Increased expression of urokinase-type plasminogen activator mRNA determines adverse prognosis in ErbB2-positive primary breast cancer.

PURPOSE: To evaluate and validate mRNA expression markers capable of identifying patients with ErbB2-positive breast cancer associated with distant metastasis and reduced survival. PATIENTS AND METHODS: Expression of 60 genes involved in breast cancer biology was assessed by quantitative real-time PCR (qrt-PCR) in 317 primary breast cancer patients and correlated with clinical outcome data. Results were validated subsequently using two previously published and publicly available microarray data sets with different patient populations comprising 295 and 286 breast cancer samples, respectively. RESULTS: Of the 60 genes measured by qrt-PCR, urokinase-type plasminogen activator (uPA or PLAU) mRNA expression was the most significant marker associated with distant metastasis-free survival (MFS) by univariate Cox analysis in patients with ErbB2-positive tumors and an independent factor in multivariate analysis. Subsequent validation in two microarray data sets confirmed the prognostic value of uPA in ErbB2-positive tumors by both univariate and multivariate analysis. uPA mRNA expression was not significantly associated with MFS in ErbB2-negative tumors. Kaplan-Meier analysis showed in all three study populations that patients with ErbB2-positive/uPA-positive tumors exhibited significantly reduced MFS (hazard ratios [HR], 4.3; 95% CI, 1.6 to 11.8; HR, 2.7; 95% CI, 1.2 to 6.2; and, HR, 2.8; 95% CI, 1.1 to 7.1; all P < .02) as compared with the group with ErbB2-positive/uPA-negative tumors who exhibited similar outcome to those with ErbB2-negative tumors, irrespective of uPA status. CONCLUSION: After evaluation of 898 breast cancer patients, uPA mRNA expression emerged as a powerful prognostic indicator in ErbB2-positive tumors. These results were consistent among three independent study populations assayed by different techniques, including qrt-PCR and two microarray platforms.

GLUT3 is induced during epithelial-mesenchymal transition and promotes tumor cell proliferation in non-small cell lung cancer.

BACKGROUND: Alterations in glucose metabolism and epithelial-mesenchymal transition (EMT) constitute two important characteristics of carcinoma progression toward invasive cancer. Despite an extensive characterization of each of them separately, the links between EMT and glucose metabolism of tumor cells remain elusive. Here we show that the neuronal glucose transporter GLUT3 contributes to glucose uptake and proliferation of lung tumor cells that have undergone an EMT. RESULTS: Using a panel of human non-small cell lung cancer (NSCLC) cell lines, we demonstrate that GLUT3 is strongly expressed in mesenchymal, but not epithelial cells, a finding corroborated in hepatoma cells. Furthermore, we identify that ZEB1 binds to the GLUT3 gene to activate transcription. Importantly, inhibiting GLUT3 expression reduces glucose import and the proliferation of mesenchymal lung tumor cells, whereas ectopic expression in epithelial cells sustains proliferation in low glucose. Using a large microarray data collection of human NSCLCs, we determine that GLUT3 expression correlates with EMT markers and is prognostic of poor overall survival. CONCLUSIONS: Altogether, our results reveal that GLUT3 is a transcriptional target of ZEB1 and that this glucose transporter plays an important role in lung cancer, when tumor cells loose their epithelial characteristics to become more invasive. Moreover, these findings emphasize the development of GLUT3 inhibitory drugs as a targeted therapy for the treatment of patients with poorly differentiated tumors.

Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

BACKGROUND: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. METHODS: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. RESULTS: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test). CONCLUSIONS: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.

Integrative analysis of RUNX1 downstream pathways and target genes.

BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications

Transcriptional analysis of left-sided colitis, pancolitis, and ulcerative colitis-associated dysplasia

BACKGROUND: It is unknown why patients with extensive ulcerative colitis (UC) have a higher risk of colorectal cancer compared with patients with left-sided UC. This study characterizes the inflammatory processes in left-sided UC, pancolitis, and UC-associated dysplasia at the transcriptional level to identify potential biomarkers and transcripts of importance for the carcinogenic behavior of chronic inflammation. METHODS: The Affymetrix GeneChip Human Genome U133 Plus 2.0 was applied on colonic biopsies from UC patients with left-sided UC, pancolitis, dysplasia, and controls. Reverse transcription polymerase chain reaction and immunohistochemistry were performed for validating selected transcripts in the initial cohort and in 2 independent cohorts of patients with UC. Microarray data were analyzed by principal component analysis, and reverse transcription polymerase chain reaction and immunohistochemistry data by the Wilcoxon's rank-sum test. RESULTS: The principal component analysis results revealed separate clusters for left-sided UC, pancolitis, dysplasia, and controls. Close clustering of dysplastic and pancolitic samples indicated similarities in gene expression. Indeed, 101 and 656 parallel upregulated and downregulated transcripts, respectively, were identified in specimens from dysplasia and pancolitis. Validation of selected transcripts hereof identified insulin receptor alpha (INSRA) and MAP kinase interacting serine/threonine kinase 2 (MKNK2) with an enhanced expression in dysplasia compared with left-sided UC and controls, whereas laminin γ2 (LAMC2) was found with a lower expression in dysplasia compared with the remaining 3 groups. CONCLUSIONS: This study demonstrates pancolitis and left-sided UC as distinct inflammatory processes at the transcriptional level, and identifies INSRA, MKNK2, and LAMC2 as potential critical transcripts in the inflammation-driven preneoplastic process of UC.

Functional analysis: evaluation of response intensities--tailoring ANOVA for lists of expression subsets.

Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect.

