combined fluorescence-activated cell sorting, gene expression profiling, and statistical modeling to generate BAGS for naive, centrocyte, centroblast, memory, and plasmablast B cells from normal human tonsils. The impact of BAGS-assigned subtyping was analyzed using five clinical cohorts (treated with cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP], n _ 270; treated with rituximab plus CHOP [R-CHOP], n _ 869) gathered across geo-graphic regions, time eras, and sampling methods. The analysis estimated subtype frequencies and drug-specific resistance and included a prognostic meta-analysis of patients treated with first-line R-CHOP therapy. Results Similar BAGS subtype frequencies were assigned across 1,139 samples from five different co-horts. Among R-CHOP–treated patients, BAGS assignment was significantly associated with overall survival and progression-free survival within the germinal center B-cell–like subclass; the centrocyte subtype had a superior prognosis compared with the centroblast subtype. In agreement with the observed therapeutic outcome, centrocyte subtypes were estimated as being less resistant than the centroblast subtype to doxorubicin and vincristine. The centroblast subtype had a complex genotype, whereas the centrocyte subtype had high TP53 mutation and insertion/deletion frequencies and expressed LMO2, CD58, and stromal-1–signature and major histocompatibility complex class II–signature genes, which are known to have a positive impact on prognosis. Conclusion Further development of a diagnostic platform using BAGS-assigned subtypes may allow pathogenetic studies to improve disease management.
2015-03-24 | GSE56313 | GEO
Project description:Current diagnostic tests for diffuse large B-cell lymphoma use the updated WHO criteria based on biologic, morphologic, and clinical heterogeneity. We propose a refined classification system based on subset-specific B-cell-associated gene signatures (BAGS) in the normal B-cell hierarchy, hypothesizing that it can provide new biologic insight and diagnostic and prognostic value.We combined fluorescence-activated cell sorting, gene expression profiling, and statistical modeling to generate BAGS for naive, centrocyte, centroblast, memory, and plasmablast B cells from normal human tonsils. The impact of BAGS-assigned subtyping was analyzed using five clinical cohorts (treated with cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP], n = 270; treated with rituximab plus CHOP [R-CHOP], n = 869) gathered across geographic regions, time eras, and sampling methods. The analysis estimated subtype frequencies and drug-specific resistance and included a prognostic meta-analysis of patients treated with first-line R-CHOP therapy.Similar BAGS subtype frequencies were assigned across 1,139 samples from five different cohorts. Among R-CHOP-treated patients, BAGS assignment was significantly associated with overall survival and progression-free survival within the germinal center B-cell-like subclass; the centrocyte subtype had a superior prognosis compared with the centroblast subtype. In agreement with the observed therapeutic outcome, centrocyte subtypes were estimated as being less resistant than the centroblast subtype to doxorubicin and vincristine. The centroblast subtype had a complex genotype, whereas the centrocyte subtype had high TP53 mutation and insertion/deletion frequencies and expressed LMO2, CD58, and stromal-1-signature and major histocompatibility complex class II-signature genes, which are known to have a positive impact on prognosis.Further development of a diagnostic platform using BAGS-assigned subtypes may allow pathogenetic studies to improve disease management.
| S-EPMC4397280 | biostudies-literature
Project description:Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.
| S-EPMC6156884 | biostudies-literature
Project description:Diffuse Large B Cell Lymphoma (DLBCL) is the most common lymphoid malignancy in adults. Despite being considered a single disease, DLBCL presents with variable backgrounds in terms of morphology, genetics, and biological behavior, which results in heterogeneous outcomes among patients. Although new tools have been developed for the classification and management of patients, 40% of them still have primary refractory disease or relapse. In addition, multiple factors regarding the pathogenesis of this disease remain unclear and identification of novel biomarkers is needed. In this context, recent investigations point to microRNAs as useful biomarkers in cancer as well as important players in the development of the disease. However, regarding DLBCL, up to date, there is inconsistency in the data reported. Therefore, in this work, the main goals were to determine a microRNA set with utility as biomarkers for DLBCL diagnosis, classification, prognosis and treatment response. To achieve these goals, we analyzed microRNA expression in a cohort of 78 DLBCL samples at diagnosis and 17 controls using small RNA sequencing. This way, we were able to define new microRNA expression signatures for diagnosis, classification, treatment response and prognosis. In summary, our study remarks that microRNAs could play an important role as biomarkers in diagnosis, classification, treatment response and prognosis in DLBCL.
2023-10-18 | GSE185796 | GEO
Project description:Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF- B pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF- B genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases.
2014-12-29 | GSE64555 | GEO
Project description:We investigated the genomic enhancer landscape of Hepatocellular Carcinoma (HCC) using H3K27ac ChIP-seq and HiC/HiChIP data from resected tumour samples of 30 patients, whose genome, transcriptome, and clinical trajectory data were available. Differential enhancer analysis revealed dysregulated enhancer loci, but without strong enrichment of underlying DNA mutation hotspots. As many of the gain-in-tumour enhancer associated genes were fetal liver hepatoblast genes, we investigated the stochastic expression pattern of the overlapping genes (epigenetic oncofetal genes) using previously published single cell RNA-seq data, in which the patients partially overlapped. The proportion of cells expressing epigenetic oncofetal genes clustered liver tissue samples into two groups - adjacent normal liver-like, or oncofetal-like. Notably, gain-in-tumour enhancer associated genes showed prognostic value, with patient clusters revealed by co-clustering the differential gene expression pattern. Altogether, we report the genomic enhancer signature that associates with differential prognosis in HCC. Findings that cohere with oncofetal reprogramming in HCC is underpinned by genome-wide enhancer rewiring. Our results present the epigenetic changes in HCC that offer the rational selection of epigenetic-driven gene targets for therapeutic intervention or disease prognostication in HCC.
2022-09-02 | GSE212342 | GEO
Project description:Inhibition of the renal production of glucose associates with a worse prognosis in chronic kidney disease
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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