Monika Hegi

Axes de recherche | Projets et contrats | Collaborations |

Axes de recherche

Molecular Mechanisms and Predictive Factors in Malignant Progression of Astrocytomas.

Glioblastoma multiforme, the most common and most malignant form of primary brain tumors may evolve over years from a lower grade astrocytoma, but more commonly develops rapidly without clinical evidence of a precursor lesion. To improve the prognosis of this devastating disease, with a median survival of less than one year, we need to identify predictive factors and discover new targets for future therapies. Thus, the design of novel treatments adapted to individual patients requires further insights into molecular aspects of pathogenesis in progression of astrocytomas.
Here we focus on molecular mechanisms underlying biological differences controlling pathogenesis of distinct subtypes of astrocytic glioma by pursuing three different approaches. (i) Taking advantage of close collaborations with the EORTC (European Organization of Research and Treatment of Cancer), the NCIC (National Cancer Institute of Canada), and our clinical partners in Lausanne and Geneva, we perform molecular analysis of tumor biopsies obtained from glioma patients enrolled in clinical trials that allows us to link molecular patterns with clinical data regarding response to therapy and outcome. (ii) Candidate genes emerging from our analysis are subjected to functional investigations in vitro and in vivo, and (iii) respective mouse brain tumor models are developed.

Recherche transversale en Neuro-Oncologie : Mécanismes moléculaires et facteurs prédictifs dans la progression des gliomes

Les gliomes représentent la tumeur primaire la plus répandue du cerveau. En utilisant la nouvelle technique des cDNA-arrays, nous établissons les profils d'expression génétiques des tumeurs pour rechercher des facteurs pronostics pour la survie et réponse à la thérapie. Ce travail est effectué dans le cadre d'une étude clinique prospective de phase II conduite dans les hôpitaux de Lausanne et de Genève pour des patients diagnostiqués avec un glioblastome de novo. Ces patients ont reçu de façon concomitante et adjuvante la Temozolomide et de la radiothérapie. Ce projet est poursuivi dans le cadre de l'étude clinique randomisée de phase III, qui fait suite à l'étude pilote (EORTC 26981). Dans un deuxième projet, nous nous intéressons aux astrocytomes de bas grade dont la survie des patients varie de quelques mois à une dizaine d'années. Les objectifs de ce travail sont la classification des tumeurs selon leurs profils génétiques, la recherche de facteurs prédictifs pour la survie en réponse au traitement, la recherche d'informations nouvelles sur les pathways génétiques impliqués, et la mise en évidence des cibles potentielles pour des traitements futurs. Dans une première analyse, les profils d'expression génétiques ont été utilisés pour regrouper les tumeurs en maximisant leur ressemblance à l'aide d'une approche statistique originale non supervisée dont la pertinence est avérée (Coupled Two-Way Clustering). Les premiers résultats démontrent une séparation effective selon la biologie et l'histologie des tumeurs. Ces résultats encourageants laissent présupposer que les profils d'expression génétiques représentent la prochaine étape pour le diagnostic moléculaire, qui permettra d'identifier les patients étant plus à même de bénéficier des thérapies courantes et d'envisager de nouvelles thérapies plus adaptées aux besoins individuels dans le future. Pour plus de details cliquez ici.

Epigenetic Silencing of the of the MGMT Gene in Glioblastoma Predicts Survival Benefit from Temozolomide (TMZ)

