Clinical Management of Diffuse Low-Grade Gliomas

Integration of amide proton transfer-weighted imaging and methionine positron emission tomography histogram parameters enhances the prediction of isocitrate dehydrogenase mutations in adult diffuse gliomas

BACKGROUND

To evaluate whether the combination of amide proton transfer-weighted imaging (APT-WI) and methionine positron emission tomography (MET-PET) enhances the non-invasive prediction of isocitrate dehydrogenase (IDH) mutation status in adult diffuse gliomas.

RESULTS

We retrospectively analysed 28 adult patients with histologically confirmed diffuse gliomas who underwent preoperative APT-WI and MET-PET imaging at our institution. Histogram analyses were conducted for both imaging modalities, extracting parameters such as the 10th, 50th, 70th, and 90th percentiles, mean, variance, skewness, and kurtosis. Parameters between IDH-mutant and IDH-wildtype gliomas were compared using the Mann-Whitney U test. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis, and combined models of the two parameters were constructed using multivariable logistic regression. IDH-wildtype gliomas exhibited significantly higher APT-WI 90th percentile (APT90) values (median: 3.51%, interquartile range [IQR]: 1.92-4.23%) compared to IDH-mutant gliomas (median: 2.24%, IQR: 1.52-2.85%, p = 0.039). Similarly, IDH-wildtype gliomas showed elevated MET-PET maximum tumour-to-normal ratios (TNRmax) (median: 2.51, IQR: 2.13-3.41) compared to IDH-mutant gliomas (median: 1.62, IQR: 1.30-2.77, p = 0.020). ROC curve analysis indicated that the combined model of APT90 and TNR kurtosis achieved an area under the curve of 0.85, demonstrating superior diagnostic accuracy compared to that of single-parameter models.

CONCLUSIONS

Combining histogram-derived parameters from APT-WI and MET-PET significantly improves the diagnostic accuracy for predicting IDH mutation status in diffuse gliomas. This non-invasive approach may serve as a valuable adjunct for preoperative evaluation and the development of personalised treatment strategies in patients with gliomas.

A 5-Year Update on the Clinical Development of Cancer Cell-Based Vaccines for Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is considered one of the most aggressive forms of brain cancer with a 15-month median survival, despite advancements in surgery, radiotherapy, and chemotherapy. The immune-suppressed tumor microenvironment and the blood-brain barrier are major contributors to its poor prognosis and treatment resistance. In the last decade, significant progress has been made in developing cell-based vaccines to boost immune responses against GBM. This review provides an extensive update on recent clinical trials involving various cancer cell vaccines, including ICT-107, the α-type-1 DC vaccine, and others. Although these trials have demonstrated potential improvements in progression-free survival (PFS) and overall survival (OS), the diverse and immune-suppressed nature of GBM poses challenges for consistent therapeutic success. We discuss the details of these trials along with the potential mechanism of vaccine efficacy and immune activations. The findings of these trials highlight the significance of a personalized immunotherapy approach and suggest that patient stratification could significantly advance the clinical management of GBM.

Multicellular Network-Informed Survival Model for Identification of Drug Targets of Gliomas

Increasing evidence suggests that communication between tumor cells (TCs) and tumor-associated macrophages (TAMs) plays a substantial role in promoting progression of low-grade gliomas (LGG). Hence, it is becoming critical to model TAM-TC interplay and interrogate how the crosstalk affects prognosis of LGG patients. This article proposed a translational research pipeline to construct the multicellular interaction gene network (MIGN) for identification of druggable targets to develop novel therapeutic strategies. Firstly, we selected immunotherapy-related feature genes (IFGs) for TAMs and TCs using RNA-seq data of glioma mice from preclinical trials. After translating the IFGs to human genome, we constructed TAM- and TC- associated networks separately, using a training set of 524 human LGGs. Subsequently, clustering analysis was performed within each network, and the concordance measure K-index was adopted to correlate gene clusters with patient survival. The MIGN was built by combining the clusters highly associated with survival in TAM- and TC-associated networks. We then developed a MIGN-based survival model to identify prognostic signatures comprised of ligands, receptors and hub genes. An independent cohort of 172 human LGG samples was leveraged to validate predictive accuracy of the signature. The areas under time-dependent ROC curves were 0.881, 0.867, and 0.839 with respect to 1-year, 3-year, and 5-year survival rates respectively in the validation set. Furthermore, literature survey was conducted on the signature genes, and potential clinical responses to targeted drugs were evaluated for LGG patients, further highlighting potential utilities of the MIGN signature to develop novel immunotherapies to extend survival of LGG patients.

Machine learning-based identification of histone deacetylase-associated prognostic factors and prognostic modeling for low-grade glioma

BACKGROUND

Low-grade glioma (LGG) is a slow-growing but invasive tumor that affects brain function. Histone deacetylases (HDACs) play a critical role in gene regulation and tumor progression. This study aims to develop a prognostic model based on HDAC-related genes to aid in risk stratification and predict therapeutic responses.

METHODS

Expression data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) were analyzed to identify an optimal HDAC-related risk signature from 73 genes using 10 machine learning algorithms. Patients were stratified into high- and low-risk groups based on the median risk score. Prognostic accuracy was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), were performed to explore pathways linked to the gene signature. Immune infiltration and tumor microenvironment characteristics were assessed using Single Sample Gene Set Enrichment Analysis (ssGSEA) and ESTIMATE algorithm. SubMap was applied to predict responsiveness to immune checkpoint inhibitors, and chemotherapeutic sensitivity was analyzed via the Genomics of Drug Sensitivity in Cancer (GDSC) database.

