Combining chromosomal arm status and significantly aberrant genomic locations reveals new cancer subtypes

Many types of tumors exhibit chromosomal losses or gains, as well as local amplifications and deletions. Within any given tumor type, sample specific amplifications and deletionsare also observed. Typically, a region that is aberrant in more tumors,or whose copy number change is stronger, would be considered as a more promising candidate to be biologically relevant to cancer. We sought for an intuitive method to define such aberrations and prioritize them. We define V, the volume associated with an aberration, as the product of three factors: a. fraction of patients with the aberration, b. the aberrations length and c. its amplitude. Our algorithm compares the values of V derived from real data to a null distribution obtained by permutations, and yields the statistical significance, p value, of the measured value of V. We detected genetic locations that were significantly aberrant and combined them with chromosomal arm status to create a succint fingerprint of the tumor genome. This genomic fingerprint is used to visualize the tumors, highlighting events that are co ocurring or mutually exclusive. We allpy the method on three different public array CGH datasets of Medulloblastoma and Neuroblastoma, and demonstrate its ability to detect chromosomal regions that were known to be altered in the tested cancer types, as well as to suggest new genomic locations to be tested. We identified a potential new subtype of Medulloblastoma, which is analogous to Neuroblastoma type 1.Comment: 34 pages, 3 figures; to appear in Cancer Informatic

Detection by 32P-postlabeling of thymidine glycol in γ-irradiated DNA

The 32P-postlabeling method has been adapted for the analysis of thymidine-cis-glycol-3′-phosphate (cis-dTGp, cis-5,6-dihydroxy-5,6-dihydrothymidine-3′-phosphate). Cis-dTGp was isolated and purified from normal nucleotides by phenylboronate affinity chromatography and phosphorylated by T4 polynucleotide kinase in presence of 1 mM BeCl2 at pH 7.5. These modifications of the postlabeling method resulted in a 5′-phosphorylation of dTGp with a labeling efficiency of up to 20% whereas the natural nucleotides were almost completely dephosphorylated at the 3′ position under these conditions. The reaction products, containing radio-labeled thymidine-cis-glycol-3′ ,5′-bis-[5′-32P]phosphate (cis-*pdTGp), were separated by two-dimensional anion-exchange TLC on polyethyleneimine cellulose sheets. Boric acid was added in the second dimension in order to selectively retard cis-glycols. The method was applied to γ-irradiated nucleotides and calf thymus DNA. In the nucleotide mixture, 330-99 000 thymine glycol (TG) moieties were detected per 106 thymines (T) in a dose range of 14-1000 Gy respectively. In DNA, these values ranged from 400 to 2700 TG/106 T. The data are in good agreement with methods using radiochemical and immunological techniques. Non-irradiated DNA showed a background level of 1OTG/106 T. This practical limit of detection was higher than can be achieved with the postlabeling technique, indicating that the present method might be a sensitive alternative for a determination of oxidative DNA damag

Clinical Implications of Molecular Neuropathology and Biomarkers for Malignant Glioma

Malignant gliomas are currently diagnosed based on morphological criteria and graded according to the World Health Organization classification of primary brain tumors. This algorithm of diagnosis and classification provides clinicians with an estimated prognosis of the natural course of the disease. It does not reflect the expected response to specific treatments beyond surgery (eg, radiotherapy or alkylating chemotherapy). Clinical experience has revealed that gliomas sharing similar histomorphological criteria might indeed have different clinical courses and exhibit highly heterogenous responses to treatments. This was very impressively demonstrated first for oligodendrogliomas. The presence or lack of combined deletions of the chromosomal segments 1p/19q was associated with different benefit from radiotherapy and chemotherapy. We review current molecular markers for malignant gliomas and discuss their current and future impact on clinical neuro-oncolog

Molecular diagnostics of gliomas: the clinical perspective

Significant progress has been made in the molecular diagnostic subtyping of brain tumors, in particular gliomas. In contrast to the classical molecular markers in this field, p53 and epidermal growth factor receptor (EGFR) status, the clinical significance of which has remained controversial, at least three important molecular markers with clinical implications have now been identified: 1p/19q codeletion, O 6-methylguanine methyltransferase (MGMT) promoter methylation and isocitrate dehydrogenase-1 (IDH1) mutations. All three are favorable prognostic markers. 1p/19q codeletion and IDH1 mutations are also useful to support and extend the histological classification of gliomas since they are strongly linked to oligodendroglial morphology and grade II/III gliomas, as opposed to glioblastoma, respectively. MGMT promoter methylation is the only potentially predictive marker, at least for alkylating agent chemotherapy in glioblastoma. Beyond these classical markers, the increasing repertoire of anti-angiogenic agents that are currently explored within registration trials for gliomas urgently calls for efforts to identify molecular markers that predict the benefit derived from these novel treatments, to

BET protein inhibition sensitizes glioblastoma cells to temozolomide treatment by attenuating MGMT expression

