IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy.

BACKGROUND: Glioblastoma (GBM) brain tumors lacking IDH1 mutations (IDHwt) have the worst prognosis of all brain neoplasms. Patients receive surgery and chemoradiotherapy but tumors almost always fatally recur. RESULTS: Using RNA sequencing data from 107 pairs of pre- and post-standard treatment locally recurrent IDHwt GBM tumors, we identify two responder subtypes based on longitudinal changes in gene expression. In two thirds of patients, a specific subset of genes is upregulated from primary to recurrence (Up responders), and in one third, the same genes are downregulated (Down responders), specifically in neoplastic cells. Characterization of the responder subtypes indicates subtype-specific adaptive treatment resistance mechanisms that are associated with distinct changes in the tumor microenvironment. In Up responders, recurrent tumors are enriched in quiescent proneural GBM stem cells and differentiated neoplastic cells, with increased interaction with the surrounding normal brain and neurotransmitter signaling, whereas Down responders commonly undergo mesenchymal transition. ChIP-sequencing data from longitudinal GBM tumors suggests that the observed transcriptional reprogramming could be driven by Polycomb-based chromatin remodeling rather than DNA methylation. CONCLUSIONS: We show that the responder subtype is cancer-cell intrinsic, recapitulated in in vitro GBM cell models, and influenced by the presence of the tumor microenvironment. Stratifying GBM tumors by responder subtype may lead to more effective treatment.

Non-IG::MYC in diffuse large B-cell lymphoma confers variable genomic configurations and MYC transactivation potential.

MYC translocation occurs in 8-14% of diffuse large B-cell lymphoma (DLBCL), and may concur with BCL2 and/or BCL6 translocation, known as double-hit (DH) or triple-hit (TH). DLBCL-MYC/BCL2-DH/TH are largely germinal centre B-cell like subtype, but show variable clinical outcome, with IG::MYC fusion significantly associated with inferior survival. While DLBCL-MYC/BCL6-DH are variable in their cell-of-origin subtypes and clinical outcome. Intriguingly, only 40-50% of DLBCL with MYC translocation show high MYC protein expression (>70%). We studied 186 DLBCLs with MYC translocation including 32 MYC/BCL2/BCL6-TH, 75 MYC/BCL2-DH and 26 MYC/BCL6-DH. FISH revealed a MYC/BCL6 fusion in 59% of DLBCL-MYC/BCL2/BCL6-TH and 27% of DLBCL-MYC/BCL6-DH. Targeted NGS showed a similar mutation profile and LymphGen genetic subtype between DLBCL-MYC/BCL2/BCL6-TH and DLBCL-MYC/BCL2-DH, but variable LymphGen subtypes among DLBCL-MYC/BCL6-DH. MYC protein expression is uniformly high in DLBCL with IG::MYC, but variable in those with non-IG::MYC including MYC/BCL6-fusion. Translocation breakpoint analyses of 8 cases by TLC-based NGS showed no obvious genomic configuration that enables MYC transactivation in 3 of the 4 cases with non-IG::MYC, while a typical promoter substitution or IGH super enhancer juxtaposition in the remaining cases. The findings potentially explain variable MYC expression in DLBCL with MYC translocation, and also bear practical implications in its routine assessment.

Cytokine receptor IL27RA is an NF-κB-responsive gene involved in CD38 upregulation in multiple myeloma.

