IDH1 mutant malignant astrocytomas are more amenable to surgical resection and have a survival benefit associated with maximal surgical resection

MRI texture analysis based on 3D tumor measurement reflects the IDH1 mutations in gliomas - A preliminary study

OBJECTIVE

To evaluate the differentiation efficiency of texture analysis of T1WI, T2WI and contrasted-enhanced T1WI MRI sequences in gliomas with and without IDH1 mutation based on entire tumor region.

MATERIALS AND METHODS

A total of 42 patients with histopathologically confirmed gliomas, including 21 patients carrying IDH1 mutation (IDH1^mutation group) and 21 with wild-type IDH1 (IDH1^wt group) were included in this study. The preoperative MRI and clinical data were collected. The regions of interest (ROIs) covering the entire tumor and edema were manually delineated on axial slices using O.K. (Omni Kinetics, GE Healthcare, China) software; and the histogram and GLCM features based on T1WI, T2WI and contrasted-enhanced T1WI sequences were automatically generated.

RESULTS

Based on contrasted-enhanced T1WI features, the inertia resulted as the best feature for diagnosis, with the AUC of 0.844. Furthermore, the AUC for gliomas prediction with IDH1^mutation was 0.800 for cluster prominence. IDH1-mutation was differentiated on T2WI with the highest AUC of 0.848, which corresponded to GLCM Entropy. After modeling, the accuracy of the contrasted-enhanced T1WI, T1WI, and T2WI features model was 0.952, 0.857, and 0.738, respectively. The AUC of Joint Variable_T1WI+C for predicting IDH1^mutation was 0.984, while the AUC of Joint Variable_T1WI for predicting the same mutation was 0.927. The diagnostic efficiency of Joint Variable_T2WI was also desirable.

CONCLUSION

MRI texture analysis could be used as a new noninvasive method for identification of gliomas with IDH1 mutation. The present results show that the Joint Variable derived from conventional MR imaging histogram and GLCM features is suitable for precise detection of IDH1-mutated gliomas.

Insular glioma surgery: an evolution of thought and practice

OBJECTIVEThe goal of this article is to review the history of surgery for low- and high-grade gliomas located within the insula with particular focus on microsurgical technique, anatomical considerations, survival, and postoperative morbidity.METHODSThe authors reviewed the literature for published reports focused on insular region anatomy, neurophysiology, surgical approaches, and outcomes for adults with World Health Organization grade II-IV gliomas.RESULTSWhile originally considered to pose too great a risk, insular glioma surgery can be performed safely due to the collective efforts of many individuals. Similar to resection of gliomas located within other cortical regions, maximal resection of gliomas within the insula offers patients greater survival time and superior seizure control for both newly diagnosed and recurrent tumors in this region. The identification and the preservation of M2 perforating and lateral lenticulostriate arteries are critical steps to preventing internal capsule stroke and hemiparesis. The transcortical approach and intraoperative mapping are useful tools to maximize safety.CONCLUSIONSThe insula's proximity to middle cerebral and lenticulostriate arteries, primary motor areas, and perisylvian language areas makes accessing and resecting gliomas in this region challenging. Maximal safe resection of insular gliomas not only is possible but also is associated with excellent outcomes and should be considered for all patients with low- and high-grade gliomas in this area.

Radiographic assessment of contrast enhancement and T2/FLAIR mismatch sign in lower grade gliomas: correlation with molecular groups

PURPOSE

With the updated World Health Organization (WHO) 2016 neuropathological diagnostic criteria, radiographic prognostic associations in lower-grade gliomas (LGG, WHO grade II and III) are undergoing re-evaluation.

METHODS

We identified 316 LGG patients (151 grade II and 165 grade III) for a combined cohort from three independent databases. We analyzed the preoperative axial FLAIR, axial T2-weighted and post-gadolinium volumetric T1-weighted MR images. The molecular data collected included the status of IDH1/2, TP53, TERT promoter and ATRX mutations, in addition to 1p/19q co-deletions. In a subset of cases (n = 133), we assessed the "T2-FLAIR mismatch" sign.

RESULTS

Gliomas were assigned to one of the three molecular groups: Group O (IDH-mutant, 1p/19q co-deleted oligodendrogliomas, n = 95), Group A (IDH-mutant, ATRX inactivated astrocytomas, n = 175) and Group G (IDH wild-type, GBM-like, n = 46). A contrast-enhancing tumor was seen in 98 patients (31%), most frequently in Group G (n = 28/45, 57%), when compared to Group A (n = 49/175, 28%) and Group O (n = 24/95, 25.3%) tumors (p = 0.008 and p = 0.0011, respectively). Consistent with previous reports, T2-FLAIR mismatch was preferentially found in Group A tumors (73.1%, 60 of 82), although its presence was not associated with survival, after controlling for molecular group. False positive mismatch sign was noted in 28.5% (12/42) Group O tumors, but none of the tumors in Group G. A combination of all three factors: age under 40 years at first diagnosis, a tumor size larger than 6 cm and T2-FLAIR mismatch was highly specific for IDH mutant astrocytoma (Group A).

CONCLUSION

We identify radiographic correlates of molecular groups in lower-grade gliomas, which join clinical demographic features in defining the characteristic presentation of these tumors. Radiographic correlates of prognosis in LGG require re-evaluation within molecular group.

