Mutations In Glioblastoma Research Articles

Dissecting and analyzing the Subclonal Mutations Associated with Poor Prognosis in Diffuse Glioma.

The prognostic and therapeutic implications in diffuse gliomas are still challenging. In this study, we first performed an integrative framework to infer the clonal status of mutations in glioblastomas (GBMs) and low-grade gliomas (LGGs) by using exome sequencing data from TCGA and observed both clonal and subclonal mutations for most mutant genes. Based on the clonal status of a given gene, we systematically investigated its prognostic value in GBM and LGG, respectively. Focusing on the subclonal mutations, our results showed that they were more likely to contribute to the poor prognosis, which could be hardly figured out without considering clonal status. These risk subclonal mutations were associated with some specific genomic features, such as genomic instability and intratumor heterogeneity, and their accumulation could enhance the prognostic value. By analyzing the regulatory mechanisms underlying the risk subclonal mutations, we found that the subclonal mutations of AHNAK and AHNAK2 in GBM and those of NF1 and PTEN in LGG could influence some important molecules and functions associated with glioma progression. Furthermore, we dissected the role of risk subclonal mutations in tumor evolution and found that advanced subclonal mutations showed poorer overall survival. Our study revealed the importance of clonal status in prognosis analysis, highlighting the role of the subclonal mutation in glioma prognosis.

TERT promoter C228T mutation in neural progenitors confers growth advantage following telomere shortening in vivo.

Heterozygous TERT (telomerase reverse transcriptase) promoter mutations (TPMs) facilitate TERT expression and are the most frequent mutation in glioblastoma (GBM). A recent analysis revealed this mutation is one of the earliest events in gliomagenesis. However, no appropriate human models have been engineered to study the role of this mutation in the initiation of these tumors. We established GBM models by introducing the heterozygous TPM in human induced pluripotent stem cells (hiPSCs) using a two-step targeting approach in the context of GBM genetic alterations, CDKN2A/B and PTEN deletion, and EGFRvIII overexpression. The impact of the mutation was evaluated through the in vivo passage and in vitro experiment and analysis. Orthotopic injection of neuronal precursor cells (NPCs) derived from hiPSCs with the TPM into immunodeficient mice did not enhance tumorigenesis compared to TERT promoter wild type NPCs at initial in vivo passage presumably due to relatively long telomeres. However, the mutation recruited GA-Binding Protein and engendered low-level TERT expression resulting in enhanced tumorigenesis and maintenance of short telomeres upon secondary passage as observed in human GBM. These results provide the first insights regarding increased tumorigenesis upon introducing a TPM compared to isogenic controls without TPMs. Our novel GBM models presented the growth advantage of heterozygous TPMs for the first time in the context of GBM driver mutations relative to isogenic controls, thereby allowing for the identification and validation of TERT promoter-specific vulnerabilities in a genetically accurate background.

The Subventricular Zone in Glioblastoma: Genesis, Maintenance, and Modeling.

Glioblastoma (GBM) is a malignant tumor with a median survival rate of 15-16 months with standard care; however, cases of successful treatment offer hope that an enhanced understanding of the pathology will improve the prognosis. The cell of origin in GBM remains controversial. Recent evidence has implicated stem cells as cells of origin in many cancers. Neural stem/precursor cells (NSCs) are being evaluated as potential initiators of GBM tumorigenesis. The NSCs in the subventricular zone (SVZ) have demonstrated similar molecular profiles and share several distinctive characteristics to proliferative glioblastoma stem cells (GSCs) in GBM. Genomic and proteomic studies comparing the SVZ and GBM support the hypothesis that the tumor cells and SVZ cells are related. Animal models corroborate this connection, demonstrating migratory patterns from the SVZ to the tumor. Along with laboratory and animal research, clinical studies have demonstrated improved progression-free survival in patients with GBM after radiation to the ipsilateral SVZ. Additionally, key genetic mutations in GBM for the most part carry regulatory roles in the SVZ as well. An exciting avenue towards SVZ modeling and determining its role in gliomagenesis in the human context is human brain organoids. Here we comprehensively discuss and review the role of the SVZ in GBM genesis, maintenance, and modeling.

