Prognostic significance of relative 1p/19q codeletion in oligodendroglial tumors

1p and/or 19q polysomy is an adverse prognostic factor in oligodendrogliomas, and easy to detect by automated FISH

OBJECTIVE

To study the feasibility of automated analysis by FISH technique in the determination of the 1p and/or 19q polysomy in oligodendrogliomas (OGs) and to explore its prognostic value.

METHODS

We analyzed a retrospective monocentric series of 145 consecutive OGs with IDH mutation and 1p/19q codeletion. For all cases, automated FISH analyses were performed to determine 1p and/or 19q polysomy status and results were compared to manual analysis to verify the concordance of the two methods. Polysomic status was then compared to clinical and histological data, the CDKN2A deletion status when available, event free survival (EFS) and overall survival (OS).

RESULTS

Our study comprised 79 grade 2 OGs (O2) and 66 grade 3 OGs (O3). Polysomy of 1p and/or 19q was observed in 58 cases (40% of whole cohort) with a significant enrichment in the high grade cohort (59% versus 24%; p < 0,0001) and recurrent cases (55%). A majority of polysomic cases were copolysomic for 1p and 19q (75% of the polysomic cohort) rather than 1p or 19q single polysomy (21% and 4% respectively). Polysomy was correlated to high grade histological criteria of high mitotic and Mib1 proliferative indices (p = 0,002 and p = 0,0005 respectively) and to vascular proliferation (p = 0,0003). Univariate and multivariate analysis showed a significant correlation betwen polysomy and a shorter EFS and OS (p = 0,02 and p = 0,016 respectively). Concordance between manual and automated analysis was almost perfect for both 1p and 19q analysis (96 and 98% respectively, κ = 0,92 and 0,95 respectively). Automated analysis revealed that the large majority of polysomic signatures are represented by a small number of R/G signals (mainly 7 signatures) allowing a very easy implementation to pre-existent FISH platforms analysis software.

CONCLUSION

1p and/ or 19q polysomy status represent a prognostic factor in OGs and can be easily determined by automated analysis. Our study supports the clinical interest to determine the polysomic status in all primitive or recurrent OGs and underline the benefits of automated analysis which offers a better archive storage and facilitates multicentric comparison.

Pediatric-type diffuse low-grade glioma with T2-FLAIR mismatch sign: a case report and literature review

INTRODUCTION

Pediatric-type diffuse low-grade gliomas are a new entity that was introduced in the fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System, which was published in 2021. Notably, the information regarding the radiophenotypes of this new entity is limited.

OBJECTIVE

T2-FLAIR mismatch sign has been mostly studied in adult-type diffuse gliomas so far. We aimed to present more pediatric cases for future research about T2-FLAIR mismatch signs in pediatric-type diffuse low-grade gliomas.

CASE PRESENTATION

The current study presents a case of a 2-year-old boy who has a subcortical tumor at the right precentral frontal region. This tumor exhibited a T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign that was identified as specific for isocitrate dehydrogenase (IDH)-mutant 1p/19q non-co-deleted astrocytomas. The tumor was pathologically identified as pediatric-type diffuse low-grade gliomas, and it tested negative for IDH-1 immunohistochemistry. The whole-exome sequencing of tumor tissue revealed negative results for IDH mutation, 1p/19q co-deletion, MYB rearrangement, and all other potential pathogenic mutations.

CONCLUSION

The T2-FLAIR mismatch sign may not be 100% specific for IDH-mutant gliomas, especially in children, and researchers must further investigate the pathophysiology of the T2-FLAIR mismatch sign in brain tumors and the radiophenotypes of entities of pediatric brain tumors.

Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review

DWI is an imaging technique commonly used for the assessment of acute ischemia, inflammatory disorders, and CNS neoplasia. It has several benefits since it is a quick, easily replicable sequence that is widely used on many standard scanners. In addition to its normal clinical purpose, DWI offers crucial functional and physiological information regarding brain neoplasia and the surrounding milieu. A narrative review of the literature was conducted based on the PubMed database with the purpose of investigating the potential role of DWI in the neuro-oncology field. A total of 179 articles were included in the study.

Diagnostic accuracy of 1p/19q codeletion tests in oligodendroglioma: A comprehensive meta-analysis based on a Cochrane systematic review

Codeletion of chromosomal arms 1p and 19q, in conjunction with a mutation in the isocitrate dehydrogenase 1 or 2 gene, is the molecular diagnostic criterion for oligodendroglioma, IDH mutant and 1p/19q codeleted. 1p/19q codeletion is a diagnostic marker and allows prognostication and prediction of the best drug response within IDH-mutant tumours. We performed a Cochrane review and simple economic analysis to establish the most sensitive, specific and cost-effective techniques for determining 1p/19q codeletion status. Fluorescent in situ hybridisation (FISH) and polymerase chain reaction (PCR)-based loss of heterozygosity (LOH) test methods were considered as reference standard. Most techniques (FISH, chromogenic in situ hybridisation [CISH], PCR, real-time PCR, multiplex ligation-dependent probe amplification [MLPA], single nucleotide polymorphism [SNP] array, comparative genomic hybridisation [CGH], array CGH, next-generation sequencing [NGS], mass spectrometry and NanoString) showed good sensitivity (few false negatives) for detection of 1p/19q codeletions in glioma, irrespective of whether FISH or PCR-based LOH was used as the reference standard. Both NGS and SNP array had a high specificity (fewer false positives) for 1p/19q codeletion when considered against FISH as the reference standard. Our findings suggest that G banding is not a suitable test for 1p/19q analysis. Within these limits, considering cost per diagnosis and using FISH as a reference, MLPA was marginally more cost-effective than other tests, although these economic analyses were limited by the range of available parameters, time horizon and data from multiple healthcare organisations.