RESULTS

A prognostic model consisting of four HDAC-related genes-SP140, BAZ1B, SP100, and SIRT1-was identified. This signature displayed strong prognostic accuracy, achieving a C-index of 0.945. Individuals with LGG were systematically divided into high-risk and low-risk cohorts based on the median risk value, enabling more precise risk stratification. The survival prognosis was significantly worse in the high-risk cohort compared to the low-risk group, highlighting distinct survival trajectories. Notably, the two cohorts exhibited marked shifts in immune checkpoint gene transcriptional profiles and immune cell infiltration maps, underscoring fundamental biological differences that contribute to these differing prognoses.

CONCLUSION

We developed an HDAC-related four-gene prognostic model that correlates with survival, immune landscape, and therapeutic response in LGG patients. This model may guide personalized treatment strategies and improve prognostic accuracy, warranting further validation in clinical settings.

The role of postoperative blood pressure management in early postoperative hemorrhage in awake craniotomy glioma patients

Postoperative hemorrhage can severely affect the patients' neurological outcome after awake craniotomy. Higher postoperative blood pressure can increase the risk of postoperative hemorrhage. The aim of this study was to investigate the role of postoperative blood pressure and other common radiological and epidemiological features with the incidence of postoperative hemorrhage. In this retrospective analysis, we included patients who underwent awake surgery at our institution. We assessed the blood pressure both intra- and postoperatively as well as the heart rate for the first 12 h. We compared a cohort with postoperative hemorrhage, who required further treatment (surgical revision or intravenous antihypertensive therapy), with a cohort with no postoperative hemorrhage. We included 48 patients with a median age of 39 years. 9 patients (19%) required further treatment due to postoperative hemorrhage, which was surgery in 2 cases and intensive blood pressure measurements in 7 cases. However, with early treatment, no significant difference in Performance scores at follow-up could be found. Patients with postoperative hemorrhage showed significantly higher postoperative systolic blood pressure during the hours 3-12 (p < 0.05) as well as intraoperatively throughout the procedure (p < 0.05). In ROC and Youden Test, a strong impact of systolic blood pressure over 140mmHg during the early postoperative course could be shown. Postoperative hemorrhage is a rare but possible complication in awake surgery glioma patients. To avoid postoperative hemorrhage, treating physicians should aim strictly on systolic blood pressure of under 140mmHg for the postoperative course.

Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Identification of Key Molecular Pathways and Associated Genes as Targets to Overcome Radiotherapy Resistance Using a Combination of Radiotherapy and Immunotherapy in Glioma Patients

Recent mechanistic studies have indicated that combinations of radiotherapy (RT) plus immunotherapy (via CSF-1R inhibition) can serve as a strategy to overcome RT resistance and improve the survival of glioma mice. Given the high mortality rate for glioma, including low-grade glioma (LGG) patients, it is of critical importance to investigate the mechanism of the combination of RT and immunotherapy and further translate the mechanism from mouse studies to improve survival of RT-treated human glioma patients. Using the RNA-seq data from a glioma mouse study, 874 differentially expressed genes (DEGs) between the group of RT-treated mice at glioma recurrence and the group of mice with combination treatment (RT plus CSF-1R inhibition) were translated to the human genome to identify significant molecular pathways using the KEGG enrichment analysis. The enrichment analysis yields statistically significant signaling pathways, including the phosphoinositide 3-kinase (PI3K)/AKT pathway, Hippo pathway, and Notch pathway. Within each pathway, a candidate gene set was selected by Cox regression models as genetic biomarkers for resistance to RT and response to the combination of RT plus immunotherapies. Each Cox model is trained using a cohort of 295 RT-treated LGG patients from The Cancer Genome Atlas (TCGA) database and validated using a cohort of 127 RT-treated LGG patients from the Chinese Glioma Genome Atlas (CGGA) database. A four-DEG signature (ITGB8, COL9A3, TGFB2, JAG1) was identified from the significant genes within the three pathways and yielded the area under time-dependent ROC curve AUC = 0.86 for 5-year survival in the validation set, which indicates that the selected DEGs have strong prognostic value and are potential intervention targets for combination therapies. These findings may facilitate future trial designs for developing combination therapies for glioma patients.

A combinatory vaccine with IMA950 plus varlilumab promotes effector memory T-cell differentiation in the peripheral blood of patients with low-grade gliomas

BACKGROUND

Central nervous system (CNS) WHO grade 2 low-grade glioma (LGG) patients are at high risk for recurrence and with unfavorable long-term prognosis due to the treatment resistance and malignant transformation to high-grade glioma. Considering the relatively intact systemic immunity and slow-growing nature, immunotherapy may offer an effective treatment option for LGG patients.

METHODS

We conducted a prospective, randomized pilot study to evaluate the safety and immunological response of the multipeptide IMA950 vaccine with agonistic anti-CD27 antibody, varlilumab, in CNS WHO grade 2 LGG patients. Patients were randomized to receive combination therapy with IMA950 + poly-ICLC and varlilumab (Arm 1) or IMA950 + poly-ICLC (Arm 2) before surgery, followed by adjuvant vaccines.

