TERT promoter mutations contribute to subset prognostication of lower-grade gliomas

TERT promoter mutations in gliomas: Molecular roles in tumorigenesis, metastasis, diagnosis, prognosis, therapeutic targeting, and drug resistance

Telomerase reverse transcriptase (TERT), a critical player in cellular immortalization, has emerged as a focal point of investigation due to its frequent promoter mutations in various human malignancies. TERT promoter mutations exhibit a significant role in tumorigenesis, fostering unbridled cellular proliferation and survival. This comprehensive review delves into the landscape of TERT promoter mutations and their profound implications in cancer, particularly within the context of gliomas. This article meticulously examines the intricate interplay between TERT promoter mutations and the metastatic cascade, shedding light on their capacity to orchestrate invasive behavior in gliomas. Moreover, this review describes the recent trends in therapeutic targeting of the TERT and dissects the evolving landscape of drug resistance associated with TERT mutations, providing insights into potential therapeutic challenges. In addition, the diagnostic and prognostic implications of TERT promoter mutations in gliomas are scrutinized, unraveling their potential as robust biomarkers. It also discusses the recent advancements in molecular diagnostics, illustrating the promise of TERT mutations as diagnostic tools and prognostic indicators. This review collectively aims to contribute to a deeper understanding of TERT promoter mutations in gliomas, offering a foundation for future research endeavors and paving the way for innovative strategies in glioma management.

Multi-center real-world data-driven web calculator for predicting outcomes in IDH-mutant gliomas: Integrating molecular subtypes and treatment modalities

Background

Isocitrate dehydrogenase (IDH)-mutant gliomas generally have a better prognosis than IDH-wild-type glioblastomas, and the extent of resection significantly impacts prognosis. However, there is a lack of integrated tools for predicting outcomes based on molecular subtypes and treatment modalities. This study aimed to identify factors influencing gross total resection (GTR) rates and to develop a clinical prognostic tool for IDH-mutant gliomas.

Methods

We analyzed 650 patients with IDH-mutant gliomas from 3 Chinese medical centers (Shanghai, Hong Kong, and Zhengzhou). Data included age, sex, extent of resection, radiotherapy status, tumor grade, histology, and molecular markers (1p19q, TERT promoter, BRAF, EGFR, 10q). Patients were categorized based on GTR status, and a nomogram predicting 3-, 5-, and 10-year overall survival (OS) was developed using Cox proportional hazards regression and validated with time-dependent ROC and calibration plot analyses.

Results

Non-GTR was associated with diffuse astrocytoma (73.0% vs. 53.5%), 1p19q non-codeletion (67.9% vs. 48.7%), and wildtype TERT promoter (63.6% vs. 52.4%). The nomogram, incorporating age, TERT promoter status, extent of resection, grade, and radiotherapy status, demonstrated strong discriminatory ability (AUC > 0.75) and good calibration. Decision curve analysis indicated that it outperformed WHO grade-based classification in identifying high-risk patients. An online calculator was developed for clinical use (http://www.szflab.site/nomogram/).

Conclusion

We developed and validated a nomogram and online tool that integrates molecular and clinical factors for predicting outcomes in IDH-mutant gliomas, enhancing clinical decision-making.

Potential of sonobiopsy as a novel diagnosis tool for brain cancer

Brain tumors have a poor prognosis. Early, accurate diagnosis and treatment are crucial. Although brain surgical biopsy can provide an accurate diagnosis, it is highly invasive and risky and is not suitable for follow-up examination. Blood-based liquid biopsies have a low detection rate of tumor biomarkers and limited evaluation ability due to the existence of the blood-brain barrier (BBB). The BBB is composed of brain capillary endothelial cells through tight junctions, which prevents the release of brain tumor markers to the human peripheral circulation, making it more difficult to diagnose, predict prognosis, and evaluate therapeutic response through brain tumor markers than other tumors. Focused ultrasound (FUS)-enabled liquid biopsy (sonobiopsy) is an emerging technique using FUS to promote the release of tumor markers into the circulatory system and cerebrospinal fluid, thus facilitating tumor detection. The feasibility and safety data from both animal models and clinical trials support sonobiopsy as a great potential in the diagnosis of brain diseases.

The Relationship Between the Molecular Phenotypes of Brain Gliomas and the Imaging Features and Sensitivity of Radiotherapy and Chemotherapy

Gliomas are the most common primary malignant tumors of the brain, accounting for about 80% of all central nervous system malignancies. With the development of molecular biology, the molecular phenotypes of gliomas have been shown to be closely related to the process of diagnosis and treatment. The molecular phenotype of glioma also plays an important role in guiding treatment plans and evaluating treatment effects and prognosis. However, due to the heterogeneity of the tumors and the trauma associated with the surgical removal of tumor tissue, the application of molecular phenotyping in glioma is limited. With the development of imaging technology, functional magnetic resonance imaging (MRI) can provide structural and function information about tumors in a noninvasive and radiation-free manner. MRI is very important for the diagnosis of intracranial lesions. In recent years, with the development of the technology for tumor molecular diagnosis and imaging, the use of molecular phenotype information and imaging procedures to evaluate the treatment outcome of tumors has become a hot topic. By reviewing the related literature on glioma treatment and molecular typing that has been published in the past 20 years, and referring to the latest 2020 NCCN treatment guidelines, summarizing the imaging characteristic and sensitivity of radiotherapy and chemotherapy of different molecular phenotypes of glioma. In this article, we briefly review the imaging characteristics of different molecular phenotypes in gliomas and their relationship with radiosensitivity and chemosensitivity of gliomas.

Prediction of TERT mutation status in gliomas using conventional MRI radiogenomic features

Objective

Telomerase reverse transcriptase (TERT) promoter mutation status in gliomas is a key determinant of treatment strategy and prognosis. This study aimed to analyze the radiogenomic features and construct radiogenomic models utilizing medical imaging techniques to predict the TERT promoter mutation status in gliomas.

Methods

This was a retrospective study of 304 patients with gliomas. T1-weighted contrast-enhanced, apparent diffusion coefficient, and diffusion-weighted imaging MRI sequences were used for radiomic feature extraction. A total of 3,948 features were extracted from MRI images using the FAE software. These included 14 shape features, 18 histogram features, 24 gray level run length matrix, 14 gray level dependence matrix, 16 gray level run length matrix, 16 gray level size zone matrix (GLSZM), 5 neighboring gray tone difference matrix, and 744 wavelet transforms. The dataset was randomly divided into training and testing sets in a ratio of 7:3. Three feature selection methods and six classification algorithms were used to model the selected features. Predictive performance was evaluated using receiver operating characteristic curve analysis.

Results

Among the evaluated classification algorithms, the combination model of recursive feature elimination (RFE) with linear regression (LR) using six features showed the best diagnostic performance (area under the curve: 0.733, 0.562, and 0.633 in the training, validation, and testing sets, respectively). The next best-performing models were naive Bayes, linear discriminant analysis, autoencoder, and support vector machine. Regarding the three feature selection algorithms, RFE showed the most consistent performance, followed by relief and ANOVA. T1-enhanced entropy and GLSZM derived from T1-enhanced images were identified as the most critical radiomics features for distinguishing TERT promoter mutation status.

Conclusion

The LR and LRLasso models, mainly based on T1-enhanced entropy and GLSZM, showed good predictive ability for TERT promoter mutations in gliomas using radiomics models.

Rare Pediatric Cerebellar High-Grade Gliomas Mimic Medulloblastomas Histologically and Transcriptomically and Show p53 Mutations

Pediatric high-grade gliomas (HGG) of the cerebellum are rare, and only a few cases have been documented in detail in the literature. A major differential diagnosis for poorly differentiated tumors in the cerebellum in children is medulloblastoma. In this study, we described the histological and molecular features of a series of five pediatric high-grade gliomas of the cerebellum. They actually showed histological and immunohistochemical features that overlapped with those of medulloblastomas and achieved high scores in NanoString-based medulloblastoma diagnostic assay. Methylation profiling demonstrated these tumors were heterogeneous epigenetically, clustering to GBM_MID, DMG_K27, and GBM_RTKIII methylation classes. MYCN amplification was present in one case, and PDGFRA amplification in another two cases. Interestingly, target sequencing showed that all tumors carried TP53 mutations. Our results highlight that pediatric high-grade gliomas of the cerebellum can mimic medulloblastomas at histological and transcriptomic levels. Our report adds to the rare number of cases in the literature of cerebellar HGGs in children. We recommend the use of both methylation array and TP53 screening in the differential diagnoses of poorly differentiated embryonal-like tumors of the cerebellum.

