Identification of variants in primary and recurrent glioblastoma using a cancer-specific gene panel and whole exome sequencing

Plasma amino acids indicate glioblastoma with ATRX loss

Glioblastoma (GB) is the most common primary brain tumour in adults. The lack of molecular biomarker, non-specific symptoms and fast growth rate often result in a significant delay in diagnosis. Despite multimodal treatment, the prognosis remains poor. Here, we verified the hypothesis that amino acids (AA) regulating the critical metabolic pathways necessary for maintenance, growth, reproduction, and immunity of an organism, may constitute a favourable target in GB biomarker research. We measured the plasma amino acids levels in 18 GB patients and 15 controls and performed the quantitative and qualitative metabolomic analysis of free AA applying high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). We present both the raw data and the results of our statistical analysis. The majority of AA were lowered in the study group in comparison to the control group. Five of these (arginine, glutamic acid, glutamine, glycine, and histidine) differed significantly (all p < 10^-5 and AUC > 0.9). Plasma levels of leucine and phenylalanine decreased in the case of GB with lost alpha-thalassemia/mental retardation X-linked (ATRX) expression on immunohistochemistry (p = 0.003 and 0.045, respectively). We demonstrated for the first time that certain plasma-free AA levels of GB patients were significantly different from those in healthy volunteers. Target profiling of plasma-free AA, identified utilizing LC-QTOF-MS, may present prognostic value by indicating GB patients with lost ATRX expression. The on-going quest for glioma biomarkers still aims to determine the detailed metabolic profile and evaluate its impact on therapy and prognosis.

Correlation of genetic alterations by whole-exome sequencing with clinical outcomes of glioblastoma patients from the Lebanese population

Introduction

Glioblastoma (GBM) is an aggressive brain tumor associated with high degree of resistance to treatment. Given its heterogeneity, it is important to understand the molecular landscape of this tumor for the development of more effective therapies. Because of the different genetic profiles of patients with GBM, we sought to identify genetic variants in Lebanese patients with GBM (LEB-GBM) and compare our findings to those in the Cancer Genome Atlas (TCGA).

Methods

We performed whole exome sequencing (WES) to identify somatic variants in a cohort of 60 patient-derived GBM samples. We focused our analysis on 50 commonly mutated GBM candidate genes and compared mutation signatures between our population and publicly available GBM data from TCGA. We also cross-tabulated biological covariates to assess for associations with overall survival, time to recurrence and follow-up duration.

Results

We included 60 patient-derived GBM samples from 37 males and 23 females, with age ranging from 3 to 80 years (mean and median age at diagnosis were 51 and 56, respectively). Recurrent tumor formation was present in 94.8% of patients (n = 55/58). After filtering, we identified 360 somatic variants from 60 GBM patient samples. After filtering, we identified 360 somatic variants from 60 GBM patient samples. Most frequently mutated genes in our samples included ATRX, PCDHX11, PTEN, TP53, NF1, EGFR, PIK3CA, and SCN9A. Mutations in NLRP5 were associated with decreased overall survival among the Lebanese GBM cohort (p = 0.002). Mutations in NLRP5 were associated with decreased overall survival among the Lebanese GBM cohort (p = 0.002). EGFR and NF1 mutations were associated with the frontal lobe and temporal lobe in our LEB-GBM cohort, respectively.

Conclusions

Our WES analysis confirmed the similarity in mutation signature of the LEB-GBM population with TCGA cohorts. It showed that 1 out of the 50 commonly GBM candidate gene mutations is associated with decreased overall survival among the Lebanese cohort. This study also highlights the need for studies with larger sample sizes to inform clinicians for better prognostication and management of Lebanese patients with GBM.

Alpha-Methylacyl-CoA Racemase (AMACR), a Potential New Biomarker for Glioblastoma

Alpha-Methylacyl-CoA racemase (AMACR), which was initially discovered as a prostate cancer marker, is critical for the chiral inversion mechanism of branched-chain fatty acids. However, the function of AMACR in brain tumors has not been investigated. In this study, AMACR appeared to be involved in glioblastoma. The protein and mRNA levels of AMACR were highly elevated in glioblastoma. Downregulation of AMACR inhibited cell proliferation. Comprehensive analysis of the public REMBRANDT GBM dataset also confirmed that the level of AMACR expression was correlated with the clinical prognosis of glioma patients. In summary, these findings indicate that AMACR expression is increased in a glioblastoma cell line and glioma patients, suggesting that AMACR might be a potential diagnostic marker and therapeutic target for cancer, including glioma.