Oncogenic transgelin-2 is differentially regulated in isocitrate dehydrogenase wild-type vs. mutant gliomas

The presence of an isocitrate dehydrogenase (IDH1/2) mutation in gliomas is associated with favorable outcomes compared to gliomas without the mutation (IDH1/2 wild-type, WT). The underlying biological mechanisms accounting for improved clinical outcomes in IDH1/2 mutant gliomas remain poorly understood, but may, in part, be due to the glioma CpG island methylator phenotype (G-CIMP) and epigenetic silencing of genes. We performed profiling of IDH1/2 WT versus IDH1/2 mutant Grade II and III gliomas and identified transgelin-2 (TAGLN2), an oncogene and actin-polymerizing protein, to be expressed at significantly higher levels in IDH1/2 WT gliomas compared to IDH1/2 mutant gliomas. This differential expression of TAGLN2 was primarily due to promoter hypermethylation in IDH1/2 mutant gliomas, suggesting involvement of TAGLN2 in the G-CIMP. Our results also suggest that TAGLN2 may be involved in progression due to higher expression in glioblastomas compared to IDH1/2 WT gliomas of lower grades. Furthermore, our results suggest that TAGLN2 functions as an oncogene by contributing to proliferation and invasion when overexpressed in IDH1/2 WT glioma cells. Taken together, this study demonstrates a possible link between increased TAGLN2 expression, invasion and poor patient outcomes in IDH1/2 WT gliomas and identifies TAGLN2 as a potential novel therapeutic target for IDH1/2 WT gliomas.

Analysis of human gliomas by swab touch spray-mass spectrometry: applications to intraoperative assessment of surgical margins and presence of oncometabolites

Touch spray mass spectrometry using medical swabs is an ambient ionization technique (ionization of unprocessed sample in the open air) that has potential intraoperative application in quickly identifying the disease state of tissue and in better characterizing the resection margin. To explore this potential, we studied 29 human brain tumor specimens and obtained evidence that this technique can provide diagnostic molecular information that is relevant to brain cancer. Touch spray using medical swabs involves the physical sampling of tissue using a medical swab on a spatial scale of a few mm² with subsequent ionization occurring directly from the swab tip upon addition of solvent and application of a high voltage. Using a tertiary mixture of acetonitrile, N,N-dimethylformamide, and ethanol, membrane-derived phospholipids and oncometabolites are extracted from the tissue, incorporated into the sprayed microdroplets, vacuumed into the mass spectrometer, and characterized in the resulting mass spectra. The tumor cell load was assessed from the complex phospholipid pattern in the mass spectra and also separately by measurement of N-acetylaspartate. Mutation status of the isocitrate dehydrogenase gene was determined via detection of the oncometabolite 2-hydroxyglutarate. The lack of sample pretreatment makes touch spray mass spectrometry using medical swabs a feasible intraoperative strategy for rapid surgical assessment.

The clinical use of IDH1 and IDH2 mutations in gliomas

Introduction: Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 have been reported in a limited number of tumors. In gliomas, IDH mutations are primarily detected in WHO grade II-III tumors and represent a major biomarker with diagnostic, prognostic, and predictive implications. The recent development of IDH inhibitors and vaccines suggests that the IDH mutation is also an appealing target for therapy. Areas covered: This review focuses on the role of IDH mutations in diffuse gliomas. Besides discussing their role in gliomagenesis, we will emphasize the role of IDH mutations in clinical practice as a diagnostic, prognostic and predictive biomarker, and as a potential therapeutic target. Noninvasive detection of the IDH mutation by means of liquid biopsy and MR spectroscopy will also be discussed. Expert commentary: While IDH mutation is a consolidated diagnostic and prognostic biomarker in clinical practice, its role in oncogenesis is far from being elucidated, and there are several pending issues. The routine use of noninvasive techniques for detection and monitoring of the IDH status remains challenging. Although the IDH mutation is a very early alteration in gliomagenesis, it may then be omitted during tumor progression. This observation has important implications when designing targeted clinical trials.

Bridging Cancer Biology with the Clinic: Comprehending and Exploiting IDH Gene Mutations in Gliomas

Isocitrate dehydrogenases 1 and 2 (IDH1/2) are enzymes that play a major role in the Krebs cycle. Mutations in these enzymes are found in the majority of lower gliomas and secondary glioblastomas, but also in myeloid malignancies and other cancers. IDH1 and IDH2 mutations are restricted to specific arginine residues in the active site of the enzymes and are gain-of-function, i.e. they confer a neomorphic enzyme activity resulting in the accumulation of D-2-hydroxyglutarate (2-HG). 2-HG is an oncometabolite causing profound metabolic dysregulation which, among others, results in methylator phenotypes and in defects in homologous recombination repair. In this review, we summarize current knowledge regarding the function of normal and mutated IDH, explain the possible mechanisms through which these mutations might drive malignant transformation of progenitor cells in the central nervous system, and provide a comprehensive review of potential treatment strategies for IDH-mutated malignancies, focusing on gliomas.

Anaplastic Pleomorphic Xanthoastrocytoma Presenting with Musical Hallucination

Musical hallucinations are a relatively rare form of auditory hallucination characterized by hearing of music in the absence of any external stimuli. This phenomenon has been linked to both psychiatric and structural lesions. We present the case of a previously healthy young male whose presentation with musical hallucinations led to the diagnosis of a rare tumour, anaplastic pleomorphic xanthoastrocytoma.

Brain T1ρ mapping for grading and IDH1 gene mutation detection of gliomas: a preliminary study

INTRODUCTION

The longitudinal relaxation time in the rotating frame (T1ρ) has proved to be sensitive to metabolism and useful in application to neurodegenerative diseases. However, few literature exists on its utility in gliomas. Thus, this study was conducted to explore the performance of T1ρ mapping in tumor grading and characterization of isocitrate dehydrogenase 1 (IDH1) gene mutation status of gliomas.

METHODS

Fifty-seven patients with gliomas underwent brain MRI and quantitative measurements of T1ρ and apparent diffusion coefficient (ADC) were recorded. Parameters were compared between high-grade gliomas (HGG) and low-grade gliomas (LGG) and between IDH1 mutant and wildtype groups.

RESULTS

HGG showed significantly higher T1ρ values in both the solid and peritumoral edema areas compared with LGG (P < 0.001 and P = 0.005, respectively), whereas no significant differences in the two areas were found for ADC (both P > 0.05). Receiver operating characteristic (ROC) curve analysis showed that T1ρ value in the solid area achieved the highest area under the ROC curve (AUC, 0.841) in grading with a sensitivity of 80.6% and a specificity of 81.0%. In the grade II/III glioma group, multivariate logistic regression showed that both tumor frontal lobe location (odds ratio [OR] 526.608; P = 0.045) and T1ρ value of the peritumoral edema area (OR 0.863; P = 0.037) were significant predictors of IDH1 mutation. Using the combination, the diagnostic sensitivity and specificity for IDH1 mutated gliomas were 93.3% and 88.9%, respectively.