Cerebrospinal fluid circulating tumour DNA genotyping and survival analysis in lung adenocarcinoma with leptomeningeal metastases

PURPOSE

The prognosis of patients with leptomeningeal metastasis (LM) remains poor. Circulating tumour DNA (ctDNA) has been proven to be abundantly present in cerebrospinal fluid (CSF); hence, its clinical implication as a biomarker needs to be further verified.

METHODS

We conducted a retrospective study of 35 lung adenocarcinoma (LUAD) patients with LM, and matched CSF and plasma samples were collected from all patients. All paired samples underwent next-generation sequencing (NGS) of 139 lung cancer-associated genes. The clinical characteristics and genetic profiling of LM were analysed in association with survival prognosis.

RESULTS

LM showed genetic heterogeneity, in which CSF had a higher detection rate of ctDNA (P = 0.003), a higher median mutation count (P < 0.0001), a higher frequency of driver mutations (P < 0.01), and more copy number variation (CNV) alterations (P < 0.001) than plasma. The mutation frequencies of the EGFR, TP53, CDKN2A, MYC and CDKN2B genes were easier to detect in CSF than in LUAD tissue (P < 0.05), possibly reflecting the underlying mechanism of LM metastasis. CSF ctDNA is helpful for analysing the mechanism of EGFR-TKI resistance. In cohort 1, which comprised patients who received 1/2 EGFR-TKIs before the diagnosis of LM, TP53 and CDKN2A were the most common EGFR-independent resistant mutations. In cohort 2, comprising those who progressed after osimertinib and developed LM, 7 patients (43.75%) had EGFR CNV detected in CSF but not plasma. Furthermore, patient characteristics and various genes were included for interactive survival analysis. Patients with EGFR-mutated LUAD (P = 0.042) had a higher median OS, and CSF ctDNA mutation with TERT (P = 0.013) indicated a lower median OS. Last, we reported an LM case in which CSF ctDNA dynamic changes were well correlated with clinical treatment.

CONCLUSIONS

CSF ctDNA could provide a more comprehensive genetic landscape of LM, indicating the potential metastasis-related and EGFR-TKI resistance mechanisms of LM patients. In addition, genotyping of CSF combined with clinical outcomes can predict the prognosis of LUAD patients with LM.

Association of human telomerase reverse transcriptase promoter mutation with unfavorable prognosis in glioma: A systematic review and meta-analysis

Background

Glioma is one of the most malignant and aggressive tumors, with an extremely poor prognosis. Human telomerase reverse transcriptase (hTERT) promoter mutation is regarded as a risk factor in tumor growth. Although the prevalence of hTERT promoter (pTERT) mutation in gliomas has been investigated, the results are inconsistent. This meta-analysis aims to investigate the prognostic value of hTERT in glioma patients and its interaction with other biomarkers.

Materials and Methods

We searched 244 citations from four databases: PubMed (2000-2021), Web of Science (2000-2021), Embase (2010-2021), and Cochrane Library (2000-2021) with 28 articles included.

Results

We calculated hazard ratios (HRs) using the random effect model and the pooled result suggested that TERT promoter mutation predicted poorer overall survival (HR: 1.53, 95% confidence interval [CI]: 1.34-1.75, P < 0.001, I2: 49.9%, pheterogeneity:0.002) and progression-free survival (HR: 1.55, 95% CI: 1.27-1.88, P < 0.001, I2: 0.0%, pheterogeneity: 0.473). For subgroup analysis, we analyzed multiple factors including iso-citrate dehydrogenase (IDH) genotype, age, diagnosis, pTERT region, so as to locate the sources of heterogeneity. Interestingly, in IDH mutant subgroup, pTERT mutation became a beneficial prognostic factor (HR: 0.73, 95% CI: 0.57-0.93, I2: 22.3%, pheterogeneity: 0.277), which is contrary to the results in pooled analysis.

Conclusion

In general, pTERT mutation may result in shorter survival time in glioma patients, but longer survival time when glioma patients are combined with IDH mutation.

DNA Methylation and Histone Modification in Low-Grade Gliomas: Current Understanding and Potential Clinical Targets

Gliomas, the most common type of malignant primary brain tumor, were conventionally classified through WHO Grades I-IV (now 1-4), with low-grade gliomas being entities belonging to Grades 1 or 2. While the focus of the WHO Classification for Central Nervous System (CNS) tumors had historically been on histopathological attributes, the recently released fifth edition of the classification (WHO CNS5) characterizes brain tumors, including gliomas, using an integration of histological and molecular features, including their epigenetic changes such as histone methylation, DNA methylation, and histone acetylation, which are increasingly being used for the classification of low-grade gliomas. This review describes the current understanding of the role of DNA methylation, demethylation, and histone modification in pathogenesis, clinical behavior, and outcomes of brain tumors, in particular of low-grade gliomas. The review also highlights potential diagnostic and/or therapeutic targets in associated cellular biomolecules, structures, and processes. Targeting of MGMT promoter methylation, TET-hTDG-BER pathway, association of G-CIMP with key gene mutations, PARP inhibition, IDH and 2-HG-associated processes, TERT mutation and ARL9-associated pathways, DNA Methyltransferase (DNMT) inhibition, Histone Deacetylase (HDAC) inhibition, BET inhibition, CpG site DNA methylation signatures, along with others, present exciting avenues for translational research. This review also summarizes the current clinical trial landscape associated with the therapeutic utility of epigenetics in low-grade gliomas. Much of the evidence currently remains restricted to preclinical studies, warranting further investigation to demonstrate true clinical utility.

Feasibility of evaluating the histologic and genetic subtypes of WHO grade II-IV gliomas by diffusion-weighted imaging

BACKGROUND

To explore the feasibility of diffusion-weighted imaging (DWI) metrics to predict the histologic subtypes and genetic status of gliomas (e.g., IDH, MGMT, and TERT) noninvasively.

METHODS

One hundred and eleven patients with pathologically confirmed WHO grade II-IV gliomas were recruited retrospectively. Apparent diffusion coefficient (ADC) values were measured in solid parts of gliomas on co-registered T2-weighted images and were compared with each other in terms of WHO grading and genotypes using t-tests. Receiver operating characteristic analysis was performed to assess the diagnostic performances of ADC. Subsequently, multiple linear regression was used to find independent variables, which can directly affect ADC values.

RESULTS

The values of overall mean ADC (omADC) and normalized ADC (nADC) of high grade gliomas and IDH wildtype gliomas were lower than low grade gliomas and IDH mutated gliomas (P < 0.05). nADC values showed better diagnostic performance than omADC in identifying tumor grade (AUC: 0.787 vs. 0.750) and IDH status (AUC: 0.836 vs. 0.777). ADC values had limited abilities in distinguishing TERT status (AUC = 0.607 for nADC and 0.617 for omADC) and MGMT status (AUC = 0.651 for nADC). Only tumor grade and IDH status were tightly associated with ADC values.

CONCLUSION

DWI metrics can predict glioma grading and IDH mutation noninvasively, but have limited use in detecting TERT mutation and MGMT methylation.

Molecular landscape of pediatric type IDH wildtype, H3 wildtype hemispheric glioblastomas

The WHO (2021) Classification classified a group of pediatric-type high-grade gliomas as IDH wildtype, H3 wildtype but as of currently, they are characterized only by negative molecular features of IDH and H3. We recruited 35 cases of pediatric IDH wildtype and H3 wildtype hemispheric glioblastomas. We evaluated them with genome-wide methylation profiling, targeted sequencing, RNAseq, TERT promoter sequencing, and FISH. The median survival of the cohort was 27.6 months. With Capper et al.'s³⁶ methylation groups as a map, the cases were found to be epigenetically heterogeneous and were clustered in proximity or overlay of methylation groups PXA-like (n = 8), LGG-like (n = 10), GBM_MYCN (n = 9), GBM_midline (n = 5), and GBM_RTKIII (n = 3). Histology of the tumors in these groups was not different from regular glioblastomas. Methylation groups were not associated with OS. We were unable to identify groups specifically characterized by EGFR or PDGFRA amplification as proposed by other authors. EGFR, PDGFRA, and MYCN amplifications were not correlated with OS. 4/9 cases of the GBM_MYCN cluster did not show MYCN amplification; the group was also enriched for EGFR amplification (4/9 cases) and the two biomarkers overlapped in two cases. Overall, PDGFRA amplification was found in only four cases and they were not restricted to any groups. Cases in proximity to GBM_midline were all hemispheric and showed loss of H3K27me3 staining. Fusion genes ALK/NTRK/ROS1/MET characteristic of infantile glioblastomas were not identified in 17 cases successfully sequenced. BRAF V600E was only found in the PXA group but CDKN2A deletion could be found in other methylation groups. PXA-like cases did not show PXA histological features similar to findings by other authors. No case showed TERT promoter mutation. Mutations of mismatch repair (MMR) genes were poor prognosticators in single (p ≤ 0.001) but not in multivariate analyses (p = 0.229). MGMT had no survival significance in this cohort. Of the other common biomarkers, only TP53 and ATRX mutations were significant poor prognosticators and only TP53 mutation was significant after multivariate analyses (p = 0.024). We conclude that IDH wildtype, H3 wildtype pediatric hemispheric glioblastomas are molecularly heterogeneous and in routine practice, TP53, ATRX, and MMR status could profitably be screened for risk stratification in laboratories without ready access to methylation profiling.