Dissecting Molecular Features of Gliomas: Genetic Loci and Validated Biomarkers

Recently, several studies focused on the genetics of gliomas. This allowed identifying several germline loci that contribute to individual risk for tumor development, as well as various somatic mutations that are key for disease classification. Unfortunately, none of the germline loci clearly confers increased risk per se. Contrariwise, somatic mutations identified within the glioma tissue define tumor genotype, thus representing valid diagnostic and prognostic markers. Thus, genetic features can be used in glioma classification and guided therapy. Such copious genomic variabilities are screened routinely in glioma diagnosis. In detail, Sanger sequencing or pyrosequencing, fluorescence in-situ hybridization, and microsatellite analyses were added to immunohistochemistry as diagnostic markers. Recently, Next Generation Sequencing was set-up as an all-in-one diagnostic tool aimed at detecting both DNA copy number variations and mutations in gliomas. This approach is widely used also to detect circulating tumor DNA within cerebrospinal fluid from patients affected by primary brain tumors. Such an approach is providing an alternative cost-effective strategy to genotype all gliomas, which allows avoiding surgical tissue collection and repeated tumor biopsies. This review summarizes available molecular features that represent solid tools for the genetic diagnosis of gliomas at present or in the next future.

Challenges in the Treatment of Glioblastoma: Multisystem Mechanisms of Therapeutic Resistance

Glioblastoma is one of the most lethal human cancers, with poor survival despite surgery, radiation treatment, and chemotherapy. Advances in the treatment of this type of brain tumor are limited because of several resistance mechanisms. Such mechanisms involve limited drug entry into the central nervous system compartment by the blood-brain barrier and by actions of the normal brain to counteract tumor-targeting medications. In addition, the vast heterogeneity in glioblastoma contributes to significant therapeutic resistance by preventing adequate control of the entire tumor mass by a single drug and by facilitating escape mechanisms from targeted agents. The stem cell-like characteristics of glioblastoma promote resistance to chemotherapy, radiation, and immunotherapy through upregulation of efflux transporters, promotion of glioblastoma stem cell proliferation in neurogenic zones, and immune suppression, respectively. Metabolic cascades in glioblastoma prevent effective treatments through the optimization of glucose use, the use of alternative nutrient precursors for energy production, and the induction of hypoxia to enhance tumor growth. In the era of precision medicine, an assortment of molecular techniques is being developed to target an individual's unique tumor, with the hope that this personalized strategy will bypass therapeutic resistance. Although each resistance mechanism presents an array of challenges to effective treatment of glioblastoma, as the field recognizes and addresses these difficulties, future treatments may have more efficacy and promise for patients with glioblastoma.

Fluorescent In Situ Hybridization in Surgical Pathology Practice

There have been rapid and significant advances in diagnostic and predictive molecular techniques in recent years with profound impact on patient care. In situ hybridization (ISH) studies have become well entrenched in surgical pathology practice and their role in the evaluation of HER2 in breast carcinoma and their diagnostic utility in soft tissue pathology are well known. Fluorescent ISH is being increasingly used in other sites such as the head and neck and the gynecologic tract. Like most tests in surgical pathology, ISH studies require good quality tissue, correlation with clinical and histopathologic findings, and adherence to guidelines for optimal assay performance and interpretation. Although ISH studies are largely performed in tertiary centers, the tissue is often processed by a variety of laboratories and the referring pathologists are required to discuss the need, relevance, and significance of these tests and the results with their clinical colleagues. Here we review the predictive and diagnostic utility of fluorescent ISH studies in a variety of organ systems, the preanalytical factors that may affect the results, and the pitfalls in the interpretation that all practicing surgical pathologists should be aware of.

The immune-related microRNA miR-146b is upregulated in glioblastoma recurrence

Background

Glioblastoma (GBM) has a high rate of local recurrence despite chemoradiotherapy (CRT). Genome-wide expression profiling was performed on patient tumors before and after chemoradiotherapy to identify genes and gene pathways associated with recurrence.

Results

Median time to recurrence was 8.9 months with median time to second surgery of 9.6 months. The microRNA (miRNA) analysis identified 9 oncologic and immune-related miRNAs to be differentially expressed, including the hypoxia-related miR-210 and the immune-modulatory miR-146b. More than 1200 differentially-expressed genes were identified with RNA-sequencing (RNA-seq). Gene set enrichment analysis (GSEA) identified p53 signaling, Notch, Wnt, VEGF, and MEK gene sets enriched in recurrent GBM. Consistent with the miRNA profiling data, the miR-146b target gene set from GSEA analysis was also associated with recurrence.