Molecular alterations associated with improved outcome in patients with glioblastoma treated with Tumor-Treating Fields.

BackgroundThe genomic and overall biologic landscape of glioblastoma (GB) has become clearer over the past 2 decades, as predictive and prognostic biomarkers of both de novo and transformed forms of GB have been identified. The oral chemotherapeutic agent temozolomide (TMZ) has been integral to standard-of-care treatment for nearly 2 decades. More recently, the use of non-pharmacologic interventions, such as application of alternating electric fields, called Tumor-Treating Fields (TTFields), has emerged as a complementary treatment option that increases overall survival (OS) in patients with newly diagnosed GB. The genomic factors associated with improved or lack of response to TTFields are unknown.MethodsWe performed comprehensive genomic analysis of GB tumors resected from 55 patients who went on to receive treatment using TTFields, and compared results to 57 patients who received standard treatment without TTFields.ResultsWe found that molecular driver alterations in NF1, and wild-type PIK3CA and epidermal growth factor receptor (EGFR), were associated with increased benefit from TTFields as measured by progression-free survival (PFS) and OS. There were no differences when stratified by TP53 status. When NF1, PIK3CA, and EGFR status were combined as a Molecular Survival Score, the combination of the 3 factors significantly correlated with improved OS and PFS in TTFields-treated patients compared to patients not treated with TTFields.ConclusionsThese results shed light on potential driver and passenger mutations in GB that can be validated as predictive biomarkers of response to TTFields treatment, and provide an objective and testable genomic-based approach to assessing response.

Association of MGMT Gene Promoter Methylation With Clinicopathological Parameters in Patients With Wild-type IDH Glioblastoma.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter plays a key role in response to temozolomide chemotherapy and disease prognosis in patients with wild-type isocitrate dehydrogenase (IDH) glioblastoma (GBM). The MGMT promoter methylation status and its association with clinicopathological parameters were retrospectively analysed in a cohort of 316 patients with GBM with wild-type IDH. MGMT methylation was significantly associated with ATRX chromatin remodeler (ATRX) loss and completion of the standard Stupp protocol. The median durations of overall and progression-free survival for the unmethylated, low-methylated (10-39%), and hypermethylated (≥40%) groups were 15, 23, and 30 months and 11, 18, and 21 months, respectively. However, the improvement in the survival of the hypermethylated group was not statistically significant. We suggest a possible association between MGMT methylation status and ATRX mutations in GBM with wild-type IDH.

NIMG-52. RADIOGENOMICS SIGNATURES IN KEY DRIVER GENES IN GLIOBLASTOMA EVALUATED WITH AND WITHOUT THE PRESENCE OF CO-OCCURRING MUTATIONS

Abstract PURPOSE Glioblastomas display significant heterogeneity on the molecular level, typically harboring several co-occurring mutations, which likely contributes to failure of molecularly targeted therapeutic approaches. Radiogenomics has emerged as a promising tool for in vivo characterization of this heterogeneity. We derive radiogenomic signatures of four mutations via machine learning (ML) analysis of multiparametric MRI (mpMRI) and evaluate them in the presence and absence of other co-occurring mutations. METHODS We identified a retrospective cohort of 359 IDH-wildtype glioblastoma patients, with available pre-operative mpMRI (T1, T1Gd, T2, T2-FLAIR) scans and targeted next generation sequencing (NGS) data. Radiomic features, including morphologic, histogram, texture, and Gabor wavelet descriptors, were extracted from the mpMRI. Multivariate predictive models were trained using cross-validated SVM with LASSO feature selection to predict mutation status in key driver genes, EGFR, PTEN, TP53, and NF1. ML models and spatial population atlases of genetic mutations were generated for stratification of the tumors (1) with co-occurring mutations versus wildtypes, (2) with exclusive mutations in each driver gene versus the tumors without any mutations in the pathways associated with these genes. RESULTS ML models yielded AUCs of 0.75 (95%CI:0.62-0.88) / 0.87 (95%CI:0.70-1) for co-occurring / exclusive EGFR mutations, 0.69 (95%CI:0.58-0.80) / 0.80 (95%CI:0.61-0.99) for co-occurring / exclusive PTEN mutations, and 0.77 (95%CI:0.65-0.88) / 0.86 (95%CI:0.69-1) for co-occurring / exclusive TP53 cases. Spatial atlases revealed a predisposition of left temporal lobe for NF1 and right frontotemporal region for TP53 in mutually exclusive tumors, which was not observed in the co-occurring mutation atlases. CONCLUSION Our results suggest the presence of distinct radiogenomic signatures of several glioblastoma mutations, which become even more pronounced when respective mutations do not co-occur with other mutations. These in vivo signatures can contribute to pre-operative stratification of patients for molecular targeted therapies, and potentially longitudinal monitoring of mutational changes during treatment.