Multiple myeloma (MM) shows constitutive activation of canonical and noncanonical nuclear factor κB (NF-κB) signaling via genetic mutations or tumor microenvironment (TME) stimulations. A subset of MM cell lines showed dependency for cell growth and survival on the canonical NF-κB transcription factor RELA alone, suggesting a critical role for a RELA-mediated biological program in MM pathogenesis. Here, we determined the RELA-dependent transcriptional program in MM cell lines and found the expression of the cell surface molecules interleukin-27 receptor-α (IL-27Rα) and the adhesion molecule JAM2 to be responsive to RELA at the messenger RNA and protein levels. IL-27Rα and JAM2 were expressed on primary MM cells at higher levels than on healthy long-lived plasma cells (PCs) in the bone marrow. IL-27 activated STAT1, and to a lesser extent STAT3, in MM cell lines and in PCs generated from memory B cells in an IL-21-dependent in vitro PC differentiation assay. Concomitant activity of IL-21 and IL-27 enhanced differentiation into PCs and increased the cell-surface expression of the known STAT target gene CD38. In accordance, a subset of MM cell lines and primary MM cells cultured with IL-27 upregulated CD38 cell-surface expression, a finding with potential implications for enhancing the efficacy of CD38-directed monoclonal antibody therapies by increasing CD38 expression on tumor cells. The elevated expression of IL-27Rα and JAM2 on MM cells compared with that on healthy PCs may be exploited for the development of targeted therapeutic strategies that modulate the interaction of MM cells with the TME.

Differential Efficacy From the Addition of Bortezomib to R-CHOP in Diffuse Large B-Cell Lymphoma According to the Molecular Subgroup in the REMoDL-B Study With a 5-Year Follow-Up.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.The REMoDL-B phase III adaptive trial compared rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) versus R-CHOP + bortezomib (RB-CHOP) in patients with diffuse large B-cell lymphoma (DLBCL), stratified by molecular subtype. Primary analysis at a median follow-up of 30 months found no effect of bortezomib on progression-free survival (PFS) or overall survival (OS). Retrospective analysis using a gene expression-based classifier identified a molecular high-grade (MHG) group with worse outcomes. We present an updated analysis for patients successfully classified by the gene expression profile (GEP). Eligible patients were age older than 18 years with untreated DLBCL, fit enough for full-dose chemotherapy, and with adequate biopsies for GEP. Of 1,077 patients registered, 801 were identified with Activated B-Cell (ABC), Germinal Center B-cell, or MHG lymphoma. At a median follow-up of 64 months, there was no overall benefit of bortezomib on PFS or OS (5-year PFS hazard ratio [HR], 0.81; P = .085; OS HR, 0.86; P = .32). However, improved PFS and OS were seen in ABC lymphomas after RB-CHOP: 5-year OS 67% with R-CHOP versus 80% with RB-CHOP (HR, 0.58; 95% CI, 0.35 to 0.95; P = .032). Five-year PFS was higher in MHG lymphomas: 29% versus 55% (HR, 0.46; 95% CI, 0.26 to 0.84). Patients with ABC and MHG DLBCL may benefit from the addition of bortezomib to R-CHOP in initial therapy.

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type diffuse large B-cell lymphoma.

Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell-like (ABC) to germinal center B-cell-like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC-DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year-old patients with superior PFS and OS treated with ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data.

Intratumour heterogeneity provides tumours with the ability to adapt and acquire treatment resistance. The development of more effective and personalised treatments for cancers, therefore, requires accurate characterisation of the clonal architecture of tumours, enabling evolutionary dynamics to be tracked. Many methods exist for achieving this from bulk tumour sequencing data, involving identifying mutations and performing subclonal deconvolution, but there is a lack of systematic benchmarking to inform researchers on which are most accurate, and how dataset characteristics impact performance. To address this, we use the most comprehensive tumour genome simulation tool available for such purposes to create 80 bulk tumour whole exome sequencing datasets of differing depths, tumour complexities, and purities, and use these to benchmark subclonal deconvolution pipelines. We conclude that i) tumour complexity does not impact accuracy, ii) increasing either purity or purity-corrected sequencing depth improves accuracy, and iii) the optimal pipeline consists of Mutect2, FACETS and PyClone-VI. We have made our benchmarking datasets publicly available for future use.

Comparative analysis of gene expression platforms for cell-of-origin classification of diffuse large B-cell lymphoma shows high concordance.

