Personalized Pathway Enrichment Map of Putative Cancer Genes from Next Generation Sequencing Data

BACKGROUND: Pathway analysis of a set of genes represents an important area in large-scale omic data analysis. However, the application of traditional pathway enrichment methods to next-generation sequencing (NGS) data is prone to several potential biases, including genomic/genetic factors (e.g., the particular disease and gene length) and environmental factors (e.g., personal life-style and frequency and dosage of exposure to mutagens). Therefore, novel methods are urgently needed for these new data types, especially for individual-specific genome data. METHODOLOGY: In this study, we proposed a novel method for the pathway analysis of NGS mutation data by explicitly taking into account the gene-wise mutation rate. We estimated the gene-wise mutation rate based on the individual-specific background mutation rate along with the gene length. Taking the mutation rate as a weight for each gene, our weighted resampling strategy builds the null distribution for each pathway while matching the gene length patterns. The empirical P value obtained then provides an adjusted statistical evaluation. PRINCIPAL FINDINGS/CONCLUSIONS: We demonstrated our weighted resampling method to a lung adenocarcinomas dataset and a glioblastoma dataset, and compared it to other widely applied methods. By explicitly adjusting gene-length, the weighted resampling method performs as well as the standard methods for significant pathways with strong evidence. Importantly, our method could effectively reject many marginally significant pathways detected by standard methods, including several long-gene-based, cancer-unrelated pathways. We further demonstrated that by reducing such biases, pathway crosstalk for each individual and pathway co-mutation map across multiple individuals can be objectively explored and evaluated. This method performs pathway analysis in a sample-centered fashion, and provides an alternative way for accurate analysis of cancer-personalized genomes. It can be extended to other types of genomic data (genotyping and methylation) that have similar bias problems

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

‘The longest suicide vote in history’: the Labour Party leadership election of 2015

The Labour leadership contest of 2015 resulted in the election of the veteran Left-wing backbencher, Jeremy Corbyn, who clearly defeated the early favourite, Andy Burnham. Yet Corbyn enjoyed very little support among Labour MPs, and his victory plunged the PLP into turmoil, particularly as he was widely viewed as incapable of leading the Party to victory in the 2020 general election. Given that, much of the established academic literature on Party leadership contests emphasises the ability to foster unity, and thereby render a party electable, as two of the key criteria for electing a new leader, coupled with overall competence, important questions are raised about how and why the Labour Party chose someone to lead them who clearly does not meet these criteria. We will argue that whilst these are the natural priorities of MPs when electing a new leader, in Corbyn’s case, much of the extra-parliamentary Labour Party was more concerned about ideological conviction and purity of principles, regardless of how far these diverged from public opinion. This was especially true of those who signed-up to the Labour Party following the 2015 general election defeat. Indeed, many of these only did so after Corbyn had become a candidate. This clearly suggests a serious tension between maximising intra-party democracy and ensuring the electability of the parliamentary party itself

ER-Alpha-cDNA As Part of a Bicistronic Transcript Gives Rise to High Frequency, Long Term, Receptor Expressing Cell Clones

Within the large group of Estrogen Receptor alpha (ERα)-negative breast cancer patients, there is a subgroup carrying the phenotype ERα−, PR−, and Her2−, named accordingly “Triple-Negative” (TN). Using cell lines derived from this TN group, we wished to establish cell clones, in which ERα is ectopically expressed, forming part of a synthetic lethality screening system. Initially, we generated cell transfectants expressing a mono-cistronic ERα transcription unit, adjacent to a separate dominant selectable marker transcription unit. However, the yield of ERα expressing colonies was rather low (5–12.5%), and only about half of these displayed stable ectopic ERα expression over time. Generation and maintenance of such cell clones under minimal exposure to the ERα ligand, did not improve yield or expression stability. Indeed, other groups have also reported grave difficulties in obtaining ectopic expression of ERα in ERα-deficient breast carcinoma cells. We therefore switched to transfecting these cell lines with pERα-IRES, a plasmid vector encoding a bicistronic translation mRNA template: ERα Open Reading Frame (ORF) being upstream followed by a dominant-positive selectable marker (hygroR) ORF, directed for translation from an Internal Ribosome Entry Site (IRES). Through usage of this bicistronic vector linkage system, it was possible to generate a very high yield of ERα expressing cell clones (50–100%). The stability over time of these clones was also somewhat improved, though variations between individual cell clones were evident. Our successful experience with ERα in this system may serve as a paradigm for other genes where ectopic expression meets similar hardships

Epidemiology of Doublet/Multiplet Mutations in Lung Cancers: Evidence that a Subset Arises by Chronocoordinate Events

