Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

#22 TCGA

Combined media monoprints on photographic paper. 16" x 20", DNA/Transformation Series. Private Collection

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

A novel saliva-based microRNA biomarker panel to detect head and neck cancers

Background MicroRNAs (miRNAs) are known to play an important role in cancer development by post-transcriptionally affecting the expression of critical genes. The aims of this study were two-fold: (i) to develop a robust method to isolate miRNAs from small volumes of saliva and (ii) to develop a panel of saliva-based diagnostic biomarkers for the detection of head and neck squamous cell carcinoma (HNSCC). Methods Five differentially expressed miRNAs were selected from miScript™ miRNA microarray data generated using saliva from five HNSCC patients and five healthy controls. Their differential expression was subsequently confirmed by RT-qPCR using saliva samples from healthy controls (n = 56) and HNSCC patients (n = 56). These samples were divided into two different cohorts, i.e., a first confirmatory cohort (n = 21) and a second independent validation cohort (n = 35), to narrow down the miRNA diagnostic panel to three miRNAs: miR-9, miR-134 and miR-191. This diagnostic panel was independently validated using HNSCC miRNA expression data from The Cancer Genome Atlas (TCGA), encompassing 334 tumours and 39 adjacent normal tissues. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic capacity of the panel. Results On average 60 ng/μL miRNA was isolated from 200 μL of saliva. Overall a good correlation was observed between the microarray data and the RT-qPCR data. We found that miR-9 (P <0.0001), miR-134 (P <0.0001) and miR-191 (P <0.001) were differentially expressed between saliva from HNSCC patients and healthy controls, and that these miRNAs provided a good discriminative capacity with area under the curve (AUC) values of 0.85 (P <0.0001), 0.74 (P < 0.001) and 0.98 (P < 0.0001), respectively. In addition, we found that the salivary miRNA data showed a good correlation with the TCGA miRNA data, thereby providing an independent validation. Conclusions We show that we have developed a reliable method to isolate miRNAs from small volumes of saliva, and that the saliva-derived miRNAs miR-9, miR-134 and miR-191 may serve as novel biomarkers to reliably detect HNSCC. © 2014 International Society for Cellular Oncology.

A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

Fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group

Background: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Methods: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. Results: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p < 0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. Conclusion: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.

A DNA methylation prognostic signature of glioblastoma: identification of NPTX2-PTEN-NF-kappa B nexus

Glioblastoma (GBM) is the most common, malignant adult primary tumor with dismal patient survival, yet the molecular determinants of patient survival are poorly characterized. Global methylation profile of GBM samples (our cohort; n = 44) using high-resolution methylation microarrays was carried out. Cox regression analysis identified a 9-gene methylation signature that predicted survival in GBM patients. A risk-score derived from methylation signature predicted survival in univariate analysis in our and The Cancer Genome Atlas (TCGA) cohort. Multivariate analysis identified methylation risk score as an independent survival predictor in TCGA cohort. Methylation risk score stratified the patients into low-risk and high-risk groups with significant survival difference. Network analysis revealed an activated NF-kappa B pathway association with high-risk group. NF-kappa B inhibition reversed glioma chemoresistance, and RNA interference studies identified interleukin-6 and intercellular adhesion molecule-1 as key NF-kappa B targets in imparting chemoresistance. Promoter hypermethylation of neuronal pentraxin II (NPTX2), a risky methylated gene, was confirmed by bisulfite sequencing in GBMs. GBMs and glioma cell lines had low levels of NPTX2 transcripts, which could be reversed upon methylation inhibitor treatment. NPTX2 overexpression induced apoptosis, inhibited proliferation and anchorage-independent growth, and rendered glioma cells chemosensitive. Furthermore, NPTX2 repressed NF-kappa B activity by inhibiting AKT through a p53-PTEN-dependent pathway, thus explaining the hypermethylation and downregulation of NPTX2 in NF-kappa B-activated high-risk GBMs. Taken together, a 9-gene methylation signature was identified as an independent GBM prognosticator and could be used for GBM risk stratification. Prosurvival NF-kappa B pathway activation characterized high-risk patients with poor prognosis, indicating it to be a therapeutic target. (C) 2013 AACR.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

MiR-433 induces cellular senescence rendering ovarian cancer cells less likely to undergo chemotherapy-induced apoptosis

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynaecological malignancy. Such mortality is predominantly associated with the development of an intrinsic and acquired resistance to chemotherapy, the lack of targeted therapies and the lack of biomarkers predicting therapeutic response.

