Identification of Predictive Response Markers and Novel Treatment Targets for Gliomas

Gliomas are the most frequent primary brain tumors in adults. Despite multimodality treatment strategies, the survival of patients with a diffuse glioma remains poor. There has been an increasing use of molecular markers to assist diagnosis and predict prognosis and response to therapy. Although several prognostic and predictive response markers have been identified, considerable research still needs to be done to improve on these. Therefore, the identification of novel predictive response markers and therapeutic targets are desperately needed for this dismal disease. In this thesis, we describe prognostic and identify novel predictive markers in randomized clinical trials. We determined the gene expression profiles of samples of anaplastic oligodendrogliomas and oligoastrocytomas from the EORTC 26951 study and samples of recurrent glioblastomas of the BELOB study to evaluate the treatment responses within defined intrinsic glioma subtypes (IGSs). IGSs are molecularly similar tumors that have been previously identified by unsupervised gene expression analysis. We found that IGSs can be used to assess the molecular heterogeneity within clinical trials. In addition, we confirmed that IGS subtypes are prognostic for survival and predictive. Tumors assigned to IGS-9 showed benefit from adjuvant PCV chemotherapy. In the BELOB study, we found that tumors assigned to IGS-18 (classical GBMs) showed a trend towards benefit from Beva+CCNU treatment. Expression of FMO4 and OSBPL3 were particularly associated with treatment response. Intrinsic subtypes can therefore be used to assess the molecular heterogeneity within clinical trials and may be used as a prognostic and predictive marker. Another method to profile gliomas is based on DNA methylation. We performed genome-wide methylation profiling on material from EORTC 26951 and assessed CIMP and MGMT-STP27 status. We have shown that survival in patients with CIMP+ or MGMT-STP27 methylated tumors was improved compared to CIMP- and/or MGMT-STP27 unmethylated tumors. Importantly, the MGMT-STP27 status was predictive for response to adjuvant PCV chemotherapy in these tumors. MGMT-STP27 may therefore be used to identify AODs and AOAs with improved prognosis and identify patients that are likely to benefit from adjuvant PCV chemotherapy. We also performed functional analysis on different mutations on the EGFR gene and infrequently mutated genes in oligodendrogliomas. We have shown that different mutations within a single gene (EGFR) can have different molecular consequences and have different binding partners for EGFRvIII, EGFRL858 and EGFRwildtype. As these mutations have different functions, each mutation may need its own unique treatment. Functional analysis on infrequently mutated genes showed that the function of many of ‘low frequency’ genes, differs from its wildtype counterpart. This differential effect suggests that these genes can contribute to the disease and therefore may offer new therapeutic targets for oligodendrogliomas

Tumor-specific mutations in low-frequency genes affect their functional properties

Causal genetic changes in oligodendrogliomas (OD) with 1p/19q co-deletion include mutations in IDH1, IDH2, CIC, FUBP1, TERT promoter and NOTCH1. However, it is generally assumed that more somatic mutations are required for tumorigenesis. This study aimed to establish whether genes mutated at low frequency can be involved in OD initiation and/or progression. We performed whole-genome sequencing on three anaplastic ODs with 1p/19q co-deletion. To estimate mutation frequency, we performed targeted resequencing on an additional 39 ODs. Whole-genome sequencing identified a total of 55 coding mutations (range 8–32 mutations per tumor), including known abnormalities in IDH1, IDH2, CIC and FUBP1. We also identified mutations in genes, most of which were previously not implicated in ODs. Targeted resequencing on 39 additional ODs confirmed that these genes are mutated at low frequency. Most of the mutations identified were predicted to have a deleterious functional effect. Functional analysis on a subset of these genes (e.g. NTN4 and MAGEH1) showed that the mutation affects the subcellular localization of the protein (n = 2/12). In addition, HOG cells stably expressing mutant GDI1 or XPO7 showed altered cell proliferation compared to those expressing wildtype constructs. Similarly, HOG cells expressing mutant SASH3 or GDI1 showed altered migration. The significantly higher rate of predicted deleterious mutations, the changes in subcellular localization and the effects on proliferation and/or migration indicate that many of these genes functionally may contribute to gliomagenesis and/or progression. These low-frequency genes and their affected pathways may provide new treatment targets for this tumor type

Glioma Through the Looking GLASS: Molecular Evolution of Diffuse Gliomas and the Glioma Longitudinal AnalySiS Consortium

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas (TCGA) and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal AnalySiS Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities, and ultimately, improved outcomes for a patient population in need

Expression-based intrinsic glioma subtypes are prognostic in low-grade gliomas of the EORTC22033-26033 clinical trial

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Real-time monitoring of drug-laboratory test interactions with an automated decision support application

Background-aim: The lack of knowledge of the presence of Drug-Laboratory Test Interactions (DLTIs) can cause misinterpretation of laboratory test results and delayed or erroneous diagnosis with extra healthcare costs and even harm to patients. There are over 50.000 physiological and/or analytical drug-test interactions described. In this pilot study, an automated decision support application was used to detect drug laboratory test interactions in real-time. Methods: In this multicentre study, 34 clinical rules about DLTI were programmed and validated in an automated decision support application (Gaston, Medecs B.V.). The DLTIs were described in a validated database from the Dutch Society for Clinical Chemistry. The application is able to generate a DLTI-based advisory text based on predefined aberrant laboratory test results and medication data from individual patients and present this alert text to the laboratory specialist in the laboratory information system. The software application was successfully connected and installed in one hospital laboratory in 2018 with two other hospitals to follow in 2019. Generated real-time DLTI alerts were collected and monitored during 4 weeks. Results: A mean of 45 DLTI alerts were generated per day. Twenty-one out of 34 clinical rules were generated at least once in this period. The most frequently reported interactions were magnesium - proton pump inhibitors (14%), creatine kinase – statins (13%) and potassium - ACE-inhibitors (13%). Most DLTI alerts were from the internal medicine department (43%), cardiology department (22%) and the emergency department (10%). Conclusions: In this study, an automated decision support application was implemented to facilitate signalling the presence of drug laboratory test interactions. A mean of 45 DLTI alerts per day were generated in this study. The clinical relevance of the alerts for laboratory specialists and physicians will be examined

Mutation specific functions of EGFR result in a mutation-specific downstream pathway activation

Background: Epidermal growth factor receptor (EGFR) is frequently mutated in various types of cancer. Although all oncogenic mutations are considered activating, different tumour types have different mutation spectra. It is possible that functional differences underlie this tumour-type specific mutation spectrum. Methods: We have determined whether specific mutations in EGFR (EGFR, EGFRvIII and EGFR-L858R) have differences in binding partners, differences in downstream pathway activation (gene expression and phosphoproteins), and have functional consequences on cellular growth and migration. Results: Using biotin pulldown and subsequent mass spectrometry we were able to detect mutation specific binding partners for EGFR. Differential binding was confirmed using a proximity ligation assay and/or Western Blot for the dedicator of cytokinesis 4 (DOCK4), UDP-glucose glycoprotein glucosyltransferase 1 (UGGT1), MYC binding protein 2 (MYCBP2) and Smoothelin (SMTN). We also demonstrate that each mutation induces the expression of a specific set of genes, and that each mutation is associated with specific phosphorylation patterns. Finally, we demonstrate using stably expressing cell lines that EGFRvIII and EGFL858R display reduced growth and migration compared to EGFR ildtype expressing cells