Histopathological grading affects survival in patients with IDH-mutant grade II and grade III diffuse gliomas

Intraoperative rapid molecular diagnosis aids glioma subtyping and guides precise surgical resection

OBJECTIVE

The molecular era of glioma diagnosis and treatment has arrived, and a single rapid histopathology is no longer sufficient for surgery. This study sought to present an automatic integrated gene detection system (AIGS), which enables rapid intraoperative detection of IDH/TERTp mutations.

METHODS

A total of 78 patients with gliomas were included in this study. IDH/TERTp mutations were detected intraoperatively using AIGS in 41 of these patients, and they were guided to surgical resection (AIGS detection group). The remaining 37 underwent histopathology-guided conventional surgical resection (non-AIGS detection group). The clinical utility of this technique was evaluated by comparing the accuracy of glioma subtype diagnosis before and after TERTp mutation results were obtained by pathologists and the extent of resection (EOR) and patient prognosis for molecular pathology-guided glioma surgery.

RESULTS

With NGS/Sanger sequencing and chromosome detection as the gold standard, the accuracy of AIGS results was 100%. And the timing was well matched to the intraoperative rapid pathology report. After obtaining the TERTp mutation detection results, the accuracy of the glioma subtype diagnosis made by the pathologists increased by 19.51%. Molecular pathology-guided surgical resection of gliomas significantly increased EOR (99.06% vs. 93.73%, p < 0.0001) and also improved median OS (26.77 vs. 13.47 months, p = 0.0289) and median PFS (15.90 vs. 10.57 months, p = 0.0181) in patients with glioblastoma.

INTERPRETATION

Using AIGS intraoperatively to detect IDH/TERTp mutations to accurately diagnose glioma subtypes can help achieve maximum safe resection of gliomas, which in turn improves the survival prognosis of patients.

Revisiting oligodendroglioma grading in the 2021 WHO classification: calcification and larger contrast-enhancing tumor volume may predict higher oligodendroglioma grade

PURPOSE

To investigate whether qualitative and quantitative imaging phenotypes can predict the grade of oligodendroglioma.

METHODS

Retrospective chart and imaging reviews were conducted on 180 adults with oligodendroglioma (IDH-mutant and 1p/19q codeleted) between 2005 and 2021. Qualitative imaging characteristics including tumor location, calcification, gliomatosis cerebri, cystic change, necrosis, and infiltrative pattern were analyzed. Quantitative imaging assessment was performed from the tumor mask via automatic segmentation to calculate total, contrast-enhancing (CE), non-enhancing (NE), and necrotic tumor volumes. Logistic analyses were conducted to determine predictors of oligodendroglioma grade.

RESULTS

This study included 180 patients (84 [46.7%] with grade 2 and 96 [53.3%] with grade 3 oligodendrogliomas), with a median age of 42 years (range 23-76 years), comprising 91 females and 89 males. On univariable analysis, calcification (odds ratio [OR] = 6.00, P < 0.001), necrosis (OR = 21.84, P = 0.003), presence of CE tumor (OR = 7.86, P < 0.001), larger total (OR = 1.01, P < 0.001), larger CE (OR = 2.22, P = 0.010), and larger NE (OR = 1.01, P < 0.001) tumor volumes were predictors of grade 3 oligodendroglioma. On multivariable analysis, calcification (OR = 3.79, P < 0.001) and larger CE tumor volume (OR = 2.70, P = 0.043) remained as independent predictors of grade 3 oligodendroglioma. The multivariable model exhibited an AUC, accuracy, sensitivity, specificity of 0.78 (95% confidence interval 0.72-0.84), 72.8%, 79.2%, 69.1%, respectively.

CONCLUSION

Presence of calcification and larger CE tumor volume may serve as useful imaging biomarkers for prediction of oligodendroglioma grade.

CLINICAL RELEVANCE STATEMENT

Assessment of intratumoral calcification and CE tumor volume may facilitate accurate preoperative estimation of oligodendroglioma grade. Presence of intratumoral calcification and larger contrast-enhancing tumor volume were the significant predictors of higher grade oligodendroglioma based on the 2021 WHO classification.

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

BACKGROUND

The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor.

PURPOSE

To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index.

MATERIAL AND METHODS

The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index.

RESULTS

The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade.

CONCLUSION

Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

Subclonal Cancer Driver Mutations Are Prevalent in the Unresected Peritumoral Edema of Adult Diffuse Gliomas

Adult diffuse gliomas commonly recur regardless of therapy. As recurrence typically arises from the peritumoral edema adjacent to the resected bulk tumor, the profiling of somatic mutations from infiltrative malignant cells within this critical, unresected region could provide important insights into residual disease. A key obstacle has been the inability to distinguish between next-generation sequencing (NGS) noise and the true but weak signal from tumor cells hidden among the noncancerous brain tissue of the peritumoral edema. Here, we developed and validated True2 sequencing to reduce NGS-associated errors to <1 false positive/100 kb panel positions while detecting 97.6% of somatic mutations with an allele frequency ≥0.1%. True2 was then used to study the tumor and peritumoral edema of 22 adult diffuse gliomas including glioblastoma, astrocytoma, oligodendroglioma, and NF1-related low-grade neuroglioma. The tumor and peritumoral edema displayed a similar mutation burden, indicating that surgery debulks these cancers physically but not molecularly. Moreover, variants in the peritumoral edema included unique cancer driver mutations absent in the bulk tumor. Finally, analysis of multiple samples from each patient revealed multiple subclones with unique mutations in the same gene in 17 of 22 patients, supporting the occurrence of convergent evolution in response to patient-specific selective pressures in the tumor microenvironment that may form the molecular foundation of recurrent disease. Collectively, True2 enables the detection of ultralow frequency mutations during molecular analyses of adult diffuse gliomas, which is necessary to understand cancer evolution, recurrence, and individual response to therapy.