Our clinical data demonstrates that increased miR-433 expression in primary high grade serous OC (HGSOCs) is significantly associated with poor PFS (n=46, p=0.024). Interestingly, the IHC analysis of two miR-433 targets: MAD2 [Furlong et al., 2012 PMID:22069160] and HDAC6 shows that low IHC levels of both proteins is also significantly associated with worse outcome (p=0.002 and 0.002 respectively; n=43). Additionally, the analysis of miR 433 in the publicly available TCGA dataset corroborates that high miR-433 is significantly correlated with worse OS for patients presenting with OC (n=558 and p=0.027). In vitro, in a panel of OC cell lines, higher miR-433 and lower MAD2 and HDAC6 levels were associated with resistance to paclitaxel.

To further investigate the role of miR-433 in the cellular response to chemotherapy, we generated an OC cell line stably expressing miR-433, or miR-control. MTT viability assays and Western Blot analyses established that miR-433 cells were more resistant to paclitaxel treatment (50nM) compared to miR-controls. Importantly, we have shown for the first time that miR 433 induced senescence, exemplified by a flattened morphology and down-regulation of phosphorylated Retinoblastoma (p-Rb), a molecular marker of senescence. Surprisingly, miR 433 induced senescence was independent from two well recognised senescent drivers: namely p53/p21 and p16. To explore this further we performed an in silico analysis of seven microRNA platforms which indicated that miR 433 potentially targets Cyclin-dependent kinase CDK6, which promotes sustained phosphorylation of Rb and thus cell cycle progression. In vitro, the overexpression of pre-miR-433 resulted in diminished CDK6 expression demonstrating a novel interaction between miR-433 and CDK6.

In conclusion, this study demonstrates that high miR-433 expression predicts poor outcome in OC patients by putatively rendering OC cells resistant to paclitaxel treatment through the induction of cellular senescence identifying this microRNA as a potential marker of chemoresponse.

MIR-433 Predicts poor response to chemotherapy in ovarian cancer patients by the induction of cellular senescence

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynaecological malignancy. Such mortality is predominantly associated with the development of an intrinsic and acquired resistance to chemotherapy, the lack of targeted therapies and the lack of biomarkers predicting response to standard treatment.

Our clinical data demonstrates that increased miR-433 expression in primary high grade serous OC (HGSOCs) is significantly associated with poor PFS (n=46, p=0.024). Interestingly, the IHC analysis of two miR-433 targets: MAD2 [1] and HDAC6 shows that low IHC levels of both proteins is also significantly associated with worse outcome (p=0.002 and 0.002 respectively; n=43). Additionally, the analysis of miR 433 in the publicly available TCGA dataset corroborates that high miR-433 is significantly correlated with worse OS for patients presenting with OC (n=558 and p=0.027). In vito, in a panel of OC cell lines, higher miR-433 and lower MAD2 and HDAC6 levels were associated with resistance to paclitaxel.

To further investigate the role of miR-433 in the cellular response to chemotherapy, we generated an OC cell line stably expressing miR-433 or miR-control. MTT viability assays and Western Blot analyses established that miR-433 cells were more resistant to paclitaxel treatment (50nM) compared to miR-controls. Importantly, we have shown for the first time that miR 433 induced senescence resulting in a chracteristic flattened morphology and down-regulation of phosphorylated Retinoblastoma (p Rb), a molecular marker of senescence. Surprisingly, miR 433 induced senescence was independent from two well recognised senescent drivers: namely p53/p21 and p16. To explore this further we performed an in silico analysis of seven microRNA platforms which indicated that miR 433 potentially targets Cyclin-dependent kinase CDK6, which promotes sustained phosphorylation of Rb and thus cell cycle progression. In vitro, the overexpression of pre-miR-433 resulted in diminished CDK6 expression demonstrating a novel interaction between miR-433 and CDK6.

In conclusion, this study demonstrates that high miR-433 expression predicts poor outcome in OC patients by putatively rendering OC cells resistant to paclitaxel treatment through the induction of cellular senescence identifying this microRNA as a potential marker of chemoresponse.

A miR-433 mediated mechanism of chemoresistance in high grade serous ovarian cancer (HGSOC).