Diagnostic test accuracy and cost-effectiveness of tests for codeletion of chromosomal arms 1p and 19q in people with glioma

BACKGROUND

Complete deletion of both the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q), known as 1p/19q codeletion, is a mutation that can occur in gliomas. It occurs in a type of glioma known as oligodendroglioma and its higher grade counterpart known as anaplastic oligodendroglioma. Detection of 1p/19q codeletion in gliomas is important because, together with another mutation in an enzyme known as isocitrate dehydrogenase, it is needed to make the diagnosis of an oligodendroglioma. Presence of 1p/19q codeletion also informs patient prognosis and prediction of the best drug treatment. The main two tests in use are fluorescent in situ hybridisation (FISH) and polymerase chain reaction (PCR)-based loss of heterozygosity (LOH) assays (also known as PCR-based short tandem repeat or microsatellite analysis). Many other tests are available. None of the tests is perfect, although PCR-based LOH is expected to have very high sensitivity.

OBJECTIVES

To estimate the sensitivity and specificity and cost-effectiveness of different deoxyribonucleic acid (DNA)-based techniques for determining 1p/19q codeletion status in glioma.

SEARCH METHODS

We searched MEDLINE, Embase and BIOSIS up to July 2019. There were no restrictions based on language or date of publication. We sought economic evaluation studies from the results of this search and using the National Health Service Economic Evaluation Database.

SELECTION CRITERIA

We included cross-sectional studies in adults with glioma or any subtype of glioma, presenting raw data or cross-tabulations of two or more DNA-based tests for 1p/19q codeletion. We also sought economic evaluations of these tests.

DATA COLLECTION AND ANALYSIS

We followed procedures outlined in the Cochrane Handbook for Diagnostic Test Accuracy Reviews. Two review authors independently screened titles/abstracts/full texts, performed data extraction, and undertook applicability and risk of bias assessments using QUADAS-2. Meta-analyses used the hierarchical summary ROC model to estimate and compare test accuracy. We used FISH and PCR-based LOH as alternate reference standards to examine how tests compared with those in common use, and conducted a latent class analysis comparing FISH and PCR-based LOH. We constructed an economic model to evaluate cost-effectiveness.

MAIN RESULTS

We included 53 studies examining: PCR-based LOH, FISH, single nucleotide polymorphism (SNP) array, next-generation sequencing (NGS), comparative genomic hybridisation (CGH), array comparative genomic hybridisation (aCGH), multiplex-ligation-dependent probe amplification (MLPA), real-time PCR, chromogenic in situ hybridisation (CISH), mass spectrometry (MS), restriction fragment length polymorphism (RFLP) analysis, G-banding, methylation array and NanoString. Risk of bias was low for only one study; most gave us concerns about how patients were selected or about missing data. We had applicability concerns about many of the studies because only patients with specific subtypes of glioma were included. 1520 participants contributed to analyses using FISH as the reference, 1304 participants to analyses involving PCR-based LOH as the reference and 262 participants to analyses of comparisons between methods from studies not including FISH or PCR-based LOH. Most evidence was available for comparison of FISH with PCR-based LOH (15 studies, 915 participants): PCR-based LOH detected 94% of FISH-determined codeletions (95% credible interval (CrI) 83% to 98%) and FISH detected 91% of codeletions determined by PCR-based LOH (CrI 78% to 97%). Of tumours determined not to have a deletion by FISH, 94% (CrI 87% to 98%) had a deletion detected by PCR-based LOH, and of those determined not to have a deletion by PCR-based LOH, 96% (CrI 90% to 99%) had a deletion detected by FISH. The latent class analysis suggested that PCR-based LOH may be slightly more accurate than FISH. Most other techniques appeared to have high sensitivity (i.e. produced few false-negative results) for detection of 1p/19q codeletion when either FISH or PCR-based LOH was considered as the reference standard, although there was limited evidence. There was some indication of differences in specificity (false-positive rate) with some techniques. Both NGS and SNP array had high specificity when considered against FISH as the reference standard (NGS: 6 studies, 243 participants; SNP: 6 studies, 111 participants), although we rated certainty in the evidence as low or very low. NGS and SNP array also had high specificity when PCR-based LOH was considered the reference standard, although with much more uncertainty as these results were based on fewer studies (just one study with 49 participants for NGS and two studies with 33 participants for SNP array). G-banding had low sensitivity and specificity when PCR-based LOH was the reference standard. Although MS had very high sensitivity and specificity when both FISH and PCR-based LOH were considered the reference standard, these results were based on only one study with a small number of participants. Real-time PCR also showed high specificity with FISH as a reference standard, although there were only two studies including 40 participants. We found no relevant economic evaluations. Our economic model using FISH as the reference standard suggested that the resource-optimising test depends on which measure of diagnostic accuracy is most important. With FISH as the reference standard, MLPA is likely to be cost-effective if society was willing to pay GBP 1000 or less for a true positive detected. However, as the value placed on a true positive increased, CISH was most cost-effective. Findings differed when the outcome measure changed to either true negative detected or correct diagnosis. When PCR-based LOH was used as the reference standard, MLPA was likely to be cost-effective for all measures of diagnostic accuracy at lower threshold values for willingness to pay. However, as the threshold values increased, none of the tests were clearly more likely to be considered cost-effective.