CONCLUSIONS

Our study shows the feasibility of applying T1ρ mapping in assessing the histologic grade and IDH1 mutation status of gliomas.

How to Build a Neurosurgical Oncology Practice Specializing in Gliomas

For the neurosurgical oncologist, a specialty practice in gliomas represents an intersection of tailored surgical approaches, emerging intraoperative technologies, expanding surgical trial portfolios, and new paradigms in glioma biology. Assembling these disparate pieces into a cohesive career trajectory is a difficult task but ultimately enables the subspecialist to navigate all domains relevant to improving glioma patient outcomes. Within the larger clinical and basic science community, thoughtful integration and intensive collaborations are essential mechanisms when building a multidisciplinary glioma program.

A Critical Overview of Targeted Therapies for Glioblastoma

Over the past century, treatment of malignant tumors of the brain has remained a challenge. Refinements in neurosurgical techniques, discovery of powerful chemotherapeutic agents, advances in radiotherapy, applications of biotechnology, and improvements in methods of targeted delivery have led to some extension of length of survival of glioblastoma patients. Refinements in surgery are mentioned because most of the patients with glioblastoma undergo surgery and many of the other innovative therapies are combined with surgery. However, cure of glioblastoma has remained elusive because it requires complete destruction of the tumor. Radical surgical ablation is not possible in the brain and even a small residual tumor leads to rapid recurrence that eventually kills the patient. Blood-brain barrier (BBB) comprising brain endothelial cells lining the cerebral microvasculature, limits delivery of drugs to the brain. Even though opening of the BBB in tumor core occurs locally, BBB limits systemic chemotherapy especially at the tumor periphery, where tumor cells invade normal brain structure comprising intact BBB. Comprehensive approaches are necessary to gain maximally from promising targeted therapies. Common methods used for critical evaluation of targeted therapies for glioblastoma include: (1) novel methods for targeted delivery of chemotherapy; (2) strategies for delivery through BBB and blood-tumor barriers; (3) innovations in radiotherapy for selective destruction of tumor; (4) techniques for local destruction of tumor; (5) tumor growth inhibitors; (6) immunotherapy; and (7) cell/gene therapies. Suggestions for improvements in glioblastoma therapy include: (1) controlled targeted delivery of anticancer therapy to glioblastoma through the BBB using nanoparticles and monoclonal antibodies; (2) direct introduction of genetically modified bacteria that selectively destroy cancer cells but spare the normal brain into the remaining tumor after resection; (3) use of better animal models for preclinical testing; and (4) personalized/precision medicine approaches to therapy in clinical trials and translation into practice of neurosurgery and neurooncology. Advances in these techniques suggest optimism for the future management of glioblastoma.

The Role of Intraoperative MRI in Awake Neurosurgical Procedures: A Systematic Review

Background: Awake craniotomy for brain tumors remains an important tool in the arsenal of the treating neurosurgeon working in eloquent areas of the brain. Furthermore, with the implementation of intraoperative magnetic resonance imaging (I-MRI), one can afford the luxury of imaging to assess surgical resection of the underlying gross imaging defined neuropathology and the surrounding eloquent areas. Ideally, the combination of I-MRI and awake craniotomy could provide the maximal lesion resection with the least morbidity and mortality. However, more resection with the aid of real time imaging and awake craniotomy techniques might give opposite outcome results. The goal of this systematic review.is to identify the available literature on combined I-MRI and awake craniotomy techniques, to better understand the potential morbidity and mortality associated.

Methods: MEDLINE, EMBASE, and CENTRAL were searched from inception up to December 2016. A total of 10 articles met inclusion in to the review, with a total of 324 adult patients.

Results: All studies showed transient neurological deficits between 2.9 to 76.4%. In regards to persistent morbidity, the mean was ~10% (ranges from zero to 35.3%) with a follow up period between 5 days and 6 months.

Conclusion: The preliminary results of this review also suggest this combined technique may impose acceptable post-operative complication profiles and morbidity. However, this is based on low quality evidence, and is therefore questionable. Further, well-designed future trials with the long-term follow-up are needed to provide various aspects of feasibility and outcome data for this approach.

Longitudinal Patterns in Clinical and Imaging Measurements Predict Residual Survival in Glioblastoma Patients

The growing amount of longitudinal data for a large population of patients has necessitated the application of algorithms that can discover patterns to inform patient management. This study demonstrates how temporal patterns generated from a combination of clinical and imaging measurements improve residual survival prediction in glioblastoma patients. Temporal patterns were identified with sequential pattern mining using data from 304 patients. Along with patient covariates, the patterns were incorporated as features in logistic regression models to predict 2-, 6-, or 9-month residual survival at each visit. The modeling approach that included temporal patterns achieved test performances of 0.820, 0.785, and 0.783 area under the receiver operating characteristic curve for predicting 2-, 6-, and 9-month residual survival, respectively. This approach significantly outperformed models that used tumor volume alone (p < 0.001) or tumor volume combined with patient covariates (p < 0.001) in training. Temporal patterns involving an increase in tumor volume above 122 mm³/day, a decrease in KPS across multiple visits, moderate neurologic symptoms, and worsening overall neurologic function suggested lower residual survival. These patterns are readily interpretable and found to be consistent with known prognostic indicators, suggesting they can provide early indicators to clinicians of changes in patient state and inform management decisions.

Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas

The presence of contrast enhancement (CE) on magnetic resonance (MR) imaging is conventionally regarded as an indicator for tumor malignancy. However, the biological behaviors and molecular mechanism of enhanced tumor are not well illustrated. The aim of this study was to investigate the molecular profiles associated with anaplastic gliomas (AGs) presenting CE on postcontrast T1‐weighted MR imaging. In this retrospective database study, RNA sequencing and MR imaging data of 91 AGs from the Cancer Genome Atlas (TCGA) and 64 from the Chinese Glioma Genome Atlas (CGGA) were collected. Gene set enrichment analysis (GSEA), significant analysis of microarray, generalized linear models, and Least absolute shrinkage and selection operator algorithm were used to explore radiogenomic and prognostic signatures of AG patients. GSEA indicated that angiogenesis and epithelial‐mesenchymal transition were significantly associated with post‐CE. Genes driving immune system response, cell proliferation, and focal adhesions were also significantly enriched. Gene ontology of 237 differential genes indicated consistent results. A 48‐gene signature for CE was identified in TCGA and validated in CGGA dataset (area under the curve = 0.9787). Furthermore, seven genes derived from the CE‐specific signature could stratify AG patients into two subgroups based on overall survival time according to corresponding risk score. Comprehensive analysis of post‐CE and genomic characteristics leads to a better understanding of radiology‐pathology correlations. Our gene signature helps interpret the occurrence of radiological traits and predict clinical outcomes. Additionally, we found nine prognostic quantitative radiomic features of CE and investigated the underlying biological processes of them.

Biological Role and Therapeutic Potential of IDH Mutations in Cancer

Hotspot mutations in isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) occur in a variety of myeloid malignancies and solid tumors. Mutant IDH proteins acquire a neomorphic enzyme activity to produce the putative oncometabolite D-2-hydroxyglutarate, which is thought to block cellular differentiation by competitively inhibiting α-ketoglutarate-dependent dioxygenases involved in histone and DNA demethylation. Small-molecule inhibitors of mutant IDH1 and IDH2 have been developed and are progressing through pre-clinical and clinical development. In this review, we provide an overview of mutant IDH-targeted therapy and discuss a number of important recent pre-clinical studies using models of IDH-mutant solid tumors.

Genotype-targeted local therapy of glioma

Aggressive neurosurgical resection to achieve sustained local control is essential for prolonging survival in patients with lower-grade glioma. However, progression in many of these patients is characterized by local regrowth. Most lower-grade gliomas harbor isocitrate dehydrogenase 1 (IDH1) or IDH2 mutations, which sensitize to metabolism-altering agents. To improve local control of IDH mutant gliomas while avoiding systemic toxicity associated with metabolic therapies, we developed a precision intraoperative treatment that couples a rapid multiplexed genotyping tool with a sustained release microparticle (MP) drug delivery system containing an IDH-directed nicotinamide phosphoribosyltransferase (NAMPT) inhibitor (GMX-1778). We validated our genetic diagnostic tool on clinically annotated tumor specimens. GMX-1778 MPs showed mutant IDH genotype-specific toxicity in vitro and in vivo, inducing regression of orthotopic IDH mutant glioma murine models. Our strategy enables immediate intraoperative genotyping and local application of a genotype-specific treatment in surgical scenarios where local tumor control is paramount and systemic toxicity is therapeutically limiting.

Synthesis and Evaluation of a 18F-Labeled Triazinediamine Analogue for Imaging Mutant IDH1 Expression in Gliomas by PET

Mutations in the isocitrate dehydrogenase gene 1 (IDH1) are common in gliomas. Studies suggest that IDH1 mutations are early events in glioma formation and are important drivers of malignant progression. Herein, we report the synthesis and evaluation of a ¹⁸F-labeled triazinediamine analogue, [¹⁸F]1, as a candidate radiotracer for noninvasive imaging of IDH1 mutations in gliomas by positron emission tomography (PET). In vitro studies revealed good binding inhibition potency and binding affinity for [¹⁸F]1 in IDH1 mutant glioma cell lines, with a half-maximal inhibitory concentration value (IC₅₀) of 54 nM and an equilibrium dissociation constant (K_d) of 40 nM. In vivo studies using mutant IDH1 glioma xenografts showed good tumor uptake of [¹⁸F]1 and specific inhibition by the unlabeled 1, but also elevated radioactivity uptake in the bone, suggesting significant defluorination. The results support further optimization of the triazinediamine scaffold to develop a more stable and potent ¹⁸F-labeled analogue for PET imaging of IDH1 mutations in gliomas.

A surgical strategy for lower grade gliomas using intraoperative molecular diagnosis

Lower grade gliomas are both treated and diagnosed via surgical resection. Maximum tumor resection is currently the standard of care; however, this risks the loss of brain function. Glioma can be genetically subdivided into three different types, based on isocitrate dehydrogenase (IDH) mutation status and the presence of 1p/19q codeletion, which have radically different prognoses and responses to adjuvant therapies. Therefore, the means to identify the subtype and evaluate the surrounding tissues during surgery would be advantageous. In this study, we have developed a new surgical strategy for lower grade glioma based on the fourth edition of the World Health Organization Brain Tumor Classification, involving intraoperative molecular diagnosis. High-resolution melting analysis was used to evaluate IDH mutational status, while rapid immunohistochemistry of p53 and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) was used to evaluate the 1p/19q codeletion status, allowing genetic classification during surgery. In addition, intraoperative flow cytometry was used to evaluate the surgical cavity for additional tumor lesions, allowing maximal resection while mitigating the risk of functional losses. This strategy allows the rapid intraoperative diagnosis and mapping of lower grade gliomas, and its clinical use could dramatically improve its prognosis.

Grade II and III Oligodendroglioma and Astrocytoma

In the 2016 WHO classification of diffuse glioma, the diagnosis of an (anaplastic) oligodendroglioma requires the presence of both an IDH mutation (mt) and 1p/19q codeletion, whereas (anaplastic) astrocytoma are divided in IDH wild-type and IDHmt tumors. Standard of care for grade II and III glioma consists of resection. For patients with tumors that require postoperative treatment, radiotherapy and chemotherapy are recommended. Trials in newly diagnosed grade II and III glioma have shown survival benefit of the addition of chemotherapy to radiotherapy compared with initial treatment with radiotherapy alone; both temozolomide and PCV have been shown to improve survival.