SIGNIFICANCE

True2 is a next-generation sequencing workflow that facilitates unbiased discovery of somatic mutations across the full range of variant allele frequencies, which could help identify residual disease vulnerabilities for targeted adjuvant therapies.

Oligodendroglioma, IDH-mutant and 1p/19q-codeleted-prognostic factors, standard of care and chemotherapy, and future perspectives with neoadjuvant strategy

Oligodendroglioma, IDH-mutant and 1p/19q-codeleted is known for their relative chemosensitivity and indolent clinical course among diffuse gliomas of adult type. Based on the data from phase 3 clinical trials, the standard of post-surgical care for those tumors is considered to be initial chemoradiotherapy regardless of histopathological grade, particularly with PCV. However, partly due to its renewed definition in late years, prognostic factors in patients with those tumors are not well established. Moreover, the survival rate declines over 15 years, with only a 37% OS rate at 20 years for grade 3 tumors, even with the current standard of care. Given that most of this disease occurs in young or middle-aged adults, further improvements in treatment and management are necessary. Here, we discuss prognostic factors, standard of care and chemotherapy, and future perspectives with neoadjuvant strategy in those tumors.

Comparison of MRI Sequences to Predict IDH Mutation Status in Gliomas Using Radiomics-Based Machine Learning

OBJECTIVES

Regarding the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the isocitrate dehydrogenase (IDH) mutation status is one of the most important factors for CNS tumor classification. The aim of our study is to analyze which of the commonly used magnetic resonance imaging (MRI) sequences is best suited to obtain this information non-invasively using radiomics-based machine learning models. We developed machine learning models based on different MRI sequences and determined which of the MRI sequences analyzed yields the highest discriminatory power in predicting the IDH mutation status.

MATERIAL AND METHODS

In our retrospective IRB-approved study, we used the MRI images of 106 patients with histologically confirmed gliomas. The MRI images were acquired using the T1 sequence with and without administration of a contrast agent, the T2 sequence, and the Fluid-Attenuated Inversion Recovery (FLAIR) sequence. To objectively compare performance in predicting the IDH mutation status as a function of the MRI sequence used, we included only patients in our study cohort for whom MRI images of all four sequences were available. Seventy-one of the patients had an IDH mutation, and the remaining 35 patients did not have an IDH mutation (IDH wild-type). For each of the four MRI sequences used, 107 radiomic features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects associated with the data partitioning. Feature preselection and subsequent model development were performed using Random Forest, Lasso regression, LDA, and Naïve Bayes. The performance of all models was determined with independent test data.

RESULTS

Among the different approaches we examined, the T1-weighted contrast-enhanced sequence was found to be the most suitable for predicting IDH mutations status using radiomics-based machine learning models. Using contrast-enhanced T1-weighted MRI images, our seven-feature model developed with Lasso regression achieved a mean area under the curve (AUC) of 0.846, a mean accuracy of 0.792, a mean sensitivity of 0.847, and a mean specificity of 0.681. The administration of contrast agents resulted in a significant increase in the achieved discriminatory power.

CONCLUSIONS

Our analyses show that for the prediction of the IDH mutation status using radiomics-based machine learning models, among the MRI images acquired with the commonly used MRI sequences, the contrast-enhanced T1-weighted images are the most suitable.

The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma

PURPOSE

Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA.

METHODS

A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

RESULTS

Among 55 glioblastoma cases, gene fusions were detected in 11 cases (20%), including novel MET fusions. Seven tyrosine kinase genes were found to be overexpressed in 15 cases (27.3%). In contrast to isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH-mutant tumors, including astrocytomas and oligodendrogliomas, barely harbor fusion genes or gene overexpression. Of the 34 overexpressed tyrosine kinase genes, MDM2 and CDK4 in glioblastoma, 22 copy number amplifications (64.7%) were observed. When comparing astrocytomas and oligodendrogliomas in gene set enrichment analysis, the gene sets related to 1p36 and 19q were highly enriched in astrocytomas, suggesting that regional genomic DNA copy number alterations can be evaluated by gene expression analysis.

CONCLUSIONS

TOP2-RNA is a highly sensitive assay for detecting fusion genes, exon skipping, and aberrant gene expression. Alterations in targetable driver genes were identified in more than 50% of glioblastoma. Molecular profiling by TOP2-RNA provides ample predictive, prognostic, and diagnostic biomarkers that may not be identified by conventional assays and, therefore, is expected to increase treatment options for individual patients with glioma.

Verbal fluency predicts work resumption after awake surgery in low-grade glioma patients

BACKGROUND

Resuming professional activity after awake surgery for diffuse low-grade glioma (DLGG) is an important goal, which is not reached in every patient. Cognitive deficits can occur and persist after surgery. In this study, we analyzed the impact of mild cognitive impairments on the work resumption.

METHODS

Fifty-four surgeries (including five redo surgeries) performed between 2012 and 2020 for grade 2 (45) and 3 (nine) DLGG in 49 professionally active patients (mean age 40 [range 23-58.) were included. We retrospectively extracted the results of semantic and phonemic verbal fluency tests from preoperative and 4-month postoperative cognitive assessments. Patients were interviewed about their working life after surgery, between April and June 2021.