Methods

Fourteen patients with GBM recurrence after CRT who had available tumor tissue from the initial diagnosis as well as recurrence were selected. Total RNA was isolated from formalin-fixed paraffin-embedded (FFPE) tumor specimens. Genome-wide expression profiling using RT-PCR for miRNA analysis and RNA-seq for messenger RNA (mRNA) analysis were conducted to identify differentially-expressed genes. GSEA was performed on the differential expression data.

Conclusions

Genome-wide expression profiling identifies multiple oncologic and immune-related gene sets associated with GBM recurrence. In particular, immune-related miR-146b is upregulated in recurrence and deserves further investigation.

Prognostic stratification of adult primary glioblastoma multiforme patients based on their tumor gene amplification profiles

Several classification systems have been proposed to address genomic heterogeneity of glioblastoma multiforme, but they either showed limited prognostic value and/or are difficult to implement in routine diagnostics. Here we propose a prognostic stratification model for these primary tumors based on tumor gene amplification profiles, that might be easily implemented in routine diagnostics, and potentially improve the patients management. Gene amplification profiles were prospectively evaluated in 80 primary glioblastoma multiforme tumors using single-nucleotide polymorphism arrays and the results obtained validated in publicly available data from 267/347 cases. Gene amplification was detected in 45% of patients, and chromosome 7p11.2 including the EGFR gene, was the most frequently amplified chromosomal region – either alone (18%) or in combination with amplification of DNA sequences in other chromosomal regions (10% of cases). Other frequently amplified DNA sequences included regions in chromosomes 12q(10%), 4q12(7%) and 1q32.1(4%). Based on their gene amplification profiles, glioblastomas were subdivided into: i) tumors with no gene amplification (55%); ii) tumors with chromosome 7p/EGFR gene amplification (with or without amplification of other chromosomal regions) (38%); and iii) glioblastoma multiforme with a single (11%) or multiple (6%) amplified DNA sequences in chromosomal regions other than chromosome 7p. From the prognostic point of view, these amplification profiles showed a significant impact on overall survival of glioblastoma multiforme patients (p>0.001). Based on these gene amplification profiles, a risk-stratification scoring system was built for prognostic stratification of glioblastoma which might be easily implemented in routine diagnostics, and potentially contribute to improved patient management.

Sequencing the next generation of glioblastomas

The most aggressive brain malignancy, glioblastoma, accounts for 60-70% of all gliomas and is uniformly fatal. According to the molecular signature, glioblastoma is divided into four subtypes (proneural, neural, classical, and mesenchymal), each with its own genetic background. The Cancer Genome Atlas project provides information about the most common genetic changes in glioblastoma. They involve mutations in TP53, TERT, and PTEN, and amplifications in EFGR, PDGFRA, CDK4, CDK6, MDM2, and MDM4. Recently, epigenetics was used to demonstrate the oncogenic roles of miR-124, miR-137, and miR-128. The most important findings so far are mutations in IDH1/2 and MGMT promoter methylation, which are routinely used as predictive biomarkers in patient care. Current clinical treatment leaves patients with only a 10% chance for 5-year survival. Attempts to define the mutational profile of glioblastoma to identify clinically relevant changes have not yet yielded significant results. This can be attributed to inter- and intra-tumor heterogeneity that is present in most glioblastomas, as well as hypermutation that appears as a consequence of chemotherapy. The evolving field of radiogenomics aims to classify glioblastoma using a combination of magnetic resonance imaging and genomic information. In the era of genomic medicine, next-generation sequencing is extensively used in glioblastoma research because it can detect multiple changes in a single biological sample; its potential in detecting circulating cell-free DNA has been tested in cerebrospinal fluid and plasma, and it shows promise in the examination of the cellular content of extracellular vesicles as a potential source of biomarkers. Next-generation sequencing is making its way into glioblastoma diagnostics. Gene panels like GlioSeq, which includes the most commonly mutated genes, are currently being tested on snap frozen and formalin fixed paraffin embedded tissues. This new methodology is helping to define the "next generation of glioblastomas" - clinically defined and better understood, with greater potential to improve patient care. However, limitations of the necessary infrastructure, space for data storage, technical expertise, and data ownership need to be considered carefully.

