Effects of brain radiotherapy on cognitive performance in adult low-grade glioma patients: A systematic review

Multidisciplinary Management of Isocitrate Dehydrogenase-Mutated Gliomas in a Contemporary Molecularly Defined Era

Mutations in isocitrate dehydrogenase (IDH) genes, an early step in the ontogeny of lower-grade gliomas, induce global epigenetic changes characterized by a hypermethylation phenotype and are critical to tumor classification, treatment decision making, and estimation of patient prognosis. The introduction of IDH inhibitors to block the oncogenic neomorphic function of the mutated protein has resulted in new therapeutic options for these patients. To appreciate the implications of these recent IDH inhibitor results, it is important to juxtapose historical outcomes with chemoradiotherapy. Herein, we rationally evaluate recent IDH inhibitor data within historical precedents to guide contemporary decisions regarding the role of observation, maximal safe resection, adjuvant therapies, and the import of patient and tumor variables. The biological underpinnings of the IDH pathway and the mechanisms, impact, and limitations of IDH inhibitors, the actual magnitude of tumor regression and patient benefit, and emergence of resistance pathways are presented to guide future trial development. Management in the current, molecularly defined era will require careful patient selection and risk factor assessment, followed by an open dialog about the results of studies such as INDIGO, as well as mature data from legacy trials, and a discussion about risk-versus-benefit for the choice of treatment, with multidisciplinary decision making as an absolute prerequisite.

Revolutionizing Brain Tumor Care: Emerging Technologies and Strategies

Glioblastoma multiforme (GBM) is one of the most aggressive forms of brain tumor, characterized by a daunting prognosis with a life expectancy hovering around 12-16 months. Despite a century of relentless research, only a select few drugs have received approval for brain tumor treatment, largely due to the formidable barrier posed by the blood-brain barrier. The current standard of care involves a multifaceted approach combining surgery, irradiation, and chemotherapy. However, recurrence often occurs within months despite these interventions. The formidable challenges of drug delivery to the brain and overcoming therapeutic resistance have become focal points in the treatment of brain tumors and are deemed essential to overcoming tumor recurrence. In recent years, a promising wave of advanced treatments has emerged, offering a glimpse of hope to overcome the limitations of existing therapies. This review aims to highlight cutting-edge technologies in the current and ongoing stages of development, providing patients with valuable insights to guide their choices in brain tumor treatment.

Management of glioblastoma in elderly patients: A review of the literature

High grade gliomas are the most common primary aggressive brain tumours with a very poor prognosis and a median survival of less than 2 years. The standard management protocol of newly diagnosed glioblastoma patients involves surgery followed by radiotherapy, chemotherapy in the form of temozolomide and further adjuvant temozolomide. The recent advances in molecular profiling of high-grade gliomas have further enhanced our understanding of the disease. Although the management of glioblastoma is standardised in newly diagnosed adult patients there is a lot of debate regarding the best treatment approach for the newly diagnosed elderly glioblastoma patients. In this review article we attempt to summarise the findings regarding surgery, radiotherapy, chemotherapy, and their combination in order to offer the best possible management modality for this group of patients. Elderly patients 65-70 with an excellent functional level could be considered as candidates for the standards treatment consisting of surgery, standard radiotherapy with concomitant and adjuvant temozolomide. Similarly, elderly patients above 70 with good functional status could receive the above with the exception of receiving a shorter course of radiotherapy instead of standard. In elderly GBM patients with poorer functional status and MGMT promoter methylation temozolomide chemotherapy can be considered. For elderly patients who cannot tolerate chemotherapy, hypofractionated radiotherapy is an option. In contrast to the younger adult patients, it seems that a careful individualised approach is a key element in deciding the best treatment options for this group of patients.

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.