RESULTS

Patients (85%) returned to work, most within 3 to 6 months. Patients (76%) reported subjective complaints (primarily fatigue). Self-reported symptoms and individual and clinical variables had no impact on the work resumption. Late-postoperative average Z-scores in verbal fluency tasks were significantly lower than preoperative for the entire cohort (Wilcoxon test, p < 0.001 for semantic and p = 0.008 for phonemic fluency). The decrease in Z-scores was significantly greater (Mann Whitney U-test, semantic, p = 0.018; phonemic, p = 0.004) in the group of patients who did not return to work than in the group of patients who did.

CONCLUSION

The proportion of patients returning to work was comparable to similar studies. A decrease in verbal fluency tasks could predict the inability to return to work.

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning

Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a combination of molecular markers that could be used to identify patients who may have a greater need for adjuvant radiation therapy machine learning technology. 507 WHO Grade 2 and 3 glioma cases from The Cancer Genome Atlas, and 1309 cases from AACR GENIE v13.0 datasets were studied for genetic disparities between IDH1-wildtype and IDH1-mutant cohorts, and between different age groups. Genetic features such as mutations and copy number variations (CNVs) correlated with IDH1 mutation status were selected as potential inputs to train artificial neural networks (ANNs) to predict IDH1 mutation status. Grade 2 and 3 glioma cases from the Memorial Sloan Kettering dataset (n = 404) and Grade 3 glioma cases with subtotal resection (STR) from Northwestern University (NU) (n = 21) were used to further evaluate the best performing ANN model as independent datasets. IDH1 mutation is associated with decreased CNVs of EGFR (21% vs. 3%), CDKN2A (20% vs. 6%), PTEN (14% vs. 1.7%), and increased percentage of mutations for TP53 (15% vs. 63%), and ATRX (10% vs. 54%), which were all statistically significant (p < 0.001). Age > 40 was unable to identify high-risk IDH1-mutant with early progression. A glioma early progression risk prediction (GlioPredictor) score generated from the best performing ANN model (6/6/6/6/2/1) with 6 inputs, including CNVs of EGFR, PTEN and CDKN2A, mutation status of TP53 and ATRX, patient's age can predict IDH1 mutation status with over 90% accuracy. The GlioPredictor score identified a subgroup of high-risk IDH1-mutant in TCGA and NU datasets with early disease progression (p = 0.0019, 0.0238, respectively). The GlioPredictor that integrates age at diagnosis, CNVs of EGFR, CDKN2A, PTEN and mutation status of TP53, and ATRX can identify a small cohort of IDH-mutant with high risk of early progression. The current version of GlioPredictor mainly incorporated clinically often tested genetic biomarkers. Considering complexity of clinical and genetic features that correlate with glioma progression, future derivatives of GlioPredictor incorporating more inputs can be a potential supplement for adjuvant radiotherapy patient selection of IDH-mutant glioma patients.

Improved prognostic stratification of patients with isocitrate dehydrogenase-mutant astrocytoma

Prognostic factors and standards of care for astrocytoma, isocitrate dehydrogenase (IDH)-mutant, CNS WHO grade 4, remain poorly defined. Here we sought to explore disease characteristics, prognostic markers, and outcome in patients with this newly defined tumor type. We determined molecular biomarkers and assembled clinical and outcome data in patients with IDH-mutant astrocytomas confirmed by central pathology review. Patients were identified in the German Glioma Network cohort study; additional cohorts of patients with CNS WHO grade 4 tumors were identified retrospectively at two sites. In total, 258 patients with IDH-mutant astrocytomas (114 CNS WHO grade 2, 73 CNS WHO grade 3, 71 CNS WHO grade 4) were studied. The median age at diagnosis was similar for all grades. Karnofsky performance status at diagnosis inversely correlated with CNS WHO grade (p < 0.001). Despite more intensive treatment upfront with higher grade, CNS WHO grade was strongly prognostic: median overall survival was not reached for grade 2 (median follow-up 10.4 years), 8.1 years (95% CI 5.4-10.8) for grade 3, and 4.7 years (95% CI 3.4-6.0) for grade 4. Among patients with CNS WHO grade 4 astrocytoma, median overall survival was 5.5 years (95% CI 4.3-6.7) without (n = 58) versus 1.8 years (95% CI 0-4.1) with (n = 12) homozygous CDKN2A deletion. Lower levels of global DNA methylation as detected by LINE-1 methylation analysis were strongly associated with CNS WHO grade 4 (p < 0.001) and poor outcome. MGMT promoter methylation status was not prognostic for overall survival. Histomolecular stratification based on CNS WHO grade, LINE-1 methylation level, and CDKN2A status revealed four subgroups of patients with significantly different outcomes. In conclusion, CNS WHO grade, global DNA methylation status, and CDKN2A homozygous deletion are prognostic in patients with IDH-mutant astrocytoma. Combination of these parameters allows for improved prediction of outcome. These data aid in designing upcoming trials using IDH inhibitors.

Integrated clustering signature of genomic heterogeneity, stemness and tumor microenvironment predicts glioma prognosis and immunotherapy response

BACKGROUND

Glioma is the most frequent primary tumor of the central nervous system. The high heterogeneity of glioma tumors enables them to adapt to challenging environments, leading to resistance to treatment. Therefore, to detect the driving factors and improve the prognosis of glioma, it is essential to have a comprehensive understanding of the genomic heterogeneity, stemness, and immune microenvironment of glioma.

