Neuroblastic tumours may occur in a predisposition context. Two main genes are involved: PHOX2B, observed in familial cases and frequently associated with other neurocristopathies (Ondine's and Hirschsprung's disease); and ALK, mostly in familial tumours. We have assessed the frequency of mutations of these two genes in patients with a presumable higher risk of predisposition. We sequenced both genes in 26 perinatal cases (prebirth and <1 month of age, among which 10 were multifocal), 16 multifocal postnatal (>1 month) cases, 3 pairs of affected relatives and 8 patients with multiple malignancies. The whole coding sequences of the two genes were analysed in tumour and/or constitutional DNAs. We found three ALK germline mutations, all in a context of multifocal tumours. Two mutations (T1151R and R1192P) were inherited and shared by several unaffected patients, thus illustrating an incomplete penetrance. Younger age at tumour onset did not seem to offer a relevant selection criterion for ALK analyses. Conversely, multifocal tumours might be the most to benefit from the genetic screening. Finally, no PHOX2B germline mutation was found in this series. In conclusion, ALK deleterious mutations are rare events in patients with a high probability of predisposition. Other predisposing genes remain to be discovered.

Pediatric medulloblastoma is considered a highly heterogeneous disease and a new strategy of risk stratification to optimize therapeutic outcomes is required. We aimed to investigate a new risk-stratification approach based on expression profiles of medulloblastoma cohorts. We analyzed gene expression profiles of 30 primary medulloblastomas and detected strong evidence that poor survival outcome was significantly associated with mRNA expression profiles of 17p loss. However, it was not supported in independent cohorts from previously published data (n = 100). We speculated that this discrepancy might come from complex conditions of two important prognostic determinants: loss of tumor suppressors (chromosome 17p) and high expression of oncogenes c-myc (MYCC) or N-myc (MYCN). When patients were stratified into 5 or 7 subgroups based on simultaneous consideration of these 2 factors while defining the Wnt group as independent, obviously different survival expectancies were detected between the subgroups. For instance, predicted 5-year survival probabilities ranged from 19% to 81% in the 5 subgroups. We also found that age became a significant prognostic marker after adjusting for 17p, MYCC, and MYCN status. Diminished survival in age <3 years was more substantial in subgroups with high expression of MYCC, MYCN, or 17p loss but not in other subgroups, indicating that poor survival outcome might be synergistically affected by these 3 factors. Here we suggest a more tailored subgrouping system based on expression profiles of chromosome 17p, MYCC, and MYCN, which could provide the basis for a novel risk-stratification strategy in pediatric medulloblastoma.

Background

Social parasitism is an important selective pressure for social insect species. It is particularly the case for the hosts of dulotic (so called slave-making) ants, which pillage the brood of host colonies to increase the worker force of their own colony. Such raids can have an important impact on the fitness of the host nest. An arms race which can lead to geographic variation in host defenses is thus expected between hosts and parasites. In this study we tested whether the presence of a social parasite (the dulotic ant Myrmoxenus ravouxi) within an ant community correlated with a specific behavioral defense strategy of local host or non-host populations of Temnothorax ants. Social recognition often leads to more or less pronounced agonistic interactions between non-nestmates ants. Here, we monitored agonistic behaviors to assess whether ants discriminate social parasites from other ants. It is now well-known that ants essentially rely on cuticular hydrocarbons to discriminate nestmates from aliens. If host species have evolved a specific recognition mechanism for their parasite, we hypothesize that the differences in behavioral responses would not be fully explained simply by quantitative dissimilarity in cuticular hydrocarbon profiles, but should also involve a qualitative response due to the detection of particular compounds. We scaled the behavioral results according to the quantitative chemical distance between host and parasite colonies to test this hypothesis.

Results

Cuticular hydrocarbon profiles were distinct between species, but host species did not show a clearly higher aggression rate towards the parasite than toward non-parasite intruders, unless the degree of response was scaled by the chemical distance between intruders and recipient colonies. By doing so, we show that workers of the host and of a non-host species in the parasitized site displayed more agonistic behaviors (bites and ejections) towards parasite than toward non-parasite intruders.

Conclusions

We used two different analyses of our behavioral data (standardized with the chemical distance between colonies or not) to test our hypothesis. Standardized data show behavioral differences which could indicate qualitative and specific parasite recognition. We finally stress the importance of considering the whole set of potentially interacting species to understand the coevolution between social parasites and their hosts.