RESULTS

A total of 14 eligible patients were enrolled in the study. Four patients received pre-surgery vaccines but were excluded from postsurgery vaccines due to the high-grade diagnosis of the resected tumor. No regimen-limiting toxicity was observed. All patients demonstrated a significant increase of anti-IMA950 CD8+ T-cell response postvaccine in the peripheral blood, but no IMA950-reactive CD8+ T cells were detected in the resected tumor. Mass cytometry analyses revealed that adding varlilumab promoted T helper type 1 effector memory CD4+ and effector memory CD8+ T-cell differentiation in the PBMC but not in the tumor microenvironment.

CONCLUSION

The combinational immunotherapy, including varlilumab, was well-tolerated and induced vaccine-reactive T-cell expansion in the peripheral blood but without a detectable response in the tumor. Further developments of strategies to overcome the blood-tumor barrier are warranted to improve the efficacy of immunotherapy for LGG patients.

Glioblastoma vaccines: past, present, and opportunities

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

Intraoperative radiotherapy in recurrent IDH-wildtype glioblastoma with gross total resection: A single-center retrospective study

BACKGROUND

Isocitrate dehydrogenase-wildtype (IDHwt) glioblastoma (GBM) is one of the most aggressive primary brain tumors. The recurrence of GBM is almost inevitable. As an adjuvant option to surgery, intraoperative radiotherapy (IORT) is gaining increasing attention in the treatment of glioma. This study is aimed to evaluate the therapeutic efficacy of IORT on recurrent IDHwt GBM.

METHODS

In total, 34 recurrent IDHwt GBM patients who received a second surgery were included in the analysis (17 in the surgery group and 17 in the surgery + IORT group).

RESULTS

The progression-free survival and overall survival after the second surgery were defined as PFS2 and OS2, respectively. The median PFS2 was 7.3 months (95% CI: 6.3-10.5) and 10.6 months (95% CI: 9.3-14.6) for those patients who received surgery and surgery + IORT, respectively. Patients in the surgery + IORT group also had a longer OS2 (12.8 months, 95% CI: 11.4-17.2) than those in the surgery group (9.3 months, 95% CI: 8.9-12.9). The Kaplan-Meier survival curves, analyzed by log-rank test, revealed a statistically significant difference in PFS2 and OS2 between both groups, suggesting that IORT plays an active role in the observed benefits for PFS2 and OS2. The effects of IORT on PFS2 and OS2 were further confirmed by multivariate Cox hazards regression analysis. Two patients in the surgery group developed distant glioma metastases, and no radiation-related complications were observed in the IORT group.

CONCLUSIONS

This study suggests that low-dose IORT may improve the prognosis of recurrent IDHwt GBM patients. Future prospective large-scale studies are needed to validate the efficacy and safety of IORT.

Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Precise Construction of Dual-Promising Anticancer Drugs Associated with Gold Nanomaterials on Glioma Cancer Cells

Multiple chemodrugs with nanotechnology have proven to be an effective cancer treatment technique. When taken combined, cabazitaxel (CTX) and cisplatin (PT) have more excellent cytotoxic effects than drugs used alone in the chemotherapy of several different cancers. However, several severe side effects are associated with using these chemotherapy drugs in cancer patients. Gold nanomaterials (AuNMs) are promising as drug carriers because of their small diameter, easy surface modifications, good biocompatibility, and strong cell penetration. This work aimed to determine the CTX and PT encapsulated with AuNMs against human glioma U87 cancer cells. The fabrication of the AuNMs achieved a negative surface charge, polydispersity index, and the mean sizes. The combined cytotoxic effect of CTX and PT bound to AuNMs was greater than that of either drug alone when tested on U87 cells. The half inhibitory concentration (IC50) values for free PT were 54.7 μg/mL (at 24 h) and 4.8 g μg/mL (at 72 h). Results acquired from the MTT assay show cell growth decreases time- and concentration-dependent AuNMs, free CTX, free PT, and AuNMs@CTX/PT-induced cytotoxicity and, ultimately, the cell death of U87 cells via apoptosis. The biochemical apoptosis staining techniques investigated the cells' morphological changes of the cells (acridine orange and ethidium bromide (AO-EB) and nuclear staining (DAPI) techniques). The AO-EB and nuclear staining results reveal that the NPs effectively killed cancer cells. Furthermore, the flow cytometry analysis examined the mode of cell death. Therefore, AuNMs@CTX/PT has excellent potential in the cancer therapy of different cancer cells.

Intra-operative applications of augmented reality in glioma surgery: a systematic review

Background

Augmented reality (AR) is increasingly being explored in neurosurgical practice. By visualizing patient-specific, three-dimensional (3D) models in real time, surgeons can improve their spatial understanding of complex anatomy and pathology, thereby optimizing intra-operative navigation, localization, and resection. Here, we aimed to capture applications of AR in glioma surgery, their current status and future potential.

Methods

A systematic review of the literature was conducted. This adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. PubMed, Embase, and Scopus electronic databases were queried from inception to October 10, 2022. Leveraging the Population, Intervention, Comparison, Outcomes, and Study design (PICOS) framework, study eligibility was evaluated in the qualitative synthesis. Data regarding AR workflow, surgical application, and associated outcomes were then extracted. The quality of evidence was additionally examined, using hierarchical classes of evidence in neurosurgery.