Identification and modelling of human breast cancer subtypes

Résumé Le cancer du sein est le cancer le plus commun chez les femmes et est responsable de presque 30% de tous les nouveaux cas de cancer en Europe. On estime le nombre de décès liés au cancer du sein en Europe est à plus de 130.000 par an. Ces chiffres expliquent l'impact social considérable de cette maladie. Les objectifs de cette thèse étaient: (1) d'identifier les prédispositions et les mécanismes biologiques responsables de l'établissement des sous-types spécifiques de cancer du sein; (2) les valider dans un modèle ín vivo "humain-dans-souris"; et (3) de développer des traitements spécifiques à chaque sous-type de cancer du sein identifiés. Le premier objectif a été atteint par l'intermédiaire de l'analyse des données d'expression de gènes des tumeurs, produite dans notre laboratoire. Les données obtenues par puces à ADN ont été produites à partir de 49 biopsies des tumeurs du sein provenant des patientes participant dans l'essai clinique EORTC 10994/BIG00-01. Les données étaient très riches en information et m'ont permis de valider des données précédentes des autres études d'expression des gènes dans des tumeurs du sein. De plus, cette analyse m'a permis d'identifier un nouveau sous-type biologique de cancer du sein. Dans la première partie de la thèse, je décris I identification des tumeurs apocrines du sein par l'analyse des puces à ADN et les implications potentielles de cette découverte pour les applications cliniques. Le deuxième objectif a été atteint par l'établissement d'un modèle de cancer du sein humain, basé sur des cellules épithéliales mammaires humaines primaires (HMECs) dérivées de réductions mammaires. J'ai choisi d'adapter un système de culture des cellules en suspension basé sur des mammosphères précédemment décrit et pat décidé d'exprimer des gènes en utilisant des lentivirus. Dans la deuxième partie de ma thèse je décris l'établissement d'un système de culture cellulaire qui permet la transformation quantitative des HMECs. Par la suite, j'ai établi un modèle de xénogreffe dans les souris immunodéficientes NOD/SCID, qui permet de modéliser la maladie humaine chez la souris. Dans la troisième partie de ma thèse je décris et je discute les résultats que j'ai obtenus en établissant un modèle estrogène-dépendant de cancer du sein par transformation quantitative des HMECs avec des gènes définis, identifiés par analyse de données d'expression des gènes dans le cancer du sein. Les cellules transformées dans notre modèle étaient estrogène-dépendantes pour la croissance, diploïdes et génétiquement normales même après la culture cellulaire in vitro prolongée. Les cellules formaient des tumeurs dans notre modèle de xénogreffe et constituaient des métastases péritonéales disséminées et du foie. Afin d'atteindre le troisième objectif de ma thèse, j'ai défini et examiné des stratégies de traitement qui permettent réduire les tumeurs et les métastases. J'ai produit un modèle de cancer du sein génétiquement défini et positif pour le récepteur de l'estrogène qui permet de modéliser le cancer du sein estrogène-dépendant humain chez la souris. Ce modèle permet l'étude des mécanismes impliqués dans la formation des tumeurs et des métastases. Abstract Breast cancer is the most common cancer in women and accounts for nearly 30% of all new cancer cases in Europe. The number of deaths from breast cancer in Europe is estimated to be over 130,000 each year, implying the social impact of the disease. The goals of this thesis were first, to identify biological features and mechanisms --responsible for the establishment of specific breast cancer subtypes, second to validate them in a human-in-mouse in vivo model and third to develop specific treatments for identified breast cancer subtypes. The first objective was achieved via the analysis of tumour gene expression data produced in our lab. The microarray data were generated from 49 breast tumour biopsies that were collected from patients enrolled in the clinical trial EORTC 10994/BIG00-01. The data set was very rich in information and allowed me to validate data of previous breast cancer gene expression studies and to identify biological features of a novel breast cancer subtype. In the first part of the thesis I focus on the identification of molecular apacrine breast tumours by microarray analysis and the potential imptìcation of this finding for the clinics. The second objective was attained by the production of a human breast cancer model system based on primary human mammary epithelial cells {HMECs) derived from reduction mammoplasties. I have chosen to adopt a previously described suspension culture system based on mammospheres and expressed selected target genes using lentiviral expression constructs. In the second part of my thesis I mainly focus on the establishment of a cell culture system allowing for quantitative transformation of HMECs. I then established a xenograft model in immunodeficient NOD/SCID mice, allowing to model human disease in a mouse. In the third part of my thesis I describe and discuss the results that I obtained while establishing an oestrogen-dependent model of breast cancer by quantitative transformation of HMECs with defined genes identified after breast cancer gene expression data analysis. The transformed cells in our model are oestrogen-dependent for growth; remain diploid and genetically normal even after prolonged cell culture in vitro. The cells farm tumours and form disseminated peritoneal and liver metastases in our xenograft model. Along the lines of the third objective of my thesis I defined and tested treatment schemes allowing reducing tumours and metastases. I have generated a genetically defined model of oestrogen receptor alpha positive human breast cancer that allows to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.

Neuronal activity in the hub of extrasynaptic Schwann cell-axon interactions.

The integrity and function of neurons depend on their continuous interactions with glial cells. In the peripheral nervous system glial functions are exerted by Schwann cells (SCs). SCs sense synaptic and extrasynaptic manifestations of action potential propagation and adapt their physiology to support neuronal activity. We review here existing literature data on extrasynaptic bidirectional axon-SC communication, focusing particularly on neuronal activity implications. To shed light on underlying mechanisms, we conduct a thorough analysis of microarray data from SC-rich mouse sciatic nerve at different developmental stages and in neuropathic models. We identify molecules that are potentially involved in SC detection of neuronal activity signals inducing subsequent glial responses. We further suggest that alterations in the activity-dependent axon-SC crosstalk impact on peripheral neuropathies. Together with previously reported data, these observations open new perspectives for deciphering glial mechanisms of neuronal function support.

