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.
Translational Research in Neuro Oncology
Using the novel technique of cDNA-arrays we establish gene expression profiles of human gliomas. This translational research effort includes a project with newly diagnosed glioblastomas of patients enrolled in a phase II trial conducted in Lausanne and Geneva, testing concomitant and adjuvant temozolomide and radiotherapy. This project is extended to the respective randomized phase III trial (EORTC 26981/22981). In a second project we are interested in low grade astrocytomas that eventually recur, usually progressed to a higher grade tumor. However, time to progression and survival varies greatly, and ranges from a few months to over ten years. The objectives of these efforts are (i) classification of the tumors according to their expression profiles, (ii) finding predictive factors for survival and response to therapy, (iii) gaining insights into underlying molecular pathways involved in the evolution of brain tumors, and (iv) identification of new molecular targets for future therapies. In a first analysis, gene expression profiles alone were used to group the tumors employing a powerful unsupervised statistical procedure (Coupled Two-Way Clustering)
, partitioning the tumors in a biologically meaningful manner. These encouraging first results suggest that gene expression profiling may represent a first step towards molecular diagnostics. The ability to differentiate response to therapy and outcome would have great clinical impact since it would allow to identify a subgroup of patients who are most likely to benefit from respective therapies. For details of the analysis please click here
. This work is supported by the Jacqueline Seroussi Foundation
, the NCCR
Molecular Oncology at the ISREC, the EORTC-TRF, the ANOCEF, the SNF, and OncoSuisse.
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 Micro Arrays (TMA)
In order to test candidate genes emerging from gene expression analysis in larger series of tumors, we have constructed tissue arrays. The tissues included are derived from archived paraffin embedded biopsies from patients surgically treated between 1985 and 2000 at the CHUV. The first comprising 190 histologically confirmed glioblastomas linked to clinical data. The median age of the patients is 55.7 years and their median survival was 39 weeks from diagnosis. A second tissue array comprises histologically verified gliomas grade I to III.
More recently we have constructed a TMA comprising over 160 tissues from patients enrolled in the EORTC/NCIC phase III clinical trial for newly diagnosed glioblastoma.
These tools allow rapid screening for the most promising predictive factors using classic immunohistochemistry, in situ hybridization, and 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.