Higher expression of the miR-433 microRNA (miRNA) is associated with poorer survival outcomes in patients with HGSOC that may be overcome by a greater understanding of the functional role of this miRNA. We previously described miR-433 as a critical cell cycle regulator and mediator of cellular senescence. Downregulation of the mitotic arrest deficiency 2 (MAD2) protein by miR-433 led to increased cellular resistance to paclitaxel in epithelial ovarian cancer cells (EOC). Furthermore immunohistochemical (IHC) analysis of MAD2 expression in patients with HGSOC showed that loss of MAD2 was significantly associated with poorer patient survival. Higher miR-433 expression is also associated with an increased resistance to the platins which is unrelated to loss of MAD2 expression. In silico analysis of the miR-433 target proteins in the TCGA database identified the association between a number of miR-433 targets and poorer patient survival. IHC analysis of the miR-433 target, histone deacetylase 6 (HDAC6), confirmed that its expression was significantly associated with a decrease in patient overall survival. The knock-down of HDAC6 by siRNA in EOC cells did not attenuate apoptotic responses to paclitaxel or platin although lower endogenous HDAC6 expression was associated with more resistant EOC cell lines. In vitro analysis revealed that EOC cells which survived chemotherapeutic kill with high doses of paclitaxel expressed higher miR-433 and concomitant decreased expression of the miR-433 targets. These cells were more chemoresistant compared to the parental cell line and repopulated as 3d organoid cultures in non-adherent stem cell selective conditions; thus indicating that the cells which survive chemotherapy were viable, capable of regrowth and had an increased potential for pluripotency. In conclusion, our data suggests that chemotherapy is not driving the transcriptional upregulation of miR-433 but rather selecting a population of cells with high miR-433 expression that may contribute to chemoresistant disease and tumour recurrence.

Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes

BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

Understanding the transcriptional control of EIF4E and its dysregulation in acute myeloid leukemia: role of NF-κB

EIF4E, le facteur d’initiation de la traduction chez les eucaryotes est un oncogène puissant et qui se trouve induit dans plusieurs types de cancers, parmi lesquels les sous-types M4 et M5 de la leucémie aiguë myéloblastique (LAM). EIF4E est régulé à plusieurs niveaux cependant, la régulation transcriptionnelle de ce gène est peu connue. Mes résultats montrent que EIF4E est une cible transcriptionnelle directe du facteur nucléaire « kappa-light- chain- enhancer of activated B cells » (NF-κB).Dans les cellules hématopoïétiques primaires et les lignées cellulaires, les niveaux de EIF4E sont induits par des inducteurs de NF-κB. En effet, l’inactivation pharmaceutique ou génétique de NF-κB réprime l’activation de EIF4E. En effet, suite à l’activation de NF-κB chez l’humain, le promoteur endogène de EIF4E recrute p65 (RelA) et c-Rel aux sites évolutionnaires conservés κB in vitro et in vivo en même temps que p300 ainsi que la forme phosphorylée de Pol II. De plus, p65 est sélectivement associé au promoteur de EIF4E dans les sous-types LAM M4/M5 mais non pas dans les autres sous-types LAM ou dans les cellules hématopoïétiques primaires normales. Ceci indique que ce processus représente un facteur essentiel qui détermine l’expression différentielle de EIF4E dans la LAM. Les analyses de données d’expressions par séquençage de l’ARN provenant du « Cancer Genome Atlas » (TCGA) suggèrent que les niveaux d’ARNm de EIF4E et RELA se trouvent augmentés dans les cas LAM à pronostic intermédiaire ou faible mais non pas dans les groupes cytogénétiquement favorables. De plus, des niveaux élevés d’ARNm de EIF4E et RELA sont significativement associés avec un taux de survie relativement bas chez les patients. En effet, les sites uniques κB se trouvant dans le promoteur de EIF4E recrutent le régulateur de transcription NF-κB p65 dans 47 nouvelles cibles prévues. Finalement, 6 nouveaux facteurs de transcription potentiellement impliqués dans la régulation du gène EIF4E ont été prédits par des analyses de données ChIP-Seq provenant de l’encyclopédie des éléments d’ADN (ENCODE). Collectivement, ces résultats fournissent de nouveaux aperçus sur le control transcriptionnel de EIF4E et offrent une nouvelle base moléculaire pour sa dérégulation dans au moins un sous-groupe de spécimens de LAM. L’étude et la compréhension de ce niveau de régulation dans le contexte de spécimens de patients s’avère important pour le développement de nouvelles stratégies thérapeutiques ciblant l’expression du gène EIF4E moyennant des inhibiteurs de NF-κB en combinaison avec la ribavirine.