Evolution of mRNA expression levels of autosomal and sex-linked genes in amniotes

In addition to differences in protein-coding gene sequences, changes in expression resulting from mutations in regulatory sequences have long been hypothesized to be responsible for phenotypic differences between species. However, unlike comparison of genome sequences, few studies, generally restricted to pairwise comparisons of closely related mammalian species, have assessed between-species differences at the transcriptome level. They reported that gene expression evolves at different rates in various organs and in a pattern that is overall consistent with neutral models of evolution. In the first part of my thesis, I investigated the evolution of gene expression in therian mammals (i.e.7 placental and marsupials), based on microarray data from human, mouse and the gray short-tailed opossum (Monodelphis domestica). In addition to autosomal genes, a special focus was given to the evolution of X-linked genes. The therian X chromosome was recently shown to be younger than previously thought and to harbor a specific gene content (e.g., genes involved in brain or reproductive functions) that is thought to have been shaped by specific sex-related evolutionary forces. Sex chromosomes derive from ordinary autosomes and their differentiation led to the degeneration of the Y chromosome (in mammals) or W chromosome (in birds). Consequently, X- or Z-linked genes differ in gene dose between males and females such that the heterogametic sex has half the X/Z gene dose compared to the ancestral state. To cope with this dosage imbalance, mammals have been reported to have evolved mechanisms of dosage compensation.¦In the first project, I could first show that transcriptomes evolve at different rates in different organs. Out of the five tissues I investigated, the testis is the most rapidly evolving organ at the gene expression level while the brain has the most conserved transcriptome. Second, my analyses revealed that mammalian gene expression evolution is compatible with a neutral model, where the rates of change in gene expression levels is linked to the efficiency of purifying selection in a given lineage, which, in turn, is determined by the long-term effective population size in that lineage. Thus, the rate of DNA sequence evolution, which could be expected to determine the rate of regulatory sequence change, does not seem to be a major determinant of the rate of gene expression evolution. Thus, most gene expression changes seem to be (slightly) deleterious. Finally, X-linked genes seem to have experienced elevated rates of gene expression change during the early stage of X evolution. To further investigate the evolution of mammalian gene expression, we generated an extensive RNA-Seq gene expression dataset for nine mammalian species and a bird. The analyses of this dataset confirmed the patterns previously observed with microarrays and helped to significantly deepen our view on gene expression evolution.¦In a specific project based on these data, I sought to assess in detail patterns of evolution of dosage compensation in amniotes. My analyses revealed the absence of male to female dosage compensation in monotremes and its presence in marsupials and, in addition, confirmed patterns previously described for placental mammals and birds. I then assessed the global level of expression of X/Z chromosomes and contrasted this with its ancestral gene expression levels estimated from orthologous autosomal genes in species with non-homologous sex chromosomes. This analysis revealed a lack of up-regulation for placental mammals, the level of expression of X-linked genes being proportional to gene dose. Interestingly, the ancestral gene expression level was at least partially restored in marsupials as well as in the heterogametic sex of monotremes and birds. Finally, I investigated alternative mechanisms of dosage compensation and found that gene duplication did not seem to be a widespread mechanism to restore the ancestral gene dose. However, I could show that placental mammals have preferentially down-regulated autosomal genes interacting with X-linked genes which underwent gene expression decrease, and thus identified a novel alternative mechanism of dosage compensation.

Meta-analysis of heat- and chemically upregulated chaperone genes in plant and human cells.

Molecular chaperones are central to cellular protein homeostasis. In mammals, protein misfolding diseases and aging cause inflammation and progressive tissue loss, in correlation with the accumulation of toxic protein aggregates and the defective expression of chaperone genes. Bacteria and non-diseased, non-aged eukaryotic cells effectively respond to heat shock by inducing the accumulation of heat-shock proteins (HSPs), many of which molecular chaperones involved in protein homeostasis, in reducing stress damages and promoting cellular recovery and thermotolerance. We performed a meta-analysis of published microarray data and compared expression profiles of HSP genes from mammalian and plant cells in response to heat or isothermal treatments with drugs. The differences and overlaps between HSP and chaperone genes were analyzed, and expression patterns were clustered and organized in a network. HSPs and chaperones only partly overlapped. Heat-shock induced a subset of chaperones primarily targeted to the cytoplasm and organelles but not to the endoplasmic reticulum, which organized into a network with a central core of Hsp90s, Hsp70s, and sHSPs. Heat was best mimicked by isothermal treatments with Hsp90 inhibitors, whereas less toxic drugs, some of which non-steroidal anti-inflammatory drugs, weakly expressed different subsets of Hsp chaperones. This type of analysis may uncover new HSP-inducing drugs to improve protein homeostasis in misfolding and aging diseases.

Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.

Transcriptional dissection of pancreatic tumors engrafted in mice.

BACKGROUND: Engraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient-derived xenograft (PDX) models is a promising platform for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine tumor environment on the gene expression of the engrafted human tumoral cells. METHODS: We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data of 18 PDX models, 53 primary tumors and 41 cell lines from PDAC. The results obtained in the PDAC system were further compared with public available microarray data from 42 PDX models, 108 primary tumors and 32 cell lines from hepatocellular carcinoma (HCC). We developed a robust analysis protocol to explore the gene expression space. In addition, we completed the analysis with a functional characterization of PDX models, including if changes were caused by murine environment or by serial passing. RESULTS: Our results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable from each other based on their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models can be separated into two different groups that share some partial similarity with their corresponding original primary tumors. Our results point to the lack of human stromal involvement in PDXs as a major factor contributing to their differences from the original primary tumors. The main functional differences between pancreatic PDX models and human PDAC are the lower expression of genes involved in pathways related to extracellular matrix and hemostasis and the up- regulation of cell cycle genes. Importantly, most of these differences are detected in the first passages after the tumor engraftment. CONCLUSIONS: Our results suggest that PDX models of PDAC and HCC retain, to some extent, a gene expression memory of the original primary tumors, while this pattern is not detected in conventional cancer cell lines. Expression changes in PDXs are mainly related to pathways reflecting the lack of human infiltrating cells and the adaptation to a new environment. We also provide evidence of the stability of gene expression patterns over subsequent passages, indicating early phases of the adaptation process.