Molecular Aberrations Stratify Grade 2 Astrocytomas Into Several Rare Entities: Prognostic and Therapeutic Implications

The identification of specific molecular aberrations guides the prognostic stratification and management of grade 2 astrocytomas. Mutations in isocitrate dehydrogenase (IDH) 1 and 2, found in the majority of adult diffuse low-grade glioma (DLGG), seem to relate to a favorable prognosis compared to IDH wild-type (IDH-wt) counterparts. Moreover, the IDH-wt group can develop additional molecular alterations worsening the prognosis, such as epidermal growth factor receptor amplification (EGFR-amp) and mutation of the promoter of telomerase reverse transcriptase (pTERT-mut). This review analyzes the prognostic impact and therapeutic implications of genetic alterations in adult LGG.

Inhibiting the growth of melanoma cells via hTERT gene editing using CRISPR-dCas9-dnmt3a system

CRISPR-Cas9 gene-editing technology has pushed the boundaries of genetic modification. The principle of this method is based on the purposeful defense system of DNA degradation and will be one of the most powerful instruments for gene editing shortly. The purpose of this study was to evaluate the capability of this approach to manage melanoma cells. The present study used EF1a-hsaCas9-U6-gRNA as a hybrid vector of sgRNA and Cas9 for the transfection of A-375 melanoma cells. Transfection efficiency was enhanced by examining the two concentrations of 4 and 8 µg/mL of hexadimethrine bromide (trade name Polybrene). The existence of Cas9 in transfected cells was detected by flow cytometry. The expression level of the metabisulfite-modified hTERT gene was measured by real-time PCR technique. The presence of telomerase in cells was determined by flow cytometry and western blotting analysis. The hTERT gene promoter methylation was also evaluated by HRM assay. Finally, the induction of apoptosis in transfected A375 cells was assessed using flow cytometry. The results showed that the presence of gRNA significantly increased the transfection efficiency (up to about 7.75 times higher). The hTERT expression levels in A-375 cells were significantly decreased at different concentrations of Polybrene (in a dose-dependent manner) and various amounts of transfection (P < 0.05). The expression of hTERT in basal cells was not significantly different from the group transfected without gRNA (P˃0.05) but was significantly higher than the group transfected with gRNA (P < 0.05). The results of flow cytometry and western blotting analysis showed a decrease in hTERT level compared to cells transfected without gRNA as well as basal cells. The methylation of hTERT gene promoter in the cells transfected with gRNA at a concentration of 80 μg/mL in the presence of both 4 μg/mL and 8 μg/mL of Polybrene was significantly increased compared to those transfected without sRNA (P < 0.05). The flow cytometry results indicated no significant difference in the induction of apoptosis in the transfected cells compared to the basal cells (P < 0.05). Evidence suggests that the designed CRISPR/Cas9 system reduces the expression of the hTERT gene and telomerase presence, thereby inhibiting the growth of melanoma cells.

A Novel Multi-Omics Analysis Model for Diagnosis and Survival Prediction of Lower-Grade Glioma Patients

Background

Lower-grade gliomas (LGGs) are characterized by remarkable genetic heterogeneity and different clinical outcomes. Classification of LGGs is improved by the development of molecular stratification markers including IDH mutation and 1p/19q chromosomal integrity, which are used as a hallmark of survival and therapy sensitivity of LGG patients. However, the reproducibility and sensitivity of the current classification remain ambiguous. This study aimed to construct more accurate risk-stratification approaches.

Methods

According to bioinformatics, the sequencing profiles of methylation and transcription and imaging data derived from LGG patients were analyzed and developed predictable risk score and radiomics score. Moreover, the performance of predictable models was further validated.

Results

In this study, we determined a cluster of 6 genes that were correlated with IDH mutation/1p19q co-deletion status. Risk score model was calculated based on 6 genes and showed gratifying sensitivity and specificity for survival prediction and therapy response of LGG patients. Furthermore, a radiomics risk score model was established to noninvasively assist judgment of risk score in pre-surgery. Taken together, a predictable nomogram that combined transcriptional signatures and clinical characteristics was established and validated to be preferable to the histopathological classification. Our novel multi-omics nomograms showed a satisfying performance. To establish a user-friendly application, the nomogram was further developed into a web-based platform: https://drw576223193.shinyapps.io/Nomo/, which could be used as a supporting method in addition to the current histopathological-based classification of gliomas.

Conclusions

Our novel multi-omics nomograms showed the satisfying performance of LGG patients and assisted clinicians to draw up individualized clinical management.

Combinations of Single-Gene Biomarkers Can Precisely Stratify 1,028 Adult Gliomas for Prognostication

Advanced genomic techniques have now been incorporated into diagnostic practice in neuro-oncology in the literature. However, these assays are expensive and time-consuming and demand bioinformatics expertise for data interpretation. In contrast, single-gene tests can be run much more cheaply, with a short turnaround time, and are available in general pathology laboratories. The objective of this study was to establish a molecular grading scheme for adult gliomas using combinations of commonly available single-gene tests. We retrospectively evaluated molecular diagnostic data of 1,275 cases of adult diffuse gliomas from three institutions where we were testing for IDH1/2 mutation, TERTp mutation, 1p19q codeletion, EGFR amplification, 10q deletion, BRAF V600E, and H3 mutations liberally in our regular diagnostic workup. We found that a molecular grading scheme of Group 1 (1p19q codeleted, IDH mutant), Group 2 (IDH mutant, 1p19q non-deleted, TERT mutant), Group 3 (IDH mutant, 1p19q non-deleted, TERT wild type), Group 4 (IDH wild type, BRAF mutant), Group 5 (IDH wild type, BRAF wild type and not possessing the criteria of Group 6), and Group 6 (IDH wild type, and any one of TERT mutant, EGFR amplification, 10q deletion, or H3 mutant) could significantly stratify this large cohort of gliomas for risk. A total of 1,028 (80.6%) cases were thus classifiable with sufficient molecular data. There were 270 cases of molecular Group 1, 59 cases of molecular Group 2, 248 cases of molecular Group 3, 27 cases of molecular Group 4, 117 cases of molecular Group 5, and 307 cases of molecular Group 6. The molecular groups were independent prognosticators by multivariate analyses and in specific instances, superseded conventional histological grades. We were also able to validate the usefulness of the Groups with a cohort retrieved from The Cancer Genome Atlas (TCGA) where similar molecular tests were liberally available. We conclude that a single-gene molecular stratification system, useful for fine prognostication, is feasible and can be adopted by a general pathology laboratory.

Molecular Biomarker Testing for the Diagnosis of Diffuse Gliomas

CONTEXT.—

The diagnosis and clinical management of patients with diffuse gliomas (DGs) have evolved rapidly over the past decade with the emergence of molecular biomarkers that are used to classify, stratify risk, and predict treatment response for optimal clinical care.

OBJECTIVE.—

To develop evidence-based recommendations for informing molecular biomarker testing for pediatric and adult patients with DGs and provide guidance for appropriate laboratory test and biomarker selection for optimal diagnosis, risk stratification, and prediction.

DESIGN.—

The College of American Pathologists convened an expert panel to perform a systematic review of the literature and develop recommendations. A systematic review of literature was conducted to address the overarching question, "What ancillary tests are needed to classify DGs and sufficiently inform the clinical management of patients?" Recommendations were derived from quality of evidence, open comment feedback, and expert panel consensus.

RESULTS.—

Thirteen recommendations and 3 good practice statements were established to guide pathologists and treating physicians on the most appropriate methods and molecular biomarkers to include in laboratory testing to inform clinical management of patients with DGs.

CONCLUSIONS.—

Evidence-based incorporation of laboratory results from molecular biomarker testing into integrated diagnoses of DGs provides reproducible and clinically meaningful information for patient management.

A Qualitative Signature to Identify TERT Promoter Mutant High-Risk Tumors in Low-Grade Gliomas

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.

Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.

Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.

Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances

This article reviews the existing approaches to determining the TERT promoter mutational status in patients with various tumoral diseases of the central nervous system. The operational characteristics of the most common methods and their transferability in medical practice for the selection or monitoring of personalized treatments based on the TERT status and other related molecular biomarkers in patients with the most common tumors, such as glioblastoma, oligodendroglioma, and astrocytoma, are compared. The inclusion of new molecular markers in the course of CNS clinical management requires their rapid and reliable assessment. Availability of molecular evaluation of gliomas facilitates timely decisions regarding patient follow-up with the selection of the most appropriate treatment protocols. Significant progress in the inclusion of molecular biomarkers for their subsequent clinical application has been made since 2016 when the WHO CNS classification first used molecular markers to classify gliomas. In this review, we consider the methodological approaches used to determine mutations in the promoter region of the TERT gene in tumors of the central nervous system. In addition to classical molecular genetical methods, other methods for determining TERT mutations based on mass spectrometry, magnetic resonance imaging, next-generation sequencing, and nanopore sequencing are reviewed with an assessment of advantages and disadvantages. Beyond that, noninvasive diagnostic methods based on the determination of the mutational status of the TERT promoter are discussed.

CCNB2 is a novel prognostic factor and a potential therapeutic target in Low-grade glioma (LGG)

Background: Cyclin B2 (CCNB2) is an important component of the cyclin pathway and plays a key role in the occurrence and development of cancer. However, the correlation between prognosis of low-grade glioma (LGG), CCNB2, and tumor infiltrating lymphocytes is not clear. Methods: The expression of CCNB2 in LGG was queried in Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and TIMER databases. The relationships between CCNB2 and the clinicopathological features of LGG were analyzed using the Chinese Glioma Genome Atlas (CGGA) database. The relationship between CCNB2 expression and overall survival (OS) was evaluated by GEPIA2. The correlation between CCNB2 and LGG immune infiltration was analyzed by the TIMER database. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect CCNB2 expression. Results: The expression of CCNB2 differed across different tumor tissues, but was higher in LGG than in normal tissues. LGG patients with high expression of CCNB2 have poorer prognosis. The expression of CCNB2 was correlated with age, WHO grade, IDH mutational status, 1p/19q codeletion status, and other clinicopathological features. The expression of CCNB2 in LGG was positively correlated with the infiltration level of B cells, dendritic cells, and macrophages. qRT-PCR results revealed that the expression of CCNB2 in LGG tissues was higher than normal tissues and higher expression of CCNB2 was associated with worse prognosis. Conclusion: CCNB2 may be used as a potential biomarker to determine the prognosis of LGG and is also related to immune infiltration.

Chemoradiotherapy with temozolomide vs. radiotherapy alone in patients with IDH wild-type and TERT promoter mutation WHO grade II/III gliomas: A prospective randomized study

PURPOSE

Patients with grade II/III diffuse glioma (lower grade glioma, LGG) with isocitrate dehydrogenase wild-type (IDH-wt) and telomerase reverse-transcriptase promoter mutation (TERTp-mut) experience shorter overall survival (OS) time than IDH mutant patients. The optimal treatment strategy for these patients is unclear. We compared the effects of radiotherapy (RT) alone vs. RT concurrent with temozolomide (TMZ) followed by adjuvant TMZ in these LGG patients.

PATIENTS AND METHODS

Thirty-seven LGG patients with IDH-wt and TERTp-mut were randomly allocated to either RT alone treatment (RT group, n = 18; 60 Gy in 30 daily fractions) or RT concurrent with TMZ (75 mg/m²/d, 7 d/week) followed by adjuvant TMZ (CRT group, n = 19). The median follow-up duration was 17 months. Log-rank test was used for OS and PFS comparisons.

RESULTS

The 1-year OS rate was 94.1% [95% confidence interval (CI) 82.9-100] in the CRT group and 74.6% (95% CI, 52.9-96.4) in the RT group. The median OS values in the CRT and RT groups were statistically different [25 vs. 17 months, respectively; hazard ratio (HR) 0.271; 95% CI, 0.092-0.793; P = 0.017], while PFS values were not (16 vs. 7 months, respectively; HR, 0.917; 95% CI, 0.397-2.120; P = 0.840). Multivariate analysis indicated that CRT treatment and female sex were associated with significantly longer OS (P = 0.001, P = 0.016, respectively).

CONCLUSION

CRT treatment for IDH-wt/TERTp-mut grade II/III gliomas resulted in significantly longer OS than RT alone. Female sex was a significant favorable prognostic factor.

RUNX1 and REXO2 are associated with the heterogeneity and prognosis of IDH wild type lower grade glioma

Based on isocitrate dehydrogenase (IDH) alterations, lower grade glioma (LGG) is divided into IDH mutant and wild type subgroups. However, the further classification of IDH wild type LGG was unclear. Here, IDH wild type LGG patients in The Cancer Genome Atlas and Chinese Glioma Genome Atlas were divided into two sub-clusters using non-negative matrix factorization. IDH wild type LGG patients in sub-cluster2 had prolonged overall survival and low frequency of CDKN2A alterations and low immune infiltrations. Differentially expressed genes in sub-cluster1 were positively correlated with RUNX1 transcription factor. Moreover, IDH wild type LGG patients with higher stromal score or immune score were positively correlated with RUNX1 transcription factor. RUNX1 and its target gene REXO2 were up-regulated in sub-cluster1 and associated with the worse prognosis of IDH wild type LGG. RUNX1 and REXO2 were associated with the higher immune infiltrations. Furthermore, RUNX1 and REXO2 were correlated with the worse prognosis of LGG or glioma. IDH wild type LGG in sub-cluster2 was hyper-methylated. REXO2 hyper-methylation was associated with the favorable prognosis of LGG or glioma. At last, we showed that, age, tumor grade and REXO2 expression were independent prognostic factors in IDH wild type LGG.

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection. Considering that GBM cancer stem cells (CSCs) play a non-negligible role in tumorigenesis and chemoradiotherapy resistance, we proposed a novel stemness-based classification of GBM and screened out certain population more responsive to immunotherapy. The one-class logistic regression algorithm was used to calculate the stemness index (mRNAsi) of 518 GBM patients from The Cancer Genome Atlas (TCGA) database based on transcriptomics of GBM and pluripotent stem cells. Based on their stemness signature, GBM patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS but poorer progression-free survival than Stemness Subtype II. Genomic variations revealed patients in Stemness Subtype I had higher somatic mutation loads and copy number alteration burdens. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. Tumor Immune Dysfunction and Exclusion and subclass mapping analysis further demonstrated patients in Stemness Subtype I were more likely to respond to immunotherapy, especially anti-PD1 treatment. The pRRophetic algorithm also indicated patients in Stemness Subtype I were more resistant to temozolomide therapy. Finally, multiple machine learning algorithms were used to develop a 7-gene Stemness Subtype Predictor, which were further validated in two external independent GBM cohorts. This novel stemness-based classification could provide a promising prognostic predictor for GBM and may guide physicians in selecting potential responders for preferential use of immunotherapy.

FABP5 enhances malignancies of lower-grade gliomas via canonical activation of NF-κB signaling

Low‐grade gliomas (LGGs) are grade III gliomas based on the WHO classification with significant genetic heterogeneity and clinical properties. Traditional histological classification of gliomas has been challenged by the improvement of molecular stratification; however, the reproducibility and diagnostic accuracy of LGGs classification still remain poor. Herein, we identified fatty acid binding protein 5 (FABP5) as one of the most enriched genes in malignant LGGs and elevated FABP5 revealed severe outcomes in LGGs. Functionally, lentiviral suppression of FABP5 reduced malignant characters including proliferation, cloning formation, immigration, invasion and TMZ resistance, contrarily, the malignancies of LGGs were enhanced by exogenous overexpression of FABP5. Mechanistically, epithelial‐mesenchymal transition (EMT) was correlated to FABP5 expression in LGGs and tumour necrosis factor α (TNFα)‐dependent NF‐κB signalling was involved in this process. Furthermore, FABP5 induced phosphorylation of inhibitor of nuclear factor kappa‐B kinase α (IKKα) thus activated nuclear factor kappa‐B (NF‐κB) signalling. Taken together, our study indicated that FABP5 enhances malignancies of LGGs through canonical activation of NF‐κB signalling, which could be used as individualized prognostic biomarker and potential therapeutic target of LGGs.

Role of traditional CHO PET parameters in distinguishing IDH, TERT and MGMT alterations in primary diffuse gliomas

OBJECTIVE

Isocitrate dehydrogenase (IDH) mutation, telomerase reverse transcriptase (TERT) promoter mutation and O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation status are diagnostic, prognostic, predictive and therapeutic biomarkers for primary diffuse gliomas, and this study aimed to explore the relationship between choline (CHO) positron emission tomography (PET) parameters and these molecular alterations.