Prognostic Impact of the Combination of MGMT Methylation and TERT Promoter Mutation in Glioblastoma.

Background The concept of combinational analysis between the methylation of O 6 -methylguanine-DNA methyltransferase ( MGMT ) and telomerase reverse transcriptase promoter ( pTERT ) mutation in glioblastoma (GBM) has been reported. The main study objective was to determine the prognosis of patients with GBM based on MGMT/pTERT classification, while the secondary objective was to estimate the temozolomide effect on the survival time of GBM with MGMT/pTERT classification. Methods A total of 50 GBM specimens were collected after tumor resection and were selected for investigating MGMT methylation and pTERT mutation. Clinical imaging and pathological characteristics were retrospectively analyzed. Patients with MGMT/pTERT classification were analyzed using survival analysis to develop the nomogram for forecasting and individual prognosis. Results All patients underwent resection (total resection: 28%, partial resection: 64%, biopsy: 8%). Thirty-two percent of all cases received adjuvant temozolomide with radiotherapy. Sixty-four percent of the case was found methylated MGMT , and 56% of the present cohort found pTERT mutation. Following combinational analysis of biomarkers, results showed that the GBMs with methylated MGMT and wild-type pTERT had a superior prognosis compared with other subtypes. Using Cox regression analysis with multivariable analysis, the extent of resection, postoperative chemoradiotherapy, MGMT/pTERT classification were associated with a favorable prognosis. Hence, a web-based nomogram was developed for deploying individual prognostication. Conclusions The interaction of MGMT methylation and pTERT mutation was confirmed for predicting prognosis. The results from the present study could help physicians create treatment strategies for GBM patients in real-world situations.

Detection of Isocitrate Dehydrogenase Mutated Glioblastomas Through Anomaly Detection Analytics.

The rarity of Isocitrate Dehydrogenase mutated (mIDH) glioblastomas relative to wild-type IDH glioblastomas, as well as their distinct tumor physiology, effectively render them "outliers". Specialized tools are needed to identify these outliers. To carefully craft and apply anomaly detection methods to identify mIDH glioblastoma based on radiomic features derived from magnetic resonance imaging. T1-post gadolinium images for 188 patients and 138 patients were downloaded from The Cancer Imaging Archive's (TCIA) The Cancer Genome Atlas (TCGA) glioblastoma collection, and from the University of Minnesota Medical Center (UMMC), respectively. Anomaly detection methods were tested on glioblastoma image features for the precision of mIDH detection and compared to standard classification methods. Using anomaly detection training methods, we were able to detect IDH mutations from features in noncontrast-enhancing regions in glioblastoma with an average precision of 75.0%, 69.9%, and 69.8% using three different models. Anomaly detection methods consistently outperformed traditional two-class classification methods from 2 unique learning models (67.9%, 67.6%). The disparity in performances could not be overcome through newer, popular models such as neural networks (67.4%). We employed an anomaly detection strategy in the detection of IDH mutation in glioblastoma using preoperative T1 postcontrast imaging. We show these methods outperform traditional two-class classification in the setting of dataset imbalances inherent to IDH mutation prevalence in glioblastoma. We validate our results using an external dataset and highlight new possible avenues for radiogenomic rare event prediction in glioblastoma and beyond.