AUTHORS' CONCLUSIONS

In our review, most techniques (except G-banding) appeared to have good sensitivity (few false negatives) for detection of 1p/19q codeletions in glioma against both FISH and PCR-based LOH as a reference standard. However, we judged the certainty of the evidence low or very low for all the tests. There are possible differences in specificity, with both NGS and SNP array having high specificity (fewer false positives) for 1p/19q codeletion when considered against FISH as the reference standard. The economic analysis should be interpreted with caution due to the small number of studies.

Predicting 1p/19q codeletion status using diffusion-, susceptibility-, perfusion-weighted, and conventional MRI in IDH-mutant lower-grade gliomas

BACKGROUND

Isocitrate dehydrogenase (IDH)-mutant lower-grade gliomas (LGGs) are further classified into two classes: with and without 1p/19q codeletion. IDH-mutant and 1p/19q codeleted LGGs have better prognosis compared with IDH-mutant and 1p/19q non-codeleted LGGs.

PURPOSE

To evaluate conventional magnetic resonance imaging (cMRI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) for predicting 1p/19q codeletion status of IDH-mutant LGGs.

MATERIAL AND METHODS

We retrospectively reviewed cMRI, DWI, SWI, and DSC-PWI in 142 cases of IDH mutant LGGs with known 1p/19q codeletion status. Features of cMRI, relative ADC (rADC), intratumoral susceptibility signals (ITSSs), and the value of relative cerebral blood volume (rCBV) were compared between IDH-mutant LGGs with and without 1p/19q codeletion. Receiver operating characteristic curve and logistic regression were used to determine diagnostic performances.

RESULTS

IDH-mutant and 1p/19q non-codeleted LGGs tended to present with the T2/FLAIR mismatch sign and distinct borders (P < 0.001 and P = 0.038, respectively). Parameters of rADC, ITSSs, and rCBV_max were significantly different between the 1p/19q codeleted and 1p/19q non-codeleted groups (P < 0.001, P = 0.017, and P < 0.001, respectively). A combination of cMRI, SWI, DWI, and DSC-PWI for predicting 1p/19q codeletion status in IDH-mutant LGGs resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and an AUC of 80.36%, 78.57%, 83.30%, 75.00%, and 0.88, respectively.

CONCLUSION

1p/19q codeletion status of IDH-mutant LGGs can be stratified using cMRI and advanced MRI techniques, including DWI, SWI, and DSC-PWI. A combination of cMRI, rADC, ITSSs, and rCBV_max may improve the diagnostic performance for predicting 1p/19q codeletion status.

Prognostic and Predictive Biomarkers in Gliomas

Gliomas are the most common central nervous system tumors. New technologies, including genetic research and advanced statistical methods, revolutionize the therapeutic approach to the patient and reveal new points of treatment options. Moreover, the 2021 World Health Organization Classification of Tumors of the Central Nervous System has fundamentally changed the classification of gliomas and incorporated many molecular biomarkers. Given the rapid progress in neuro-oncology, here we compile the latest research on prognostic and predictive biomarkers in gliomas. In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. Finally, we discussed liquid biopsies, which are promising diagnostic, prognostic, and predictive techniques, but further work is needed to implement these novel technologies in clinical practice.