Molecular Markers of Therapy-Resistant Glioblastoma and Potential Strategy to Combat Resistance

Glioblastoma (GBM) is the most common primary malignant tumor of the central nervous system. With its overall dismal prognosis (the median survival is 14 months), GBMs demonstrate a resounding resilience against all current treatment modalities. The absence of a major progress in the treatment of GBM maybe a result of our poor understanding of both GBM tumor biology and the mechanisms underlying the acquirement of treatment resistance in recurrent GBMs. A comprehensive understanding of these markers is mandatory for the development of treatments against therapy-resistant GBMs. This review also provides an overview of a novel marker called acid ceramidase and its implication in the development of radioresistant GBMs. Multiple signaling pathways were found altered in radioresistant GBMs. Given these global alterations of multiple signaling pathways found in radioresistant GBMs, an effective treatment for radioresistant GBMs may require a cocktail containing multiple agents targeting multiple cancer-inducing pathways in order to have a chance to make a substantial impact on improving the overall GBM survival.

Shedding Light on IDH1 Mutation in Gliomas

IDH mutation is of central importance in the diagnosis and treatment of gliomas. Fourier-transform infrared spectroscopy, in combination with a supervised machine-learning approach, can be used to detect metabolic alterations induced by IDH1 mutations in a fraction of the time of conventional techniques. Clin Cancer Res; 24(11); 2467-9. ©2018 AACRSee related article by Uckermann et al., p. 2530.

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status

INTRODUCTION

Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a glioma. The aim of this study is to devise a machine learning algorithm that may be used by radiologists in routine practice to aid diagnosis of both: WHO grade and IDH mutation status in de novo gliomas.

METHODS

To evaluate the status quo, we interrogated the accuracy of neuroradiology reports in relation to WHO grade: grade II 96.49% (95% confidence intervals [CI] 0.88, 0.99); III 36.51% (95% CI 0.24, 0.50); IV 72.9% (95% CI 0.67, 0.78). We derived five MRI parameters from the same diagnostic brain scans, in under two minutes per case, and then supplied these data to a random forest algorithm.

RESULTS

Machine learning resulted in a high level of accuracy in prediction of tumour grade: grade II/III; area under the receiver operating characteristic curve (AUC) = 98%, sensitivity = 0.82, specificity = 0.94; grade II/IV; AUC = 100%, sensitivity = 1.0, specificity = 1.0; grade III/IV; AUC = 97%, sensitivity = 0.83, specificity = 0.97. Furthermore, machine learning also facilitated the discrimination of IDH status: AUC of 88%, sensitivity = 0.81, specificity = 0.77.

CONCLUSIONS

These data demonstrate the ability of machine learning to accurately classify diffuse gliomas by both WHO grade and IDH status from routine MRI alone-without significant image processing, which may facilitate usage as a diagnostic adjunct in clinical practice.

IDH1 mutation in human glioma induces chemical alterations that are amenable to optical Raman spectroscopy

INTRODUCTION

Mutations in the isocytrate dehydrogenase 1 (IDH1) gene are early genetic events in glioma pathogenesis and cause profound metabolic changes. Because this genotype is found in virtually every tumor cell, therapies targeting mutant IDH1 protein are being developed. The intraoperative administration of those therapies would require fast technologies for the determination of IDH1 genotype. As of today, there is no such diagnostic test available. Recently, infrared spectroscopy was shown to bridge this gap. Here, we tested Raman spectroscopy for analysis of IDH1 genotype in glioma, which constitutes an alternative contact-free technique with the potential of being applicable in situ.

METHODS

Human glioma samples (n = 36) were obtained during surgery and cryosections were prepared. IDH1 mutations were assessed using DNA sequencing and 100 Raman spectra were obtained for each sample.

RESULTS

Analysis of Raman spectra revealed increased intensities in spectral bands related to DNA in IDH1 mutant glioma while bands assigned to molecular vibrations of lipids were significantly decreased. Moreover, intensities of Raman bands assigned to proteins differed in IDH1 mutant and IDH1 wild-type glioma, suggesting alterations in the protein profile. The selection of five bands (498, 826, 1003, 1174 and 1337 cm^-1) allowed the classification of Raman spectra according to IDH1 genotype with a correct rate of 89%.

CONCLUSION

Raman spectroscopy constitutes a simple, rapid and safe procedure for determination of the IDH1 mutation that shows great promise for clinically relevant in situ diagnostics.

Surgical Considerations in the Optimal Management of Patients with Malignant Brain Tumors

OPINION STATEMENT

Advances in technology are revolutionizing medicine and the limits of what we can offer to our patients. In neurosurgery, technology continues to reduce morbidity, increase surgical accuracy, facilitate tissue acquisition, and promote novel techniques for prolonging survival in patients with neuro-oncologic disease. Surgery has been the backbone of glioma diagnosis and treatment by providing adequate, high quality material for precise histologic diagnosis, and genomic characterization in the setting of significant intratumoral heterogeneity, thus allowing personalized treatment selection in the clinic. The ability to obtain and accurately measure the maximal extent of resection in glioma surgery also remains a central role of the neurosurgeon in managing this cancer. To meet these goals, today's operating room has transformed from the traditional operating table and anesthesia machine to include neuronavigation instrumentation, intraoperative computed tomography, and magnetic resonance imaging scanners, advanced surgical microscopes fitted with fluorescent light filters, and electrocorticography machines. While surgeons, oncologists, and radiation oncologists all play unique critical roles in the care of patients with malignant gliomas, familiarity with developing techniques in complimentary subspecialties can enhance coordination of patient care, research productivity, professional interactions, and patient confidence and comfort with the physician team. Herein, we provide a summary of the advances in the field of neurosurgical oncology which allow more precise and optimal surgical resection for patients with malignant gliomas.