The roles of TRIO and F-actin-binding protein in glioblastoma cells

TRIO and F-actin-binding protein (TrioBP), which was initially discovered as a binding partner of Trio and F-actin, is a critical factor associated with hearing loss in humans. However, the function of TrioBP in cancer has not been investigated. In the present study, TrioBP expression was indicated to be highly elevated in U87-MG and U343-MG cells. Furthermore, the TrioBP mRNA expression level was markedly increased in U87-MG and U251-MG cells compared with that in cerebral cortex cells, as determined by deep sequencing. Comprehensive analysis of a public TCGA dataset confirmed that TrioBP expression is elevated in patients with glioblastoma. In summary, the present data indicate that TrioBP expression is increased in glioblastoma cell lines and in patients with glioma, suggesting that TrioBP has potential as a diagnostic marker or therapeutic agent for glioma.

Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

Recognition of Transmembrane Protein 39A as a Tumor-Specific Marker in Brain Tumor

Transmembrane protein 39A (TMEM39A) belongs to the TMEM39 family. TMEM39A gene is a susceptibility locus for multiple sclerosis. In addition, TMEM39A seems to be implicated in systemic lupus erythematosus. However, any possible involvement of TMEM39A in cancer remains largely unknown. In the present report, we provide evidence that TMEM39A may play a role in brain tumors. Western blotting using an anti-TMEM39A antibody indicated that TMEM39A was overexpressed in glioblastoma cell lines, including U87-MG and U251-MG. Deep-sequencing transcriptomic profiling of U87-MG and U251-MG cells revealed that TMEM39A transcripts were upregulated in such cells compared with those of the cerebral cortex. Confocal microscopic analysis of U251-MG cells stained with anti-TMEM39A antibody showed that TMEM39A was located in dot-like structures lying close to the nucleus. TMEM39A probably located to mitochondria or to endosomes. Immunohistochemical analysis of glioma tissue specimens indicated that TMEM39A was markedly upregulated in such samples. Bioinformatic analysis of the Rembrandt knowledge base also supported upregulation of TMEM39A mRNA levels in glioma patients. Together, the results afford strong evidence that TMEM39A is upregulated in glioma cell lines and glioma tissue specimens. Therefore, TMEM39A may serve as a novel diagnostic marker of, and a therapeutic target for, gliomas and other cancers.

Protein Analysis of Glioblastoma Primary and Posttreatment Pairs Suggests a Mesenchymal Shift at Recurrence

Glioblastomas (GBM) are aggressive brain tumors that inevitably recur despite surgical resection, chemotherapy, and radiation. The degree to which recurrent GBM retains its initial immunophenotype is incompletely understood. We generated tissue microarrays of paired initial and posttreatment GBM (3 pairs positive and 17 negative for IDH1^R132H) from the same patients and made comparisons in the IDH1^R132H-negative group for immunohistochemical and gene expression differences between primary and recurrent tumors. In initial tumors, immunopositivity for Ki-67 in > 20% of tumor cells was associated with shorter progression-free and overall survival. Recurrent tumors showed decreased staining for CD34 suggesting lower vessel density. A subset of tumors showed increased staining for markers associated with the mesenchymal gene expression pattern, including CD44, phosphorylated STAT3, and YKL40. Recurrent tumors with the greatest increase in mesenchymal marker expression had rapid clinical progression, but no difference in overall survival after second surgery. Comparison of protein and gene expression data from the same samples revealed a poor correlation. A subset of tumors (15%) showed loss of neurofibromin protein in both initial and recurrent tumors. These data support the notion that GBM progression is associated with a shift toward a mesenchymal phenotype in a subset of tumors and this may portend a more aggressive behavior.

Crossroad between linear and nonlinear transcription concepts in the discovery of next-generation sequencing systems-based anticancer therapies

The unprecedented potential of standard and new next-generation sequencing applications and methods to explore cancer genome evolution and tumor heterogeneity as well as transcription networks in time and space shapes the development of next-generation therapeutics. However, biomedical and pharmaceutical research for overcoming heterogeneity-based therapeutic resistance is at an important crossroads. Focus on linear transcription-based drug development targeting dynamics of simple intrapatient structured genome diversity represents a realistic medium-term goal. By contrast, the discovery of nonlinear transcription drugs for targeting structural and functional genome and transcriptome heterogeneity represents a long-term rational strategy. This review compares effectiveness, challenges and expectations between linear and nonlinear drugs targeting simple intrapatient variation and aberrant transcriptional biocircuits, respectively.