Predicting BRAF V600E mutation in glioblastoma: utility of radiographic features

Detection of BRAF V600E mutation in glioblastomas (GBMs) is important because of potential therapeutic implications. Still, the relative paucity of these mutations makes molecular detection in all GBMs controversial. In the present study, we analyzed clinical, radiographic and pathologic features of 12 BRAF V600E-mutant GBMs and 12 matched controls from 2 institutions. We found that a majority of BRAF V600E-mutant GBMs displayed a combination of well-circumscribed lesions, large cystic components with thin walls and solid cortical component on MRI, but with some overlap with matched BRAF wildtype controls (p = 0.069). BRAF V600E-mutant GBMs were also apt to gross total resection (83% vs 17%, p = 0.016) and morphologically displayed epithelioid features (83% vs 0%, p < 0.0001). Identification of these clinical, radiographic, and pathologic characteristics should prompt testing for BRAF V600E in IDH-wildtype GBM.

FSMP-08. TARGETING PYRIMIDINE SYNTHESIS ACCENTUATES MOLECULAR THERAPY RESPONSE IN GLIOBLASTOMA STEM CELLS

Glioblastoma stem cells (GSCs) reprogram glucose metabolism by hijacking high-affinity glucose uptake to survive in a nutritionally dynamic microenvironment. Here, we trace metabolic aberrations in GSCs to link core genetic mutations in glioblastoma to dependency on de novo pyrimidine synthesis. Targeting the pyrimidine synthetic rate-limiting step enzyme carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, dihydroorotase (CAD) or the critical downstream enzyme dihydroorotate dehydrogenase (DHODH) inhibited GSC survival, self-renewal, and in vivo tumor initiation through the depletion of the pyrimidine nucleotide supply in rodent models. Mutations in EGFR or PTEN generated distinct CAD phosphorylation patterns to activate carbon influx through pyrimidine synthesis. Simultaneous abrogation of tumor-specific driver mutations and DHODH activity with clinically approved inhibitors demonstrated sustained inhibition of metabolic activity of pyrimidine synthesis and GSC tumorigenic capacity in vitro. Higher expression of pyrimidine synthesis genes portends poor prognosis of patients with glioblastoma. Collectively, our results demonstrate a therapeutic approach of precision medicine through targeting the nexus between driver mutations and metabolic reprogramming in cancer stem cells.

Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma.

The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma. This retrospective study included glioblastoma cases (n = 199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined. Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (ĸ = 0.49 [-0.11-1.00]), necrosis (ĸ = 0.55 [0.34-0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68-0.99]), multifocal disease (ĸ = 0.55 [0.39-0.70]), and primary lobe (ĸ = 0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3cm [0.2-0.5], p < 0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, ∞], p < 0.001), younger age (OR 0.93 [0.86, 0.98], p = 0.009), frontal lobe location (OR 11.08 [1.14, 352.97], p = 0.037), and less peritumoral edema (OR 0.15 [0, 0.65], p = 0.044). Conventional MRI metrics and patient age predict IDH-mutation status in glioblastoma. Among MRI markers, fluid attenuation in nCET represents a novel marker with high inter-reader agreement that is strongly associated with Glioblastoma, IDH-mutant.

Optimising gene editing for cancer therapy

Gene editing holds promise for the treatment of cancers that are driven by well-characterised molecular alterations. A study now provides a proof of concept for the feasibility of in vivo gene editing to correct TERT mutations in glioblastoma, providing a platform for the direct manipulation of genetic alterations to reduce tumour growth.

GENE-59. NOT ALL p53 MUTATIONS ARE CREATED EQUAL: A MURINE ASTROCYTE MODEL FOR HIGH-THROUGHPUT FUNCTIONAL ASSESSMENT OF p53 MISSENSE MUTATIONS