High Content Screening (HCS) platforms allow screening living cells under a wide range of experimental conditions and give access to a whole panel of cellular responses to a specific treatment. The outcome is a series of cell population images. Within these images, the heterogeneity of cellular response to the same treatment leads to a whole range of observed values for the recorded cellular features. Consequently, it is difficult to compare and interpret experiments. Moreover, the definition of phenotypic classes at a cell population level remains an open question, although this would ease experiments analyses. In the present work, we tackle these two questions. The input of the method is a series of cell population images for which segmentation and cellular phenotype classification has already been performed. We propose a probabilistic model to represent and later compare cell populations. The model is able to fully exploit the HCS-specific information: “dependence structure of population descriptors” and “within-population variability”. The experiments we carried out illustrate how our model accounts for this specific information, as well as the fact that the model benefits from considering them. We underline that these features allow richer HCS data analysis than simpler methods based on single cellular feature values averaged over each well. We validate an HCS data analysis method based on control experiments. It accounts for HCS specificities that were not taken into account by previous methods but have a sound biological meaning. Biological validation of previously unknown outputs of the method constitutes a future line of work.

MicroRNAs (miRNAs) have emerged as fundamental regulators that silence gene expression at the post-transcriptional and translational levels. The identification of their targets is a major challenge to elucidate the regulated biological processes. The overall effect of miRNA is reflected on target mRNA expression, suggesting the design of new investigative methods based on high-throughput experimental data such as miRNA and transcriptome profiles. We propose a novel statistical measure of non-linear dependence between miRNA and mRNA expression, in order to infer miRNA-target interactions. This approach, which we name antagonism pattern detection, is based on the statistical recognition of a triangular-shaped pattern in miRNA-target expression profiles. This pattern is observed in miRNA-target expression measurements since their simultaneously elevated expression is statistically under-represented in the case of miRNA silencing effect. The proposed method enables miRNA target prediction to strongly rely on cellular context and physiological conditions reflected by expression data. The procedure has been assessed on synthetic datasets and tested on a set of real positive controls. Then it has been applied to analyze expression data from Ewing’s sarcoma patients. The antagonism relationship is evaluated as a good indicator of real miRNA-target biological interaction. The predicted targets are consistently enriched for miRNA binding site motifs in their 3′UTR. Moreover, we reveal sets of predicted targets for each miRNA sharing important biological function. The procedure allows us to infer crucial miRNA regulators and their potential targets in Ewing’s sarcoma disease. It can be considered as a valid statistical approach to discover new insights in the miRNA regulatory mechanisms.

Purpose

Medulloblastomas are heterogeneous tumors that collectively represent the most common malignant brain tumor in children. To understand the molecular characteristics underlying their heterogeneity and to identify whether such characteristics represent risk factors for patients with this disease, we performed an integrated genomic analysis of a large series of primary tumors.

Patients and Methods

We profiled the mRNA transcriptome of 194 medulloblastomas and performed high-density single nucleotide polymorphism array and miRNA analysis on 115 and 98 of these, respectively. Non-negative matrix factorization–based clustering of mRNA expression data was used to identify molecular subgroups of medulloblastoma; DNA copy number, miRNA profiles, and clinical outcomes were analyzed for each. We additionally validated our findings in three previously published independent medulloblastoma data sets.

Results

Identified are six molecular subgroups of medulloblastoma, each with a unique combination of numerical and structural chromosomal aberrations that globally influence mRNA and miRNA expression. We reveal the relative contribution of each subgroup to clinical outcome as a whole and show that a previously unidentified molecular subgroup, characterized genetically by c-MYC copy number gains and transcriptionally by enrichment of photoreceptor pathways and increased miR-183∼96∼182 expression, is associated with significantly lower rates of event-free and overall survivals.

Conclusion

Our results detail the complex genomic heterogeneity of medulloblastomas and identify a previously unrecognized molecular subgroup with poor clinical outcome for which more effective therapeutic strategies should be developed.

