Clinical roles of EGFR amplification in diffuse gliomas: a real-world study using the 2021 WHO classification of CNS tumors.

Background: The 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM). Purpose: This study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification. Methods: We reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes. Results: 163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM. Conclusion: Our study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-containing therapy.

Predictive markers and prognostic models are useful for the individualization of cancer treatment. In this study, we sought to identify clinical and molecular factors to predict overall survival in recurrent glioma patients receiving bevacizumab-containing regimens. A cohort of 102 patients was retrospectively collected from June 2011 to January 2022 at our institution. A nomogram was generated by Cox regression and feature selection algorithms based on 19 clinicopathological and 60 molecular variables. The model's performance was internally evaluated by bootstrapping in terms of discrimination and calibration. The median overall survival from the initiation of bevacizumab administration to death or last follow-up was 11.6 months (95% CI: 9.2-13.8 months) for all 102 patients, 10.2 months (95% CI: 6.4-13.3 months) for 66 patients with grade 4 tumors, and 13.8 months (lower limit of 95% CI: 11.5 months) for 36 patients with tumors of grade lower or not available. In the final model, a lower WHO 2021 grade (Grade lower or not available vs. Grade 4, HR: 0.398, 95% CI: 0.223-0.708, p = 0.00172), having received adjuvant radiochemotherapy (Yes vs. No, HR: 0.488, 95% CI: 0.268-0.888, p = 0.0189), and wildtype EGFR (Wildtype vs. Altered, HR: 0.193, 95% CI: 0.0506-0.733, p = 0.0157; Not available vs. Altered, HR: 0.386, 95% CI: 0.184-0.810, p = 0.0118) were significantly associated with longer overall survival in multivariate Cox regression. The overall concordance index was 0.652 (95% CI: 0.566-0.714), and the areas under the time-dependent curves for 6-, 12-, and 18-month overall survival were 0.677 (95% CI: 0.516-0.816), 0.654 (95% CI: 0.470-0.823), and 0.675 (95% CI: 0.491-0.860), respectively. A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-based therapy was established and internally validated. It could serve as a reference tool for clinicians to assess the extent the patients may benefit from bevacizumab and stratify their treatment response.

Molecular Determinants of Neurocognitive Deficits in Glioma: Based on 2021 WHO Classification.

Cognitive impairment is a common feature among patients with diffuse glioma. The objective of the study is to investigate the relationship between preoperative cognitive function and clinical as well as molecular factors, firstly based on the new 2021 World Health Organization's updated classification of central nervous system tumors. A total of 110 diffuse glioma patients enrolled underwent preoperative cognitive assessments using the Mini-Mental State Examination and Montreal Cognitive Assessment. Clinical information was collected from medical records, and gene sequencing was performed to analyze the 18 most influenced genes. The differences in cognitive function between patients with and without glioblastoma were compared under both the 2016 and 2021 WHO classification of tumors of the central nervous system to assess their effect of differentiation on cognition. The study found that age, tumor location, and glioblastoma had significant differences in cognitive function. Several genetic alterations were significantly correlated with cognition. Especially, IDH, CIC, and ATRX are positively correlated with several cognitive domains, while most other genes are negatively correlated. For most focused genes, patients with a low number of genetic alterations tended to have better cognitive function. Our study suggested that, in addition to clinical characteristics such as age, histological type, and tumor location, molecular characteristics play a crucial role in cognitive function. Further research into the mechanisms by which tumors affect brain function is expected to enhance the quality of life for glioma patients. This study highlights the importance of considering both clinical and molecular factors in the management of glioma patients to improve cognitive outcomes.

Novel insight into histological and molecular astrocytoma, IDH-mutant, Grade 4 by the updated WHO classification of central nervous system tumors.

BACKGROUND: The latest fifth edition of the World Health Organization (WHO) classification of the central nervous system (CNS) tumors (WHO CNS 5 classification) released in 2021 defined astrocytoma, IDH-mutant, Grade 4. However, the understanding of this subtype is still limited. We conducted this study to describe the features of astrocytoma, IDH-mutant, Grade 4 and explored the similarities and differences between histological and molecular subtypes. METHODS: Patients who underwent surgery from January 2011 to January 2022, classified as astrocytoma, IDH-mutant, Grade 4 were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis. RESULTS: Altogether 33 patients with astrocytoma, IDH-mutant, Grade 4 were selected, including 20 with histological and 13 with molecular WHO Grade 4 astrocytoma. Tumor enhancement, intratumoral-necrosis like presentation, larger peritumoral edema, and more explicit tumor margins were frequently observed in histological WHO Grade 4 astrocytoma. Additionally, molecular WHO Grade 4 astrocytoma showed a tendency for relatively longer overall survival, while a statistical significance was not reached (47 vs. 25 months, p = 0.22). TP53, CDK6, and PIK3CA alteration was commonly observed, while PIK3R1 (p = 0.033), Notch1 (p = 0.027), and Mycn (p = 0.027) alterations may affect the overall survival of molecular WHO Grade 4 astrocytomas. CONCLUSIONS: Our study scrutinized IDH-mutant, Grade 4 astrocytoma. Therefore, further classification should be considered as the prognosis varied between histological and molecular WHO Grade 4 astrocytomas. Notably, therapies aiming at PIK3R1, Notch 1, and Mycn may be beneficial.