Bromodomain and extra-terminal tail (BET) proteins have been identified as potential epigenetic targets in cancer, including glioblastoma. These epigenetic modifiers link the histone code to gene transcription that can be disrupted with small molecule BET inhibitors (BETi). With the aim of developing rational combination treatments for glioblastoma, we analyzed BETi-induced differential gene expression in glioblastoma derived-spheres, and identified 6 distinct response patterns. To uncover emerging actionable vulnerabilities that can be targeted with a second drug, we extracted the 169 significantly disturbed DNA Damage Response genes and inspected their response pattern. The most prominent candidate with consistent downregulation, was the O-6-methylguanine-DNA methyltransferase (MGMT) gene, a known resistance factor for alkylating agent therapy in glioblastoma. BETi not only reduced MGMT expression in GBM cells, but also inhibited its induction, typically observed upon temozolomide treatment. To determine the potential clinical relevance, we evaluated the specificity of the effect on MGMT expression and MGMT mediated treatment resistance to temozolomide. BETi-mediated attenuation of MGMT expression was associated with reduction of BRD4- and Pol II-binding at the MGMT promoter. On the functional level, we demonstrated that ectopic expression of MGMT under an unrelated promoter was not affected by BETi, while under the same conditions, pharmacologic inhibition of MGMT restored the sensitivity to temozolomide, reflected in an increased level of γ-H2AX, a proxy for DNA double-strand breaks. Importantly, expression of MSH6 and MSH2, which are required for sensitivity to unrepaired O6-methylguanine-lesions, was only briefly affected by BETi. Taken together, the addition of BET-inhibitors to the current standard of care, comprising temozolomide treatment, may sensitize the 50% of patients whose glioblastoma exert an unmethylated MGMT promoter

Weakly Supervised Learning with Automated Labels from Radiology Reports for Glioma Change Detection

Gliomas are the most frequent primary brain tumors in adults. Glioma change detection aims at finding the relevant parts of the image that change over time. Although Deep Learning (DL) shows promising performances in similar change detection tasks, the creation of large annotated datasets represents a major bottleneck for supervised DL applications in radiology. To overcome this, we propose a combined use of weak labels (imprecise, but fast-to-create annotations) and Transfer Learning (TL). Specifically, we explore inductive TL, where source and target domains are identical, but tasks are different due to a label shift: our target labels are created manually by three radiologists, whereas our source weak labels are generated automatically from radiology reports via NLP. We frame knowledge transfer as hyperparameter optimization, thus avoiding heuristic choices that are frequent in related works. We investigate the relationship between model size and TL, comparing a low-capacity VGG with a higher-capacity ResNeXt model. We evaluate our models on 1693 T2-weighted magnetic resonance imaging difference maps created from 183 patients, by classifying them into stable or unstable according to tumor evolution. The weak labels extracted from radiology reports allowed us to increase dataset size more than 3-fold, and improve VGG classification results from 75% to 82% AUC. Mixed training from scratch led to higher performance than fine-tuning or feature extraction. To assess generalizability, we ran inference on an open dataset (BraTS-2015: 15 patients, 51 difference maps), reaching up to 76% AUC. Overall, results suggest that medical imaging problems may benefit from smaller models and different TL strategies with respect to computer vision datasets, and that report-generated weak labels are effective in improving model performances. Code, in-house dataset and BraTS labels are released.Comment: This work has been submitted as Original Paper to a Journa

Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma.

Glioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted "Warburg effect". However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM

Expression of O6-methylguanine-DNA methyltransferase in childhood medulloblastoma

Medulloblastomas (MB) are the most common malignant brain tumors in childhood. Alkylator-based drugs are effective agents in the treatment of patients with MB. In several tumors, including malignant glioma, elevated O6-methylguanine-DNA methyltransferase (MGMT) expression levels or lack of MGMT promoter methylation have been found to be associated with resistance to alkylating chemotherapeutic agents such as temozolomide (TMZ). In this study, we examined the MGMT status of MB and central nervous system primitive neuroectodermal tumor (PNET) cells and two large sets of primary MB. In sevenMB/PNET cell lines investigated, MGMT promoter methylation was detected only in D425 human MB cells as assayed by the qualitative methylation-specific PCR and the more quantitative pyrosequencing assay. In D425 human MB cells, MGMT mRNA and protein expression was clearly lower when compared with the MGMT expression in the other MB/PNET cell lines. In MB/PNET cells, sensitivity towards TMZ and 1-(2-chloroethyl)-3-cyclohexyl-1-nitrosourea (CCNU) correlated with MGMT methylation and MGMT mRNA expression. Pyrosequencing in 67 primary MB samples revealed a mean percentage of MGMT methylation of 3.7-92% (mean: 13.25%, median: 10.67%). Percentage of MGMT methylation and MGMT mRNA expression as determined by quantitative RT-PCR correlated inversely (n=46; Pearson correlation r 2=0.14, P=0.01). We then analyzed MGMT mRNA expression in a second set of 47 formalin-fixed paraffin-embedded primary MB samples from clinically well-documented patients treated within the prospective randomized multicenter trial HIT'91. No association was found between MGMT mRNA expression and progression-free or overall survival. Therefore, it is not currently recommended to use MGMT mRNA expression analysis to determine who should receive alkylating agents and who should no