Detrimental effects of exuberant and restrained immune responses against the central nervous system in the context of multiple sclerosis and glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common and most aggressive astrocytic tumor of the central nervous system (CNS) in adults. The standard treatment consisting of surgery, followed by a combinatorial radio- and chemotherapy, is only palliative and prolongs patient median survival to 12 to 15 months. The tumor subpopulation of stem cell-like glioma-initiating cells (GICs) shows resistance against radiation as well as chemotherapy, and has been suggested to be responsible for relapses of more aggressive tumors after therapy. The efficacy of immunotherapies, which exploit the immune system to specifically recognize and eliminate malignant cells, is limited due to strong immunosuppressive activities of the GICs and the generation of a specialized protective microenvironment. The molecular mechanisms underlying the therapy resistance of GICs are largely unknown. rnThe first aim of this study was to identify immune evasion mechanisms in GICs triggered by radiation. A model was used in which patient-derived GICs were treated in vitro with fractionated ionizing radiation (2.5 Gy in 7 consecutive passages) to select for a more radio-resistant phenotype. In the model cell line 1080, this selection process resulted in increased proliferative but diminished migratory capacities in comparison to untreated control GICs. Furthermore, radio-selected GICs downregulated various proteins involved in antigen processing and presentation, resulting in decreased expression of MHC class I molecules on the cellular surface and diminished recognition potential by cytotoxic CD8+ T cells. Thus, sub-lethal fractionated radiation can promote immune evasion and hamper the success of adjuvant immunotherapy. Among several immune-associated proteins, interferon-induced transmembrane protein 3 (IFITM3) was found to be upregulated in radio-selected GICs. While high expression of IFITM3 was associated with a worse overall survival of GBM patients (TCGA database) and increased proliferation and migration of differentiated glioma cell lines, a strong contribution of IFITM3 to proliferation in vitro as well as tumor growth and invasiveness in a xenograft model could not be observed. rnMultiple sclerosis (MS) is the most common autoimmune disease of the CNS in young adults of the Western World, which leads to progressive disability in genetically susceptible individuals, possibly triggered by environmental factors. It is assumed that self-reactive, myelin-specific T helper cell 1 (Th1) and Th17 cells, which have escaped the control mechanisms of the immune system, are critical in the pathogenesis of the human disease and its animal model experimental autoimmune encephalomyelitis (EAE). It was observed that in vitro differentiated interleukin 17 (IL-17) producing Th17 cells co-expressed the Th1-phenotypic cytokine Interferon-gamma (IFN-γ) in combination with the two respective lineage-associated transcription factors RORγt and T-bet after re-isolation from the CNS of diseased mice. Pathogenic molecular mechanisms that render a CD4+ T cell encephalitogenic have scarcely been investigated up to date. rnIn the second part of the thesis, whole transcriptional changes occurring in in vitro differentiated Th17 cells in the course of EAE were analyzed. Evaluation of signaling networks revealed an overrepresentation of genes involved in communication between the innate and adaptive immune system and metabolic alterations including cholesterol biosynthesis. The transcription factors Cebpa, Fos, Klf4, Nfatc1 and Spi1, associated with thymocyte development and naïve T cells were upregulated in encephalitogenic CNS-isolated CD4+ T cells, proposing a contribution to T cell plasticity. Correlation of the murine T-cell gene expression dataset to putative MS risk genes, which were selected based on their proximity (± 500 kb; ensembl database, release 75) to the MS risk single nucleotide polymorphisms (SNPs) proposed by the most recent multiple sclerosis GWAS in 2011, revealed that 67.3% of the MS risk genes were differentially expressed in EAE. Expression patterns of Bach2, Il2ra, Irf8, Mertk, Odf3b, Plek, Rgs1, Slc30a7, and Thada were confirmed in independent experiments, suggesting a contribution to T cell pathogenicity. Functional analysis of Nfatc1 revealed that Nfatc1-deficient CD4+ T cells were restrained in their ability to induce clinical signs of EAE. Nfatc1-deficiency allowed proper T cell activation, but diminished their potential to fully differentiate into Th17 cells and to express high amounts of lineage cytokines. As the inducible Nfatc1/αA transcript is distinct from the other family members, it could represent an interesting target for therapeutic intervention in MS.rn

TBX3-Mutationsanalysen und Konstruktion einer Zelllinie für TBX2-Inhibitorscreenings