Abstract The tumor suppressor TP53 (p53) is the most commonly mutated gene in cancer and among the most frequently mutated genes in glioblastoma (GBM). The majority of p53 mutations in GBM are missense mutations in the DNA binding domain that lead to the production of full length mutant p53 protein. In addition to the complete loss of tumor suppressor function, these mutations have gain-of-function (GOF) properties either through attenuation of wild-type function or neomorphic functions. The variability in GOF mutations results in heterogeneity in cancer phenotypes between mutants that remain poorly understood. Here, we developed a murine astrocyte model to functionally assess a library of p53 mutants in parallel. Primary astrocytes were isolated from postnatal day one pups possessing a single copy of wild-type p53 flanked by loxP sites (TRP53f/-). We then built a library of 17 individual alleles of recurring mutations in GBM with flanking loxP sites. When co-transfected into the mouse astrocytes with a plasmid expressing Cre recombinase, the endogenous WT p53 was excised and replaced with a single copy of the mutant allele. In this way, all astrocytes expressed a single copy of mutant p53 from the endogenous p53 locus. As the mutant p53 cells expanded, aliquots of cells were extracted for targeted genomic sequencing of the p53 allele. Comparing the allelic frequencies of each mutant overtime revealed a wide distribution of growth rates between mutants. To validate the screen results, wildtype astrocytes were transduced with mutant p53-IRES-eGFP retrovirus to overexpress one of three mutations with divergent growth phenotypes. As observed in the initial screen, equivalent overexpression of the different p53 mutants was sufficient to induce significant differences in growth phenotype, with astrocytes expressing the Y217C growing the fastest, R172H second, and Y202C growing the slowest. Ongoing studies are evaluating mutation-specific p53 binding partners and transcriptional outputs.

TMIC-47. INHIBITION OF GLIOBLASTOMA GROWTH THROUGH TUMOR-MICROENVIRONMENT CROSSTALK USING CLINICALLY SUITABLE NANOBIOCONJUGATE

Abstract Tumor environment in glioblastoma (GBM) is a dynamic interactive complex between tumor, immune and stem cells and extracellular matrix (ECM). In 226 patient glioma samples, we found a clinical correlation between expression of tumor vascular laminin-411 (α4β1γ1) and cancer stem cell (CSC) markers: Notch pathway members, CD133, Nestin, and c-Myc, with faster tumor recurrence and shorter survival of patients (Tao S, et al, Cancer Res., 2019). Novel nanotechnology approach to block trimeric ECM laminin-411 was developed for GBM treatment in experimental and preclinical models on human U87MG and LN229, and patient-derived TS543 and TS576 GBM cell lines. Nanobioconjugates (NBC) based on natural polymer, poly(β-L-malic acid), with antisense against laminin-411 α4 and β-chains, endosome escape unit (Ding H, et al, PNAS, USA, 2010), antibodies for blood-brain barrier (BBB) crossing and tumor targeting was characterized for toxicity and biodistribution according to FDA guidelines. Ex vivo depletion of laminin-411 α4 and β1 chains with CRISPR/Cas9 in human GBM cells led to reduced growth of intracranial tumors in mice, and significantly increased survival in hosts compared to mice with untreated cells. A nanobioconjugate potentially suitable for clinical use and capable of crossing BBB was designed to block laminin-411 expression. In biodistribution studies the NBC labeled with 125I on tyrosines of attached antibodies was accumulated in GBM but not in healthy brain tissue. Nanobioconjugate treatment of mice carrying intracranial GBM significantly increased animal survival and inhibited multiple CSC markers, Notch signaling system through the b1 integrin-Dll4 (Notch ligand) pathway. No toxicity revealed in 4 naïve Cynomolgus macaques after administration of three therapeutic 1X and acute 10X dosages of NBC. Conclusion: An efficient strategy of GBM treatment was developed via targeting a critical component of the tumor microenvironment, laminin-411, which is independent of heterogeneous genetic mutations in glioblastomas. Support: NIH grants U01CA151815, R01CA188743, R01CA206220, R01CA209921.