Cell-of-origin subclassification of diffuse large B cell lymphoma (DLBCL) into activated B cell-like (ABC), germinal centre B cell-like (GCB) and unclassified (UNC) or type III by gene expression profiling is recommended in the latest update of the World Health Organization's classification of lymphoid neoplasms. There is, however, no accepted gold standard method or dataset for this classification. Here, we compare classification results using gene expression data for 68 formalin-fixed paraffin-embedded DLBCL samples measured on four different gene expression platforms (Illumina wG-DASLTM arrays, Affymetrix PrimeView arrays, Illumina TrueSeq RNA sequencing and the HTG EdgeSeq DLBCL Cell of Origin Assay EU using an established platform agnostic classification algorithm (DAC) and the classifier native to the HTG platform, which is CE marked for in vitro diagnostic use (CE-IVD). Classification methods and platforms show a high level of concordance, with agreement in at least 80% of cases and rising to much higher levels for classifications of high confidence. Our results demonstrate that cell-of-origin classification by gene expression profiling on different platforms is robust, and that the use of the confidence value alongside the classification result is important in clinical applications.

Distinct genetic changes reveal evolutionary history and heterogeneous molecular grade of DLBCL with MYC/BCL2 double-hit.

Using a Burkitt lymphoma-like gene expression signature, we recently defined a high-risk molecular high-grade (MHG) group mainly within germinal centre B-cell like diffuse large B-cell lymphomas (GCB-DLBCL), which was enriched for MYC/BCL2 double-hit (MYC/BCL2-DH). The genetic basis underlying MHG-DLBCL and their aggressive clinical behaviour remain unknown. We investigated 697 cases of DLBCL, particularly those with MYC/BCL2-DH (n = 62) by targeted sequencing and gene expression profiling. We showed that DLBCL with MYC/BCL2-DH, and those with BCL2 translocation, harbour the characteristic mutation signatures that are associated with follicular lymphoma and its high-grade transformation. We identified frequent MYC hotspot mutations that affect the phosphorylation site (T58) and its adjacent amino acids, which are important for MYC protein degradation. These MYC mutations were seen in a subset of cases with MYC translocation, but predominantly in those of MHG. The mutations were more frequent in double-hit lymphomas with IG as the MYC translocation partner, and were associated with higher MYC protein expression and poor patient survival. DLBCL with MYC/BCL2-DH and those with BCL2 translocation alone are most likely derived from follicular lymphoma or its precursor lesion, and acquisition of MYC pathogenic mutations may augment MYC function, resulting in aggressive clinical behaviour.

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets.

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.

Ibrutinib induces chromatin reorganisation of chronic lymphocytic leukaemia cells.

Chronic lymphocytic leukaemia (CLL) is the most common leukaemia in Western countries. It has recently been shown that the homogeneity of the chromatin landscape between CLL cells contrasts with the important observed genetic heterogeneity of the disease. To gain further insight into the consequences of disease evolution on the epigenome's plasticity, we monitored changes in chromatin structure occurring in vivo in CLL cells from patients receiving continuous Ibrutinib treatment. Ibrutinib, an oral inhibitor of the Bruton's tyrosine kinase (BTK) has proved to be remarkably efficient against treatment naïve (TN), heavily pre-treated and high-risk chronic lymphocytic leukaemia (CLL), with limited adverse events. We established that the chromatin landscape is significantly and globally affected in response to Ibrutinib. However, we observed that prior to treatment, CLL cells show qualitative and quantitative variations in chromatin structure correlated with both EZH2 protein level and cellular response to external stimuli. Then, under prolonged exposure to Ibrutinib, a loss of the two marks associated with lysine 27 (acetylation and trimethylation) was observed. Altogether, these data indicate that the epigenome of CLL cells from the peripheral blood change dynamically in response to stimuli and suggest that these cells might adapt to the Ibrutinib "hit" in a process leading toward a possible reduced sensitivity to treatment.

Gene-expression profiling of bortezomib added to standard chemoimmunotherapy for diffuse large B-cell lymphoma (REMoDL-B): an open-label, randomised, phase 3 trial.