METHODS

We classified gliomas into various subtypes based on stemness, genomic heterogeneity, and immune microenvironment consensus clustering analysis. We identified risk hub genes linked to heterogeneous characteristics using WGCNA, LASSO, and multivariate Cox regression analysis and utilized them to create an effective risk model.

RESULTS

We thoroughly investigated the genomic heterogeneity, stemness, and immune microenvironment of glioma and identified the risk hub genes RAB42, SH2D4A, and GDF15 based on the TCGA dataset. We developed a risk model utilizing these genes that can reliably predict the prognosis of glioma patients. The risk signature showed a positive correlation with T cell exhaustion and increased infiltration of immunosuppressive cells, and a negative correlation with the response to immunotherapy. Moreover, we discovered that SH2D4A, one of the risk hub genes, could stimulate the migration and proliferation of glioma cells.

CONCLUSIONS

This study identified risk hub genes and established a risk model by analyzing the genomic heterogeneity, stemness, and immune microenvironment of glioma. Our findings will facilitate the diagnosis and prediction of glioma prognosis and may lead to potential treatment strategies for glioma.

A threshold for mitotic activity and post-surgical residual volume defines distinct prognostic groups for astrocytoma IDH-mutant

AIMS

The distinction between CNS WHO grade 2 and grade 3 is instrumental in choosing between observational follow-up and adjuvant treatment for resected astrocytomas IDH-mutant. However, the criteria of CNS WHO grade 2 vs 3 have not been updated since the pre-IDH era.

METHODS

Maximal mitotic activity in consecutive high-power fields corresponding to 3 mm2 was examined for 118 lower-grade astrocytomas IDH-mutant. The prognostic value for time-to-treatment (TTT) and overall survival (OS) of mitotic activity and other putative prognostic factors (including age, performance status, pre-surgical tumour volume, multilobar involvement, post-surgical residual tumour volume and midline involvement) was assessed for tumours with ATRX loss and the absence of CDKN2A homozygous deletion or CDK4 amplification, contrast enhancement, histological necrosis and microvascular proliferation.

RESULTS

Seventy-one per cent of the samples had <6 mitoses per 3 mm2 . Mitotic activity, residual volume and multilobar involvement were independent prognostic factors of TTT. The threshold of ≥6 mitoses per 3 mm2 identified patients with a shorter TTT (median 18.5 months). A residual volume ≥1 cm3 also identified patients with a shorter TTT (median 24.5 months). The group defined by <6 mitoses per 3 mm2 and a residual volume <1 cm3 had the longest TTT (median 73 months) and OS (100% survival at 7 years). These findings were confirmed in a validation cohort of 52 tumours.

CONCLUSIONS

Mitotic activity and post-surgical residual volume can be combined to evaluate the prognosis for patients with resected astrocytomas IDH-mutant. Patients with <6 mitoses per 3 mm2 and a residual volume <1 cm3 were the best candidates for observational follow-up.

Investigating survival, quality of life and cognition in PROton versus photon therapy for IDH-mutated diffuse grade 2 and 3 GLIOmas (PRO-GLIO): a randomised controlled trial in Norway and Sweden

INTRODUCTION

The use of proton therapy increases globally despite a lack of randomised controlled trials demonstrating its efficacy and safety. Proton therapy enables sparing of non-neoplastic tissue from radiation. This is principally beneficial and holds promise of reduced long-term side effects. However, the sparing of seemingly non-cancerous tissue is not necessarily positive for isocitrate dehydrogenase (IDH)-mutated diffuse gliomas grade 2-3, which have a diffuse growth pattern. With their relatively good prognosis, yet incurable nature, therapy needs to be delicately balanced to achieve a maximal survival benefit combined with an optimised quality of life.

METHODS AND ANALYSIS

PRO-GLIO (PROton versus photon therapy in IDH-mutated diffuse grade 2 and 3 GLIOmas) is an open-label, multicentre, randomised phase III non-inferiority study. 224 patients aged 18-65 years with IDH-mutated diffuse gliomas grade 2-3 from Norway and Sweden will be randomised 1:1 to radiotherapy delivered with protons (experimental arm) or photons (standard arm). First intervention-free survival at 2 years is the primary endpoint. Key secondary endpoints are fatigue and cognitive impairment, both at 2 years. Additional secondary outcomes include several survival measures, health-related quality of life parameters and health economy endpoints.

ETHICS AND DISSEMINATION

To implement proton therapy as part of standard of care for patients with IDH-mutated diffuse gliomas grade 2-3, it should be deemed safe. With its randomised controlled design testing proton versus photon therapy, PRO-GLIO will provide important information for this patient population concerning safety, cognition, fatigue and other quality of life parameters. As proton therapy is considerably more costly than its photon counterpart, cost-effectiveness will also be evaluated. PRO-GLIO is approved by ethical committees in Norway (Regional Committee for Medical & Health Research Ethics) and Sweden (The Swedish Ethical Review Authority) and patient inclusion has commenced. Trial results will be published in international peer-reviewed journals, relevant conferences, national and international meetings and expert forums.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT05190172).

Updates on the WHO diagnosis of IDH-mutant glioma

PURPOSE

The WHO classification of Tumors of the Central Nervous System represents the international standard classification for brain tumors. In 2021 the 5th edition (WHO CNS5) was published, and this review summarizes the changes regarding IDH-mutant gliomas and discusses unsolved issues and future perspectives.

METHODS

This review is based on the 5th edition of the WHO Blue Book of CNS tumors (WHO CNS5) and relevant related papers.