Results

The search returned 77 articles. Forty were subject to title and abstract screening, while 25 proceeded to full text screening. Of these, 22 articles met eligibility criteria and were included in the final review. During abstraction, studies were classified as "development" or "intervention" based on primary aims. Overall, AR was qualitatively advantageous, due to enhanced visualization of gliomas and critical structures, frequently aiding in maximal safe resection. Non-rigid applications were also useful in disclosing and compensating for intra-operative brain shift. Irrespective, there was high variance in registration methods and measurements, which considerably impacted projection accuracy. Most studies were of low-level evidence, yielding heterogeneous results.

Conclusions

AR has increasing potential for glioma surgery, with capacity to positively influence the onco-functional balance. However, technical and design limitations are readily apparent. The field must consider the importance of consistency and replicability, as well as the level of evidence, to effectively converge on standard approaches that maximize patient benefit.

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.

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.

DUSP10 is a novel immune-related biomarker connected with survival and cellular proliferation in lower-grade glioma

OBJECTIVE

The role of dual-specificity phosphatase 10 (DUSP10) has been investigated in several types of cancer. Nevertheless, the underlying function of DUSP10 in lower-grade glioma (LGG) remains undetermined.

METHODS

We entirely determined the expression features and prognostic significance of DUSP10 in numerous tumors by implementing a pan-cancer analysis. Adjacently, we thoroughly inspected the correlation between DUSP10 expression and clinicopathologic features, prognosis, biological processes, immune traits, gene variations, and treatment responses based on the expression features in LGG. In vitro studies were conducted to detect the underlying functions of DUSP10 in LGG.

RESULTS

Unconventionally boosted DUSP10 expression and higher DUSP10 expression correlated with poorer prognosis were discovered in various tumors, including LGG. Fortunately, DUSP10 expression was proven to be an independent prognostic indicator of patients with LGG. Additionally, DUSP10 expression was tightly linked to the immune modulation, gene mutations, and response to immunotherapy/chemotherapy in LGG patients. In vitro studies illustrated that the DUSP10 was abnormally increased and pivotal for cell proliferation in LGG.

CONCLUSIONS

Collectively, we verified that DUSP10 was an independent prognostic indicator and may become a novelty target of targeted therapy of LGG.

Diagnostic and Therapeutic Approaches for Glioblastoma and Neuroblastoma Cancers Using Chlorotoxin Nanoparticles

Glioblastoma multiforme (GB) and high-risk neuroblastoma (NB) are known to have poor therapeutic outcomes. As for most cancers, chemotherapy and radiotherapy are the current mainstay treatments for GB and NB. However, the known limitations of systemic toxicity, drug resistance, poor targeted delivery, and inability to access the blood-brain barrier (BBB), make these treatments less satisfactory. Other treatment options have been investigated in many studies in the literature, especially nutraceutical and naturopathic products, most of which have also been reported to be poorly effective against these cancer types. This necessitates the development of treatment strategies with the potential to cross the BBB and specifically target cancer cells. Compounds that target the endopeptidase, matrix metalloproteinase 2 (MMP-2), have been reported to offer therapeutic insights for GB and NB since MMP-2 is known to be over-expressed in these cancers and plays significant roles in such physiological processes as angiogenesis, metastasis, and cellular invasion. Chlorotoxin (CTX) is a promising 36-amino acid peptide isolated from the venom of the deathstalker scorpion, Leiurus quinquestriatus, demonstrating high selectivity and binding affinity to a broad-spectrum of cancers, especially GB and NB through specific molecular targets, including MMP-2. The favorable characteristics of nanoparticles (NPs) such as their small sizes, large surface area for active targeting, BBB permeability, etc. make CTX-functionalized NPs (CTX-NPs) promising diagnostic and therapeutic applications for addressing the many challenges associated with these cancers. CTX-NPs may function by improving diffusion through the BBB, enabling increased localization of chemotherapeutic and genotherapeutic drugs to diseased cells specifically, enhancing imaging modalities such as magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), optical imaging techniques, image-guided surgery, as well as improving the sensitization of radio-resistant cells to radiotherapy treatment. This review discusses the characteristics of GB and NB cancers, related treatment challenges as well as the potential of CTX and its functionalized NP formulations as targeting systems for diagnostic, therapeutic, and theranostic purposes. It also provides insights into the potential mechanisms through which CTX crosses the BBB to bind cancer cells and provides suggestions for the development and application of novel CTX-based formulations for the diagnosis and treatment of GB and NB in the future.

An N6-methyladenosine regulation- and mRNAsi-related prognostic index reveals the distinct immune microenvironment and immunotherapy responses in lower-grade glioma

BACKGROUND

N6-methyladenosine (m6A) modification is involved in tumorigenesis and progression as well as closely correlated with stem cell differentiation and pluripotency. Moreover, tumor progression includes the acquisition of stemness characteristics and accumulating loss of differentiation phenotype. Therefore, we integrated m6A modification and stemness indicator mRNAsi to classify patients and predict prognosis for LGG.

METHODS

We performed consensus clustering, weighted gene co-expression network analysis, and least absolute shrinkage and selection operator Cox regression analysis to identify an m6A regulation- and mRNAsi-related prognostic index (MRMRPI). Based on this prognostic index, we also explored the differences in immune microenvironments between high- and low-risk populations. Next, immunotherapy responses were also predicted. Moreover, single-cell RNA sequencing data was further used to verify the expression of these genes in MRMRPI. At last, the tumor-promoting and tumor-associated macrophage polarization roles of TIMP1 in LGG were validated by in vitro experiments.