Histological and molecular glioblastoma, IDH-wildtype: a real-world landscape using the 2021 WHO classification of central nervous system tumors.

Introduction: Glioblastoma (GBM), the most lethal primary brain malignancy, is divided into histological (hist-GBM) and molecular (mol-GBM) subtypes according to the 2021 World Health Organization classification of central nervous system tumors. This study aimed to characterize the clinical, radiological, molecular, and survival features of GBM under the current classification scheme and explore survival determinants. Methods: We re-examined the genetic alterations of IDH-wildtype diffuse gliomas at our institute from 2011 to 2022, and enrolled GBMs for analysis after re-classification. Univariable and multivariable analyses were used to identify survival determinants. Results: Among 209 IDH-wildtype gliomas, 191 were GBMs, including 146 hist-GBMs (76%) and 45 mol-GBMs (24%). Patients with mol-GBMs were younger, less likely to develop preoperative motor dysfunction, and more likely to develop epilepsy than hist-GBMs. Mol-GBMs exhibited lower radiographic incidences of contrast enhancement and intratumoral necrosis. Common molecular features included copy-number changes in chromosomes 1, 7, 9, 10, and 19, as well as alterations in EGFR, TERT, CDKN2A/B, and PTEN, with distinct patterns observed between the two subtypes. The median overall survival (mOS) of GMB was 12.6 months. Mol-GBMs had a higher mOS than hist-GBMs, although not statistically significant (15.6 vs. 11.4 months, p=0.17). Older age, male sex, tumor involvement of deep brain structure or functional area, and genetic alterations in CDK4, CDK6, CIC, FGFR3, KMT5B, and MYB were predictors for a worse prognosis, while MGMT promoter methylation, maximal tumor resection, and treatment based on the Stupp protocol were predictive for better survival. Conclusion: The definition of GBM and its clinical, radiological, molecular, and prognostic characteristics have been altered under the current classification.

An online survival predictor in glioma patients using machine learning based on WHO CNS5 data.

Background: The World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms. Methods: We extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011-2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM). Results: A total of 198 patients with complete WHO5 molecular data and follow-up information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19-38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and OS time of glioma. To better predict the prognosis of glioma patients, we constructed a WHO5-related risk signature and nomogram. The AUC values of the ROC curves of the nomogram for predicting the 1, 3, and 5-year OS were 0.849, 0.835, and 0.821 in training set, and, 0.844, 0.943, and 0.959 in validation set. The calibration plot confirmed the reliability of the nomogram, and the c-index was 0.742 in training set and 0.775 in validation set. Additionally, our nomogram showed a superior net benefit across a broader scale of threshold probabilities in decision curve analysis. Therefore, we selected it as the backend for the online survival prediction tool (Glioma Survival Calculator, https://who5pumch.shinyapps.io/DynNomapp/), which can calculate the survival probability for a specific time of the patients. Conclusion: An online prognosis predictor based on WHO5-related biomarkers was constructed. This therapeutically promising tool may increase the precision of forecast therapy outcomes and assess prognosis.

Spotlights on adult patients with pediatric-type diffuse gliomas in accordance with the 2021 WHO classification of CNS tumors.

Introduction: The fifth edition of the World Health Organization (WHO) classification of central nervous system (CNS) tumors released in 2021 formally defines pediatric-type diffuse gliomas. However, there is still little understanding of pediatric-type diffuse gliomas, and even less attention has been paid to adult patients. Therefore, this study describes the clinical radiological, survival, and molecular features of adult patients with pediatric-type glioma. Methods: Adult patients who underwent surgery from January 2011 to January 2022, classified as pediatric-type glioma, were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis. Results: Among 596 adult patients, 20 patients with pediatric-type glioma were screened, including 6 with diffuse astrocytoma, MYB- or MYBL1-altered, 2 with diffuse midline glioma, H3 K27-altered, and 12 with diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype. Pediatric high-grade glioma (pHGG) frequently showed tumor enhancement, peritumoral edema, and intratumoral necrosis. Adult patients with pHGG showed a longer life expectancy than adult patients with glioblastoma. Common molecular alterations included chromosome alterations and CDKN2A/B, PIK3CA, and PTEN, while altered KMT5B and MET were found to affect the overall survival. Conclusion: Our study demonstrated adult patients with pediatric-type glioma. Notably, our research aims to expand the current understanding of adult patients with pediatric-type diffuse gliomas. Furthermore, personalized therapies consisting of targeted molecular inhibitors for MET and VEGFA may exhibit beneficial effects in the corresponding population.

Clinical updates on gliomas and implications of the 5th edition of the WHO classification of central nervous system tumors.