The longitudinal relation between executive functioning and multilayer network topology in glioma patients

Many patients with glioma, primary brain tumors, suffer from poorly understood executive functioning deficits before and/or after tumor resection. We aimed to test whether frontoparietal network centrality of multilayer networks, allowing for integration across multiple frequencies, relates to and predicts executive functioning in glioma. Patients with glioma (n = 37) underwent resting-state magnetoencephalography and neuropsychological tests assessing word fluency, inhibition, and set shifting before (T1) and one year after tumor resection (T2). We constructed binary multilayer networks comprising six layers, with each layer representing frequency-specific functional connectivity between source-localized time series of 78 cortical regions. Average frontoparietal network multilayer eigenvector centrality, a measure for network integration, was calculated at both time points. Regression analyses were used to investigate associations with executive functioning. At T1, lower multilayer integration (p = 0.017) and epilepsy (p = 0.006) associated with poorer set shifting (adj. R2 = 0.269). Decreasing multilayer integration (p = 0.022) and not undergoing chemotherapy at T2 (p = 0.004) related to deteriorating set shifting over time (adj. R2 = 0.283). No significant associations were found for word fluency or inhibition, nor did T1 multilayer integration predict changes in executive functioning. As expected, our results establish multilayer integration of the frontoparietal network as a cross-sectional and longitudinal correlate of executive functioning in glioma patients. However, multilayer integration did not predict postoperative changes in executive functioning, which together with the fact that this correlate is also found in health and other diseases, limits its specific clinical relevance in glioma.

A novel, effective machine learning-based RNA editing profile for predicting the prognosis of lower-grade gliomas

Patients with low-grade glioma (LGG) may survive for long time periods, but their tumors often progress to higher-grade lesions. Currently, no cure for LGG is available. A-to-I RNA editing accounts for nearly 90% of all RNA editing events in humans and plays a role in tumorigenesis in various cancers. However, little is known regarding its prognostic role in LGG. On the basis of The Cancer Genome Atlas (TCGA) data, we used LASSO and univariate Cox regression to construct an RNA editing site signature. The results derived from the TCGA dataset were further validated with Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA) datasets. Five machine learning algorithms (Decision Trees C5.0, XGboost, GBDT, Lightgbm, and Catboost) were used to confirm the prognosis associated with the RNA editing site signature. Finally, we explored immune function, immunotherapy, and potential therapeutic agents in the high- and low-risk groups by using multiple biological prediction websites. A total of 22,739 RNA editing sites were identified, and a signature model consisting of four RNA editing sites (PRKCSH|chr19:11561032, DSEL|chr18:65174489, UGGT1|chr2:128952084, and SOD2|chr6:160101723) was established. Cox regression analysis indicated that the RNA editing signature was an independent prognostic factor, according to the ROC curve (AUC = 0.823), and the nomogram model had good predictive power (C-index = 0.824). In addition, the predictive ability of the RNA editing signature was confirmed with the machine learning model. The sensitivity of PCI-34051 and Elephantin was significantly higher in the high-risk group than the low-risk group, thus potentially providing a marker to predict the effects of lung cancer drug treatment. RNA editing may serve as a novel survival prediction tool, thus offering hope for developing editing-based therapeutic strategies to combat LGG progression. In addition, this tool may help optimize survival risk assessment and individualized care for patients with low-grade gliomas.

Factors affecting cognitive functions of patients with high-grade gliomas: a systematic review

BACKGROUND

Gliomas make up approximately 26.5% of all primary CNS tumors and 80.7% of malignant tumors. They are classified according to histology, location, and genetics. Grade III and IV gliomas are considered high-grade gliomas (HGGs). The cognitive signs and symptoms are attributed to mass defects depending on location, growth rapidity, and edema. Our purpose is to review the cognitive status of patients diagnosed with HGGs; the effect of treatments including surgical resection, radiotherapy, and chemotherapy; and the predictors of the cognitive status.

METHODS

We utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as a template for the methodology. A comprehensive literature search was performed from three databases (PubMed, ScienceDirect, and Cochrane Library) for clinical trials and longitudinal studies on patients diagnosed with HGGs assessing their cognitive status.

RESULTS

Thirteen studies were selected among which 9 assessed cognitive function before and after treatment. One assessed the consistency of cognitive complaints and objective cognitive functioning. Three reported factors affecting disease progression and cognitive status. Most HGG patients have impairment in at least one cognitive domain. Treatments including surgical resection or radio-chemotherapy did not impair cognitive status.