Vasculogenic Mimicry Formation Predicts Tumor Progression in Oligodendroglioma

Vasculogenic mimicry (VM) has been identified as an important vasculogenic mechanism in malignant tumors, but little is known about its clinical meanings and mechanisms in oligodendroglioma. In this study, VM-positive cases were detected in 28 (20.6%) out of 136 oligodendroglioma samples, significantly associated with higher WHO grade, lower Karnofsky performance status (KPS) scores, and recurrent tumor (p < 0.001, p = 0.040, and p = 0.020 respectively). Patients with VM-positive oligodendroglioma had a shorter progress-free survival (PFS) compared with those with VM-negative tumor (p < 0.001), whereas no significant difference was detected in overall survival (OS) between these patients. High levels of phosphorylate serine/threonine kinases Ataxia-telangiectasia mutated (pATM) and phosphorylate Ataxia-telangiectasia and Rad3-Related (pATR) were detected in 31 (22.8%) and 34 (25.0%), respectively out of 136 oligodendroglioma samples. Higher expressions of pATM and pATR were both associated with a shorter PFS (p < 0.001 and p < 0.001). VM-positive oligodendroglioma specimens tended to exhibit higher pATM and pATR staining than VM-negative specimens (r_s = 0.435, p < 0.001 and r_s = 0.317, p < 0.001). Besides, Hypoxia-inducible factor-1α (HIF1α) expression was detected in 14(10.3%) samples, correlated with higher WHO grade and non-frontal lobe (p = 0.010 and p = 0.029). However, no obvious connection was detected between HIF1α expression and VM formation (p = 0.537). Finally, either univariate or multivariate analysis suggested that VM was an independent unfavorable predictor for oligodendroglioma patients (p < 0.001, HR = 7.928, 95%CI: 3.382-18.584, and p = 0.007, HR = 4.534, 95%CI: 1.504-13.675, respectively). VM is a potential prognosticator for tumor progression in oligodendroglioma patients. Phosphorylation of ATM and ATR linked to treatment-resistance may be associated with VM formation. The role of VM in tumor progression and the implication of pATM/pATR in VM formation may provide potential therapeutic targets for oligodendroglioma treatment.

Extent of resection, molecular signature, and survival in 1p19q-codeleted gliomas

OBJECTIVE

Genomic analysis in neurooncology has underscored the importance of understanding the patterns of survival in different molecular subtypes within gliomas and their responses to treatment. In particular, diffuse gliomas are now principally characterized by their mutation status (IDH1 and 1p/19q codeletion), yet there remains a paucity of information regarding the prognostic value of molecular markers and extent of resection (EOR) on survival. Furthermore, given the modern emphasis on molecular rather than histological diagnosis, it is important to examine the effect of maximal resection on survival in all gliomas with 1p/q19 codeletions, as these will now be classified as oligodendrogliomas under the new WHO guidelines. The objectives of the present study were twofold: 1) to assess the association between EOR and survival for patients with oligodendrogliomas in the National Cancer Database (NCDB), which includes information on mutation status, and 2) to demonstrate the same effect for all patients with 1p/19q codeleted gliomas in the NCDB.

METHODS

The NCDB was queried for all cases of oligodendroglioma between 2004 and 2014, with follow-up dates through 2016. The authors found 2514 cases of histologically confirmed oligodendrogliomas for the final analysis of the effect of EOR on survival. Upon further query, 1067 1p/19q-codeleted tumors were identified in the NCDB. Patients who received subtotal resection (STR) or gross-total resection (GTR) were compared to those who received no tumor debulking surgery. Univariable and multivariable analyses of both overall survival and cause-specific survival were performed.

RESULTS

EOR was associated with increased overall survival for both histologically confirmed oligodendrogliomas and all 1p/19q-codeleted-defined tumors (p < 0.001 and p = 0.002, respectively). Tumor grade, location, and size covaried predictably with EOR. When evaluating tumors by each classification system for predictors of overall survival, facility setting, age, comorbidity index, grade, location, chemotherapy, and radiation therapy were all shown to be significantly associated with overall survival. STR and GTR were independent predictors of improved survival in historically classified oligodendrogliomas (HR 0.83, p = 0.18; HR 0.69, p = 0.01, respectively) and in 1p/19q-codeleted tumors (HR 0.49, p < 0.01; HR 0.43, p < 0.01, respectively).

CONCLUSIONS

By using the NCDB, the authors have demonstrated a side-by-side comparison of the survival benefits of greater EOR in 1p/19q-codeleted gliomas.

Integrated Analysis Reveals Prognostic Value and Immune Correlates of CD86 Expression in Lower Grade Glioma

Background

CD86 has great potential to be a new target of immunotherapy by regulating cancer immune response. However, it remains unclear whether CD86 is a friend or foe in lower-grade glioma (LGG).

Methods

The prognostic value of CD86 expression in pan-cancer was analyzed using Cox regression and Kaplan-Meier analysis with data from the cancer genome atlas (TCGA). Cancer types where CD86 showed prognostic value in overall survival and disease-specific survival were identified for further analyses. The Chinese Glioma Genome Atlas (CGGA) dataset were utilized for external validation. Quantitative real-time PCR (qRT-PCR), Western blot (WB), and Immunohistochemistry (IHC) were conducted for further validation using surgical samples from Jiangsu Province hospital. The correlations between CD86 expression and tumor immunity were analyzed using the Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm, Tumor IMmune Estimation Resource (TIMER) database, and expressions of immune checkpoint molecules. Gene Set Enrichment Analysis (GSEA) was performed using clusterprofiler r package to reveal potential pathways.