METHODS

Twenty-eight patients who were histopathologically diagnosed with primary diffuse glioma and underwent presurgical CHO PET/CT were retrospectively analyzed, and IDH, TERT and MGMT alterations were examined. The volume of interest (VOI) was semiautomatically defined based on standardized uptake value (SUV) thresholds, and 5 traditional CHO parameters, namely, SUVmax, SUVmean, metabolic tumor volume (MTV), total lesion CHO uptake (TLC) and tumor-to-normal contralateral cortex activity ratio (T/N ratio), were calculated. Wilcoxon rank-sum tests and receiver operating characteristic (ROC) curves were applied to evaluate the differences and performances of the CHO parameters, and their capability to stratify patient prognosis was also evaluated.

RESULTS

All 5 parameters were significantly higher in IDH-wildtype gliomas than in IDH-mutant gliomas (p = 0.0001-0.037), and SUVmax, SUVmean, TLC and the T/N ratio exhibited good performances in distinguishing the IDH status (areas under the ROC curve (AUCs) 0.856-0.918, accuracies 0.857-0.893) as well as stratifying patient prognosis. Although the differences and performances of the traditional parameters in distinguishing diverse TERT and MGMT statuses were moderate in the whole population, the T/N ratio and TLC displayed certain predictive value in discriminating the TERT status in the IDH-mutant and IDH-wildtype subgroups (p = 0.028-0.048, AUCs 0.857-0.860, accuracies 0.800-0.917, respectively).

CONCLUSIONS

Traditional CHO PET parameters are capable of distinguishing IDH but not TERT or MGMT alterations in the whole population. In accordance with the clinical understanding of TERT promoter mutations, the T/N ratio and TLC can also discriminate the TERT status in IDH subgroups.

MRI Features May Predict Molecular Features of Glioblastoma in Isocitrate Dehydrogenase Wild-Type Lower-Grade Gliomas

BACKGROUND AND PURPOSE

Isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas (histologic grades II and III) with epidermal growth factor receptor (EGFR) amplification or telomerase reverse transcriptase (TERT) promoter mutation are reported to behave similar to glioblastoma. We aimed to evaluate whether MR imaging features could identify a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.

MATERIALS AND METHODS

In this multi-institutional retrospective study, pathologically confirmed IDH wild-type lower-grade gliomas from 2 tertiary institutions and The Cancer Genome Atlas constituted the training set (institution 1 and The Cancer Genome Atlas, 64 patients) and the independent test set (institution 2, 57 patients). Preoperative MRIs were analyzed using the Visually AcceSAble Rembrandt Images and radiomics. The molecular glioblastoma status was determined on the basis of the presence of EGFR amplification and TERT promoter mutation. Molecular glioblastoma was present in 73.4% and 56.1% in the training and test sets, respectively. Models using clinical, Visually AcceSAble Rembrandt Images, and radiomic features were built to predict the molecular glioblastoma status in the training set; then they were validated in the test set.

RESULTS

In the test set, a model using both Visually AcceSAble Rembrandt Images and radiomic features showed superior predictive performance (area under the curve = 0.854) than that with only clinical features or Visually AcceSAble Rembrandt Images (areas under the curve = 0.514 and 0.648, respectively; P < . 001, both). When both Visually AcceSAble Rembrandt Images and radiomics were added to clinical features, the predictive performance significantly increased (areas under the curve = 0.514 versus 0.863, P < .001).

CONCLUSIONS

MR imaging features integrated with machine learning classifiers may predict a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.

Advances in Research of Adult Gliomas

Diffuse gliomas are the most frequent brain tumours, representing 75% of all primary malignant brain tumours in adults. Because of their locally aggressive behaviour and the fact that they cannot be cured by current therapies, they represent one of the most devastating cancers. The present review summarises recent advances in our understanding of glioma development and progression by use of various in vitro and in vivo models, as well as more complex techniques including cultures of 3D organoids and organotypic slices. We discuss the progress that has been made in understanding glioma heterogeneity, alteration in gene expression and DNA methylation, as well as advances in various in silico models. Lastly current treatment options and future clinical trials, which aim to improve early diagnosis and disease monitoring, are also discussed.

Machine learning classifiers for predicting 3-year progression-free survival and overall survival in patients with gliomas after surgery

Background: To develop machine-learning based models to predict the progression-free survival (PFS) and overall survival (OS) in patients with gliomas and explore the effect of different feature selection methods on the prediction.

Methods: We included 505 patients (training cohort, n = 354; validation cohort, n = 151) with gliomas between January 1, 2011 and December 31, 2016. The clinical, neuroimaging, and molecular genetic data of patients were retrospectively collected. The multi-causes discovering with structure learning (McDSL) algorithm, least absolute shrinkage and selection operator regression (LASSO), and Cox proportional hazards regression model were employed to discover the predictors for 3-year PFS and OS, respectively. Eight machine learning classifiers with 5-fold cross-validation were developed to predict 3-year PFS and OS. The area under the curve (AUC) was used to evaluate the prognostic performance of classifiers.

Results: McDSL identified four causal factors (tumor location, WHO grade, histologic type, and molecular genetic group) for 3-year PFS and OS, whereas LASSO and Cox identified wide-range number of factors associated with 3-year PFS and OS. The performance of each machine learning classifier based on McDSL, LASSO, and Cox was not significantly different. Logistic regression yielded the optimal performance in predicting 3-year PFS based on the McDSL (AUC, 0.872, 95% confidence interval [CI]: 0.828-0.916) and 3-year OS based on the LASSO (AUC, 0.901, 95% CI: 0.861-0.940).

Conclusions: McDSL is more reproducible than LASSO and Cox model in the feature selection process. Logistic regression model may have the highest performance in predicting 3-year PFS and OS of gliomas.

FoundationOne CDx testing accurately determines whole arm 1p19q codeletion status in gliomas

BACKGROUND

Molecular profiling of gliomas is vital to ensure diagnostic accuracy, inform prognosis, and identify clinical trial options for primary and recurrent tumors. This study aimed to determine the accuracy of reporting the whole arm 1p19q codeletion status from the FoundationOne platform.

METHODS

Testing was performed on glioma samples as part of clinical care and analyzed up to 395 cancer-associated genes (including IDH1/2). The whole arm 1p19q codeletion status was predicted from the same assay using a custom research-use only algorithm, which was validated using 463 glioma samples with available fluorescence in-situ hybridization (FISH) data. For 519 patients with available outcomes data, progression-free and overall survival were assessed based on whole arm 1p19q codeletion status derived from sequencing data.

RESULTS

Concordance between 1p19q status based on FISH and our algorithm was 96.7% (449/463) with a positive predictive value (PPV) of 100% and a positive percent agreement (PPA) of 91.0%. All discordant samples were positive for codeletion by FISH and harbored genomic alterations inconsistent with oligodendrogliomas. Median overall survival was 168 months for the IDH1/2 mutant, codeleted group, and 122 months for IDH1/2 mutant-only (hazard ratio (HR): 0.42; P < .05).

CONCLUSIONS

1p19q codeletion status derived from FoundationOne testing is highly concordant with FISH results. Genomic profiling may be a reliable substitute for traditional FISH testing while also providing IDH1/2 status.

Telomerase-based Cancer Therapeutics: A Review on their Clinical Trials

Telomeres are protective chromosomal ends that shield the chromosomes from DNA damage, exonucleolytic degradation, recombination, and end-to-end fusion. Telomerase is a ribonucleoprotein that adds TTAGGG tandem repeats to the telomeric ends. It has been observed that 85 to 90% of human tumors express high levels of telomerase, playing a crucial role in the development of cancers. Interestingly, the telomerase activity is generally absent in normal somatic cells. This selective telomerase expression has driven scientists to develop novel anti-cancer therapeutics with high specificity and potency. Several advancements have been made in this area, which is reflected by the enormous success of the anticancer agent Imetelstat. Since the discovery of Imetelstat, several research groups have contributed to enrich the therapeutic arsenal against cancer. Such contributions include the application of new classes of small molecules, peptides, and hTERT-based immunotherapeutic agents (p540, GV1001, GRNVAC1 or combinations of these such as Vx-001). Many of these therapeutic tools are under different stages of clinical trials and have shown promising outcomes. In this review, we highlight the current status of telomerase-based cancer therapeutics and the outcome of these investigations.