Pharmacodynamics of mutant-IDH1 inhibitors in glioma patients probed by in vivo 3D MRS imaging of 2-hydroxyglutarate

Inhibitors of the mutant isocitrate dehydrogenase 1 (IDH1) entered recently in clinical trials for glioma treatment. Mutant IDH1 produces high levels of 2-hydroxyglurate (2HG), thought to initiate oncogenesis through epigenetic modifications of gene expression. In this study, we show the initial evidence of the pharmacodynamics of a new mutant IDH1 inhibitor in glioma patients, using non-invasive 3D MR spectroscopic imaging of 2HG. Our results from a Phase 1 clinical trial indicate a rapid decrease of 2HG levels by 70% (CI 13%, P = 0.019) after 1 week of treatment. Importantly, inhibition of mutant IDH1 may lead to the reprogramming of tumor metabolism, suggested by simultaneous changes in glutathione, glutamine, glutamate, and lactate. An inverse correlation between metabolic changes and diffusion MRI indicates an effect on the tumor-cell density. We demonstrate a feasible radiopharmacodynamics approach to support the rapid clinical translation of rationally designed drugs targeting IDH1/2 mutations for personalized and precision medicine of glioma patients.

Molecular Diagnosis of Diffuse Gliomas through Sequencing of Cell-Free Circulating Tumor DNA from Cerebrospinal Fluid

Purpose: Diffuse gliomas are the most common primary tumor of the brain and include different subtypes with diverse prognosis. The genomic characterization of diffuse gliomas facilitates their molecular diagnosis. The anatomical localization of diffuse gliomas complicates access to tumor specimens for diagnosis, in some cases incurring high-risk surgical procedures and stereotactic biopsies. Recently, cell-free circulating tumor DNA (ctDNA) has been identified in the cerebrospinal fluid (CSF) of patients with brain malignancies.Experimental Design: We performed an analysis of IDH1, IDH2, TP53, TERT, ATRX, H3F3A, and HIST1H3B gene mutations in two tumor cohorts from The Cancer Genome Atlas (TCGA) including 648 diffuse gliomas. We also performed targeted exome sequencing and droplet digital PCR (ddPCR) analysis of these seven genes in 20 clinical tumor specimens and CSF from glioma patients and performed a histopathologic characterization of the tumors.Results: Analysis of the mutational status of the IDH1, IDH2, TP53, TERT, ATRX, H3F3A, and HIST1H3B genes allowed the classification of 79% of the 648 diffuse gliomas analyzed, into IDH-wild-type glioblastoma, IDH-mutant glioblastoma/diffuse astrocytoma and oligodendroglioma, each subtype exhibiting diverse median overall survival (1.1, 6.7, and 11.2 years, respectively). We developed a sequencing platform to simultaneously and rapidly genotype these seven genes in CSF ctDNA allowing the subclassification of diffuse gliomas.Conclusions: The genomic analysis of IDH1, IDH2, TP53, ATRX, TERT, H3F3A, and HIST1H3B gene mutations in CSF ctDNA facilitates the diagnosis of diffuse gliomas in a timely manner to support the surgical and clinical management of these patients. Clin Cancer Res; 24(12); 2812-9. ©2018 AACR.

Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors

Brain tumors are the most common malignant neurologic tumors with the highest mortality and disability rate. Because of the delicate structure of the brain, the clinical use of several commonly used biopsy diagnosis is limited for brain tumors. Radiomics is an emerging technique for noninvasive diagnosis based on quantitative medical image analyses. However, current radiomics techniques are not standardized regarding feature extraction, feature selection, and decision making. In this paper, we propose a sparse representation-based radiomics (SRR) system for the diagnosis of brain tumors. First, we developed a dictionary learning- and sparse representation-based feature extraction method that exploits the statistical characteristics of the lesion area, leading to fine and more effective feature extraction compared with the traditional explicitly calculation-based methods. Then, we set up an iterative sparse representation method to solve the redundancy problem of the extracted features. Finally, we proposed a novel multi-feature collaborative sparse representation classification framework that introduces a new coefficient of regularization term to combine features from multi-modal images at the sparse representation coefficient level. Two clinical problems were used to validate the performance and usefulness of the proposed SRR system. One was the differential diagnosis between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), and the other was isocitrate dehydrogenase 1 estimation for gliomas. The SRR system had superior PCNSL and GBM differentiation performance compared with some advanced imaging techniques and yielded 11% better performance for estimating IDH1 compared with the traditional radiomics methods.

Clinical and immunological correlates of long term survival in glioblastoma

Glioblastoma (GBM) is the most common and most aggressive type of primary brain tumour in adults. It represents 54% of all gliomas and 16% of all brain tumours (Ostrom et al. 2016). Despite surgery and treatment with radiotherapy plus an oral alkylating agent, temozolomide (TMZ), tumours invariably recur, and the patient survival is an average of ~14–16 months. In this review we summarise the current understanding of multiple factors that may affect survival of patients with GBMs. In particular, we discuss recent advancements in surgery and detection of genomic-based markers with prognostic values, such as IDH1/2 mutations, MGMT gene promoter methylation, and TERT gene promoter alterations. We address the issue of tumour heterogeneity and evolution that may result in different parts of the same tumour exhibiting different GBM subtypes and in subtype switching, which may restrict the usefulness of the expression-based classification as a prognostic marker before relapse. The determinants of long-term survival in patients with IDH1/2wt GBM, beyond MGMT promoter methylation, remain to be identified, and even the absence of both IDH1/2 mutations and MGMT promoter methylation does not preclude long-term survival. These findings suggest that host-derived factors, such as immune system responsiveness may contribute to long-term survival in such patients. We report the results of high-throughput approaches, suggesting links between long-term survival and enhanced immune-related gene expression. The further search for new gene candidates, promoter methylation status, and specific features of host immunity should provide prognostic biomarkers for the evaluation of survival of IDH1 wild-type/non-G-CIMP GBMs.