RESULTS

Ten genes (DGCR10, CYP2E1, CSMD3, HOXB3, CABP4, AVIL, PTCRA, TIMP1, CLEC18A, and SAMD9) were identified to construct the MRMRPI, which was able to successfully classify patients into high- and low-risk group. Significant differences in prognosis, immune microenvironment, and immunotherapy responses were found between distinct groups. A nomogram integrating the MRMRPI and other prognostic factors were also developed to accurately predict prognosis. Moreover, in vitro experiments illustrated that inhibition of TIMP1 could inhibit the proliferation, migration, and invasion of LGG cells and also inhibit the polarization of tumor-associated macrophages.

CONCLUSION

These findings provide novel insights into understanding the interactions of m6A methylation regulation and tumor stemness on LGG development and contribute to guiding more precise immunotherapy strategies.

Surgical management of Glioma Grade 4: technical update from the neuro-oncology section of the Italian Society of Neurosurgery (SINch®): a systematic review

PURPOSE

The extent of resection (EOR) is an independent prognostic factor for overall survival (OS) in adult patients with Glioma Grade 4 (GG4). The aim of the neuro-oncology section of the Italian Society of Neurosurgery (SINch®) was to provide a general overview of the current trends and technical tools to reach this goal.

METHODS

A systematic review was performed. The results were divided and ordered, by an expert team of surgeons, to assess the Class of Evidence (CE) and Strength of Recommendation (SR) of perioperative drugs management, imaging, surgery, intraoperative imaging, estimation of EOR, surgery at tumor progression and surgery in elderly patients.

RESULTS

A total of 352 studies were identified, including 299 retrospective studies and 53 reviews/meta-analysis. The use of Dexamethasone and the avoidance of prophylaxis with anti-seizure medications reached a CE I and SR A. A preoperative imaging standard protocol was defined with CE II and SR B and usefulness of an early postoperative MRI, with CE II and SR B. The EOR was defined the strongest independent risk factor for both OS and tumor recurrence with CE II and SR B. For intraoperative imaging only the use of 5-ALA reached a CE II and SR B. The estimation of EOR was established to be fundamental in planning postoperative adjuvant treatments with CE II and SR B and the stereotactic image-guided brain biopsy to be the procedure of choice when an extensive surgical resection is not feasible (CE II and SR B).

CONCLUSIONS

A growing number of evidences evidence support the role of maximal safe resection as primary OS predictor in GG4 patients. The ongoing development of intraoperative techniques for a precise real-time identification of peritumoral functional pathways enables surgeons to maximize EOR minimizing the post-operative morbidity.

Identification of thioredoxin domain containing family members' expression pattern and prognostic value in diffuse gliomas via in silico analysis

BACKGROUND

Gliomas are the most prevalent primary tumors of the central nervous system. Their aggressive nature and the obstacles arising during therapy highlights the importance of finding new prognostic markers and therapy targets for gliomas. TXNDC genes are members of the thioredoxin superfamily and were shown to play a role in redox homeostasis, protein folding, electron transfer and also acting as cellular adapters. The well known contribution of these processes in cancer progression prompted us to investigate if TXNDC family members may also play a role in carcinogenesis, in particular diffuse gliomas.

METHODS

The present study used in silico analysis tools GEPIA, UCSC Xena, Gliovis, cBioPortal, and Ivy GAP to evaluate the expression pattern, prognostic value and clinical significance of TXNDC family members in diffuse gliomas.

RESULTS

Our analysis showed that TXNDC family members' expression pattern differ between tumors and healthy tissues and among tumors with different grades. The detailed analysis of TXNDC5 in glioma pathogenesis revealed that TXNDC5 expression is associated with more aggressive clinical and molecular features and poor therapy success both in LGG and GBM samples. Kaplan-Meier survival curves represented a worse prognosis for patients with leveated TXNDC5 levels in LGG and all grade glioma patients. The levels of TXNDC5 was shown to be possibly regulated by hypoxia-ER stress axis and a potential mechanism for TXNDC5-driven glioma progression was found to be extracellular matrix (ECM) production which is known to promote tumor aggressiveness.

CONCLUSIONS

Our results uncovered the previously unknown role of TXNDC family members in glioma pathogenesis and showed that TXNDC5 levels could serve as a predictor of clinical outcome and therapy success and may very well be used for targeted therapy.

Low-grade epilepsy-associated neuroepithelial tumors: Tumor spectrum and diagnosis based on genetic alterations

Brain tumors can always result in seizures when involving the cortical neurons or their circuits, and they were found to be one of the most common etiologies of intractable focal seizures. The low-grade epilepsy-associated neuroepithelial tumors (LEAT), as a special group of brain tumors associated with seizures, share common clinicopathological features, such as seizure onsets at a young age, a predilection for involving the temporal lobe, and an almost benign course, including a rather slow growth pattern and thus a long-term history of seizures. Ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) are the typical representatives of LEATs. Surgical treatments with complete resection of tumors and related epileptogenic zones are deemed the optimal way to achieve postoperative seizure control and lifetime recurrence-free survival in patients with LEATs. Although the term LEAT was originally introduced in 2003, debates on the tumor spectrum and the diagnosis or classification of LEAT entities are still confusing among epileptologists and neuropathologists. In this review, we would further discuss these questions, especially based on the updated classification of central nervous system tumors in the WHO fifth edition and the latest molecular genetic findings of tumor entities in LEAT entities.