RESULTS

Major changes include taxonomy and nomenclature of IDH-mutant gliomas. Essential and desirable criteria for classification were established considering technical developments. For the first time molecular features are not only relevant for the classification of IDH-mutant gliomas but may impact grading as well.

CONCLUSION

WHO CNS5 classification moves forward towards a classification which is founded on tumor biology and serves clinical needs. The rapidly increasing knowledge on the molecular landscape of IDH-mutant gliomas is expected to further refine classification and grading in the future.

MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma

PURPOSE

Nearly all literature for predicting tumor grade in astrocytoma and oligodendroglioma pre-dates the molecular classification system. We investigated the association between contrast enhancement, ADC, and rCBV with tumor grade separately for IDH-mutant astrocytomas and molecularly-defined oligodendrogliomas.

METHODS

For this retrospective study, 44 patients with IDH-mutant astrocytomas (WHO grades II, III, or IV) and 39 patients with oligodendrogliomas (IDH-mutant and 1p/19q codeleted) (WHO grade II or III) were enrolled. Two readers independently assessed preoperative MRI for contrast enhancement, ADC, and rCBV. Inter-reader agreement was calculated, and statistical associations between MRI metrics and WHO grade were determined per reader.

RESULTS

For IDH-mutant astrocytomas, both readers found a stepwise positive association between contrast enhancement and WHO grade (Reader A: OR 7.79 [1.97, 30.80], p = 0.003; Reader B: OR 6.62 [1.70, 25.82], p = 0.006); both readers found that ADC was negatively associated with WHO grade (Reader A: OR 0.74 [0.61, 0.90], p = 0.002); Reader B: OR 0.80 [0.66, 0.96], p = 0.017), and both readers found that rCBV was positively associated with WHO grade (Reader A: OR 2.33 [1.35, 4.00], p = 0.002; Reader B: OR 2.13 [1.30, 3.57], p = 0.003). For oligodendrogliomas, both readers found a positive association between contrast enhancement and WHO grade (Reader A: OR 15.33 [2.56, 91.95], p = 0.003; Reader B: OR 20.00 [2.19, 182.45], p = 0.008), but neither reader found an association between ADC or rCBV and WHO grade.

CONCLUSIONS

Contrast enhancement predicts WHO grade for IDH-mutant astrocytomas and oligodendrogliomas. ADC and rCBV predict WHO grade for IDH-mutant astrocytomas, but not for oligodendrogliomas.

Proton radiotherapy in the treatment of IDH-mutant diffuse gliomas: an early experience from shanghai proton and heavy ion center

PURPOSE

According to the presence or absence of isocitrate dehydrogenase (IDH) mutation, the 2021 WHO classification system bisected diffuse gliomas into IDH-mutant tumors and IDH-wildtype tumors. This study was aimed to evaluate the outcomes of proton radiotherapy treating IDH-mutant diffuse gliomas.

PATIENTS AND METHODS

Between May 2015 and May 2022, a total of 52 consecutive patients with IDH-mutant diffuse gliomas were treated at Shanghai Proton and Heavy Ion Center. Tumor histologies were 33 cases of astrocytoma and 19 cases of oligodendroglioma. Tumor classified by WHO grade 2, 3 and 4 were 22, 25, and 5 cases, respectively. All 22 patients with WHO grade 2 tumors and one patient with brain stem WHO grade 4 tumor were irradiated with 54GyE. The other 29 patients with WHO grade 3 and 4 tumors were irradiated with 60GyE. Temozolomide was recommended to all patients, and was eventually conducted in 50 patients.

RESULTS

The median follow-up time was 21.7 months. The 12/24-month progression-free survival (PFS) and overall survival (OS) rates for the entire cohort were 97.6%/78.4% and 100%/91.0% group. Examined by both univariate and multivariate analysis, WHO grade of tumor were of the most significant impact for both PFS and OS. No severe acute toxicity (grade 3 or above) was found. In terms of late toxicity, grade 3 radio-necrosis was developed in one case of oligodendroglioma, WHO grade 3.

CONCLUSION

Proton radiotherapy produced a favorable outcome with acceptable adverse-effects in patients with IDH-mutant diffuse gliomas.

Machine learning in neuro-oncology: toward novel development fields

PURPOSE

Artificial Intelligence (AI) involves several and different techniques able to elaborate a large amount of data responding to a specific planned outcome. There are several possible applications of this technology in neuro-oncology.

METHODS

We reviewed, according to PRISMA guidelines, available studies adopting AI in different fields of neuro-oncology including neuro-radiology, pathology, surgery, radiation therapy, and systemic treatments.

RESULTS

Neuro-radiology presented the major number of studies assessing AI. However, this technology is being successfully tested also in other operative settings including surgery and radiation therapy. In this context, AI shows to significantly reduce resources and costs maintaining an elevated qualitative standard. Pathological diagnosis and development of novel systemic treatments are other two fields in which AI showed promising preliminary data.

CONCLUSION

It is likely that AI will be quickly included in some aspects of daily clinical practice. Possible applications of these techniques are impressive and cover all aspects of neuro-oncology.

Two Novel Nomograms Predicting the Risk and Prognosis of Pancreatic Cancer Patients With Lung Metastases: A Population-Based Study

Background

Pancreatic cancer (PC) is one of the most common malignant types of cancer, with the lung being the frequent distant metastatic site. Currently, no population-based studies have been done on the risk and prognosis of pancreatic cancer with lung metastases (PCLM). As a result, we intend to create two novel nomograms to predict the risk and prognosis of PCLM.

