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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. Subclonal deconvolution in cancer sequencing data is a complex task, and the optimal tools to use are unclear. Here, the authors systematically benchmark subclonal deconvolution pipelines with a comprehensive set of simulated tumour genomes and identify the best-performing methods.

Organismal proteostasis is maintained by intercellular signaling processes including cell nonautonomous stress responses such as transcellular chaperone signaling (TCS). When TCS is activated upon tissue-specific knockdown of hsp-90 in the Caenorhabditis elegans intestine, heat-inducible hsp-70 is induced in muscle cells at the permissive temperature resulting in increased heat stress resistance and lifespan extension. However, our understanding of the molecular mechanism and signaling factors mediating transcellular activation of hsp-70 expression from one tissue to another is still in its infancy. Here, we conducted a combinatorial approach using transcriptome RNA-Seq profiling and a forward genetic mutagenesis screen to elucidate how stress signaling from the intestine to the muscle is regulated. We find that the TCS-mediated “gut-to-muscle” induction of hsp-70 expression is suppressed by HSF-1 and instead relies on transcellular-X-cross-tissue (txt) genes. We identify a key role for the PDZ-domain guanylate cyclase txt-1 and the homeobox transcription factor ceh-58 as signaling hubs in the stress receiving muscle cells to initiate hsp-70 expression and facilitate TCS-mediated heat stress resistance and lifespan extension. Our results provide a new view on cell-nonautonomous regulation of “inter-tissue” stress responses in an organism that highlight a key role for the gut. Our data suggest that the HSF-1–mediated heat shock response is switched off upon TCS activation, in favor of an intercellular stress-signaling route to safeguard survival.

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.

Abbreviations: BN, Bayesian network; BIC, Bayesian information criterion; CPD, conditional probability distribution, CPT, conditional probability table; DAG, directed acyclic graph; DBN, dynamic Bayesian network; EM, expectation-maximisation; HMM, hidden Markov model; JPD, joint probability distribution; MAP;, maximum a posteriori; MCMC, Markov chain Monte Carlo; ML, maximum likelihood Introduction Bayesian networks (BNs) provide a neat and compact representation for expressing joint probability distributions (JPDs) and for inference. A benefit of BNs is that they may be interpreted as a causal model which generated the data. [...]arrows (directed edges) in the DAG can represent causal relations/dependencies between variables.

Cell of origin classification of diffuse large B-cell lymphoma (DLBCL) identifies subsets with biological and clinical significance. Despite the established nature of the classification existing studies display variability in classifier implementation, and a comparative analysis across multiple data sets is lacking. Here we describe the validation of a cell of origin classifier for DLBCL, based on balanced voting between 4 machine-learning tools: the DLBCL automatic classifier (DAC). This shows superior survival separation for assigned Activated B-cell (ABC) and Germinal Center B-cell (GCB) DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. We use DAC to perform a comparative analysis of gene expression in 10 data sets (2030 cases). We generate ranked meta-profiles of genes showing consistent class-association using ≥6 data sets as a cut-off: ABC (414 genes) and GCB (415 genes). The transcription factor ZBTB32 emerges as the most consistent and differentially expressed gene in ABC-DLBCL while other transcription factors such as ARID3A, BATF, and TCF4 are also amongst the 24 genes associated with this class in all datasets. Analysis of enrichment of 12323 gene signatures against meta-profiles and all data sets individually confirms consistent associations with signatures of molecular pathways, chromosomal cytobands, and transcription factor binding sites. We provide DAC as an open access Windows application, and the accompanying meta-analyses as a resource.

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.

Background Brain metastases (BrM) affect up to 60% of patients with metastatic melanoma and are associated with poor prognosis. While combined immune checkpoint blockade of programmed death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) demonstrates intracranial efficacy in a proportion of patients with melanoma, the responses are rarely durable, particularly in patients with symptomatic BrM. The brain is an immune-specialized organ and immune responses are regulated differently to the periphery.Methods Using our previously established two-site model of melanoma BrM with concomitant intracranial and extracranial tumors, in which clinically observed efficacy of the combined PD-1/CTLA-4 (PC) blockade can be reproduced, we here explored the role of natural killer (NK) cells in BrM, using functional studies, immunophenotyping and molecular profiling.Results We demonstrate that NK cells are required for the intracranial efficacy of PC blockade. While both perforin and interferon gamma were necessary for the PC blockade-dependent control of intracranial tumor growth, NK cells isolated from intracranial tumors demonstrated only a limited cancer cell killing ability, and PC blockade did not alter the abundance of NK cells within tumors. However, the depletion of NK cells in PC blockade-treated mice led to tumor molecular profiles reminiscent of those observed in intracranial tumors that failed to respond to therapy. Furthermore, the depletion of NK cells resulted in a strikingly reduced abundance of CD8+ T cells within intracranial tumors, while the abundance of other immune cell populations including CD4+ T cells, macrophages and microglia remained unaltered. Adoptive T cell transfer experiments demonstrated that PC blockade-induced trafficking of CD8+ T cells to intracranial tumors was chemokine-dependent. In line with this, PC blockade enhanced intratumoral expression of several T cell-attracting chemokines and we observed high expression levels of cognate chemokine receptors on BrM-infiltrating CD8+ T cells in mice, as well as in human BrM. Importantly, the depletion of NK cells strikingly reduced the intratumoral expression levels of T cell attracting chemokines and vascular T cell entry receptors that were upregulated following PC blockade.Conclusion Our data demonstrate that NK cells underpin the efficacy of PC blockade in BrM by orchestrating the \"responder\" molecular profile in tumors, and by controlling the intratumoral abundance of CD8+ T cells through regulation of multiple key molecular mediators of T cell trafficking.

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. 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. 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. 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. Janssen-Cilag, Bloodwise, and Cancer Research UK.

In vitro analyses of plant GATA transcription factors have implicated some proteins in light-mediated and circadian-regulated gene expression, and, more recently, the analysis of mutants has uncovered further diverse roles for plant GATA factors. To facilitate function discovery for the 29 GATA genes in Arabidopsis (Arabidopsis thaliana), we have experimentally verified gene structures and determined expression patterns of all family members across adult tissues and suspension cell cultures, as well as in response to light and signals from the circadian clock. These analyses have identified two genes that are strongly developmentally light regulated, expressed predominantly in photosynthetic tissue, and with transcript abundance peaking before dawn. In contrast, several GATA factor genes are light down-regulated. The products of these light-regulated genes are candidates for those proteins previously implicated in light-regulated transcription. Coexpression of these genes with well-characterized light-responsive transcripts across a large microarray data set supports these predictions. Other genes show additional tissue-specific expression patterns suggesting novel and unpredicted roles. Genome-wide analysis using coexpression scatter plots for paralogous gene pairs reveals unexpected differences in cocorrelated gene expression profiles. Clustering the Arabidopsis GATA factor gene family by similarity of expression patterns reveals that genes of recent descent do not uniformly show conserved current expression profiles, yet some genes showing more distant evolutionary origins have acquired common expression patterns. In addition to defining developmental and environmental dynamics of GATA transcript abundance, these analyses offer new insights into the evolution of gene expression profiles following gene duplication events.

We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients. 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. 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). 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. •An 8-microRNA algorithm predicts glioblastoma response to bevacizumab.•The predictive value was bevacizumab specific.•The algorithm was independently validated using BELOB trial patients.