Systematic Analysis of a Pyroptosis-Related Signature to Predict the Prognosis and Immune Microenvironment of Lower-Grade Glioma

Current treatments for lower-grade glioma (LGG) do not effectively improve life expectancy rates, and this is a major global health concern. Improving our knowledge of this disease will ultimately help to improve prevention, accurate prognosis, and treatment strategies. Pyroptosis is an inflammatory form of regulated cell death, which plays an important role in tumor progression and occurrence. There is still a lack of effective markers to evaluate the prognosis of LGG patients. We collected paraffin-embedded tissue samples and prognostic information from 85 patients with low-grade gliomas and fabricated them into a tissue microarray. Combining data from public databases, we explored the relationship between pyroptosis-related genes (PRGs) and the prognoses of patients with LGG and investigated their correlations with the tumor microenvironment (TME) by means of machine learning, single-cell, immunohistochemical, nomogram, GSEA, and Cox regression analyses. We developed a six-gene PRG-based prognostic model, and the results have identified CASP4 as an effective marker for LGG prognosis predictions. Furthermore, the effects on immune cell infiltration may also provide guidance for future immunotherapy strategies.

Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Management of Low-Grade Gliomas and Radiation Necrosis: A Single-Institution Case Series

BACKGROUND

Laser interstitial thermal therapy (LITT) has emerged as a minimally invasive treatment modality for ablation of low-grade glioma (LGG) and radiation necrosis (RN).

OBJECTIVE

To evaluate the efficacy, safety, and survival outcomes of patients with radiographically presumed recurrent or newly diagnosed LGG and RN treated with LITT.

METHODS

The neuro-oncological database of a quaternary center was reviewed for all patients who underwent LITT for management of LGG between 1 January 2013 and 31 December 2020. Clinical data including demographics, lesion characteristics, and clinical and radiographic outcomes were collected. Kaplan-Meier analyses comprised overall survival (OS) and progression-free survival (PFS).

RESULTS

Nine patients (7 men, 2 women; mean [SD] age 50 [16] years) were included. Patients underwent LITT at a mean (SD) of 11.6 (8.5) years after diagnosis. Two (22%) patients had new lesions on radiographic imaging without prior treatment. In the other 7 patients, all (78%) had surgical resection, 6 (67%) had intensity-modulated radiation therapy and chemotherapy, respectively, and 4 (44%) had stereotactic radiosurgery. Two (22%) patients had lesions that were wild-type IDH1 status. Volumetric assessment of preoperative T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences yielded mean (SD) lesion volumes of 4.1 (6.5) cm³ and 26.7 (27.9) cm³, respectively. Three (33%) patients had evidence of radiographic progression after LITT. The pooled median (IQR) PFS for the cohort was 52 (56) months, median (IQR) OS after diagnosis was 183 (72) months, and median (IQR) OS after LITT was 52 (60) months. At the time of the study, 2 (22%) patients were deceased.

CONCLUSIONS

LITT is a safe and effective treatment option for management of LGG and RN, however, there may be increased risk of permanent complications with treatment of deep-seated subcortical lesions.

New perspectives in liquid biopsy for glioma patients

PURPOSE OF REVIEW

Gliomas are the most common primary tumors of the central nervous system. They are characterized by a disappointing prognosis and ineffective therapy that has shown no substantial improvements in the past 20 years. The lack of progress in treating gliomas is linked with the inadequacy of suitable tumor samples to plan translational studies and support laboratory developments. To overcome the use of tumor tissue, this commentary review aims to highlight the potential for the clinical application of liquid biopsy (intended as the study of circulating biomarkers in the blood), focusing on circulating tumor cells, circulating DNA and circulating noncoding RNA.

RECENT FINDINGS

Thanks to the increasing sensitivity of sequencing techniques, it is now possible to analyze circulating nucleic acids and tumor cells (liquid biopsy).

SUMMARY

Although studies on the use of liquid biopsy are still at an early stage, the potential clinical applications of liquid biopsy in the study of primary brain cancer are many and have the potential to revolutionize the approach to neuro-oncology, and importantly, they offer the possibility of gathering information on the disease at any time during its history.

Identification of Prognostic Signature of Necroptosis-Related lncRNAs and Molecular Subtypes in Glioma

Background

In tumor progression and epigenetic regulation, long non-coding RNA (lncRNA) and necroptosis are crucial regulators. However, in glioma microenvironment, the role of necroptosis-related lncRNAs (NRLs) remains unknown.

Method

In this study, the RNA-seq and clinical annotation of glioma patients were analyzed using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To investigate prognosis and tumor microenvironment of NRLs in gliomas, we conducted a prediction model based on the training cohort. The accuracy of the model was verified in the verification cohort.

Results

A signature composed of 13 NRLs was identified, and all glioma patients were divided into two groups. We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status. The necroptosis-related lncRNA signature (NRLS) model was found to be an independent risk factor in multivariate Cox analysis. Immunosuppressive microenvironment was positively correlated with the high-risk group. Due to significantly different IC50 between risk groups, NRLS could be used as a guide for chemotherapeutic treatment. Further, the entire cohort was divided into two clusters depending on NRLs. Consensus clustering method and the risk scoring system were basically similar. Survival probability was higher in Cluster 2, while Cluster 1 has stronger immunologic infiltration.

Conclusion

The predictive signature could be a prognostic factor independently and serve to detect the role of NRLs in glioma immunotherapy response.

Full-course resection control strategy in glioma surgery using both intraoperative ultrasound and intraoperative MRI

Background

Intraoperative ultrasound(iUS) and intraoperative MRI (iMRI) are effective ways to perform resection control during glioma surgery. However, most published studies employed only one modality. Few studies have used both during surgery. How to combine these two techniques reasonably, and what advantages they could have for glioma surgery are still open questions.