Results

Pan-cancer survival analysis established CD86 expression as an unfavorable prognostic factor in tumor progression and survival for LGG. CD86 expression between Grade-II and Grade-III LGG was validated using qRT-PCR and WB. Additionally, CD86 expression in LGG with unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter was significantly higher than those with methylated MGMT (P<0.05), while in LGG with codeletion of 1p/19q it was significantly downregulated as opposed to those with non-codeletion (P<2.2*10-16). IHC staining validated that CD86 expression was correlated with MGMT status and X1p/19q subtypes, which was independent of tumor grade. Multivariate regression validated that CD86 expression acts as an unfavorable prognostic factor independent of clinicopathological factors in overall survival of LGG patients. Analysis of tumor immunity and GSEA revealed pivotal role of CD86 in immune response for LGG.

Conclusions

Integrated analysis shows that CD86 is an unfavorable prognostic biomarker in LGG patients. Targeting CD86 may become a novel approach for immunotherapy of LGG.

Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

BACKGROUND

Molecular characterization of glioma has implications for prognosis, treatment planning, and prediction of treatment response. Current histopathology is limited by intratumoral heterogeneity and variability in detection methods. Advances in computational techniques have led to interest in mining quantitative imaging features to noninvasively detect genetic mutations.

OBJECTIVE

To evaluate the diagnostic accuracy of machine learning (ML) models in molecular subtyping gliomas on preoperative magnetic resonance imaging (MRI).

METHODS

A systematic search was performed following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify studies up to April 1, 2020. Methodological quality of studies was assessed using the Quality Assessment for Diagnostic Accuracy Studies (QUADAS)-2. Diagnostic performance estimates were obtained using a bivariate model and heterogeneity was explored using metaregression.

RESULTS

Forty-four original articles were included. The pooled sensitivity and specificity for predicting isocitrate dehydrogenase (IDH) mutation in training datasets were 0.88 (95% CI 0.83-0.91) and 0.86 (95% CI 0.79-0.91), respectively, and 0.83 to 0.85 in validation sets. Use of data augmentation and MRI sequence type were weakly associated with heterogeneity. Both O6-methylguanine-DNA methyltransferase (MGMT) gene promoter methylation and 1p/19q codeletion could be predicted with a pooled sensitivity and specificity between 0.76 and 0.83 in training datasets.

CONCLUSION

ML application to preoperative MRI demonstrated promising results for predicting IDH mutation, MGMT methylation, and 1p/19q codeletion in glioma. Optimized ML models could lead to a noninvasive, objective tool that captures molecular information important for clinical decision making. Future studies should use multicenter data, external validation and investigate clinical feasibility of ML models.

Imaging Findings of New Entities and Patterns in Brain Tumor: Isocitrate Dehydrogenase Mutant, Isocitrate Dehydrogenase Wild-Type, Codeletion, and MGMT Methylation

Molecular features are now essential in distinguishing between glioma histologic subtypes. Currently, isocitrate dehydrogenase mutation, 1p19q codeletion, and MGMT methylation status play significant roles in optimizing medical and surgical treatment. Noninvasive pretreatment and post-treatment determination of glioma subtype is of great interest. Although imaging cannot replace the genetic panel at present, image findings have shown promising signs to identify and diagnose the types and subtypes of gliomas. This article details key imaging findings in the most common molecular glioma subtypes and highlights recent advances in imaging technologies to differentiate these lesions noninvasively.

Feature-based PET/MRI radiomics in patients with brain tumors

Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.

Radiomics in neuro-oncology: Basics, workflow, and applications

Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and cost-effective evaluation of imaging data is hardly feasible without the support of methods from the field of artificial intelligence (AI). AI can facilitate and shorten various time-consuming steps in the image processing workflow, e.g., tumor segmentation, thereby optimizing productivity. Besides, the automated and computer-based analysis of imaging data may help to increase data comparability as it is independent of the experience level of the evaluating clinician. Importantly, AI offers the potential to extract new features from the routinely acquired neuroimages of brain tumor patients. In combination with patient data such as survival, molecular markers, or genomics, mathematical models can be generated that allow, for example, the prediction of treatment response or prognosis, as well as the noninvasive assessment of molecular markers. The subdiscipline of AI dealing with the computation, identification, and extraction of image features, as well as the generation of prognostic or predictive mathematical models, is termed radiomics. This review article summarizes the basics, the current workflow, and methods used in radiomics with a focus on feature-based radiomics in neuro-oncology and provides selected examples of its clinical application.

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors

Background

Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.

Methods

This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases.

Results

Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80–90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods.

Conclusion

Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.

Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes

BACKGROUND AND PURPOSE

Despite the improved prognostic relevance of the 2016 WHO molecular-based classification of lower-grade gliomas, variability in clinical outcome persists within existing molecular subtypes. Our aim was to determine prognostically significant metrics on preoperative MR imaging for lower-grade gliomas within currently defined molecular categories.