Recently, activating mutations of the full length ALK receptor, with two hot spots at positions F1174 and R1275, have been characterized in sporadic cases of neuroblastoma. Here, we report similar basal patterns of ALK phosphorylation between the neuroblastoma IMR-32 cell line, which expresses only the wild-type receptor (ALKWT), and the SH-SY5Y cell line, which exhibits a heterozygous ALK F1174L mutation and expresses both ALKWT and ALKF1174L receptors. We demonstrate that this lack of detectable increased phosphorylation in SH-SY5Y cells is a result of intracellular retention and proteasomal degradation of the mutated receptor. As a consequence, in SH-SY5Y cells, plasma membrane appears strongly enriched for ALKWT whereas both ALKWT and ALKF1174L were present in intracellular compartments. We further explored ALK receptor trafficking by investigating the effect of agonist and antagonist mAb (monoclonal antibodies) on ALK internalization and down-regulation, either in SH-SY5Y cells or in cells expressing only ALKWT. We observe that treatment with agonist mAbs resulted in ALK internalization and lysosomal targeting for receptor degradation. In contrast, antagonist mAb induced ALK internalization and recycling to the plasma membrane. Importantly, we correlate this differential trafficking of ALK in response to mAb with the recruitment of the ubiquitin ligase Cbl and ALK ubiquitylation only after agonist stimulation. This study provides novel insights into the mechanisms regulating ALK trafficking and degradation, showing that various ALK receptor pools are regulated by proteasome or lysosome pathways according to their intracellular localization.

Medulloblastoma is the most common malignant brain tumor in childhood. Molecular studies from several groups around the world demonstrated that medulloblastoma is not one disease but comprises a collection of distinct molecular subgroups. However, all these studies reported on different numbers of subgroups. The current consensus is that there are only four core subgroups, which should be termed WNT, SHH, Group 3 and Group 4. Based on this, we performed a meta-analysis of all molecular and clinical data of 550 medulloblastomas brought together from seven independent studies. All cases were analyzed by gene expression profiling and for most cases SNP or array-CGH data were available. Data are presented for all medulloblastomas together and for each subgroup separately. For validation purposes, we compared the results of this meta-analysis with another large medulloblastoma cohort (n = 402) for which subgroup information was obtained by immunohistochemistry. Results from both cohorts are highly similar and show how distinct the molecular subtypes are with respect to their transcriptome, DNA copy-number aberrations, demographics, and survival. Results from these analyses will form the basis for prospective multi-center studies and will have an impact on how the different subgroups of medulloblastoma will be treated in the future.

Electronic supplementary material

The online version of this article (doi:10.1007/s00401-012-0958-8) contains supplementary material, which is available to authorized users.

Introduction

Identification of new therapeutic agents for breast cancer (BC) requires preclinical models that reproduce the molecular characteristics of their respective clinical tumors. In this work, we analyzed the genomic and gene expression profiles of human BC xenografts and the corresponding patient tumors.

Methods

Eighteen BC xenografts were obtained by grafting tumor fragments from patients into Swiss nude mice. Molecular characterization of patient tumors and xenografts was performed by DNA copy number analysis and gene expression analysis using Affymetrix Microarrays.

Results

Comparison analysis showed that 14/18 pairs of tumors shared more than 56% of copy number alterations (CNA). Unsupervised hierarchical clustering analysis showed that 16/18 pairs segregated together, confirming the similarity between tumor pairs. Analysis of recurrent CNA changes between patient tumors and xenografts showed losses in 176 chromosomal regions and gains in 202 chromosomal regions. Gene expression profile analysis showed that less than 5% of genes had recurrent variations between patient tumors and their respective xenografts; these genes largely corresponded to human stromal compartment genes. Finally, analysis of different passages of the same tumor showed that sequential mouse-to-mouse tumor grafts did not affect genomic rearrangements or gene expression profiles, suggesting genetic stability of these models over time.

Conclusions

This panel of human BC xenografts maintains the overall genomic and gene expression profile of the corresponding patient tumors and remains stable throughout sequential in vivo generations. The observed genomic profile and gene expression differences appear to be due to the loss of human stromal genes. These xenografts, therefore, represent a validated model for preclinical investigation of new therapeutic agents.

The European Network for Cancer Research in Children and Adolescents (ENCCA) provides an interaction platform for stakeholders in research and care of children with cancer. Among ENCCA objectives is the establishment of biology-based prioritization mechanisms for the selection of innovative targets, drugs, and prognostic markers for validation in clinical trials. Specifically for sarcomas, there is a burning need for novel treatment options, since current chemotherapeutic treatment protocols have met their limits. This is most obvious for metastatic Ewing sarcoma (ES), where long term survival rates are still below 20%. Despite significant progress in our understanding of ES biology, clinical translation of promising laboratory results has not yet taken place due to fragmentation of research and lack of an institutionalized discussion forum. To fill this gap, ENCCA assembled 30 European expert scientists and five North American opinion leaders in December 2011 to exchange thoughts and discuss the state of the art in ES research and latest results from the bench, and to propose biological studies and novel promising therapeutics for the upcoming European EWING2008 and EWING2012 clinical trials.