Clinical and mutational profiles of adult medulloblastoma groups

Adult medulloblastomas are clinically and molecularly understudied due to their rarity. We performed molecular grouping, targeted sequencing, and TERT promoter Sanger sequencing on a cohort of 99 adult medulloblastomas. SHH made up 50% of the cohort, whereas Group 3 (13%) was present in comparable proportion to WNT (19%) and Group 4 (18%). In contrast to paediatric medulloblastomas, molecular groups had no prognostic impact in our adult cohort (p = 0.877). Most frequently mutated genes were TERT (including promoter mutations, mutated in 36% cases), chromatin modifiers KMT2D (31%) and KMT2C (30%), TCF4 (31%), PTCH1 (27%) and DDX3X (24%). Adult WNT patients showed enrichment of TP53 mutations (6/15 WNT cases), and 3/6 TP53-mutant WNT tumours were of large cell/anaplastic histology. Adult SHH medulloblastomas had frequent upstream pathway alterations (PTCH1 and SMO mutations) and few downstream alterations (SUFU mutations, MYCN amplifications). TERT promoter mutations were found in 72% of adult SHH patients, and were restricted to this group. Adult Group 3 tumours lacked hallmark MYC amplifications, but had recurrent mutations in KBTBD4 and NOTCH1. Adult Group 4 tumours harboured recurrent mutations in TCF4 and chromatin modifier genes. Overall, amplifications of MYC and MYCN were rare (3%). Since molecular groups were not prognostic, alternative prognostic markers are needed for adult medulloblastoma. KMT2C mutations were frequently found across molecular groups and were associated with poor survival (p = 0.002). Multivariate analysis identified histological type (p = 0.026), metastasis (p = 0.031) and KMT2C mutational status (p = 0.046) as independent prognosticators in our cohort. In summary, we identified distinct clinical and mutational characteristics of adult medulloblastomas that will inform their risk stratification and treatment.

Development and Validation of a Novel DNA Methylation-Driven Gene Based Molecular Classification and Predictive Model for Overall Survival and Immunotherapy Response in Patients With Glioblastoma: A Multiomic Analysis

Purpose

Glioblastoma (GBM) is the most common primary malignant tumor of the central nervous system, with a 5-year overall survival (OS) rate of only 5.6%. This study aimed to develop a novel DNA methylation-driven gene (MDG)-based molecular classification and risk model for individualized prognosis prediction for GBM patients.

Methods

The DNA methylation profiles (458 samples) and gene expression profiles (376 samples) of patients were enrolled to identify MDGs using the MethylMix algorithm. Unsupervised consensus clustering was performed to develop the MDG-based molecular classification. By performing the univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis, a MDG-based prognostic model was developed and validated. Then, Bisulfite Amplicon Sequencing (BSAS) and quantitative real-time polymerase chain reaction (qPCR) were performed to verify the methylation and expressions of MDGs in GBM cell lines.

Results

A total of 199 MDGs were identified, the expression patterns of which enabled TCGA and CGGA GBM patients to be divided into 2 clusters by unsupervised consensus clustering. Cluster 1 patients commonly exhibited a poor prognosis, were older in age, and were more sensitive to immunotherapies. Then, six MDGs (ANKRD10, BMP2, LOXL1, RPL39L, TMEM52, and VILL) were further selected to construct the prognostic risk score model, which was validated in the CGGA cohort. Kaplan-Meier survival analysis demonstrated that high-risk patients had significantly poorer OS than low-risk patients (logrank P = 3.338 × 10-6). Then, a prognostic nomogram was constructed and validated. Calibration plots, receiver operating characteristic curves, and decision curve analysis indicated excellent predictive performance for the nomogram in both the TCGA training and CGGA validation cohorts. Finally, in vitro BSAS and qPCR analysis validated that the expressions of the MDGs were negatively regulated by methylations of target genes, especially promoter region methylation.

Conclusion

The MDG-based prognostic model could serve as a promising prognostic indicator and potential therapeutic target to facilitate individualized survival prediction and better treatment options for GBM patients.

Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas

OBJECTIVES

Isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas of histologic grades II and III follow heterogeneous clinical outcomes, which necessitates risk stratification. We aimed to evaluate whether radiomics from MRI would allow prediction of overall survival in patients with IDHwt lower-grade gliomas and to investigate the added prognostic value of radiomics over clinical features.

METHODS

Preoperative MRIs of 117 patients with IDHwt lower-grade gliomas from January 2007 to February 2018 were retrospectively analyzed. The external validation cohort consisted of 33 patients from The Cancer Genome Atlas. A total of 182 radiomic features were extracted. Radiomics risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator (LASSO) and elastic net. Multivariable Cox regression analyses, including clinical features and RRSs, were performed. The integrated areas under the receiver operating characteristic curves (iAUCs) from models with and without RRSs were calculated for comparisons. The prognostic value of RRS was assessed in the validation cohort.

RESULTS

The RRS derived from LASSO and elastic net independently predicted survival with hazard ratios of 9.479 (95% confidence interval [CI], 3.220-27.847) and 6.148 (95% CI, 3.009-12.563), respectively. Those RRSs enhanced model performance for predicting overall survival (iAUC increased to 0.780-0.797 from 0.726), which was externally validated. The RRSs stratified IDHwt lower-grade gliomas in the validation cohort with significantly different survival.

CONCLUSION

Radiomics has the potential for noninvasive risk stratification and can improve prediction of overall survival in patients with IDHwt lower-grade gliomas when integrated with clinical features.

KEY POINTS

• Isocitrate dehydrogenase wild-type lower-grade gliomas with histologic grades II and III follow heterogeneous clinical outcomes, which necessitates further risk stratification. • Radiomics risk scores derived from MRI independently predict survival even after incorporating strong clinical prognostic features (hazard ratios 6.148-9.479). • Radiomics risk scores derived from MRI have the potential to improve survival prediction when added to clinical features (integrated areas under the receiver operating characteristic curves increased from 0.726 to 0.780-0.797).

Clinico-neuropathological features of isocitrate dehydrogenase 2 gene mutations in lower-grade gliomas

Background:

Mutations in the isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are important for both the integrated diagnosis and the prognosis of diffuse gliomas. The p.R132H mutation of IDH1 is the most frequently observed IDH mutation, while IDH2 mutations were relatively rarely studied. The aim of the study was to determine the pathological and genetic characteristics of lower-grade gliomas that carry IDH2 mutations.

Methods:

Data from 238 adult patients with lower-grade gliomas were retrospectively analyzed. The status of IDH1/2 gene mutations, telomerase reverse transcriptase (TERT) promoter mutations, O⁶-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, 1p/19q co-deletion and the expressions of IDH1 R132H, alpha-thalassemia X-linked mental retardation, and p53 were evaluated. Progression-free survival (PFS) and overall survival (OS) were calculated via Kaplan-Meier estimation using the log-rank test.

Results:

Totally, 71% (169/238) of patients were positive for IDH mutations, including 12 patients harboring mutations in IDH2. Among the 12 patients with IDH2 mutations, ten patients harbored the R172K mutation, one patient harbored the R172S mutation and one harbored the R172W mutation. Of these, 11 tumors occurred in the frontal lobe and showed morphology typical of oligodendroglioma. The proportion of grade II tumors was higher than that of grade III tumors in IDH2 mutant-gliomas. IDH2 mutations were frequently associated with TERT promoter mutations, 1p/19q co-deletion and MGMT promoter methylation. IDH2 mutations were associated with better outcomes compared with IDH wild-type gliomas (P < 0.05). However, the PFS and OS did not differ from that of IDH1 mutant patients (P = 0.95 and P = 0.60, respectively).

Conclusions:

IDH2 mutations are more frequent in oligodendrogliomas and associated with a better prognosis. IDH2 mutations may segregate in distinct clinico-pathological and genetic subtypes of gliomas, and therefore may merit routine investigation.

Molecular Classification of Diffuse Gliomas

Technological advances in the field of molecular genetics have improved the ability to classify brain tumors into subgroups with distinct clinical features and important therapeutic implications. The World Health Organization’s newest update on classification of gliomas (2016) incorporated isocitrate dehydrogenase 1 and 2 mutations, ATRX loss, 1p/19q codeletion status, and TP53 mutations to allow for improved classification of glioblastomas, low-grade and anaplastic gliomas. This paper reviews current advances in the understanding of diffuse glioma classification and the impact of molecular markers and DNA methylation studies on survival of patients with these tumors. We also discuss whether the classification and grading of diffuse gliomas should be based on histological findings, molecular markers, or DNA methylation subgroups in future iterations of the classification system.

Conventional magnetic resonance imaging-based radiomic signature predicts telomerase reverse transcriptase promoter mutation status in grade II and III gliomas

PURPOSE

Telomerase reverse transcriptase (TERT) promoter mutation status is an important biomarker for the precision diagnosis and prognosis prediction of lower grade glioma (LGG). This study aimed to construct a radiomic signature to noninvasively predict the TERT promoter status in LGGs.