MATERIALS AND METHODS

We undertook a retrospective analysis of 306 patients with lower-grade gliomas accrued from an institutional data base and The Cancer Genome Atlas. Two neuroradiologists in consensus analyzed preoperative MRIs of each lower-grade glioma to determine the following: tumor size, tumor location, number of involved lobes, corpus callosum involvement, hydrocephalus, midline shift, eloquent cortex involvement, ependymal extension, margins, contrast enhancement, and necrosis. Adjusted hazard ratios determined the association between MR imaging metrics and overall survival per molecular subtype, after adjustment for patient age, patient sex, World Health Organization grade, and surgical resection status.

RESULTS

For isocitrate dehydrogenase (IDH) wild-type lower-grade gliomas, tumor size (hazard ratio, 3.82; 95% CI, 1.94-7.75; P < .001), number of involved lobes (hazard ratio, 1.70; 95% CI, 1.28-2.27; P < .001), hydrocephalus (hazard ratio, 4.43; 95% CI, 1.12-17.54; P = .034), midline shift (hazard ratio, 1.16; 95% CI, 1.03-1.30; P = .013), margins (P = .031), and contrast enhancement (hazard ratio, 0.34; 95% CI, 0.13-0.90; P = .030) were associated with overall survival. For IDH-mutant 1p/19q-codeleted lower-grade gliomas, tumor size (hazard ratio, 2.85; 95% CI, 1.06-7.70; P = .039) and ependymal extension (hazard ratio, 6.34; 95% CI, 1.07-37.59; P = .042) were associated with overall survival.

CONCLUSIONS

MR imaging metrics offers prognostic information for patients with lower-grade gliomas within molecularly defined classes, with the greatest prognostic value for IDH wild-type lower-grade gliomas.

Extent of resection and survival for oligodendroglioma: a U.S. population-based study

BACKGROUND

National guidelines recommend maximal safe resection of low-grade and high-grade oligodendrogliomas. However, there is no level 1 evidence to support these guidelines, and recent retrospective studies on the topic have yielded mixed results.

OBJECTIVE

To assess the association between extent of resection (EOR) and survival for oligodendrogliomas in the general U.S.

POPULATION

METHODS

Cases diagnosed between 2004 and 2013 were selected from the Surveillance, Epidemiology, and End-Results (SEER) Program and retrospectively analyzed for treatment, prognostic factors, and survival times. Cases that did not undergo tumor de-bulking surgery (e.g. no surgery or biopsy alone) were compared to subtotal resection (resection) and gross-total resection (GTR). The primary end-points were overall survival (OS) and cause-specific survival (CSS). An external validation cohort with 1p/19q-codeleted tumors was creating using the TCGA and GSE16011 datasets.

RESULTS

3135 Cases were included in the final analysis. The 75% survival time (75ST) and 5-year survival rates were 47 months and 70.8%, respectively. Subtotal resection (STR, 75ST = 50 months) and GTR (75ST = 61 months) were associated with improved survival times compared to cases that did not undergo surgical debulking (75ST = 20 months, P < 0.001 for both), with reduced hazard ratios (HRs) after controlling for other factors (HR 0.81 [0.68-0.97] and HR 0.65 [0.54-0.79], respectively). GTR was associated with improved OS in both low-grade and anaplastic oligodendroglioma subgroups (HR 0.74 [0.58-0.95], HR 0.60 [0.44-0.82], respectively) while STR fell short of significance in the subgroup analysis. All findings were corroborated by multivariable analysis of CSS and externally validated in a cohort of patients with 1p19q-codeleted tumors.

CONCLUSION

Greater EOR is associated with improved survival in oligodendrogliomas. Our findings in this U.S. population-based cohort support national guidelines.

Neuroimaging-Based Classification Algorithm for Predicting 1p/19q-Codeletion Status in IDH-Mutant Lower Grade Gliomas

BACKGROUND AND PURPOSE

Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics.

MATERIALS AND METHODS

One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas.

RESULTS

Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n = 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79).

CONCLUSIONS

We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.

LST1: A multifunctional gene encoded in the MHC class III region

The LST1 gene is located in the MHC class III cluster between the MHC class I and II regions. While most genes in this cluster have been sufficiently characterised, a definitive function and expression pattern for LST1 still remains elusive. In the present review we describe its promotor, gene organisation, splice variants and expression in human tissues, cell lines and cancer. We focus on LST1 expression in inflammation and discuss known correlations with autoimmune diseases and cancer. Current data on LST1 polymorphisms and their known associations with pathologies are also discussed in detail. We summarize the potential functions that have been described for the full-length LST1 protein including its function as a transmembrane adaptor protein with inhibitory signal transduction and its role as a membrane scaffold facilitating the formation of tunnelling nanotubes. We also discuss further potential functions by compiling all known LST1-interacting proteins. Furthermore, we address knowledge gaps and conflictive issues regarding disease association, non-hematopoietic expression and the discrepancy between RNA and protein expression data.