Summary: More and more cancer studies use next-generation sequencing (NGS) data to detect various types of genomic variation. However, even when researchers have such data at hand, single-nucleotide polymorphism arrays have been considered necessary to assess copy number alterations and especially loss of heterozygosity (LOH). Here, we present the tool Control-FREEC that enables automatic calculation of copy number and allelic content profiles from NGS data, and consequently predicts regions of genomic alteration such as gains, losses and LOH. Taking as input aligned reads, Control-FREEC constructs copy number and B-allele frequency profiles. The profiles are then normalized, segmented and analyzed in order to assign genotype status (copy number and allelic content) to each genomic region. When a matched normal sample is provided, Control-FREEC discriminates somatic from germline events. Control-FREEC is able to analyze overdiploid tumor samples and samples contaminated by normal cells. Low mappability regions can be excluded from the analysis using provided mappability tracks.

Availability: C++ source code is available at: http://bioinfo.curie.fr/projects/freec/

Contact: freec@curie.fr

Supplementary information: Supplementary data are available at Bioinformatics online.

BACKGROUND

More accurate prognostic assessment of patients with neuroblastoma is required to improve the choice of risk-related therapy. The aim of this study is to develop and validate a gene expression signature for improved outcome prediction.

METHODS

Fifty-nine genes were carefully selected based on an innovative data-mining strategy and profiled in the largest neuroblastoma patient series (n=579) to date using RT-qPCR starting from only 20 ng of RNA. A multigene expression signature was built using 30 training samples, tested on 313 test samples and subsequently validated in a blind study on an independent set of 236 additional tumours.

FINDINGS

The signature accurately classifies patients with respect to overall and progression-free survival (p<0·0001). The signature has a performance, sensitivity, and specificity of 85·4% (95%CI: 77·7–93·2), 84·4% (95%CI: 66·5–94·1), and 86·5% (95%CI: 81·1–90·6), respectively to predict patient outcome. Multivariate analysis indicates that the signature is a significant independent predictor after controlling for currently used riskfactors. Patients with high molecular risk have a higher risk to die from disease and for relapse/progression than patients with low molecular risk (odds ratio of 19·32 (95%CI: 6·50–57·43) and 3·96 (95%CI: 1·97–7·97) for OS and PFS, respectively). Patients with increased risk for adverse outcome can also be identified within the current treatment groups demonstrating the potential of this signature for improved clinical management. These results were confirmed in the validation study in which the signature was also independently statistically significant in a model adjusted for MYCN status, age, INSS stage, ploidy, INPC grade of differentiation, and MKI. The high patient/gene ratio (579/59) underlies the observed statistical power and robustness.

INTERPRETATION

A 59-gene expression signature predicts outcome of neuroblastoma patients with high accuracy. The signature is an independent risk predictor, identifying patients with increased risk in the current clinical risk groups. The applied method and signature is suitable for routine lab testing and ready for evaluation in prospective studies.

FUNDING

The Belgian Foundation Against Cancer, found of public interest (project SCIE2006-25), the Children Cancer Fund Ghent, the Belgian Society of Paediatric Haematology and Oncology, the Belgian Kid’s Fund and the Fondation Nuovo-Soldati (JV), the Fund for Scientific Research Flanders (KDP, JH), the Fund for Scientific Research Flanders (grant number: G•0198•08), the Institute for the Promotion of Innovation by Science and Technology in Flanders, Strategisch basisonderzoek (IWT-SBO 60848), the Fondation Fournier Majoie pour l’Innovation, the Instituto Carlos III,RD 06/0020/0102 Spain, the Italian Neuroblastoma Foundation, the European Community under the FP6 (project: STREP: EET-pipeline, number: 037260), and the Belgian program of Interuniversity Poles of Attraction, initiated by the Belgian State, Prime Minister's Office, Science Policy Programming.