STEM-22. TARGETING PYRIMIDINE SYNTHESIS ACCENTUATES MOLECULAR THERAPY RESPONSE IN GLIOBLASTOMA STEM CELLS

Abstract Glioblastoma stem cells (GSCs) reprogram glucose metabolism by hijacking high-affinity glucose uptake to survive in a nutritionally dynamic microenvironment. Here, we trace metabolic aberrations in GSCs to link core genetic mutations in glioblastoma to dependency on de novo pyrimidine synthesis. Targeting the pyrimidine synthetic rate-limiting step enzyme carbamoyl-phosphate synthetase 2, aspartate transcarbamyolase, dihydroorotase (CAD) or the critical downstream enzyme, dihydroorotate dehydrogenase (DHODH) inhibited GSC survival, self-renewal, and in vivo tumor initiation through the depletion of the pyrimidine nucleotide supply in rodent models. Mutations in EGFR or PTEN generated distinct CAD phosphorylation patterns to activate carbon influx through pyrimidine synthesis. Simultaneous abrogation of tumor-specific driver mutations and DHODH activity with clinically approved inhibitors demonstrated sustained inhibition of metabolic activity of pyrimidine synthesis and GSC tumorigenic capacity. Higher expression of pyrimidine synthesis genes portend poor prognosis of glioblastoma patients. Collectively, our results demonstrate a therapeutic approach of precision medicine through targeting the nexus between driver mutations and metabolic reprogramming in cancer stem cells.

NIMG-75. RADIOMIC FEATURES LOCALIZED TO STEREOTACTIC BIOPSY LOCATIONS CAN CAPTURE EGFR PRESENCE IN GLIOBLASTOMA

Abstract PURPOSE Epidermal growth factor receptor amplification (EGFRamp), occurs in &gt;60% of Glioblastoma (GBM) patients, and can predict response to alkylating chemotherapy. However, due to high genetic instability in GBM, a significant caveat to sampling EGFRamp during biopsy, is that reliable identification of its presence is dependent on the site of the biopsy, and may vary throughout the tumor. Previous studies have employed radiomics (computerized feature extraction) from the entire tumor to characterize EGFRamp presence. Our work is based on the rationale that radiomics measurements from stereotactic biopsy locations on Gd-T1w MRI, may allow to build accurate training models for predicting EGFRamp compared to using radiomic features from the entire tumor. METHODS MRI scans from 78 GBM subjects (33 EGFRamp, 45 non-amp) were obtained, of which 54 subjects were used for training while 24 were used for testing. Stereotactic biopsy locations were mapped by co-registering CT-images with MRIs (confirmed by two radiologists). For each biopsy region (1-cm diameter sphere), gradient entropy features and gender information were used to train a discriminant analysis classifier, on a voxel-wise manner. Our training model also included per-voxel spatial probabilities that were obtained by building atlases to quantify frequency of occurrence of EGFRamp and non-amp cases. All of these features were then used within the test set to predict EGFR status. RESULTS The model achieved a training accuracy of 81.4%, correctly classifying 17/23-amp, 27/31 non-amp cases. Accuracy on test set was 79.2% (7/10 amp, 12/14 non-amp cases correctly classified). Extracting features from the entire tumor achieved a training accuracy of 74% (17/23-amp, 23/31 non-amp cases correctly classified), and a testing accuracy of 70.8% (6/10 amp, 11/14 non-amp cases correctly classified). CONCLUSION Radiomic features, trained using features from only the stereotactic biopsy locations, may be more reliable in training models to predict EGFR mutation in GBM.

Genetic and Lineage Classification of Glioma-Initiating Cells Identifies a Clinically Relevant Glioblastoma Model.

The Cancer Genome Atlas (TCGA) project described a robust gene expression-based molecular classification of glioblastoma (GBM), but the functional and biological significance of the subclasses has not been determined. The present comprehensive analysis of 25 glioma-initiating cell (GIC) lines classifies GIC lines into four subtypes (classical, mesenchymal, proneural, and neural) that are closely related to the TCGA GBM subclasses and display distinct lineage characteristics and differentiation behavior that recapitulate neural development. More importantly, the GIC subtypes exhibit distinct biological phenotypes in relation to self-renewal capacity, proliferation, invasiveness, and angiogenic potential in vitro and in vivo. In addition, the GIC subtypes exhibit divergent patterns of signaling pathway activation and deactivation of the Wnt, Notch, and TGF-β pathways. These results will improve drug discovery targeting certain genetic mutation in glioblastoma and improve the development of precision medicine.

Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging.