BACKGROUND: Evidence strongly suggests that spontaneous doublet mutations in normal mouse tissues generally arise from chronocoordinate events. These chronocoordinate mutations sometimes reflect "mutation showers", which are multiple chronocoordinate mutations spanning many kilobases. However, little is known about mutagenesis of doublet and multiplet mutations (domuplets) in human cancer. Lung cancer accounts for about 25% of all cancer deaths. Herein, we analyze the epidemiology of domuplets in the EGFR and TP53 genes in lung cancer. The EGFR gene is an oncogene in which doublets are generally driver plus driver mutations, while the TP53 gene is a tumor suppressor gene with a more typical situation in which doublets derive from a driver and passenger mutation. METHODOLOGY/PRINCIPAL FINDINGS: EGFR mutations identified by sequencing were collected from 66 published papers and our updated EGFR mutation database (www.egfr.org). TP53 mutations were collected from IARC version 12 (www-p53.iarc.fr). For EGFR and TP53 doublets, no clearly significant differences in race, ethnicity, gender and smoking status were observed. Doublets in the EGFR and TP53 genes in human lung cancer are elevated about eight- and three-fold, respectively, relative to spontaneous doublets in mouse (6% and 2.3% versus 0.7%). CONCLUSIONS/SIGNIFICANCE: Although no one characteristic is definitive, the aggregate properties of doublet and multiplet mutations in lung cancer are consistent with a subset derived from chronocoordinate events in the EGFR gene: i) the eight frameshift doublets (present in 0.5% of all patients with EGFR mutations) are clustered and produce a net in-frame change; ii) about 32% of doublets are very closely spaced (< or =30 nt); and iii) multiplets contain two or more closely spaced mutations. TP53 mutations in lung cancer are very closely spaced (< or =30 nt) in 33% of doublets, and multiplets generally contain two or more very closely spaced mutations. Work in model systems is necessary to confirm the significance of chronocoordinate events in lung and other cancers

Knowledge driven decomposition of tumor expression profiles

<p>Abstract</p> <p>Background</p> <p>Tumors have been hypothesized to be the result of a mixture of oncogenic events, some of which will be reflected in the gene expression of the tumor. Based on this hypothesis a variety of data-driven methods have been employed to decompose tumor expression profiles into component profiles, hypothetically linked to these events. Interpretation of the resulting data-driven components is often done by post-hoc comparison to, for instance, functional groupings of genes into gene sets. None of the data-driven methods allow the incorporation of that type of knowledge directly into the decomposition.</p> <p>Results</p> <p>We present a linear model which uses knowledge driven, pre-defined components to perform the decomposition. We solve this decomposition model in a constrained linear least squares fashion. From a variety of options, a lasso-based solution to the model performs best in linking single gene perturbation data to mouse data. Moreover, we show the decomposition of expression profiles from human breast cancer samples into single gene perturbation profiles and gene sets that are linked to the hallmarks of cancer. For these breast cancer samples we were able to discern several links between clinical parameters, and the decomposition weights, providing new insights into the biology of these tumors. Lastly, we show that the order in which the Lasso regularization shrinks the weights, unveils consensus patterns within clinical subgroups of the breast cancer samples.</p> <p>Conclusion</p> <p>The proposed lasso-based constrained least squares decomposition provides a stable and relevant relation between samples and knowledge-based components, and is thus a viable alternative to data-driven methods. In addition, the consensus order of component importance within clinical subgroups provides a better molecular characterization of the subtypes.</p

2-Hydroxyglutarate Production, but Not Dominant Negative Function, Is Conferred by Glioma-Derived NADP+-Dependent Isocitrate Dehydrogenase Mutations

Gliomas frequently contain mutations in the cytoplasmic NADP(+)-dependent isocitrate dehydrogenase (IDH1) or the mitochondrial NADP(+)-dependent isocitrate dehydrogenase (IDH2). Several different amino acid substitutions recur at either IDH1 R132 or IDH2 R172 in glioma patients. Genetic evidence indicates that these mutations share a common gain of function, but it is unclear whether the shared function is dominant negative activity, neomorphic production of (R)-2-hydroxyglutarate (2HG), or both.We show by coprecipitation that five cancer-derived IDH1 R132 mutants bind IDH1-WT but that three cancer-derived IDH2 R172 mutants exert minimal binding to IDH2-WT. None of the mutants dominant-negatively lower isocitrate dehydrogenase activity at physiological (40 µM) isocitrate concentrations in mammalian cell lysates. In contrast to this, all of these mutants confer 10- to 100-fold higher 2HG production to cells, and glioma tissues containing IDH1 R132 or IDH2 R172 mutations contain high levels of 2HG compared to glioma tissues without IDH mutations (54.4 vs. 0.1 mg 2HG/g protein).Binding to, or dominant inhibition of, WT IDH1 or IDH2 is not a shared feature of the IDH1 and IDH2 mutations, and thus is not likely to be important in cancer. The fact that the gain of the enzymatic activity to produce 2HG is a shared feature of the IDH1 and IDH2 mutations suggests that this is an important function for these mutants in driving cancer pathogenesis