Available data on genetic events in pediatric grade IV astrocytomas (glioblastoma [pGBM]) are scarce. This has traditionally been a major impediment in understanding the pathogenesis of this tumor and in developing ways for more effective management. Our aim is to chart DNA copy number aberrations (CNAs) and get insight into genetic pathways involved in pGBM. Using the Illumina Infinium Human-1 bead-chip-array (100K single-nucleotide polymorphisms [SNPs]), we genotyped 18 pediatric and 6 adult GBMs. Results were compared to BAC-array profiles harvested on 16 of the same pGBM, to an independent data set of 9 pediatric high-grade astrocytomas (HGAs) analyzed on Affymetrix 250K-SNP arrays, and to existing data sets on HGAs. CNAs were additionally validated by real-time qPCR in a set of genes in pGBM. Our results identify with nonrandom clustering of CNAs in several novel, previously not reported, genomic regions, suggesting that alterations in tumor suppressors and genes involved in the regulation of RNA processing and the cell cycle are major events in the pathogenesis of pGBM. Most regions were distinct from CNAs in aGBMs and show an unexpectedly low frequency of genetic amplification and homozygous deletions and a high frequency of loss of heterozygosity for a high-grade I rapidly dividing tumor. This first, complete, high-resolution profiling of the tumor cell genome fills an important gap in studies on pGBM. It ultimately guides the mapping of oncogenic networks unique to pGBM, identification of the related therapeutic predictors and targets, and development of more effective therapies. It further shows that, despite commonalities in a few CNAs, pGBM and aGBMs are two different diseases.

Summary: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs.

Availability: Source code and sample data are available at http://bioinfo-out.curie.fr/projects/freec/.

Contact: freec@curie.fr

Supplementary information: Supplementary data are available at Bioinformatics online.

Background

A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level.

Results

We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation.

Conclusions

The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.

Despite similar morphological aspects, anaplastic oligodendroglial tumors (AOTs) form a heterogeneous clinical subgroup of gliomas. The chromosome arms 1p/19q codeletion has been shown to be a relevant biomarker in AOTs and to be perfectly exclusive from EGFR amplification in gliomas. To identify new genomic regions associated with prognosis, 60 AOTs from the EORTC trial 26951 were analyzed retrospectively using BAC-array-based comparative genomic hybridization. The data were processed using a binary tree method. Thirty-three BACs with prognostic value were identified distinguishing four genomic subgroups of AOTs with different prognosis (p < 0.0001). Type I tumors (25%) were characterized by: (1) an EGFR amplification, (2) a poor prognosis, (3) a higher rate of necrosis, and (4) an older age of patients. Type II tumors (21.7%) had: (1) loss of prognostic BACs located on 1p tightly associated with 19q deletion, (2) a longer survival, (3) an oligodendroglioma phenotype, and (4) a frontal location in brain. Type III AOTs (11.7%) exhibited: (1) a deletion of prognostic BACs located on 21q, and (2) a short survival. Finally, type IV tumors (41.7%) had different genomic patterns and prognosis than type I, II and III AOTs. Multivariate analysis showed that genomic type provides additional prognostic data to clinical, imaging and pathological features. Similar results were obtained in the cohort of 45 centrally reviewed–validated cases of AOTs. Whole genome analysis appears useful to screen the numerous genomic abnormalities observed in AOTs and to propose new biomarkers particularly in the non-1p/19q codeleted AOTs.

Electronic supplementary material

The online version of this article (doi:10.1007/s11060-010-0380-9) contains supplementary material, which is available to authorized users.

Summary: We present SVDetect, a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms. Applying both sliding-window and clustering strategies, we use anomalously mapped read pairs provided by current short read aligners to localize genomic rearrangements and classify them according to their type, e.g. large insertions–deletions, inversions, duplications and balanced or unbalanced inter-chromosomal translocations. SVDetect outputs predicted structural variants in various file formats for appropriate graphical visualization.

Availability: Source code and sample data are available at http://svdetect.sourceforge.net/

Contact: svdetect@curie.fr

Supplementary information: Supplementary data are available at Bioinformatics online.

JunD regulates genes involved in antioxidant defence. We took advantage of the chronic oxidative stress resulting from junD deletion to examine the role of reactive oxygen species (ROS) in tumour development. In a model of mammary carcinogenesis, junD inactivation increased tumour incidence and revealed an associated reactive stroma. junD-inactivation in the stroma was sufficient to shorten tumour-free survival rate and enhance metastatic spread. ROS promoted conversion of fibroblasts into highly migrating myofibroblasts through accumulation of the hypoxia-inducible factor (HIF)-1α transcription factor and the CXCL12 chemokine. Accordingly, treatment with an antioxidant reduced the levels of HIF and CXCL12 and numerous myofibroblast features. CXCL12 accumulated in the stroma of HER2-human breast adenocarcinomas. Moreover, HER2 tumours exhibited a high proportion of myofibroblasts, which was significantly correlated to nodal metastases. Interestingly, this subset of tumours exhibited a significant nuclear exclusion of JunD and revealed an associated oxido-reduction signature, further demonstrating the relevance of our findings in human cancers. Collectively, our data uncover a new mechanism by which oxidative stress increases the migratory properties of stromal fibroblasts, which in turn potentiate tumour dissemination.