BACKGROUND: Biologically distinct subtypes of diffuse large B-cell lymphoma can be identified using gene-expression analysis to determine their cell of origin, corresponding to germinal centre or activated B cell. We aimed to investigate whether adding bortezomib to standard therapy could improve outcomes in patients with these subtypes. METHODS: In a randomised evaluation of molecular guided therapy for diffuse large B-cell lymphoma with bortezomib (REMoDL-B), an open-label, adaptive, randomised controlled, phase 3 superiority trial, participants were recruited from 107 cancer centres in the UK (n=94) and Switzerland (n=13). Eligible patients had previously untreated, histologically confirmed diffuse large B-cell lymphoma with sufficient diagnostic material from initial biopsies for gene-expression profiling and pathology review; were aged 18 years or older; had ECOG performance status of 2 or less; had bulky stage I or stage II-IV disease requiring full-course chemotherapy; had measurable disease; and had cardiac, lung, renal, and liver function sufficient to tolerate chemotherapy. Patients initially received one 21-day cycle of standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP; rituximab 375 mg/m2, cyclophosphamide 750 mg/m2, doxorubicin 50 mg/m2, and vincristine 1·4 mg/m2 [to a maximum of 2 mg total dose] intravenously on day 1 of the cycle, and prednisolone 100 mg orally once daily on days 1-5). During this time, we did gene-expression profiling using whole genome cDNA-mediated annealing, selection, extension, and ligation assay of tissue from routine diagnostic biopsy samples to determine the cell-of-origin subtype of each participant (germinal centre B cell, activated B cell, or unclassified). Patients were then centrally randomly assigned (1:1) via a web-based system, with block randomisation stratified by international prognostic index score and cell-of-origin subtype, to continue R-CHOP alone (R-CHOP group; control), or with bortezomib (RB-CHOP group; experimental; 1·3 mg/m2 intravenously or 1·6 mg/m2 subcutaneously) on days 1 and 8 for cycles two to six. If RNA extracted from the diagnostic tissues was of insufficient quality or quantity, participants were given R-CHOP as per the control group. The primary endpoint was 30-month progression-free survival, for the germinal centre and activated B-cell population. The primary analysis was on the modified intention-to-treat population of activated and germinal centre B-cell population. Safety was assessed in all participants who were given at least one dose of study drug. We report the progression-free survival and safety outcomes for patients in the follow-up phase after the required number of events occurred. This study was registered at ClinicalTrials.gov, number NCT01324596, and recruitment and treatment has completed for all participants, with long-term follow-up ongoing. FINDINGS: Between June 2, 2011, and June 10, 2015, 1128 eligible patients were registered, of whom 918 (81%) were randomly assigned to receive treatment (n=459 to R-CHOP, n=459 to RB-CHOP), comprising 244 (26·6%) with activated B-cell disease, 475 (51·7%) with germinal centre B cell disease, and 199 (21·7%) with unclassified disease. At a median follow-up of 29·7 months (95% CI 29·0-32·0), we saw no evidence for a difference in progression-free survival in the combined germinal centre and activated B-cell population between R-CHOP and RB-CHOP (30-month progression-free survival 70·1%, 95% CI 65·0-74·7 vs 74·3%, 69·3-78·7; hazard ratio 0·86, 95% CI 0·65-1·13; p=0·28). The most common grade 3 or worse adverse event was haematological toxicity, reported in 178 (39·8%) of 447 patients given R-CHOP and 187 (42·1%) of 444 given RB-CHOP. However, RB-CHOP was not associated with increased haematological toxicity and 398 [87·1%] of 459 participants assigned to receive RB-CHOP completed six cycles of treatment. Grade 3 or worse neuropathy occurred in 17 (3·8%) patients given RB-CHOP versus eight (1·8%) given R-CHOP. Serious adverse events occurred in 190 (42·5%) patients given R-CHOP, including five treatment-related deaths, and 223 (50·2%) given RB-CHOP, including four treatment-related deaths. INTERPRETATION: This is the first large-scale study in diffuse large B-cell lymphoma to use real-time molecular characterisation for prospective stratification, randomisation, and subsequent analysis of biologically distinct subgroups of patients. The addition of bortezomib did not improve progression-free survival. FUNDING: Janssen-Cilag, Bloodwise, and Cancer Research UK.

Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.

Cancers converge onto shared patterns that arise from constraints placed by the biology of the originating cell lineage and microenvironment on programs driven by oncogenic events. Here we define consistent expression modules reflecting this structure in colon and breast cancer by exploiting expression data resources and a new computationally efficient approach that we validate against other comparable methods. This approach, Parsimonious Gene Correlation Network Analysis (PGCNA), allows comparison of network structures between these cancer types identifying shared modules of gene co-expression reflecting: cancer hallmarks, functional and structural gene batteries, copy number variation and biology of originating lineage. These networks along with the mapping of outcome data at gene and module level provide an interactive resource that generates context for relationships between genes within and between such modules. Assigning module expression values (MEVs) provides a tool to summarize network level gene expression in individual cases illustrating potential utility in classification and allowing analysis of linkage between module expression and mutational state. Exploiting TCGA data thus defines both recurrent patterns of association between module expression and mutation at data-set level, and exemplifies the polarization of mutation patterns with the leading edge of module expression at individual case level. We illustrate the scalable nature of the approach within immune response related modules, which in the context of breast cancer demonstrates the selective association of immune subsets, in particular mast cells, with the underlying mutational pattern. Together our analyses provide evidence for a generalizable framework to enhance molecular stratification in cancer.

Cut-and-Run: A Distinct Mechanism by which V(D)J Recombination Causes Genome Instability.

V(D)J recombination is essential to generate antigen receptor diversity but is also a potent cause of genome instability. Many chromosome alterations that result from aberrant V(D)J recombination involve breaks at single recombination signal sequences (RSSs). A long-standing question, however, is how such breaks occur. Here, we show that the genomic DNA that is excised during recombination, the excised signal circle (ESC), forms a complex with the recombinase proteins to efficiently catalyze breaks at single RSSs both in vitro and in vivo. Following cutting, the RSS is released while the ESC-recombinase complex remains intact to potentially trigger breaks at further RSSs. Consistent with this, chromosome breaks at RSSs increase markedly in the presence of the ESC. Notably, these breaks co-localize with those found in acute lymphoblastic leukemia patients and occur at key cancer driver genes. We have named this reaction "cut-and-run" and suggest that it could be a significant cause of lymphocyte genome instability.

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

SUMMARY: Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data. AVAILABILITY AND IMPLEMENTATION: HeteroGenesis and w-Wessim are freely available under the GNU General Public Licence from https://github.com/GeorgetteTanner, implemented in Python and supported on linux and MS Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Growth Factor-like Gene Regulation Is Separable from Survival and Maturation in Antibody-Secreting Cells.

Recurrent mutational activation of the MAP kinase pathway in plasma cell myeloma implicates growth factor-like signaling responses in the biology of Ab-secreting cells (ASCs). Physiological ASCs survive in niche microenvironments, but how niche signals are propagated and integrated is poorly understood. In this study, we dissect such a response in human ASCs using an in vitro model. Applying time course expression data and parsimonious gene correlation network analysis (PGCNA), a new approach established by our group, we map expression changes that occur during the maturation of proliferating plasmablast to quiescent plasma cell under survival conditions including the potential niche signal TGF-ß3. This analysis demonstrates a convergent pattern of differentiation, linking unfolded protein response/endoplasmic reticulum stress to secretory optimization, coordinated with cell cycle exit. TGF-ß3 supports ASC survival while having a limited effect on gene expression including upregulation of CXCR4. This is associated with a significant shift in response to SDF1 in ASCs with amplified ERK1/2 activation, growth factor-like immediate early gene regulation and EGR1 protein expression. Similarly, ASCs responding to survival conditions initially induce partially overlapping sets of immediate early genes without sustaining the response. Thus, in human ASCs growth factor-like gene regulation is transiently imposed by niche signals but is not sustained during subsequent survival and maturation.