Methods

PC patients were selected from the Surveillance, Epidemiology, and End Results Program (SEER) database from 2010 to 2016. A multivariable logistic regression analysis was used to identify risk factors for PCLM at the time of diagnosis. The multivariate Cox regression analysis was carried out to assess PCLM patient's prognostic factors for overall survival (OS). Following that, we used area under curve (AUC), time-dependent receiver operating characteristics (ROC) curves, calibration plots, consistency index (C-index), time-dependent C-index, and decision curve analysis (DCA) to evaluate the effectiveness and accuracy of the two nomograms. Finally, we compared differences in survival outcomes using Kaplan-Meier curves.

Results

A total of 803 (4.22%) out of 19,067 pathologically diagnosed PC patients with complete baseline information screened from SEER database had pulmonary metastasis at diagnosis. A multivariable logistic regression analysis revealed that age, histological subtype, primary site, N staging, surgery, radiotherapy, tumor size, bone metastasis, brain metastasis, and liver metastasis were risk factors for the occurrence of PCLM. According to multivariate Cox regression analysis, age, grade, tumor size, histological subtype, surgery, chemotherapy, liver metastasis, and bone metastasis were independent prognostic factors for PCLM patients' OS. Nomograms were constructed based on these factors to predict 6-, 12-, and 18-months OS of patients with PCLM. AUC, C-index, calibration curves, and DCA revealed that the two novel nomograms had good predictive power.

Conclusion

We developed two reliable predictive models for clinical practice to assist clinicians in developing individualized treatment plans for patients.

Challenges of imaging interpretation to predict oligodendroglioma grade: a report from the Neuro-Oncology Branch

Background: To illustrate challenges of imaging interpretation in patients with oligodendroglioma seen at a referral center and evaluate interrater reliability. Methods: Two neuro-oncologists reviewed diagnostic preradiation MRIs of oligodendroglioma patients; interrater reliability was calculated with the kappa coefficient (k). A neuroradiologist measured presurgical apparent diffusion coefficient (ADC), if available. Results: Extensive enhancement was noted in four of 58 patients, k = 0.7; necrosis in seven of 58, k = 0.61; calcification in seven of 17, k = 1.0; diffusion restriction in two of 39 patients, k = 1.0 (all only in grade 3). ADC values with receiver operator characteristic analysis for area under the curve were 0.473, not significantly different from the null hypothesis (p = 0.14). Conclusions: Extensive enhancement, necrosis and calcification correlated with grade 3 oligodendroglioma in our sample. However, interrater variability is an important limitation when assessing radiographic features, supporting the need for standardization of imaging protocols and their interpretation.

WHO Grade Loses Its Prognostic Value in Molecularly Defined Diffuse Lower-Grade Gliomas

BACKGROUND

While molecular insights to diffuse lower-grade glioma (dLGG) have improved the basis for prognostication, most established clinical prognostic factors come from the pre-molecular era. For instance, WHO grade as a predictor for survival in dLGG with isocitrate dehydrogenase (IDH) mutation has recently been questioned. We studied the prognostic role of WHO grade in molecularly defined subgroups and evaluated earlier used prognostic factors in the current molecular setting.

MATERIAL AND METHODS

A total of 253 adults with morphological dLGG, consecutively included between 2007 and 2018, were assessed. IDH mutations, codeletion of chromosomal arms 1p/19q, and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletions were analyzed.

RESULTS

There was no survival benefit for patients with WHO grade 2 over grade 3 IDH-mut dLGG after exclusion of tumors with known CDKN2A/B homozygous deletion (n=157) (log-rank p=0.97). This was true also after stratification for oncological postoperative treatment and when astrocytomas and oligodendrogliomas were analyzed separately. In IDH-mut astrocytomas, residual tumor volume after surgery was an independent prognostic factor for survival (HR 1.02; 95% CI 1.01-1.03; p=0.003), but not in oligodendrogliomas (HR 1.02; 95% CI 1.00-1.03; p=0.15). Preoperative tumor size was an independent predictor in both astrocytomas (HR 1.03; 95% CI 1.00-1.05; p=0.02) and oligodendrogliomas (HR 1.05; 95% CI 1.01-1.09; p=0.01). Age was not a significant prognostic factor in multivariable analyses (astrocytomas p=0.64, oligodendrogliomas p=0.08).

CONCLUSION

Our findings suggest that WHO grade is not a robust prognostic factor in molecularly well-defined dLGG. Preoperative tumor size remained a prognostic factor in both IDH-mut astrocytomas and oligodendrogliomas in our cohort, whereas residual tumor volume predicted prognosis in IDH-mut astrocytomas only. The age cutoffs for determining high risk in patients with IDH-mut dLGG from the pre-molecular era are not supported by our results.

Isocitrate Dehydrogenase Mutant Grade II and III Glial Neoplasms

Mutations in isocitrate dehydrogenase (IDH) 1 or IDH2 occur in most of the adult low-grade gliomas and, less commonly, in cholangiocarcinoma, chondrosarcoma, acute myeloid leukemia, and other human malignancies. Cancer-associated mutations alter the function of the enzyme, resulting in production of R(-)-2-hydroxyglutarate and broad epigenetic dysregulation. Small molecule IDH inhibitors have received regulatory approval for the treatment of IDH mutant (mIDH) leukemia and are under development for the treatment of mIDH solid tumors. This article provides a current view of mIDH adult astrocytic and oligodendroglial tumors, including their clinical presentation and treatment, and discusses novel approaches and challenges toward improving the treatment of these tumors.