Methods

We retrospectively reviewed a series of consecutive patients who underwent initial surgical treatment of supratentorial gliomas in our center. We utilized a full-course resection control strategy to combine iUS and iMRI: IUS for pre-resection assessment and intermediate resection control; iMRI for final resection control. The basic patient characteristics, surgical results, iMRI/iUS findings, and their impacts on surgical procedures were evaluated and reported.

Results

A total of 40 patients were included. The extent of resection was 95.43 ± 10.37%, and the gross total resection rate was 72.5%. The median residual tumor size was 6.39 cm3 (range 1.06–16.23 cm3). 5% (2/40) of patients had permanent neurological deficits after surgery. 17.5% (7/40) of patients received further resection after the first iMRI scan, resulting in four (10%) more patients achieving gross total resection. The number of iMRI scans per patient was 1.18 ± 0.38. The surgical time was 4.5 ± 3.6 hours. The pre-resection iUS scan revealed that an average of 3.8 borders of the tumor were beside sulci in 75% (30/40) patients. Intermediate resection control was utilized in 67.5% (27/40) of patients. In 37.5% (15/40) of patients, the surgical procedures were changed intraoperatively based on the iUS findings. Compared with iMRI, the sensitivity and specificity of iUS for residual tumors were 46% and 96%, respectively.

Conclusion

The full-course resection control strategy by combining iUS and iMRI could be successfully implemented with good surgical results in initial glioma surgeries. This strategy might stabilize resection control quality and provide the surgeon with more intraoperative information to tailor the surgical strategy. Compared with iMRI-assisted glioma surgery, this strategy might improve efficiency by reducing the number of iMRI scans and shortening surgery time.

CCR5 as a Prognostic Factor in Lower-Grade Glioma is Involved in the Remodeling of the Tumor Microenvironment

Background: Lower-grade gliomas (LGGs) carry a high risk of malignant transformation, leading to severe neurologic deterioration and ultimately, death. The tumor microenvironment (TME) plays an essential role in tumor maintenance, progression, and immunotherapy resistance. Therefore, the LGG TME deserves comprehensive exploration for a novel therapeutic target.

Methods: The ESTIMATE algorithm was used to estimate infiltrating stromal and immune cells of LGG patients obtained from the Cancer Genome Atlas (TCGA) database. Kaplan–Meier analysis was performed to classify survival differences. TME-related differentially expressed genes were identified between the low- and high-immune/stromal groups. Hub genes were screened by constructing protein–protein interaction networks and performing the Cox regression analysis. Differential analysis, survival analysis, gene set enrichment analysis, and clinical relevance analysis specific to hub genes were evaluated by using the TCGA and the Chinese Glioma Genome Atlas datasets, and the results were validated by qRT-PCR, Western blotting, and immunohistochemistry in tissues from LGG patients.

Results: The immune and stromal components in TME were negatively related to patient prognosis. Differentially expressed genes sharing immune score and stromal score were mainly involved in the immune response. C-C chemokine receptor type 5 (CCR5), as only a hub gene, was significantly higher in LGG patients than normal patients and negatively correlated with the prognosis of patients. High-expression CCR5 was positively related to immune-related and tumor progression pathways. CCR5 protein expression was higher in LGG with isocitrate dehydrogenase wildtype. Validated results showed that CCR5 was upregulated in LGG tissues at mRNA and protein levels and could affect immune cell infiltration. These results suggested that CCR5 was a potential indicator for the status of TME.

Conclusion: Glioma cells remodel the immune microenvironment through the high expression of CCR5 and lead to a poor prognosis in patients with LGG. The inhibition of CCR5 may contribute to the efficacy of LGG immunotherapy.

Comprehensive Characterization of a Novel E3-Related Gene Signature With Implications in Prognosis and Immunotherapy of Low-Grade Gliomas

Gliomas, a type of primary brain tumor, have emerged as a threat to global mortality due to their high heterogeneity and mortality. A low-grade glioma (LGG), although less aggressive compared with glioblastoma, still exhibits high recurrence and malignant progression. Ubiquitination is one of the most important posttranslational modifications that contribute to carcinogenesis and cancer recurrence. E3-related genes (E3RGs) play essential roles in the process of ubiquitination. Yet, the biological function and clinical significance of E3RGs in LGGs need further exploration. In this study, differentially expressed genes (DEGs) were screened by three differential expression analyses of LGG samples from The Cancer Genome Atlas (TCGA) database. DEGs with prognostic significance were selected by the univariate Cox regression analysis and log-rank statistical test. The LASSO-COX method was performed to identify an E3-related prognostic signature consisting of seven genes AURKA, PCGF2, MAP3K1, TRIM34, PRKN, TLE3, and TRIM17. The Chinese Glioma Genome Atlas (CGGA) dataset was used as the validation cohort. Kaplan–Meier survival analysis showed that LGG patients in the low-risk group had significantly higher overall survival time than those in the high-risk group in both TCGA and CGGA cohorts. Furthermore, multivariate Cox regression analysis revealed that the E3RG signature could be used as an independent prognostic factor. A nomogram based on the E3RG signature was then established and provided the prediction of the 1-, 3-, and 5-year survival probability of patients with LGGs. Moreover, DEGs were analyzed based on the risk signature, on which function analyses were performed. GO and KEGG analyses uncovered gene enrichment in extracellular matrix–related functions and immune-related biological processes in the high-risk group. GSEA revealed high enrichment in pathways that promote tumorigenesis and progression in the high-risk group. Furthermore, ESTIMATE algorithm analysis showed a significant difference in immune and stroma activity between high- and low-risk groups. Positive correlations between the risk signature and the tumor microenvironment immune cell infiltration and immune checkpoint molecules were also observed, implying that patients with the high-risk score may have better responses to immunotherapy. Overall, our findings might provide potential diagnostic and prognostic markers for LGG patients and offer meaningful insight for individualized treatment.