Dramatic progress in the development of next-generation sequencing technologies has enabled accurate genome-wide characterization of the binding sites of DNA-associated proteins. This technique, baptized as ChIP-Seq, uses a combination of chromatin immunoprecipitation and massively parallel DNA sequencing. Other published tools that predict binding sites from ChIP-Seq data use only positional information of mapped reads. In contrast, our algorithm MICSA (Motif Identification for ChIP-Seq Analysis) combines this source of positional information with information on motif occurrences to better predict binding sites of transcription factors (TFs). We proved the greater accuracy of MICSA with respect to several other tools by running them on datasets for the TFs NRSF, GABP, STAT1 and CTCF. We also applied MICSA on a dataset for the oncogenic TF EWS-FLI1. We discovered >2000 binding sites and two functionally different binding motifs. We observed that EWS-FLI1 can activate gene transcription when (i) its binding site is located in close proximity to the gene transcription start site (up to ∼150 kb), and (ii) it contains a microsatellite sequence. Furthermore, we observed that sites without microsatellites can also induce regulation of gene expression—positively as often as negatively—and at much larger distances (up to ∼1 Mb).

Background

Breast cancer is a heterogeneous disease that is not totally eradicated by current therapies. The classification of breast tumors into distinct molecular subtypes by gene profiling and immunodetection of surrogate markers has proven useful for tumor prognosis and prediction of effective targeted treatments. The challenge now is to identify molecular biomarkers that may be of functional relevance for personalized therapy of breast tumors with poor outcome that do not respond to available treatments. The Mitochondrial Tumor Suppressor (MTUS1) gene is an interesting candidate whose expression is reduced in colon, pancreas, ovary and oral cancers. The present study investigates the expression and functional effects of MTUS1 gene products in breast cancer.

Methods and Findings

By means of gene array analysis, real-time RT-PCR and immunohistochemistry, we show here that MTUS1/ATIP3 is significantly down-regulated in a series of 151 infiltrating breast cancer carcinomas as compared to normal breast tissue. Low levels of ATIP3 correlate with high grade of the tumor and the occurrence of distant metastasis. ATIP3 levels are also significantly reduced in triple negative (ER- PR- HER2-) breast carcinomas, a subgroup of highly proliferative tumors with poor outcome and no available targeted therapy. Functional studies indicate that silencing ATIP3 expression by siRNA increases breast cancer cell proliferation. Conversely, restoring endogenous levels of ATIP3 expression leads to reduced cancer cell proliferation, clonogenicity, anchorage-independent growth, and reduces the incidence and size of xenografts grown in vivo. We provide evidence that ATIP3 associates with the microtubule cytoskeleton and localizes at the centrosomes, mitotic spindle and intercellular bridge during cell division. Accordingly, live cell imaging indicates that ATIP3 expression alters the progression of cell division by promoting prolonged metaphase, thereby leading to a reduced number of cells ungergoing active mitosis.

Conclusions

Our results identify for the first time ATIP3 as a novel microtubule-associated protein whose expression is significantly reduced in highly proliferative breast carcinomas of poor clinical outcome. ATIP3 re-expression limits tumor cell proliferation in vitro and in vivo, suggesting that this protein may represent a novel useful biomarker and an interesting candidate for future targeted therapies of aggressive breast cancer.

Background

Through negative regulation of gene expression, microRNAs (miRNAs) can function in cancers as oncosuppressors, and they can show altered expression in various tumor types. Here we have investigated medulloblastoma tumors (MBs), which arise from an early impairment of developmental processes in the cerebellum, where Notch signaling is involved in many cell-fate-determining stages. MBs occur bimodally, with the peak incidence seen between 3–4 years and 8–9 years of age, although it can also occur in adults. Notch regulates a subset of the MB cells that have stem-cell-like properties and can promote tumor growth. On the basis of this evidence, we hypothesized that miRNAs targeting the Notch pathway can regulated these phenomena, and can be used in anti-cancer therapies.