Survival kinase genes present prognostic significance in glioblastoma

Cancer biomarkers with a strong predictive power for diagnosis/prognosis and a potential to be therapeutic targets have not yet been fully established. Here we employed a loss-of-function screen in glioblastoma (GBM), an infiltrative brain tumor with a dismal prognosis, and identified 20 survival kinase genes (SKGs). Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that the expression of CDCP1, CDKL5, CSNK1E, IRAK3, LATS2, PRKAA1, STK3, TBRG4, and ULK4 stratified GBM prognosis with or without temozolomide (TMZ) treatment as a covariate. For the first time, we found that GBM patients with a high level of NEK9 and PIK3CB had a greater chance of having recurrent tumors. The expression of CDCP1, IGF2R, IRAK3, LATS2, PIK3CB, ULK4, or VRK1 in primary GBM tumors was associated with recurrence-related prognosis. Notably, the level of PIK3CB in recurrent tumors was much higher than that in newly diagnosed ones. Congruent with these results, genes in the PI3K/AKT pathway showed a significantly strong correlation with recurrence rate, further highlighting the pivotal role of PIK3CB in the disease progression. Importantly, 17 SKGs together presented a novel GBM prognostic signature. SKGs identified herein are associated with recurrence rate and present prognostic significance in GBM, thereby becoming attractive therapeutic targets.

Current therapeutic approaches to diffuse grade II and III gliomas

The 2016 WHO classification of Tumors of the Central Nervous System brought major conceptual and practical changes in the classification of diffuse gliomas, by combining molecular features and histology into 'integrated' diagnoses. In diffuse gliomas, molecular profiling has thus become essential for nosological purposes, as well as to plan adequate treatment strategies and identify patients susceptible of target therapy. WHO grade II (low grade) and grade III (anaplastic) diffuse gliomas form a heterogeneous group of neoplasms, also known as 'lower-grade gliomas', characterized by a wide range of malignant potential. Molecular profile accounts for this biological diversity, and provides an accurate prognostic stratification of tumors in this group. Treatment strategies in lower-grade gliomas are ultimately based on molecular profile and WHO grade, as well as on patient characteristics such as age and Karnofsky performance status. The purpose of this review is to summarize recent advances in the classification of grade II and III gliomas, synthesize current treatment schemes according to molecular profile and describe ongoing research and future perspectives for the use of target therapies.

Interaction Between the Contributions of Tumor Location, Tumor Grade, and Patient Age to the Survival Benefit Associated with Gross Total Resection

BACKGROUND

Gross total resection (GTR) in patients with glioblastoma (GB) and anaplastic astrocytoma (AA) is associated with improved survival. We examined how tumor location, tumor grade, and age affected this benefit.

METHODS

We selected patients with lobar AA or GB in the Surveillance, Epidemiology, and End Results database from 1999 to 2010. Survival analyses were performed using Kaplan-Meier curves and Cox proportional hazards models.

RESULTS

We identified and studied 1429 patients with lobar AA and 12,537 patients with lobar GB in the Surveillance, Epidemiology, and End Results database. In multivariate Cox proportional hazards analysis, GTR of frontal lobe AA was associated with approximately 50% reduction in risk of death compared with subtotal resection (STR) (hazard ratio 0.51; 95% confidence interval, 0.36-0.73; P < 0.001). This hazard ratio corresponds to a median increase in overall survival of >8 years with GTR compared with STR. In nonfrontal AAs, there was no survival difference between GTR and STR (hazard ratio 0.79; 95% confidence interval, 0.58-1.08; P = 0.143). Location-specific survival benefit from GTR in AAs was significant in patients ≤50 years old but was not evident in patients >50 years old. In patients with GB, no location-dependent survival benefit with GTR was observed.

CONCLUSIONS

Our results demonstrate complex interaction between tumor grade, frontal lobe location, and age in their various contributions to survival benefit gained from GTR. The greatest survival benefit of GTR relative to STR was observed in patients ≤50 years old with frontal AAs.

Prediction of IDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas

BACKGROUND AND PURPOSE

WHO grade II gliomas are divided into three classes: isocitrate dehydrogenase (IDH)-wildtype, IDH-mutant and no 1p/19q codeletion, and IDH-mutant and 1p/19q-codeleted. Different molecular subtypes have been reported to have prognostic differences and different chemosensitivity. Our aim was to evaluate the predictive value of imaging phenotypes assessed with the Visually AcceSAble Rembrandt Images lexicon for molecular classification of lower grade gliomas.

MATERIALS AND METHODS

MR imaging scans of 175 patients with lower grade gliomas with known IDH1 mutation and 1p/19q-codeletion status were included (78 grade II and 97 grade III) in the discovery set. MR imaging features were reviewed by using Visually AcceSAble Rembrandt Images (VASARI); their associations with molecular markers were assessed. The predictive power of imaging features for IDH1-wild type tumors was evaluated using the Least Absolute Shrinkage and Selection Operator. We tested the model in a validation set (40 subjects).

RESULTS

Various imaging features were significantly different according to IDH1 mutation. Nonlobar location, larger proportion of enhancing tumors, multifocal/multicentric distribution, and poor definition of nonenhancing margins were independent predictors of an IDH1 wild type according to the Least Absolute Shrinkage and Selection Operator. The areas under the curve for the prediction model were 0.859 and 0.778 in the discovery and validation sets, respectively. The IDH1-mutant, 1p/19q-codeleted group frequently had mixed/restricted diffusion characteristics and showed more pial invasion compared with the IDH1-mutant, no codeletion group.

CONCLUSIONS

Preoperative MR imaging phenotypes are different according to the molecular markers of lower grade gliomas, and they may be helpful in predicting the IDH1-mutation status.