Pregnancy-associated changes in host permissiveness to metastasis

THESIS SUMMARY : Metastasis is a multistep process involving tumour cell-autonomous features, the host tissue stroma of the primary tumour, the blood or lymphatic system as well as a receptive target organ. Most studies on factors influencing metastasis have concentrated on the characteristics of the disseminating tumour cell and on early steps of metastasis including invasion and angiogenesis. Although these steps are necessary for tumour cells to disseminate, it is the challenges encountered in the later steps of metastasis -survival while in the circulation and engraftment and outgrowth in the target organ -that account for the inefficiency of circulating tumour cells in establishing secondary lesions. Full understanding of the metastatic process therefore requires elucidation of the mechanisms that regulate these late steps, and in particular that determine what makes any given tissue permissive for metastatic tumour growth. To address this issue, we assessed the mechanisms whereby a physiological situation -pregnancy -can alter host permissiveness toward metastasis. We show that pregnant NOD/SCID mice -injected intravenously with tumour cells -develop more metastases than their non-pregnant counterparts irrespective of the tumour cell type. There was no direct effect of pregnancy-related circulating factors on tumour cell proliferation, and subcutaneous tumour growth does not vary between pregnant and nonpregnant animals. However, decreased elimination of tumour cells from the lung microvasculature was observed in pregnant mice, prompting us to assess whether pregnancy-related adaptations in innate immunity could account for this differential clearing. We found that natural killer (NK) cell fractions are decreased in blood and spleen of pregnant mice and that NK cell cytotoxicity is impaired, as reported previously. The use of NK-deficient mice or tumour cell lines resistant to NK killing abrogates the difference in metastasis load between pregnant and virgin mice. CD11 b+ Gr-1+ myeloid-derived suppressor cells (MDSC) have previously been shown to accumulate in tumour-bearing mice and to down-modulate NK activity. Accordingly, we show an increase in MDSC in pregnant mouse blood, spleen, lungs and liver. Depletion of MDSC prior to tumour cell injection decreased metastasis load in pregnant NOD/SCID mice but had no effect on virgin mice. Similarly, adoptive transfer of MDSC extracted from pregnant mice into virgin mice lead to increased metastasis take. In parallel, we investigated whether the lung and liver microenvironments are modified during pregnancy thereby providing a more "permissive soil" for the establishment of metastases. A comparative analysis of microarray data of pregnant mouse lungs and liver with "premetastatic niche" gene expression profiles of these organs shows that similar mechanisms could mediate an increase in lung and liver metastasis in pregnant mice and in mice harbouring an aggressive primary tumour. Several commonly up-regulated genes point towards the recruitment of myeloid cells, consistent with the accumulation of MDSC observed in pregnant mice. MDSC have never been evoked in the context of pregnancy before. Although the role of MDSC in pregnancy requires further investigation we suggest that MDSC accumulation constitutes an important and hitherto unrecognised common denominator of maternal immune tolerance and cancer immune escape. RESUME DE THESE : La métastatisation est un processus en plusieurs étapes qui implique des compétences particulières chez les cellules tumorales, le stroma de la tumeur primaire, les vaisseaux sanguins ou lymphatiques ainsi qu'un organe cible' réceptif. Jusqu'alors, la recherche s'est principalement intéressée aux facteurs qui influencent les étapes précoces de la métastatisation donc aux caractéristiques de la cellule métastatique, et aux processus tels que l'invasion et l'angiogenèse, tandis que peu d'études traitent des étapes tardives tel que la survie dans la circulation sanguine et l'établissement d'une lésion dans l'organe cible. En particulier, l'élucidation des facteurs qui déterminent la permissivité d'un tissu à la greffe de cellules disséminantes est indispensable à la compréhension de ce processus complexe qu'est la métastatisation. Nous proposons ici un modèle de souris récapitulant les étapes tardives de la métastatisation dans un contexte d'une permissivité accrue aux métastases chez la souris gravide, et nous évaluons les mécanismes impliqués. Les souris gestantes développent plus de métastases après l'injection intraveineuse de cellules tumorales, indépendamment du type de tumeur d'origine. Les taux élevés d'hormones et de facteurs de croissance chez la souris gravide n'inflúencent pas la prolifération des cellules tumorales et fa croissance de tumeurs sous-cutanées n'est pas non plus accélérée par la gestation. En revanche, une fois injectées, les cellules tumorales sont éliminées ` moins rapidement des vaisseaux pulmonaires chez la souris gravide que chez les contrôles. Cette observation est compatible avec un effet de la gestation sur l'immunité innée et nous avons mis en évidence une diminution des proportions de cellules NK (natural killer) dans le sang et la rate en particulier, ainsi qu'une cytotoxicité moindre envers des cellules tumorales. En utilisant des souris déficientes en cellules NK ou en injectant des cellules résistantes à l'attaqué par des cellules NK, la différence entre souris gestantes et non-gestantes disparaît. Il a été démontré chez des souris porteuses de tumeurs, que l'accumulation de cellules immunosuppressives de la lignée myélo-monocytaire (ou MDSC pour myeloid-derived suppressor tells) pouvait être responsable d'une inhibition de l'activité de cellules NK. Des nombres augmentés de ces cellules, caractérisées par les marqueurs de surface CD11b et Gr-1, ont été trouvés dans le sang, la rate, les poumons et le foie de souris gravides. Leur rôle dans la métastatisation est démontré par le fait que leur dépletion diminue le nombre de lésions secondaires chez la souris gestante, tandis que leur transfert dans des souris non-gestantes augmente le taux de métastases. L'utilisation de puces à ADN sur les foies et poumons de souris gravides a permis de mettre en évidence des différences d'expression génique proches de celles observées dans l'établissement de niches pré-métastatiques. Ceci suggère que des mécanismes similaires pourraient être responsables d'une permissivité accrue aux métastases chez la souris gravide et chez la souris porteuse d'une tumeur primaire agressive, telle que, en particulier, l'accumulation de cellules immunosuppressives dans les organes cibles. C'est la première fois que l'accumulation de MDSC est évoquée chez la souris gravide et nous proposons ici que celles-ci jouent un rôle dans la tolérance immunitaire envers le foetus et sont responsables de l'échappement de cellules tumorales injectées à la surveillance immunitaire par des cellules NK.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026. © 2013 Swiss Institute of Bioinformatics. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.