Radiomics derived from amino-acid PET and conventional MRI in patients with high-grade gliomas

Radiomics is a technique that uses high-throughput computing to extract quantitative features from tomographic medical images such as MRI and PET that usually are beyond visual perception. Importantly, the radiomics approach can be performed using neuroimages that have already been acquired during the routine follow-up of the patients allowing an additional data evaluation at low cost. In Neuro-Oncology, these features can potentially be used for differential diagnosis of newly diagnosed cerebral lesions suggestive for brain tumors or for the prediction of response to a neurooncological treatment option. Furthermore, especially in the light of the recent update of the World Health Organization classification of brain tumors, radiomics also has the potential to non-invasively assess important prognostic and predictive molecular markers such as a mutation in the isocitrate dehydrogenase gene or a 1p/19q codeletion which are not accessible by conventional visual interpretation of MRI or PET findings. This review summarizes the current status of the rapidly evolving field of radiomics with a special focus on patients with high-grade gliomas.

Integrating molecular markers into the World Health Organization classification of CNS tumors: a survey of the neuro-oncology community

Background

Molecular markers provide important biological and clinical information related to the classification of brain tumors, and the integration of relevant molecular parameters into brain tumor classification systems has been a widely discussed topic in neuro-oncology over the past decade. With recent advances in the development of clinically relevant molecular signatures and the 2016 World Health Organization (WHO) update, the views of the neuro-oncology community on such changes would be informative for implementing this process.

Methods

A survey with 8 questions regarding molecular markers in tumor classification was sent to an email list of Society for Neuro-Oncology members and attendees of prior meetings (n=5065). There were 403 respondents. Analysis was performed using whole group response, based on self-reported subspecialty.

Results

The survey results show overall strong support for incorporating molecular knowledge into the classification and clinical management of brain tumors. Across all 7 subspecialty groups, ≥70% of respondents agreed to this integration. Interestingly, some variability is seen among subspecialties, notably with lowest support from neuropathologists, which may reflect their roles in implementing such diagnostic technologies.

Conclusion

Based on a survey provided to the neuro-oncology community, we report strong support for the integration of molecular markers into the WHO classification of brain tumors, as well as for using an integrated "layered" diagnostic format. While membership from each specialty showed support, there was variation by specialty in enthusiasm regarding proposed changes. The initial results of this survey influenced the deliberations underlying the 2016 WHO classification of tumors of the central nervous system.

Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT

The "integrated diagnosis" for infiltrating gliomas in the 2016 revised World Health Organization (WHO) classification of tumors of the central nervous system requires assessment of the tumor for IDH mutations and 1p/19q codeletion. Since TERT promoter mutations and ATRX alterations have been shown to be associated with prognosis, we analyzed whether these tumor markers provide additional prognostic information within each of the five WHO 2016 categories. We used data for 1206 patients from the UCSF Adult Glioma Study, the Mayo Clinic and The Cancer Genome Atlas (TCGA) with infiltrative glioma, grades II-IV for whom tumor status for IDH, 1p/19q codeletion, ATRX, and TERT had been determined. All cases were assigned to one of 5 groups following the WHO 2016 diagnostic criteria based on their morphologic features, and IDH and 1p/19q codeletion status. These groups are: (1) Oligodendroglioma, IDH-mutant and 1p/19q-codeleted; (2) Astrocytoma, IDH-mutant; (3) Glioblastoma, IDH-mutant; (4) Glioblastoma, IDH-wildtype; and (5) Astrocytoma, IDH-wildtype. Within each group, we used univariate and multivariate Cox proportional hazards models to assess associations of overall survival with patient age at diagnosis, grade, and ATRX alteration status and/or TERT promoter mutation status. Among Group 1 IDH-mutant 1p/19q-codeleted oligodendrogliomas, the TERT-WT group had significantly worse overall survival than the TERT-MUT group (HR: 2.72, 95% CI 1.05-7.04, p = 0.04). In both Group 2, IDH-mutant astrocytomas and Group 3, IDH-mutant glioblastomas, neither TERT mutations nor ATRX alterations were significantly associated with survival. Among Group 4, IDH-wildtype glioblastomas, ATRX alterations were associated with favorable outcomes (HR: 0.36, 95% CI 0.17-0.81, p = 0.01). Among Group 5, IDH-wildtype astrocytomas, the TERT-WT group had significantly better overall survival than the TERT-MUT group (HR: 0.48, 95% CI 0.27-0.87), p = 0.02). Thus, we present evidence that in certain WHO 2016 diagnostic groups, testing for TERT promoter mutations or ATRX alterations may provide additional useful prognostic information.

BRM/SMARCA2-negative clear cell renal cell carcinoma is associated with a high percentage of BRM somatic mutations, deletions and promoter methylation

AIMS

The aim of this study was to investigate potential molecular mechanisms associated with loss of BRM expression in poorly differentiated clear cell renal cell carcinoma (ccRCC).

METHODS AND RESULTS

Nineteen previously selected BRM-negative RCC tissues were examined by DNA sequencing, fluorescence in-situ hybridization (FISH) and methylation-specific polymerase chain reaction (PCR) of the BRM gene. BRM mutation was identified in 78.9% (15 of 19) cases, chromosome 9 monosomy or BRM deletion in 43.8% (seven of 16) and BRM promoter region cytosine-phosphate-guanine (CpG) methylation in 42.8% (six of 14). These results indicated that 89.5% (17 of 19) of the cases harboured at least one type of BRM genetic alteration, with two or more types of alteration in 47.4% (nine of 19). Such alterations were found rarely in adjacent non-neoplastic tissues and low-grade areas of composite tumours.