Methodology/Principal Findings

In a screening of MB cell lines, the miRNA miR-199b-5p was seen to be a regulator of the Notch pathway through its targeting of the transcription factor HES1. Down-regulation of HES1 expression by miR-199b-5p negatively regulates the proliferation rate and anchorage-independent growth of MB cells. MiR-199b-5p over-expression blocks expression of several cancer stem-cell genes, impairs the engrafting potential of MB cells in the cerebellum of athymic/nude mice, and of particular interest, decreases the MB stem-cell-like (CD133+) subpopulation of cells. In our analysis of 61 patients with MB, the expression of miR-199b-5p in the non-metastatic cases was significantly higher than in the metastatic cases (P = 0.001). Correlation with survival for these patients with high levels of miR-199b expression showed a positive trend to better overall survival than for the low-expressing patients. These data showing the down-regulation of miR-199b-5p in metastatic MBs suggest a potential silencing mechanism through epigenetic or genetic alterations. Upon induction of de-methylation using 5-aza-deoxycytidine, lower miR-199b-5p expression was seen in a panel of MB cell lines, supported an epigenetic mechanism of regulation. Furthermore, two cell lines (Med8a and UW228) showed significant up-regulation of miR-199b-5p upon treatment. Infection with MB cells in an induced xenograft model in the mouse cerebellum and the use of an adenovirus carrying miR-199b-5p indicate a clinical benefit through this negative influence of miR-199b-5p on tumor growth and on the subset of MB stem-cell-like cells, providing further proof of concept.

Conclusions/Significance

Despite advances in our understanding of the pathogenesis of MB, one-third of these patients remain incurable and current treatments can significantly damage long-term survivors. Here we show that miR-199b-5p expression correlates with metastasis spread, identifying a new molecular marker for a poor-risk class in patients with MB. We further show that in a xenograft model, MB tumor burden can be reduced, indicating the use of miR199b-5p as an adjuvant therapy after surgery, in combination with radiation and chemotherapy, for the improvement of anti-cancer MB therapies and patient quality of life. To date, this is the first report that expression of a miRNA can deplete the tumor stem cells, indicating an interesting therapeutic approach for the targeting of these cells in brain tumors.

The fusion between EWS and ETS family members is a key oncogenic event in Ewing tumors and important EWS-FLI1 target genes have been identified. However, until now, the search for EWS-FLI1 targets has been limited to promoter regions and no genome-wide comprehensive analysis of in vivo EWS-FLI1 binding sites has been undertaken. Using a ChIP-Seq approach to investigate EWS-FLI1-bound DNA sequences in two Ewing cell lines, we show that this chimeric transcription factor preferentially binds two types of sequences including consensus ETS motifs and microsatellite sequences. Most bound sites are found outside promoter regions. Microsatellites containing more than 9 GGAA repeats are very significantly enriched in EWS-FLI1 immunoprecipitates. Moreover, in reporter gene experiments, the transcription activation is highly dependent upon the number of repeats that are included in the construct. Importantly, in vivo EWS-FLI1-bound microsatellites are significantly associated with EWS-FLI1-driven gene activation. Put together, these results point out the likely contribution of microsatellite elements to long-distance transcription regulation and to oncogenesis.

The combined deletion of 1p and 19q chromosomal arms is frequent in oligodendrogliomas (OD) and has recently been shown to be mediated by an unbalanced t(1;19) translocation. Recent studies of 1p/19q co-deleted OD suggest that the NOTCH2 gene is implicated in oligodendrocyte differentiation and may be involved in this rearrangement. The objective of the present study was to analyze the NOTCH2 locus either as a chromosomal translocation locus that may be altered by the 1p/19q recurrent rearrangement or as a gene that may be inactivated by a two hit process. We performed an array-CGH analysis of 15 ODs presenting 1p/19q co-deletion using a high-density oligonucleotide microarray spanning 1p and 19q pericentromeric regions with 377 bp average probe spacing. We showed that the 1p deletion extends to the centromere of chromosome 1 and includes the entire NOTCH2 gene. No internal rearrangement of this gene was observed. This strongly suggests that the t(1;19) translocation does not lead to an abnormal NOTCH2 structure. The analysis of the entire NOTCH2 coding sequence was performed in four cases and did not reveal any mutation therefore indicating that NOTCH2 does not harbor genetic characteristics of a tumor suppressor gene. Finally, the detailed analysis of chromosome 19 pericentromeric region led to the identification of two breakpoint clusters at 19p12 and 19q11–12. Interestingly, these two regions share a large stretch of homology. Together with previous observations of similarities between chromosome 1 and 19 alphoid sequences, this suggests that the t(1;19) translocation arises from complex intra and interchromosomal rearrangements.