Molecular Features of Glioma Determined and Validated Using Combined TCGA and GTEx Data Analyses

Gliomas are among the most common intracranial tumors which originated from neuroepithelial cells. Increasing evidence has revealed that long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA module regulation and tumor-infiltrating immune cells play important regulatory roles in the occurrence and progression of gliomas. However, the precise underlying molecular mechanisms remain largely unknown. Data on gliomas in The Cancer Genome Atlas lack normal control samples; to overcome this limitation, we combined 665 The Cancer Genome Atlas glioma RNA sequence datasets with 188 Genotype-Tissue Expression normal brain RNA sequences to construct an expression matrix profile after normalization. We systematically analyzed the expression of mRNAs, lncRNAs, and miRNAs between gliomas and normal brain tissues. Kaplan–Meier survival analyses were conducted to screen differentially expressed mRNAs, lncRNAs, and miRNAs. A prognostic miRNA-related competitive endogenous RNA network was constructed, and the core subnetworks were filtered using 6 miRNAs, 3 lncRNAs, and 11 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to investigate the biological functions of significantly dysregulated mRNAs. Co-expression network analysis was performed to analyze and screen the core genes. Furthermore, single-sample Gene Set Enrichment Analysis and immune checkpoint gene expression analysis were performed, as co-expression analysis indicated immune gene dysregulation in glioma. Finally, the expression of representative dysregulated genes was validated in U87 cells at the transcriptional level, establishing a foundation for further research. We identified 7017 mRNAs, 437 lncRNAs, and 9 miRNAs that were differentially expressed in gliomas. Kaplan–Meier survival analysis revealed 5684 mRNAs, 61 lncRNAs, and 7 miRNAs with potential as prognostic signatures in patients with glioma. The hub subnetwork of the competing endogenous RNA network between PART1-hsa-mir-25-SLC12A5/TACC2/BSN/TLN2/ZDHHC8 was screened out. Gene co-expression network, single-sample Gene Set Enrichment Analysis, and immune checkpoint expression analysis demonstrated that tumor-infiltrating immune cells are closely related to gliomas. We identified novel potential biomarkers to predict survival and therapeutic targets for patients with gliomas based on a large-scale sample. Importantly, we filtered pivotal genes that provide valuable information for further exploration of the molecular mechanisms underlying glioma tumorigenesis and progression.

CKS2 (CDC28 protein kinase regulatory subunit 2) is a prognostic biomarker in lower grade glioma: a study based on bioinformatic analysis and immunohistochemistry

Gliomas account for the highest cases of primary brain malignancies. Whereas previous studies have demonstrated the roles of CDC28 Protein Kinase Regulatory Subunit 2 (CKS2) in various cancer types, its functions in lower grade gliomas (LGGs) remain elusive. This study aimed to profile the expression and functions of CKS2 in LGG. Multiple online databases such as The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), Gene Expression Profiling Interactive Analysis 2nd edition (GEPIA2), Tumor Immune Estimation Resource 2nd edition (TIMER2.0) as well as Gene Expression Omnibus (GEO) were used in this study. Immunohistochemistry (IHC) was performed to evaluate CKS2 protein expression. Our data demonstrated upregulation of CKS2 in LGG tissues at both mRNA and protein level, especially in grade III gliomas. Similarly, there was increased expression of CKS2 in isocitrate dehydrogenase 1 (IDH1) wildtype gliomas. In addition, increased DNA copy number and DNA hypomethylation might be associated with the upregulation of the CKS2 in LGG. Using the Kaplan–Meier survival analysis and the Cox regression analysis, CKS2 was shown to be independently associated with poor prognosis of LGG patients. Receiver operating characteristic (ROC) analysis revealed that CKS2 could effectively predict the 1-, 3- and 5-year survival rates of LGG patients. Enrichment analyses revealed that CKS2 was mainly involved in the regulation of the cell cycle in LGG. Taken together, our study demonstrated that CKS2 might be a candidate prognostic biomarker for LGG and could predict the survival rates of LGG patients.

Abbreviations: LGG: lower grade glioma; CKS2: CDC28 protein kinase regulatory subunit 2; TCGA: The Cancer Genome Atlas; CGGA: the Chinese Glioma Genome Atlas; GEO: Gene Expression Omnibus; GEPIA: Gene Expression Profiling Interactive Analysis; TIMER: Tumor Immune Estimation Resource; IHC: immunohistochemistry; qRT-PCR: quantitative real-time polymerase chain reaction; PBS: phosphate buffered saline; DAB: diaminobenzidine tetrachloride; OS: overall survival; CAN: copy number alteration; IDH: Isocitrate dehydrogenase; GSEA: Gene Set Enrichment Analysis; DEG: differentially expressed gene; KEGG: Kyoto encyclopedia of genes and genomes; GO: Gene ontology; BP: biological process; CC: cellular component; MF: molecular function; NES: normalized enrichment score; NOM: nominal; FDR: false discovery rate

IDH1105GGT single nucleotide polymorphism improves progression free survival in patients with IDH mutated grade II and III gliomas

BACKGROUND

A synonymous single nucleotide polymorphism (SNP) is a substitution of a single base that does not modify the primary amino acid sequence but could influence protein function. In patients with brain tumors, the incidence of the silent SNP IDH 1 105GGT (rs11554137) is three times higher than the normal population.