Optical Analysis of Glioma: Fourier-Transform Infrared Spectroscopy Reveals the IDH1 Mutation Status

Purpose: Somatic mutations in the human cytosolic isocitrate dehydrogenase 1 (IDH1) gene cause profound changes in cell metabolism and are a common feature of gliomas with unprecedented predictive and prognostic impact. Fourier-transform infrared (FT-IR) spectroscopy addresses the molecular composition of cells and tissue and was investigated to deduct the IDH1 mutation status.Experimental Design: We tested the technique on human cell lines that were transduced with wild-type IDH1 or mutated IDH1 and on 34 human glioma samples. IR spectra were acquired at 256 positions from cell pellets or tissue cryosections. Moreover, IR spectra were obtained from fresh, unprocessed biopsies of 64 patients with glioma.Results:IDH1 mutation was linked to changes in spectral bands assigned to molecular groups of lipids and proteins in cell lines and human glioma. The spectra of cryosections of brain tumor samples showed high interpatient variability, for example, bands related to calcifications at 1113 cm^-1 However, supervised classification recognized relevant spectral regions at 1103, 1362, 1441, 1485, and 1553 cm^-1 and assigned 88% of the tumor samples to the correct group. Similar spectral positions allowed the classification of spectra of fresh biopsies with an accuracy of 86%.Conclusions: Here, we show that vibrational spectroscopy reveals the IDH1 genotype of glioma. Because it can provide information in seconds, an implementation into the intraoperative workflow might allow simple and rapid online diagnosis of the IDH1 genotype. The intraoperative confirmation of IDH1 mutation status might guide the decision to pursue definitive neurosurgical resection and guide future in situ therapies of infiltrative gliomas. Clin Cancer Res; 24(11); 2530-8. ©2017 AACRSee related commentary by Hollon and Orringer, p. 2467.

Defining Glioblastoma Resectability Through the Wisdom of the Crowd: A Proof-of-Principle Study

BACKGROUND

Extent of resection (EOR) correlates with glioblastoma outcomes. Resectability and EOR depend on anatomical, clinical, and surgeon factors. Resectability likely influences outcome in and of itself, but an accurate measurement of resectability remains elusive. An understanding of resectability and the factors that influence it may provide a means to control a confounder in clinical trials and provide reference for decision making.

OBJECTIVE

To provide proof of concept of the use of the collective wisdom of experienced brain tumor surgeons in assessing glioblastoma resectability.

METHODS

We surveyed 13 academic tumor neurosurgeons nationwide to assess the resectability of newly diagnosed glioblastoma. Participants reviewed 20 cases, including digital imaging and communications in medicine-formatted pre- and postoperative magnetic resonance images and clinical vignettes. The selected cases involved a variety of anatomical locations and a range of EOR. Participants were asked about surgical goal, eg, gross total resection, subtotal resection (STR), or biopsy, and rationale for their decision. We calculated a "resectability index" for each lesion by pooling responses from all 13 surgeons.

RESULTS

Neurosurgeons' individual surgical goals varied significantly ( P = .015), but the resectability index calculated from the surgeons' pooled responses was strongly correlated with the percentage of contrast-enhancing residual tumor ( R = 0.817, P < .001). The collective STR goal predicted intraoperative decision of intentional STR documented on operative notes ( P < .01) and nonresectable residual ( P < .01), but not resectable residual.

CONCLUSION

In this pilot study, we demonstrate the feasibility of measuring the resectability of glioblastoma through crowdsourcing. This tool could be used to quantify resectability, a potential confounder in neuro-oncology clinical trials.

Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging

Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the IDH status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data.Experimental Design: Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming.Results: With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively.Conclusions: We developed a deep learning technique to noninvasively predict IDH genotype in grade II-IV glioma using conventional MR imaging using a multi-institutional data set. Clin Cancer Res; 24(5); 1073-81. ©2017 AACR.

MR Elastography Analysis of Glioma Stiffness and IDH1-Mutation Status

BACKGROUND AND PURPOSE

Our aim was to noninvasively evaluate gliomas with MR elastography to characterize the relationship of tumor stiffness with tumor grade and mutations in the isocitrate dehydrogenase 1 (IDH1) gene.

MATERIALS AND METHODS

Tumor stiffness properties were prospectively quantified in 18 patients (mean age, 42 years; 6 women) with histologically proved gliomas using MR elastography from 2014 to 2016. Images were acquired on a 3T MR imaging unit with a vibration frequency of 60 Hz. Tumor stiffness was compared with unaffected contralateral white matter, across tumor grade, and by IDH1-mutation status. The performance of the use of tumor stiffness to predict tumor grade and IDH1 mutation was evaluated with the Wilcoxon rank sum, 1-way ANOVA, and Tukey-Kramer tests.

RESULTS

Gliomas were softer than healthy brain parenchyma, 2.2 kPa compared with 3.3 kPa (P < .001), with grade IV tumors softer than grade II. Tumors with an IDH1 mutation were significantly stiffer than those with wild type IDH1, 2.5 kPa versus 1.6 kPa, respectively (P = .007).

CONCLUSIONS

MR elastography demonstrated that not only were gliomas softer than normal brain but the degree of softening was directly correlated with tumor grade and IDH1-mutation status. Noninvasive determination of tumor grade and IDH1 mutation may result in improved stratification of patients for different treatment options and the evaluation of novel therapeutics. This work reports on the emerging field of "mechanogenomics": the identification of genetic features such as IDH1 mutation using intrinsic biomechanical information.

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas

We hypothesized that machine learning analysis based on texture information from the preoperative MRI can predict IDH mutational status in newly diagnosed WHO grade II and III gliomas. This retrospective study included in total 79 consecutive patients with a newly diagnosed WHO grade II or III glioma. Local binary pattern texture features were generated from preoperative B0 and fractional anisotropy (FA) diffusion tensor imaging. Using a training set of 59 patients, a single hidden layer neural network was then trained on the texture features to predict IDH status. The model was validated based on the prediction accuracy calculated in a previously unseen set of 20 gliomas. Prediction accuracy of the generated model was 92% (54/59 cases; AUC = 0.921) in the training and 95% (19/20; AUC = 0.952) in the validation cohort. The ten most important features were comprised of tumor size and both B0 and FA texture information, underlining the joint contribution of imaging data to classification. Machine learning analysis of DTI texture information and tumor size reliably predicts IDH status in preoperative MRI of gliomas. Such information may increasingly support individualized surgical strategies, supplement pathological analysis and highlight the potential of radiogenomics.