METHODS

Eighty-three local patients with pathology-confirmed LGG were retrospectively included as a training cohort, and 33 patients from The Cancer Imaging Archive (TCIA) were used as for independent validation. Three types of regions of interest (ROIs), which covered the tumor, peri-tumoral area, and tumor plus peri-tumoral area, were delineated on three-dimensional contrast-enhanced T1 (3D-CE-T1)-weighted and T2-weighted images. One hundred seven shape, first-order, and texture radiomic features from each modality under each ROI were extracted and selected through least absolute shrinkage and selection operator. Radiomic signatures were constructed with multiple classifiers and evaluated using receiver operating characteristic (ROC) analysis. The tumors were also stratified according to IDH status.

RESULTS

Three radiomic signatures, namely, tumoral radiomic signature, tumoral plus peri-tumoral radiomic signature, and fusion radiomic signature, were built, all of which exhibited good accuracy and balanced sensitivity and specificity. The tumoral signature displayed the best performance, with area under the ROC curves (AUC) of 0.948 (0.903-0.993) in the training cohort and 0.827 (0.667-0.988) in the validation cohort. In the IDH subgroups, the AUCs of the tumoral signature ranged from 0.750 to 0.940.

CONCLUSION

The MRI-based radiomic signature is reliable for noninvasive evaluation of TERT promoter mutations in LGG regardless of the IDH status. The inclusion of peri-tumoral area did not significantly improve the performance.

MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas

PURPOSE

To identify significant prognostic magnetic resonance imaging (MRI) features and their prognostic value when added to clinical features in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas.

MATERIALS AND METHODS

Preoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS.

RESULTS

The presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735).

CONCLUSION

MRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features.

KEY POINTS

• Comprehensive analysis of MRI features conveys prognostic information in patients with isocitrate dehydrogenase wild-type lower-grade gliomas. • Presence of cysts, pial invasion, and cortical involvement of the tumor were favorable prognostic factors. • Radiological phenotypes derived from MRI independently predict survival and have the potential to improve survival prediction when added to clinical features.

Identification and validation of a three-gene signature as a candidate prognostic biomarker for lower grade glioma

Background

Lower grade glioma (LGG) are a heterogeneous tumor that may develop into high-grade malignant glioma seriously shortens patient survival time. The clinical prognostic biomarker of lower-grade glioma is still lacking. The aim of our study is to explore novel biomarkers for LGG that contribute to distinguish potential malignancy in low-grade glioma, to guide clinical adoption of more rational and effective treatments.

Methods

The RNA-seq data for LGG was downloaded from UCSC Xena and the Chinese Glioma Genome Atlas (CGGA). By a robust likelihood-based survival model, least absolute shrinkage and selection operator regression and multivariate Cox regression analysis, we developed a three-gene signature and established a risk score to predict the prognosis of patient with LGG. The three-gene signature was an independent survival predictor compared to other clinical parameters. Based on the signature related risk score system, stratified survival analysis was performed in patients with different age group, gender and pathologic grade. The prognostic signature was validated in the CGGA dataset. Finally, weighted gene co-expression network analysis (WGCNA) was carried out to find the co-expression genes related to the member of the signature and enrichment analysis of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were conducted for those co-expression network. To prove the efficiency of the model, time-dependent receiver operating characteristic curves of our model and other models are constructed.

Results

In this study, a three-gene signature (WEE1, CRTAC1, SEMA4G) was constructed. Based on the model, the risk score of each patient was calculated with LGG (low-risk vs. high-risk, hazard ratio (HR) = 0.198 (95% CI [0.120-0.325])) and patients in the high-risk group had significantly poorer survival results than those in the low-risk group. Furthermore, the model was validated in the CGGA dataset. Lastly, by WGCNA, we constructed the co-expression network of the three genes and conducted the enrichment of GO and KEGG. Our study identified a three-gene model that showed satisfactory performance in predicting the 1-, 3- and 5-year survival of LGG patients compared to other models and may be a promising independent biomarker of LGG.

Practice of the New Integrated Molecular Diagnostics in Gliomas: Experiences and New Findings in a Single Chinese Center

Background: The latest WHO classification of CNS tumors using the integrated phenotypic and molecular parameters (IDH, ATRX, 1p19q, TERT etc.) have reestablished the CNS tumors classification in addition to traditional histology. The establishment of glioma molecular typing can more accurately predict prognosis, better guide individualized treatment to improve survival. Methods: The expression of IDH1, ATRX, PHH3, P53 and Ki67 was detected by IHC. Molecular status of IDH1/2 and TERT were analyzed using Sanger sequencing. MGMT was explored using methylation-specific PCR. 1p/19q codeletion status was firstly detected by FISH, then further confirmed by multiplex PCR-based next generation sequencing. Results: The mutation frequency of IDH1 was 68.7% (79/115) in WHO II astrocytoma, and 82 cases (82/344, 23.8%) were "triple-negative glioma" in our cohort. Multivariate COX analysis revealed that only IDH, 1p/19q, TERT and MGMT were independent prognostic factors. Noteworthily, we found 7 cases of the new molecular phenotype presented as "IDH wildtype and 1p/19q codeletion", not mentioned in the latest WHO guideline. Conclusion: We detected the newly recommended markers in a large cohort of Chinese glioma patients. Our data demonstrated a relatively lower frequency of IDH mutations and a higher prevalence of triple-negative glioma in Chinese compared with American and European, indicating ethnic and geographical difference in some markers. In addition, the new molecular phenotype "IDH wildtype and 1p/19q codeletion" glioma deserved special focus. These findings suggest that further stratification of infiltrating gliomas is needed for different treatment strategy and precision medicine.

Development and validation of a nomogram with an autophagy-related gene signature for predicting survival in patients with glioblastoma

Glioblastoma (GBM) is the most common brain tumor with significant morbidity and mortality. Autophagy plays a vital role in GBM development and progression. We aimed to establish an autophagy-related multigene expression signature for individualized prognosis prediction in patients with GBM. Differentially expressed autophagy-related genes (DE-ATGs) in GBM and normal samples were screened using TCGA. Univariate and multivariate Cox regression analyses were performed on DE-ATGs to identify the optimal prognosis-related genes. Consequently, NRG1 (HR=1.142, P=0.008), ITGA3 (HR=1.149, P=0.043), and MAP1LC3A (HR=1.308, P=0.014) were selected to establish the prognostic risk score model and validated in the CGGA validation cohort. GSEA revealed that these genes were mainly enriched in cancer- and autophagy-related KEGG pathways. Kaplan-Meier survival analysis demonstrated that patients with high risk scores had significantly poorer overall survival (OS, log-rank P= 6.955×10^-5). The autophagy signature was identified as an independent prognostic factor. Finally, a prognostic nomogram including the autophagy signature, age, pharmacotherapy, radiotherapy, and IDH mutation status was constructed, and TCGA/CGGA-based calibration plots indicated its excellent predictive performance. The autophagy-related three-gene risk score model could be a prognostic biomarker and suggest therapeutic targets for GBM. The prognostic nomogram could assist individualized survival prediction and improve treatment strategies.

IDH mutant lower grade (WHO Grades II/III) astrocytomas can be stratified for risk by CDKN2A, CDK4 and PDGFRA copy number alterations

In the 2016, WHO classification of tumors of the central nervous system, isocitrate dehydrogenase (IDH) mutation is a main classifier for lower grade astrocytomas and IDH-mutated astrocytomas is now regarded as a single group with longer survival. However, the molecular and clinical heterogeneity among IDH mutant lower grade (WHO Grades II/III) astrocytomas have only rarely been investigated. In this study, we recruited 160 IDH mutant lower grade (WHO Grades II/III) astrocytomas, and examined PDGFRA amplification, CDKN2A deletion and CDK4 amplification by FISH analysis, TERT promoter mutation by Sanger sequencing and ATRX loss and p53 expression by immunohistochemistry. We identified PDGFRA amplification, CDKN2A homozygous deletion and CDK4 amplification in 18.8%, 15.0% and 18.1% of our cohort respectively, and these alterations occurred in a mutually exclusive fashion. PDGFRA amplification was associated with shorter PFS (P = 0.0003) and OS (P < 0.0001). In tumors without PDGFRA amplification, CDKN2A homozygous deletion or CDK4 amplification was associated with a shorter OS (P = 0.035). Tumors were divided into three risk groups based on the presence of molecular alterations: high risk (PDGFRA amplification), intermediate risk (CDKN2A deletion or CDK4 amplification) and low risk (neither CDKN2A deletion and CDK4 amplification nor PDGFRA amplification). These three risk groups were significantly different in overall survival with mean survivals of 40.5, 62.9 and 71.5 months. The high-risk group also demonstrated a shorter PFS compared to intermediate- (P = 0.036) and low-risk (P < 0.0001) groups. One limitation of this study is the relatively short follow-up period, a common confounding factor for studies on low-grade tumors. Our data illustrate that IDH mutant lower grade astrocytomas is not a homogeneous group and should be molecularly stratified for risk.

