Impaired expression of NER gene network in sporadic solid tumors

Nucleotide repair genes are not generally altered in sporadic solid tumors. However, point mutations are found scattered throughout the genome of cancer cells indicating that the repair pathways are dysfunctional. To address this point, in this work we focus on the expression pathways rather than in the DNA structure of repair genes related to either genome stability or essential metabolic functions. We present here a novel statistical analysis comparing ten gene expression pathways in human normal and cancer cells using serial analysis of gene expression (SAGE) data. We find that in cancer cells nucleotide-excision repair (NER) and apoptosis are the most impaired pathways and have a highly altered diversity of gene expression profile when compared to normal cells. We propose that genome point mutations in sporadic tumors can be explained by a structurally conserved NER with a functional disorder generated from its entanglement with the apoptosis gene network

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

Functional Analysis of a Breast Cancer-Associated Mutation in the Intracellular Domain of the Metalloprotease ADAM12

A recently identified breast cancer-associated mutation in the metalloprotease ADAM12 alters a potential dileucine trafficking signal, which could affect protein processing and cellular localization. ADAM12 belongs to the group of A Disintegrin And Metalloproteases (ADAMs), which are typically membrane-associated proteins involved in ectodomain shedding, cell-adhesion, and signaling. ADAM12 as well as several members of the ADAM family are over-expressed in various cancers, correlating with disease stage. Three breast cancer-associated somatic mutations were previously identified in ADAM12, and two of these, one in the metalloprotease domain and another in the disintegrin domain, were investigated and found to result in protein misfolding, retention in the secretory pathway, and failure of zymogen maturation. The third mutation, p.L792F in the ADAM12 cytoplasmic tail, was not investigated, but is potentially significant given its location within a di-leucine motif, which is recognized as a potential cellular trafficking signal. The present study was motivated both by the potential relevance of this documented mutation to cancer, as well as for determining the role of the di-leucine motif in ADAM12 trafficking. Expression of ADAM12 p.L792F in mammalian cells demonstrated quantitatively similar expression levels and zymogen maturation as wild-type (WT) ADAM12, as well as comparable cellular localizations. A cell surface biotinylation assay demonstrated that cell surface levels of ADAM12 WT and ADAM12 p.L792F were similar and that internalization of the mutant occurred at the same rate and extent as for ADAM12 WT. Moreover, functional analysis revealed no differences in cell proliferation or ectodomain shedding of epidermal growth factor (EGF), a known ADAM12 substrate between WT and mutant ADAM12. These data suggest that the ADAM12 p.L792F mutation is unlikely to be a driver (cancer causing)-mutation in breast cancer

Alterations of the retinoblastoma gene in metastatic breast cancer

Germline mutations affecting the retinoblastoma gene (RB1) predispose to inherited retinoblastomas but also other malignancies, including breast cancer. While somatic RB1 mutations have been detected in different malignancies, information about the potential role of RB1 mutations in breast cancer is limited. Recently, we discovered RB1 mutations to be associated with resistance to anthracyclines/mitomycin in primary breast cancer. The present work is the first report evaluating RB1 mutation and epigenetic status in metastatic breast cancer. Among 148 breast cancer samples analyzed by MLPA, four samples harbored intragenic deletions/duplications: Thus, exons 1–2 were deleted in two tumors and exons 21–23 in one tumor, while one sample harbored duplication of exons 18–23. The entire RB1 gene was duplicated in two tumors and multiple amplifications were revealed in one sample. Reduced copy number was observed in 17 samples (11.5%). No point mutation or promoter hypermethylation was discovered (n = 38 and 114 tumors analyzed, respectively). Interestingly, among seven tumors expressing lack of response to epirubicin, two samples harbored alterations in RB1, contrasting none out of 16 tumors with stable disease or an objective response (P = 0.08). In summary, the frequency of RB1 alterations in metastatic lesions was not increased when compared to primary breast cancer, indicating that RB1 alterations do not play a major role in metastatic development. While a non-significant association suggesting RB1 alterations to be linked to therapy resistance was observed, our data do not suggest a major role for RB1 alterations explaining acquired drug resistance

Transcription factor 7-like 2 (TCF7L2) variant is associated with familial breast cancer risk: a case-control study

BACKGROUND: The transcription factor 7-like 2 (TCF7L2) is a critical component of the Wnt/β-catenin pathway. Aberrant TCF7L2 expression modifies Wnt signaling and mediates oncogenic effects through the upregulation of c-MYC and cyclin D. Genetic alterations in TCF7L2 may therefore affect cancer risk. Recently, TCF7L2 variants, including the microsatellite marker DG10S478 and the nearly perfectly linked SNP rs12233372, were identified to associate with type 2 diabetes. METHODS: We investigated the effect of the TCF7L2 rs12255372 variant on familial breast cancer (BC) risk by means of TaqMan allelic discrimination, analyzing BRCA1/2 mutation-negative index patients of 592 German BC families and 735 control individuals. RESULTS: The T allele of rs12255372 showed an association with borderline significance (OR = 1.19, 95% C.I. = 1.01-1.42, P = 0.04), and the Cochran-Armitage test for trend revealed an allele dose-dependent association of rs12255372 with BC risk (P(trend )= 0.04). CONCLUSION: Our results suggest a possible influence of TCF7L2 rs12255372 on the risk of familial BC

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

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

Studying Early Lethality of 45,XO (Turner's Syndrome) Embryos Using Human Embryonic Stem Cells

Turner's syndrome (caused by monosomy of chromosome X) is one of the most common chromosomal abnormalities in females. Although 3% of all pregnancies start with XO embryos, 99% of these pregnancies terminate spontaneously during the first trimester. The common genetic explanation for the early lethality of monosomy X embryos, as well as the phenotype of surviving individuals is haploinsufficiency of pseudoautosomal genes on the X chromosome. Another possible mechanism is null expression of imprinted genes on the X chromosome due to the loss of the expressed allele. In contrast to humans, XO mice are viable, and fertile. Thus, neither cells from patients nor mouse models can be used in order to study the cause of early lethality in XO embryos. Human embryonic stem cells (HESCs) can differentiate in culture into cells from the three embryonic germ layers as well as into extraembryonic cells. These cells have been shown to have great value in modeling human developmental genetic disorders. In order to study the reasons for the early lethality of 45,XO embryos we have isolated HESCs that have spontaneously lost one of their sex chromosomes. To examine the possibility that imprinted genes on the X chromosome play a role in the phenotype of XO embryos, we have identified genes that were no longer expressed in the mutant cells. None of these genes showed a monoallelic expression in XX cells, implying that imprinting is not playing a major role in the phenotype of XO embryos. To suggest an explanation for the embryonic lethality caused by monosomy X, we have differentiated the XO HESCs in vitro an in vivo. DNA microarray analysis of the differentiated cells enabled us to compare the expression of tissue specific genes in XO and XX cells. The tissue that showed the most significant differences between the clones was the placenta. Many placental genes are expressed at much higher levels in XX cells in compare to XO cells. Thus, we suggest that abnormal placental differentiation as a result of haploinsufficiency of X-linked pseudoautosomal genes causes the early lethality in XO human embryos

Exon expression arrays as a tool to identify new cancer genes

Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes

GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

We describe methods with enhanced power and specificity to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth. By separating SCNA profiles into underlying arm-level and focal alterations, we improve the estimation of background rates for each category. We additionally describe a probabilistic method for defining the boundaries of selected-for SCNA regions with user-defined confidence. Here we detail this revised computational approach, GISTIC2.0, and validate its performance in real and simulated datasets