Epigenetic silencing of the O-6-methylguanine-DNA methyltransferase (MGMT) gene by promoter methylation has been recognized as an important factor to predict good outcome in glioblastoma patients treated with alkylating agents. The MGMT gene codes for an excision repair enzyme removing alkyl-groups from the O6-position of guanine, one of the targets of alkylating agents and, thus reversing the treatment effect.
Here we tested the relationship of MGMT silencing with outcome in patients randomized either to initial therapy with the alkylating agent TMZ and radiotherapy (RT) or RT only (EORTC 26981/22981 & NCIC CE.3). The MGMT promoter was methylated in glioblastoma of 45% of 206 patients. In this group the 2-year overall survival rate was 46% when randomized to TMZ/RT compared to only 23% in the RT-arm (p=0.007,log-rank test). Patients with an unmethylated MGMT show a much smaller and statistically not significant difference between treatment arms. (p=0.067, log-rank test).
Here we established the methylation status of the MGMT promoter as a specific predictive factor for survival benefit from TMZ chemotherapy. For the first time patients unlikely to respond can be identified and alternative treatments may be proposed. The determination of the MGMT methylation status is an important towards molecular diagnostics and individually tailored therapy.

Tissue arrays de gliomes

Pour tester les gènes candidats révélés par les profils d'expression génétique, nous avons construit un"tissue array", à partir de blocs en paraffine provenant d'une collection de biopsies de patients opérés entre 1985 et 2000 .Ce " tissue array " contient 190 glioblastomes à l'histopathologie confirmée et pour lesquels nous disposons de données cliniques.
L' âge moyen de ces patients est de 55.7 ans et la moyenne des survies de 39 semaines à partir du diagnostic. Un deuxième "tissue array" de biopsies d'astrocytomes de grade l à grade lll, a également été construit. Ces outils nous permettent de tester rapidement les facteurs de prédiction les plus prometteurs, en utilisant l'immunohistochimie, l'hybridation in situ et la technique du FISH.

Investigating Molecular Mechanisms Involved in EGFR Signalling Pathways Relevant for Tumor Resistance

The first clinical trials in glioblastoma patients using small molecule inhibitors of the EGFR report lack of correlation between response to therapy and the EGFR-status of the tumors. Hence, identification of patients likely to respond to targeted therapies requires more in depth insights into underlying molecular aspects. We use two approaches to investigate the molecular basis of tumor resistance of glioblastoma overexpressing the EGFR or EGFRvIII to specific inhibitors thereof. We use a mouse model to establish a molecular signature for response to inhibition of the EGFR. This molecular signature will subsequently be used to identify the relevant signature in gene expression profiles obtained from untreated human glioblastoma collected in a clinical trial. In addition, the model system is used to gain insights into the molecular mechanism of the EGFR-pathway and its relationship with the dual function of Ink4a/Arf gene.
Previously, we made the novel finding that inactivation of the INK4a/Arf gene locus renders cell lines of mouse astrocytes and glioma resistant to down-regulation of the MAPK-pathway using a small molecule EGFR-inhibitor. These results obtained through in vivo and in vitro approaches are of high relevance: It is known that EGFR amplification/overexpression is associated with deletion of the INK4a/Arf gene locus in glioblastoma, suggesting a cooperative interaction between these two genetic alterations. Thus, our study will contribute to the understanding of the signalling pathways involved in resistance to specific EGFR innhibitors.

Gene Expression Signatures in Human Glioblastoma

The identification of “stem cells” in several tumor types, including glioma, has led to new concepts in cancer research, suggesting that a minority population of cancer stem-like cells may determine the biological behavior of tumors including proliferation, progression, and subsequently response to therapy. Here we propose to identify the expression signature of tumor stem-like cells within the gene expression profiles obtained from 68 glioblastoma of patients enrolled in a clinical trial. Expression profiles of tumor stem-like cells isolated from human glioblastoma and of their respective tumor mass will be determined. This will allow us to (i) establish whether our samples support the notion that stem-like expression signatures can be used to characterize glioblastoma tissue. (ii) Classify tumors according to their stem-like cell pattern, and (iii) correlate the patterns with outcome and response to therapy. Expression signatures will be analyzed for biologically relevant underlying molecular pathways in regard to (iv) biological processes involved and (v) identifying potential therapeutic targets that ultimately may allow the design of therapies aimed at the tumor stem-like cell compartment. This ambitious but realistic project will yield new and timely insights into the relevance of tumor stem-like cells in cancer.

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