Prognostic value of preoperative hematological markers combined with molecular pathology in patients with diffuse gliomas

The prediction of clinical outcome for patients with infiltrative gliomas is challenging. Although preoperative hematological markers have been proposed as predictors of survival in glioma and other cancers, systematic investigations that combine these data with other relevant clinical variables are needed to improve prognostic accuracy and patient outcomes. We investigated the prognostic value of preoperative hematological markers, alone and in combination with molecular pathology, for the survival of 592 patients with Grade II-IV diffuse gliomas. On univariate analysis, increased neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR), and decreased albumin-to-globulin ratio (AGR), all predicted poor prognosis in Grade II/III gliomas. Multivariate analysis incorporating tumor status based on the presence of IDH mutations, TERT promoter mutations, and 1p/19q codeletion showed that in lower-grade gliomas, high NLR predicted poorer survival for the triple-negative, IDH mutation only, TERT mutation only, and IDH and TERT mutation groups. NLR was an independent prognostic factor in Grade IV glioma. We therefore propose a prognostic model for diffuse gliomas based on the presence of IDH and TERT promoter mutations, 1p/19q codeletion, and NLR. This model classifies lower-grade gliomas into nine subgroups that can be combined into four main risk groups based on survival projections.

Identification of subsets of IDH-mutant glioblastomas with distinct epigenetic and copy number alterations and stratified clinical risks

Background

IDH-mutant glioblastoma is classified by the 2016 CNS WHO as a group with good prognosis. However, the actual number of cases examined in the literature is relatively small. We hypothesize that IDH-mutant glioblastoma is not a uniform group and should be further stratified.

Methods

We conducted methylation profiles and estimated copy number variations of 57 IDH-mutant glioblastomas.

Results

Our results showed that 59.6% and 40.4% of tumors belonged to glioma-CpG island methylator phenotype (G-CIMP)-high and G-CIMP-low methylation subgroups, respectively. G-CIMP-low subgroup was associated with significantly worse overall survival (OS) as compared to G-CIMP-high (P = .005). CDKN2A deletion (42.1%) was the most common gene copy number variation, and was significantly associated with G-CIMP-low subgroup (P = .004). Other frequent copy number changes included mesenchymal-epithelial transition (MET) (5.3%), CCND2 (19.3%), PDGFRA (14.0%), CDK4 (12.3%), and EGFR (12.3%) amplification. Both CDKN2A deletion (P = .036) and MET amplification (P < .001) were associated with poor OS in IDH-mutant glioblastomas. Combined epigenetic signature and gene copy number variations separated IDH-mutant glioblastomas into Group 1 (G-CIMP-high), Group 2 (G-CIMP-low without CDKN2A nor MET alteration), and Group 3 (G-CIMP-low with CDKN2A and/or MET alteration). Survival analysis revealed Groups 1 and 2 exhibited a favorable OS (median survival: 619 d [20.6 mo] and 655 d [21.8 mo], respectively). Group 3 exhibited a significant shorter OS (median survival: 252 d [8.4 mo]). Multivariable analysis confirmed the independent prognostic significance of our Groups.

Conclusions

IDH-mutant glioblastomas should be stratified for risk with combined epigenetic signature and CDKN2A/MET status and some cases have poor outcome.

Comprehensive analysis of genes based on chr1p/19q co-deletion reveals a robust 4-gene prognostic signature for lower grade glioma

Purpose: The chr1p/19q co-deletion is a favorable prognostic factor in patients with lower grade glioma. The aim of this study was to reveal key genes for prognosis and establish prognostic gene signatures based on genes encoded by chr1p/19q. Materials and methods: The data was downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between lower grade glioma tissue and normal brain were identified. The univariate COX regression, robust likelihood-base survival analysis (rbsurv) and multivariate COX regression analysis were used to establish the 4-gene-signature based on the DEGs. The receiver operating characteristic (ROC) curve and the Kaplan-Mere curve were used to verify the prediction accuracy of the signature. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were also performed to explore the reasons for good prognosis in patients with chr1p/19q deletion. Results: A total of 1346 DEGs were identified between lower grade glioma samples and normal brain samples in GSE16011, including 56 up-regulated mRNAs located on chr1p and 20 up-regulated mRNAs located on chr19q. We established a 4-gene-signature that was significantly associated with survival based on the 76 gene. The AUC of the 4-gene-signature for 5-year OS in TCGA and CGGA was 0.837 and 0.876, respectively, which was superior compared to other parameters such as chr1p/19q co-deletion, IDH mutant, WHO grade and histology type, especially in chr1p/19q non-co-deletion patients. GSEA and KEGG analysis suggested that the prolongation of chr1p/19q in patients could be associated with cell cycle and DNA mismatch repairing. Conclusions: We established a robust 4-gene-signature based on the chr1p/19q and we explored the potential function of these newly identified survival-associated genes by bioinformatics analysis. The 4-gene from the signature are promising molecular targets to be used in the future.

Changing paradigms for targeted therapies against diffuse infiltrative gliomas: tackling a moving target

Introduction: Gliomas are highly heterogeneous primary brain tumors which result in a disproportionately high degree of morbidity and mortality despite their locoregional occurrence. Advances in the understanding of the biological makeup of these malignancies have yielded a number of potential tumor-driving pathways which have been identified as rational targets for therapy. However, early trials of agents that target these pathways have uniformly failed to yield improvement in outcomes in patients with malignant gliomas. Areas covered: This review provides an overview of the most common biological features of gliomas and the strategies to target the same; in addition, the current status of immunotherapy and biological therapies are outlined and the future directions to tackle the challenges of therapy for gliomas are examined. Expert opinion: The limitations of current treatments are attributed to the inability of most of these agents to cross the blood-brain barrier and to the intrinsic heterogeneity of the tumors that result in treatment resistance. The recent emergence of immune-mediated and biological therapies and of agents that target metabolic pathways in gliomas have provided strategies that may overcome tumor heterogeneity and ongoing trials of such agents are anticipated to yield improved outcomes.

Huge heterogeneity in survival in a subset of adult patients with resected, wild-type isocitrate dehydrogenase status, WHO grade II astrocytomas

OBJECTIVE

World Health Organization grade II gliomas are infiltrating tumors that inexorably progress to a higher grade of malignancy. However, the time to malignant transformation is quite unpredictable at the individual patient level. A wild-type isocitrate dehydrogenase (IDH-wt) molecular profile has been reported as a poor prognostic factor, with more rapid progression and a shorter survival compared with IDH-mutant tumors. Here, the oncological outcomes of a series of adult patients with IDH-wt, diffuse, WHO grade II astrocytomas (AII) who underwent resection without early adjuvant therapy were investigated.

METHODS

A retrospective review of patients extracted from a prospective database who underwent resection between 2007 and 2013 for histopathologically confirmed, IDH-wt, non-1p19q codeleted AII was performed. All patients had a minimum follow-up period of 2 years. Information regarding clinical, radiographic, and surgical results and survival were collected and analyzed.

RESULTS

Thirty-one consecutive patients (18 men and 13 women, median age 39.6 years) were included in this study. The preoperative median tumor volume was 54 cm3 (range 3.5-180 cm3). The median growth rate, measured as the velocity of diametric expansion, was 2.45 mm/year. The median residual volume after surgery was 4.2 cm3 (range 0-30 cm3) with a median volumetric extent of resection of 93.97% (8 patients had a total or supratotal resection). No patient experienced permanent neurological deficits after surgery, and all patients resumed a normal life. No immediate postoperative chemotherapy or radiation therapy was given. The median clinical follow-up duration from diagnosis was 74 months (range 27-157 months). In this follow-up period, 18 patients received delayed chemotherapy and/or radiotherapy for tumor progression. Five patients (16%) died at a median time from radiological diagnosis of 3.5 years (range 2.6-4.5 years). Survival from diagnosis was 77.27% at 5 years. None of the 21 patients with a long-term follow-up greater than 5 years have died. There were no significant differences between the clinical, radiological, or molecular characteristics of the survivors relative to the patients who died.

CONCLUSIONS

Huge heterogeneity in the survival data for a subset of 31 patients with resected IDH-wt AII tumors was observed. These findings suggest that IDH mutation status alone is not sufficient to predict risk of malignant transformation and survival at the individual level. Therefore, the therapeutic management of AII tumors, in particular the decision to administer early adjuvant chemotherapy and/or radiation therapy following surgery, should not solely rely on routine molecular markers.