Die nahe verwandten T-box Transkriptionsfaktoren TBX2 und TBX3 werden in zahlreichen humanen Krebsarten überexprimiert, insbesondere in Brustkrebs und Melanomen. Die Überexpression von TBX2 und TBX3 hat verschiedene zelluläre Effekte, darunter die Unterdrückung der Seneszenz, die Förderung der Epithelialen-Mesenchymalen Transition sowie invasive Zellmotilität. Im Gegensatz dazu führt ein Funktionsverlust von TBX3 und der meisten anderen humanen T-box-Gene zu haploinsuffizienten Entwicklungsdefekten. Durch Sequenzierung des Exoms von Brustkrebsproben identifizierten Stephens et al. fünf verschiedene Mutationen in TBX3, welche allesamt die DNA-bindende T-box-Domäne betrafen. Die In-Frame-Deletion N212delN wurde zweimal gefunden. Aus der Anhäufung der Mutationen innerhalb der T-box-Domäne wurde geschlossen, dass TBX3 bei Brustkrebs ein Treibergen ist. Da Mutationen innerhalb der T-box-Domäne im Allgemeinen zu einem Funktionsverlust führen, aber die onkogene Aktivität von TBX3 meist auf eine Überexpression zurückzuführen ist, wurden die potentiellen Treibermutationen hinsichtlich einer verminderten oder gesteigerten TBX3-Funktion geprüft. Getestet wurden zwei In-Frame Deletionen, eine Missense- sowie eine Frameshift-Mutante bezüglich der DNA-Bindung in vitro und der Zielgen-Repression in Zellkultur. Zusätzlich wurde eine in silico Analyse der im The Cancer Genome Atlas (TCGA) gelisteten somatischen TBX-Brustkrebsmutationen durchgeführt. Sowohl die experimentelle als auch die in silico Analyse zeigten, dass die untersuchten Mutationen vorwiegend zum Verlust der TBX3-Funktion führen. Um den Mechanismus der Genrepression durch TBX3 besser zu verstehen, wurden weitere TBX3-Mutanten bezüglich ihrer Wirkung auf die p21-Promotoraktivität (p21-Luc-Reporter und endogene p21-Expression) analysiert. Wildtypische p21-Luc-Repression zeigten die zwei Mutationen S674A (Phosphorylierung) und D275K (SUMOylierung), welche posttranslationale Modifikationen verhindern, sowie die Interaktion mit dem Tumorsuppressor Rb1 unterbindende M302A/V304A-Mutation. Erstaunlicherweise war die endogene p21-Repression dieser Mutanten stärker als die des wildtypischen TBX3-Proteins. Alle drei Mutationen führten zu einer Stabilisierung des TBX3-Proteins. Die ursprünglich in Patienten mit Ulna-Mamma Syndrom identifizierte, DNA-bindungsdefekte Y149S-Mutante konnte weder p21-Luc noch endogenes p21 reprimieren. Mutationen in potentiellen Interaktionsdomänen für die Bindung der Co-Repressoren Groucho und C-terminalem Bindeprotein zeigten sowohl auf p21-Luc als auch auf endogenes p21-Gen wildtypische Repressoraktivität, so dass diese Co-Repressoren in COS-7-Zellen wahrscheinlich nicht an der Repression dieses Gens beteiligt sind. Da TBX2 und TBX3 interessante Ziele zur direkten Krebsbekämpfung darstellen, sollte ein zelluläres Reportersystem zur Identifikation TBX2-inhibierender, pharmakologisch aktiver Substanzen etabliert werden. Dazu sollte eine stabile Zelllinie mit vom p21-Promotor reguliertem d2EGFP-Reporter und Doxyzyklin-induzierbarem TBX2-Protein erzeugt werden, da ektopische Expression von TBX2 genetische Instabilität und Toxizität induzieren kann. In dieser Zelllinie sollte die TBX2-Expression zur Reduktion der d2EGFP-Fluoreszenz führen. Zur Erzeugung der Zelllinie wurden die folgenden drei Konstrukte Schritt-für-Schritt stabil in das Genom der Zielzelllinie COS-7 integriert: pEF1alpha-Tet3G, pTRE3G-TBX2 und p21-d2EGFP. Während die Herstellung der doppelt stabilen COS-7-Zelllinie gelang, scheiterte die Herstellung der dreifach stabilen Zelllinie.