PTEN mutation status is a pivotal biomarker for glioblastoma. This study aimed to establish a radiomic signature to predict PTEN mutation status in patients with glioblastoma, and to investigate the genetic background behind this radiomic signature. In this study, a total of 862 radiomic features were extracted from each patient. The training (n = 69) and validation (n = 40) sets were retrospectively collected from the Cancer Genome Atlas and the Chinese Glioma Genome Atlas, respectively. The minimum redundancy maximum relevance (mRMR) algorithm was used to select the best predictive features of PTEN status. A machine learning model was then built with the selected features using a support vector machine classifier. The predictive performance of each selected feature and the complete model were evaluated via the area under the curve from receiver operating characteristic analysis in both the training and validation sets. The genetic background underlying the radiomic signature was determined using radiogenomic analysis. Six features were selected using the mRMR algorithm, including two features derived from contrast-enhanced images and four features derived from T2-weighted images. The predictive performance of the machine learning model for the training and validation sets were 0.925 and 0.787, respectively, which were better than the individual features. Radiogenomics analysis revealed that the PTEN-associated biological processes could be described using the radiomic signature. These results show that radiomic features derived from preoperative MRI can predict PTEN mutation status in glioblastoma patients, thus providing a novel noninvasive imaging biomarker.

Practical Bioinformatic DNA-Sequencing Pipeline for Detecting Oncogene Amplification and EGFRvIII Mutational Status in Clinical Glioblastoma Samples

Glioblastoma is a malignant brain tumor with dismal prognosis. Oncogenic mutations in glioblastoma frequently affect receptor tyrosine kinase pathway components that are challenging to quantify because of heterogeneous expression. EGFRvIII, a common oncogenic receptor tyrosine kinase mutant protein in glioblastoma, potentiates tumor malignancy and is an emerging tumor-specific immunotarget, underlining the need for its more accessible and quantitative detection. We used normalized next-generation sequencing data from 117 brain and 371 reference clinical tumor samples to detect focal gene amplifications across the commercial Ion AmpliSeq Cancer Hotspot Panel version 2 and infer EGFRvIII status based on relative coverage dropout of the gene's truncated region within EGFR. In glioblastomas (n=45), amplification of EGFR [18 (40%)], PDGFRA [3 (7%)], KIT [2 (4%)], MET [1 (2%)], and AKT1 [1 (2%)] was detected. With respect to EGFR and PDGFRA amplification, there was near-complete agreement between next-generation sequencing and in situ hybridization. Consistent with previous reports, this method detected EGFRvIII exclusively in EGFR-amplified glioblastomas [8 (44%)], which was confirmed using long-range PCR. Our study offers a practical method for detecting oncogene amplifications and large intragenic mutations in a clinically implemented hotspot panel that can be quantified using z scores. The validated detection of EGFRvIII using DNA sequencing eliminates problems with transcript degradation, and the provided script facilitates efficient incorporation into a laboratory's bioinformatic pipeline.

Blockade of a Laminin-411-Notch Axis with CRISPR/Cas9 or a Nanobioconjugate Inhibits Glioblastoma Growth through Tumor-Microenvironment Cross-talk.

There is an unmet need for the treatment of glioblastoma multiforme (GBM). The extracellular matrix, including laminins, in the tumor microenvironment is important for tumor invasion and progression. In a panel of 226 patient brain glioma samples, we found a clinical correlation between the expression of tumor vascular laminin-411 (α4β1γ1) with higher tumor grade and with expression of cancer stem cell (CSC) markers, including Notch pathway members, CD133, Nestin, and c-Myc. Laminin-411 overexpression also correlated with higher recurrence rate and shorter survival of GBM patients. We also showed that depletion of laminin-411 α4 and β1 chains with CRISPR/Cas9 in human GBM cells led to reduced growth of resultant intracranial tumors in mice and significantly increased survival of host animals compared with mice with untreated cells. Inhibition of laminin-411 suppressed Notch pathway in normal and malignant human brain cell types. A nanobioconjugate potentially suitable for clinical use and capable of crossing blood-brain barrier was designed to block laminin-411 expression. Nanobioconjugate treatment of mice carrying intracranial GBM significantly increased animal survival and inhibited multiple CSC markers, including the Notch axis. This study describes an efficient strategy for GBM treatment via targeting a critical component of the tumor microenvironment largely independent of heterogeneous genetic mutations in glioblastoma.Significance: Laminin-411 expression in the glioma microenvironment correlates with Notch and other cancer stem cell markers and can be targeted by a novel, clinically translatable nanobioconjugate to inhibit glioma growth.