METHODS

Our aim was to investigate the prognostic role of the IDH 1 105GGT SNP. We selected only patients with diagnosis of IDH grade II or III mutated glioma. Additional inclusion criteria were: complete clinical data and adequate tumor samples for IDH 1 or 2 sequencing.

RESULTS

71 patients with grade II and III IDH-mutated glioma have been evaluated. Nine of 71 patients (12.7 %) presented the SNP ^105GGT. Patients with SNP ^105GGT had a longer Progression Free Survival (PFS - 47.3 months vs Not reached; p = 0.015). The SNP ^105GGT (HR 0.240; 95 %CI 0.074-0.784, p = 0.018) was confirmed as an independent prognostic factors in multivariate analysis.

CONCLUSIONS

Patients with IDH1 or 2 mutated grade II and III glioma presenting the SNP^105GGT had longer PFS regardless adjuvant treatment received and extension of primary surgery. A validation is warranted to confirm our preliminary results.

Diffuse Glioma Heterogeneity and Its Therapeutic Implications

Diffuse gliomas represent a heterogeneous group of universally lethal brain tumors characterized by minimally effective genotype-targeted therapies. Recent advances have revealed that a remarkable level of genetic, epigenetic, and environmental heterogeneity exists within each individual glioma. Together, these interconnected layers of intratumoral heterogeneity result in extreme phenotypic heterogeneity at the cellular level, providing for multiple mechanisms of therapeutic resistance and forming a highly adaptable and resilient disease. In this review, we discuss how glioma intratumoral heterogeneity and malignant cellular state plasticity drive resistance to existing therapies and look to a future in which these challenges may be overcome. SIGNIFICANCE: Glioma intratumoral heterogeneity and malignant cell state plasticity represent formidable hurdles to the development of novel targeted therapies. However, the convergence of genotypically diverse glioma cells into a limited set of epigenetically encoded transcriptional cell states may present an opportunity for a novel therapeutic strategy we call "State Selective Lethality." In this approach, cellular states (as opposed to genetic perturbations/mutations) are the subject of therapeutic targeting, and plasticity-mediated resistance is minimized through the design of cell state "trapping agents."

IDH1 Non-Canonical Mutations and Survival in Patients with Glioma

BACKGROUND

Non-canonical mutations of the isocitrate dehydrogenase (IDH) genes have been described in about 20-25% and 5-12% of patients with WHO grade II and III gliomas, respectively. To date, the prognostic value of these rare mutations is still a topic of debate.

METHODS

We selected patients with WHO grade II and III gliomas and IDH1 mutations with available tissue samples for next-generation sequencing. The clinical outcomes and baseline behaviors of patients with canonical IDH1 R132H and non-canonical IDH1 mutations were compared.

RESULTS

We evaluated 433 patients harboring IDH1 mutations. Three hundred and ninety patients (90.1%) had a canonical IDH1 R132H mutation while 43 patients (9.9%) had a non-canonical IDH1 mutation. Compared to those with the IDH1 canonical mutation, patients with non-canonical mutations were younger (p < 0.001) and less frequently presented the 1p19q codeletion (p = 0.017). Multivariate analysis confirmed that the extension of surgery (p = 0.003), the presence of the 1p19q codeletion (p = 0.001), and the presence of a non-canonical mutation (p = 0.041) were variables correlated with improved overall survival.

CONCLUSION

the presence of non-canonical IDH1 mutations could be associated with improved survival among patients with IDH1 mutated grade II-III glioma.

Chromatin-regulating genes are associated with postoperative prognosis and isocitrate dehydrogenase mutation in astrocytoma

Background

Abnormality in chromatin regulation is a major determinant in the progression of multiple neoplasms. Astrocytoma is a malignant histologic morphology of glioma that is commonly accompanied by chromatin dysregulation. However, the systemic interpretation of the expression characteristics of chromatin-regulating genes in astrocytoma is unclear.

Methods

In this study, we investigated the expression profile of chromatin regulation genes in 194 astrocytoma patients sourced from The Cancer Genome Atlas (TCGA) database. The relevance of gene expression and postoperative survival outcomes was assessed.

Results

Based on the expression patterns of chromatin regulation genes, two primary clusters and three subclusters with significantly different survival outcomes were identified. The patients in cluster_1 (or subcluster_1) had a poorer prognosis than the other groups, and this particular cohort were older, with a more advanced grade of tumor and isocitrate dehydrogenase-wildtype distribution. Detection of the differentially expressed genes revealed that the group with poor prognosis was characterized by downregulation of H2AFY2, WAC, HDAC5, ZMYND11, TET1, SATB1, and MYST4, and overexpression of EYA4. Moreover, all eight genes were significantly correlated with overall survival (OS) in astrocytoma. Age-associated genes were investigated and the expression levels of EYA4, TET1, SATB1, WAC, ZMYND11, and H2AFY2 were found to be closely correlated with advanced age. Regression analysis suggested that the expression levels of H2AFY2, HILS1, EYA1, EYA4, and KDM5B were independently associated with IDH mutation status. The differential expressions of 34 common genes were significantly associated with age, grade, and IDH mutant.

Conclusions

The study revealed that the expression pattern of chromatin regulation genes was significantly associated with postoperative prognosis in astrocytoma. Moreover, the differential expression of particular genes was strongly associated with clinical characteristics such as age, grade, and IDH subtype. These results suggest that the genes involved in chromatin regulation play important roles in the biological process of astrocytoma progression, and these molecules could potentially serve as therapeutic targets in astrocytoma.