Background: The 5th edition of the World Health Organization (WHO) classification of central nervous system tumors incorporated specific molecular alterations into the categorization of gliomas. The major revision of the classification scheme effectuates significant changes in the diagnosis and management of glioma. This study aimed to depict the clinical, molecular, and prognostic characteristics of glioma and its subtypes according to the current WHO classification. Methods: Patients who underwent surgery for glioma at Peking Union Medical College Hospital during 11 years were re-examined for tumor genetic alterations using next-generation sequencing, polymerase chain reaction-based assay, and fluorescence in situ hybridization methods and enrolled in the analysis. Results: The enrolled 452 gliomas were reclassified into adult-type diffuse glioma (ntotal=373; astrocytoma, n=78; oligodendroglioma, n=104; glioblastoma, n=191), pediatric-type diffuse glioma (ntotal=23; low-grade, n=8; high-grade, n=15), circumscribed astrocytic glioma (n=20), and glioneuronal and neuronal tumor (n=36). The composition, definition, and incidence of adult- and pediatric-type gliomas changed significantly between the 4th and the 5th editions of the classification. The clinical, radiological, molecular, and survival characteristics of each subtype of glioma were identified. Alterations in CDK4/6, CIC, FGFR2/3/4, FUBP1, KIT, MET, NF1, PEG3, RB1, and NTRK2 were additional factors correlated with the survival of different subtypes of gliomas. Conclusions: The updated WHO classification based on histology and molecular alterations has updated our understanding of the clinical, radiological, molecular, survival, and prognostic characteristics of varied subtypes of gliomas and provided accurate guidance for diagnosis and potential prognosis for patients.

Prognostic Value of Choline and Other Metabolites Measured Using 1H-Magnetic Resonance Spectroscopy in Gliomas: A Meta-Analysis and Systemic Review.

Glioma is the most prevalent primary central nervous system malignant tumor, with high heterogeneity observed among different grades; therefore, non-invasive prediction of prognosis could improve the clinical management of patients with glioma. 1H-magnetic resonance spectroscopy (MRS) can estimate metabolite levels non-invasively. Multiple studies have investigated its prognostic value in gliomas; however, no consensus has been reached. PubMed and Embase databases were searched up to 20 October 2022 to identify studies investigating the prognostic value of metabolites using 1H-MRS in patients with glioma. Heterogeneity across studies was evaluated using the Q and I2 tests, and a fixed- or random-effects model was used to estimate the combined overall hazard ratio (HR). Funnel plots and Begg tests were used to assess publication bias. Higher choline levels were associated with shorter overall survival (HR = 2.69, 95% CI, 1.92−2.99; p < 0.001) and progression-free survival (HR = 2.20, 95% CI, 1.16−4.17; p = 0.02) in all patients; however, in pediatric gliomas, it showed no significant correlation with overall survival (HR = 1.60, 95% CI, 0.97−2.64; p = 0.06). The estimated choline level by 1H-MRS could be used to non-invasively predict the prognosis of patients with adult gliomas, and more studies are needed to evaluate the prognostic value of other metabolites.

Tumor-Treating Fields in Glioblastomas: Past, Present, and Future.

Tumor-treating fields (TTFields), a noninvasive and innovative therapeutic approach, has emerged as the fourth most effective treatment option for the management of glioblastomas (GBMs), the most deadly primary brain cancer. According to on recent milestone randomized trials and subsequent observational data, TTFields therapy leads to substantially prolonged patient survival and acceptable adverse events. Clinical trials are ongoing to further evaluate the safety and efficacy of TTFields in treating GBMs and its biological and radiological correlations. TTFields is administered by delivering low-intensity, intermediate-frequency, alternating electric fields to human GBM function through different mechanisms of action, including by disturbing cell mitosis, delaying DNA repair, enhancing autophagy, inhibiting cell metabolism and angiogenesis, and limiting cancer cell migration. The abilities of TTFields to strengthen intratumoral antitumor immunity, increase the permeability of the cell membrane and the blood-brain barrier, and disrupt DNA-damage-repair processes make it a promising therapy when combined with conventional treatment modalities. However, the overall acceptance of TTFields in real-world clinical practice is still low. Given that increasing studies on this promising topic have been published recently, we conducted this updated review on the past, present, and future of TTFields in GBMs.

A facile method for the preparation of black TiO2 by Al reduction of TiO2 and their visible light photocatalytic activity.

Black TiO2 has attracted widespread attention due to its visible light absorption and wide range of applications. However, the currently reported preparation methods for black TiO2 are not suitable for large-scale production due to its being prepared under high vacuum and over a long time. We have successfully prepared black TiO2 under normal pressure and short time conditions. The as-prepared black titanium dioxide was characterized by XRD, XPS, TEM, UV-visible absorption spectrum and other characterization methods. The result shows that the as prepared black titanium dioxide had a disordered structure and oxygen vacancy defects on the surface, and exhibits excellent visible and near infrared absorption performance. The black TiO2 sample was prepared under 650 °C 60 min exhibits excellent visible light photocatalytic performance, and can degrade 56% MO after visible light irradiation for 120 min.