DISCUSSION

The cognitive status could be used to assess sub-clinical tumor progression. Factors correlated to cognitive status were tumor location, edema, and grade. Patient characteristics correlated were pre-operative epilepsy, corticosteroid use, and age at the time of diagnosis.

CONCLUSION

Assessment of the cognitive status of HGG patients indicates sub-clinical tumor progression and may be used to assess treatment outcomes.

Protective Prognostic Biomarkers Negatively Correlated with Macrophage M2 Infiltration in Low-Grade Glioma

Tumor-associated Macrophages (TAMs) play a vital role in the progression of glioma. Macrophage M2 has been confirmed to promote immunosuppression and proliferation of low-grade glioma (LGG). Here, we searched for genes negatively correlated with Macrophages M2 by bioinformatical methods and investigated their protective ability for prognosis. LGG and adjacent normal samples were screened out in TCGA and three GEO datasets. 326 overlapped differentially expressed genes were calculated, and their biological functions were investigated by Go and KEGG analyses. Macrophage M2 accounted for the highest proportion among all 22 immune cells by CIBERSORT deconvolution algorithm. The proportion of Macrophage M2 in LGG was also higher than that in normal tissue according to several deconvolution algorithms. 43 genes in the blue module negatively correlated with Macrophage M2 infiltration were identified by weighted gene coexpression network analysis (WGCNA). Through immune infiltration and correlation analysis, FGFBP3, VAX2, and SHD were selected and they were enriched in G protein-coupled receptors' signaling regulation and cytokine receptor interaction. They could prolong the overall and disease-free survival time. Univariate and multivariate Cox regression analyses were applied to evaluate prognosis prediction ability. Interestingly, FGFBP3 and AHD were independent prognostic predictors. A nomogram was drawn, and its 1-year, 3-year, and 5-year survival prognostic value was verified by ROC curves and calibration plots. In conclusion, FGFBP3, VAX2, and SHD were protective prognostic biomarkers against Macrophage M2 infiltration in low-grade glioma. The FGFBP3 and SHD were independent factors to effectively predict long-term survival probability.

Large tumour volume reduction of IDH-mutated anaplastic glioma involving the insular region following radiotherapy

Background

The impact of near-total resection of IDH-mutated anaplastic glioma (IDHmutAG) is well-established but there remains uncertainty of benefit in tumours of the insular cortex where the extent of safe resection may be limited. This study aimed to assess tumour volume reduction in patients following IMRT and impact of residual post-surgical volume.

Methods and materials

Patients with IDHmutAG involving insular cortex managed with IMRT from 2008 to 2019 had baseline patient, tumour and treatment factors recorded. Volumetric assessment of residual disease on MRI was performed at baseline, month+ 3 and month+ 12 post-IMRT. Potential prognostic factors were analysed for tumour reduction and relapse-free survival, and assessed by log-rank and Cox regression analyses.

Results

Thirty two patients with IDHmutAG of the insular cortex were managed with median follow-up post-IMRT of 67.2 months. Pathology was anaplastic astrocytoma (AAmut) in 20, and anaplastic oligodendroglioma (AOD) in 12 patients. Median pre-IMRT volume on T1 and T2Flair was 24.3cm³ and 52.2cm³. Twenty-seven patients were alive with 5-year relapse-free survival of 80%. There was a median 67 and 64% reduction from baseline occurring at 3 months post-IMRT for T1 and T2Flair respectively; and subsequent median 78 and 73% at 12 months. At 12 months AOD patients had median 83% T1 volume reduction compared to 63% in AAmut (p < 0.01). There was no difference on T2Flair volume (p = 0.64). No other pathological factors influenced volume reduction at 12 months. No factors were associated with relapse-free survival including baseline T1 (p = 0.52) and T2Flair (p = 0.93) volume.

Conclusion

IMRT provides large tumour volume reduction in IDHmutAG of the insular cortex. While maximal safe debulking remains standard of care when feasible, this patient cohort reported no significant negative impact of residual disease volume on relapse-free survival.