CONCLUSIONS

BRM gene mutation, chromosome 9 monosomy or BRM deletion and CpG methylation contribute collectively to the loss of BRM expression in ccRCC. This work focusing on composite tumours indicated that BRM abnormality occurred during tumour progression.

Recent advances and future of immunotherapy for glioblastoma

INTRODUCTION

Outcome for glioma (GBM) remains dismal despite advances in therapeutic interventions including chemotherapy, radiotherapy and surgical resection. The overall survival benefit observed with immunotherapies in cancers such as melanoma and prostate cancer has fuelled research into evaluating immunotherapies for GBM.

AREAS COVERED

Preclinical studies have brought a wealth of information for improving the prognosis of GBM and multiple clinical studies are evaluating a wide array of immunotherapies for GBM patients. This review highlights advances in the development of immunotherapeutic approaches. We discuss the strategies and outcomes of active and passive immunotherapies for GBM including vaccination strategies, gene therapy, check point blockade and adoptive T cell therapies. We also focus on immunoediting and tumor neoantigens that can impact the efficacy of immunotherapies.

EXPERT OPINION

Encouraging results have been observed with immunotherapeutic strategies; some clinical trials are reaching phase III. Significant progress has been made in unraveling the molecular and genetic heterogeneity of GBM and its implications to disease prognosis. There is now consensus related to the critical need to incorporate tumor heterogeneity into the design of therapeutic approaches. Recent data also indicates that an efficacious treatment strategy will need to be combinatorial and personalized to the tumor genetic signature.

1p/19q codeletion and RET rearrangements in small-cell lung cancer

The prognosis of small-cell lung cancer (SCLC) is poor despite reports suggesting modest improvement in survival. To date, chemotherapy remains the cornerstone treatment for SCLC patients, and many studies have focused on identifying the molecular characteristics of SCLC, which serve as the basis for precision treatments that improve the prognosis of SCLC. For instance, the therapeutic effect of temozolomide, recommended for patients with relapsed SCLC, is linked to 1p/19q codeletion in anaplastic oligodendroglial tumors. A subpopulation of SCLC patients may derive benefit from tyrosine kinase inhibitors targeting RET. In order to identify 1p/19q codeletion and RET rearrangement in SCLC patients, 32 SCLC resected specimens were retrospectively collected between 2008 and 2014 from the Zhejiang Cancer Hospital in People’s Republic of China. Fluorescence in situ hybridization was used to detect 1p/19q codeletion and RET rearrangement in the specimens. A 1p single deletion was detected in eight specimens, 19q single deletion was detected in three specimens, and only three specimens had a 1p/19q codeletion. None of the specimens had a RET rearrangement. The three patients whose specimens had a 1p/19q codeletion were alive after 58, 50, and 30 months of follow-up care. There was a trend toward prolonged overall survival for the patients with codeletion compared to no codeletion, 1p single deletion, 19q single deletion, and without 1p and 19q deletion (P=0.113, 0.168, 0.116, and 0.122, respectively). Our data showed that RET rearrangement may be not an ideal molecular target for SCLC therapies in People’s Republic of China. Instead, 1p/19q codeletion is a promising marker for a good prognosis and treatment with temozolomide in SCLC.

Chromosomal Aberrations in Canine Gliomas Define Candidate Genes and Common Pathways in Dogs and Humans

Spontaneous gliomas in dogs occur at a frequency similar to that in humans and may provide a translational model for therapeutic development and comparative biological investigations. Copy number alterations in 38 canine gliomas, including diffuse astrocytomas, glioblastomas, oligodendrogliomas, and mixed oligoastrocytomas, were defined using an Illumina 170K single nucleotide polymorphism array. Highly recurrent alterations were seen in up to 85% of some tumor types, most notably involving chromosomes 13, 22, and 38, and gliomas clustered into 2 major groups consisting of high-grade IV astrocytomas, or oligodendrogliomas and other tumors. Tumor types were characterized by specific broad and focal chromosomal events including focal loss of the INK4A/B locus in glioblastoma and loss of the RB1 gene and amplification of the PDGFRA gene in oligodendrogliomas. Genes associated with the 3 critical pathways in human high-grade gliomas (TP53, RB1, and RTK/RAS/PI3K) were frequently associated with canine aberrations. Analysis of oligodendrogliomas revealed regions of chromosomal losses syntenic to human 1p involving tumor suppressor genes, such as CDKN2C, as well as genes associated with apoptosis, autophagy, and response to chemotherapy and radiation. Analysis of high frequency chromosomal aberrations with respect to human orthologues may provide insight into both novel and common pathways in gliomagenesis and response to therapy.

Brain cancer: Tumour cells on neighbourhood watch

The discovery of microtube structures that link tumour cells in some invasive brain tumours reveals how these cancers spread, and how they resist treatment.