This is the first comprehensive deletion mapping by high density oligo-array of the 1p/19q co-deletion in oligodendroglioma tumors using a methodological approach superior to others previously applied. As such this paper provides clear evidence that the NOTCH2 gene is not physically rearranged by t(1;19) translocation of oligodendroglioma tumors.

Background

In high grade gliomas, 1p19q codeletion and EGFR amplification are mutually exclusive and predictive of dramatically different outcomes. We performed a microarray gene expression study of four high grade gliomas with 1p19q codeletion and nine with EGFR amplification, identified by CGH-array.

Results

The two groups of gliomas exhibited very different gene expression profiles and were consistently distinguished by unsupervised clustering analysis. One of the most striking differences was the expression of normal brain genes by oligodendrogliomas with 1p19q codeletion. These gliomas harbored a gene expression profile that partially resembled the gene expression of normal brain samples, whereas gliomas with EGFR amplification expressed many genes in common with glioblastoma cancer stem cells. The differences between the two types of gliomas and the expression of neuronal genes in gliomas with 1p19q codeletion were both validated in an independent series of 16 gliomas using real-time RT-PCR with a set of 22 genes differentiating the two groups of gliomas (AKR1C3, ATOH8, BMP2, C20orf42, CCNB1, CDK2, CHI3L1, CTTNBP2, DCX, EGFR, GALNT13, GBP1, IGFBP2, IQGAP1, L1CAM, NCAM1, NOG, OLIG2, PDPN, PLAT, POSTN, RNF135). Immunohistochemical study of the most differentially expressed neuronal gene, alpha-internexin, clearly differentiated the two groups of gliomas, with 1p19q codeletion gliomas showing specific staining in tumor cells.

Conclusion

These findings provide evidence for neuronal differentiation in oligodendrogliomas with 1p19q codeletion and support the hypothesis that the cell of origin for gliomas with 1p19q codeletion could be a bi-potential progenitor cell, able to give rise to both neurons and oligodendrocytes.

Introduction

Typical medullary breast carcinoma (MBC) has recently been recognized to be part of the basal-like carcinoma spectrum, a feature in agreement with the high rate of TP53 mutations previously reported in MBCs. The present study was therefore designed to identify phenotypic and genetic alterations that distinguish MBCs from basal-like carcinomas (BLC).

Methods

Expression levels of estrogen receptor (ER), progesterone receptor (PR), ERBB2, TP53, cytokeratins (KRTs) 5/6, 14, 8/18, epidermal growth factor receptor and KIT, as well as TP53 gene sequence and high-density array comparative genomic hybridization (CGH) profiles, were assessed and compared in a series of 33 MBCs and 26 BLCs.

Results

All tumors were negative for ER, PR and ERBB2. KRTs 5/6 were more frequently expressed in MBCs (94%) than in BLCs (56%) (p = 0.0004). TP53 mutations were disclosed in 20/26 MBCs (77%) and 20/24 BLCs (83%). Array CGH analysis showed that a higher number of gains (95 regions) and losses (34 regions) was observed in MBCs than in BLCs (36 regions of gain; 13 regions of losses). In addition, gains of 1q and 8q, and losses of X were found to be common to the two groups, whereas gains of 10p (53% of the cases), 9p (30.8% of the cases) and 16q (25.8% of the cases), and losses of 4p (34.8% of the cases), and amplicons of 1q, 8p, 10p and 12p were the genetic alterations found to characterize MBC.

Conclusion

Our study has revealed that MBCs are part of the basal-like group and share common genomic alterations with BLCs, the most frequent being 1q and 8q gains and X losses; however, MBCs are a distinct entity within the basal-like spectrum, characterized by a higher rate of KRT 5/6 expression, a higher rate of gains and losses than BLCs, recurrent 10p, 9p and 16q gains, 4p losses, and 1q, 8p, 10p and 12p amplicons. Our results thus contribute to a better understanding of the heterogeneity in basal-like breast tumors and provide potential diagnostic tools.