Molecular High-Grade B-Cell Lymphoma: Defining a Poor-Risk Group That Requires Different Approaches to Therapy.

PURPOSE: Biologic heterogeneity is a feature of diffuse large B-cell lymphoma (DLBCL), and the existence of a subgroup with poor prognosis and phenotypic proximity to Burkitt lymphoma is well known. Conventional cytogenetics identifies some patients with rearrangements of MYC and BCL2 and/or BCL6 (double-hit lymphomas) who are increasingly treated with more intensive chemotherapy, but a more biologically coherent and clinically useful definition of this group is required. PATIENTS AND METHODS: We defined a molecular high-grade (MHG) group by applying a gene expression-based classifier to 928 patients with DLBCL from a clinical trial that investigated the addition of bortezomib to standard rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) therapy. The prognostic significance of MHG was compared with existing biomarkers. We performed targeted sequencing of 70 genes in 400 patients and explored molecular pathology using gene expression signature databases. Findings were validated in an independent data set. RESULTS: The MHG group comprised 83 patients (9%), with 75 in the cell-of-origin germinal center B-cell-like group. MYC rearranged and double-hit groups were strongly over-represented in MHG but comprised only one half of the total. Gene expression analysis revealed a proliferative phenotype with a relationship to centroblasts. Progression-free survival rate at 36 months after R-CHOP in the MHG group was 37% (95% CI, 24% to 55%) compared with 72% (95% CI, 68% to 77%) for others, and an analysis of treatment effects suggested a possible positive effect of bortezomib. Double-hit lymphomas lacking the MHG signature showed no evidence of worse outcome than other germinal center B-cell-like cases. CONCLUSION: MHG defines a biologically coherent high-grade B-cell lymphoma group with distinct molecular features and clinical outcomes that effectively doubles the size of the poor-prognosis, double-hit group. Patients with MHG may benefit from intensified chemotherapy or novel targeted therapies.

Flexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer.

Clustering is used widely in 'omics' studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data (e.g. presence/absence of mutations, binding, motifs and epigenetic marks) and continuous data (e.g. gene expression, protein abundance, metabolite levels). Here, we present a generic method based on a probabilistic model for clustering this type of data, and illustrate its application to genetic regulation and the clustering of cancer samples. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival. The method is available as a stand-alone software package (GNU General Public Licence) from http://github.com/BioToolsLeeds/FlexiCoClusteringPackage.git.

Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data.

BACKGROUND: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. METHODS: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. RESULTS: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. CONCLUSION: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation.

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab.

PURPOSE: We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients. PATIENTS AND METHODS: TCGA microRNA expression data from tumors resected at first diagnosis of glioblastoma in patients treated with bevacizumab at any time during the course of their disease were randomly separated into training (n = 50) and test (n = 37) groups for model generation. MicroRNA-seq data for 51 patients whose treatment included bevacizumab in the BELOB trial were used as an independent validation cohort. RESULTS: Using penalized regression we identified 8 microRNAs as potential predictors of overall survival in the training set. We dichotomized the response score based on the most prognostic minimum of a density plot of the response scores (log-rank HR = 0.16, p = 1.2e(-5)) and validated the profile in the test cohort (one-sided log-rank HR = 0.34, p = 0.026). Analysis of the profile using all samples in the TCGA glioblastoma dataset, regardless of treatment received, (n = 473) showed that the prediction of patient benefit was not significant (HR = 0.84, p = 0.083) suggesting the profile is specific to bevacizumab. Further independent validation of our microRNA profile in RNA-seq data from patients treated with bevacizumab (alone or in combination with CCNU) at glioblastoma recurrence in the BELOB trial confirmed that our microRNA profile predicted patient benefit from bevacizumab (HR = 0.59, p = 0.043). CONCLUSION: We have identified and validated an 8-microRNA profile that predicts overall survival in patients with glioblastoma treated with bevacizumab. This may be useful for identifying patients who are likely to benefit from this agent.

Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation.

Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development.