Characterization of aging tumor microenvironment with drawing implications in predicting the prognosis and immunotherapy response in low-grade gliomas

Aging tumor microenvironment (aging TME) is emerging as a hot spot in cancer research for its significant roles in regulation of tumor progression and tumor immune response. The immune and stromal scores of low-grade gliomas (LGGs) from TCGA and CGGA databases were determined by using ESTIMATE algorithm. Differentially expressed genes (DEGs) between high and low immune/stromal score groups were identified. Subsequently, weighted gene co-expression network analysis (WGCNA) was conducted to screen out aging TME related signature (ATMERS). Based on the expression patterns of ATMERS, LGGs were classified into two clusters with distinct prognosis via consensus clustering method. Afterwards, the aging TME score for each sample was calculated via gene set variation analysis (GSVA). Furthermore, TME components were quantified by MCP counter and CIBERSORT algorithm. The potential response to immunotherapy was evaluated by Tumor Immune Dysfunction and Exclusion analysis. We found that LGG patients with high aging TME scores showed poor prognosis, exhibited an immunosuppressive phenotype and were less likely to respond to immunotherapy compared to those with low scores. The predictive performance of aging TME score was verified in three external datasets. Finally, the expression of ATMERS in LGGs was confirmed at protein level through the Human Protein Atlas website and western blot analysis. This novel aging TME-based scoring system provided a robust biomarker for predicting the prognosis and immunotherapy response in LGGs.

Surveillance imaging frequency in adult patients with lower-grade (WHO Grade 2 and 3) gliomas

With improved outcome following aggressive treatment in patients with grade 2 and 3 IDH-mutant (IDHmt), 1p/19q codeleted oligodendroglioma and IDHmt, non-codeleted astrocytoma, prolonged surveillance is desirable for early detection of tumor growth and malignant transformation. Current National Comprehensive Cancer Network (NCCN) guidelines provide imaging follow-up recommendations based on molecular classification of lower-grade gliomas, although individualized imaging guidelines based on treatments received and after tumor recurrence are not clearly specified. Other available guidelines have yet to incorporate the molecular biomarkers that inform the WHO classification of gliomas, and in some cases do not adequately consider current knowledge on IDHmt glioma growth rate and recurrence patterns. Moreover, these guidelines also do not provide specific recommendations for concerning clinical symptoms or radiographic findings warranting imaging studies out of prespecified intervals. Focusing on molecularly defined grade 2 and 3 IDHmt astrocytomas and oligodendrogliomas, we review current knowledge of tumor growth rates and time to tumor progression for each tumor type and propose a range of recommended MRI surveillance intervals for both the newly diagnosed and recurrent tumor setting. Additionally, we summarize situations in which imaging is advisable outside of these intervals.

Fluorescent diagnostics with chlorin e6 in surgery of low-grade glioma

Intraoperative fluorescence diagnostics of high-grade gliomas is widely used in neurosurgical practice. This work analyzes the possibilities of fluorescence diagnostics for low-grade gliomas (LGG) using chlorin e6 photosensitizer. The study included patients with newly diagnosed LGG, for whom chlorin e6 was used for intraoperative fluorescence control at a dose of 1 mg/kg. During the operation, the fluorescence intensity of various areas of the putative tumor tissue was analyzed using the RSS Cam – Endo 1.4.313 software. Tissue samples with various degrees of fluorescence intensity were compared with the results of their histopathological analysis (WHO tumor diagnosis, Ki-67 index, P53, VEGF). Fluorescence was detected in more than half of the cases, but in most cases had a focal character and low fluorescence intensity. The fluorescence intensity directly correlated with the data of histopathological examination of tumor tissues (Ki-67 index (p=0.002), expression of P53 (p=0.0015) and VEGF (p=0.001)). The sensitivity of the method for LGG surgery was 72%, the specificity was 56,7%. Intraoperative fluorescence diagnostics with chlorin e6 can be used in LGG surgery, especially to visualize intratumoral areas with a higher degree of anaplasia.

Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition

Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at the forefront of large-scale data acquisition and well positioned towards both the production and analysis of large-scale oncologic data with the potential for clinically driven endpoints and advancement of patient outcomes. Neuro-oncology is comprised of malignancies that often carry poor prognosis and significant neurological sequelae. The analysis of radiation therapy mediated treatment and the potential for computationally mediated analyses may lead to more precise therapy by employing large scale data. We analysed the state of the literature pertaining to large scale data, computational analysis, and the advancement of molecular biomarkers in neuro-oncology with emphasis on radiation oncology. We aimed to connect existing and evolving approaches to realistic avenues for clinical implementation focusing on low grade gliomas (LGG), high grade gliomas (HGG), management of the elderly patient with HGG, rare central nervous system tumors, craniospinal irradiation, and re-irradiation to examine how computational analysis and molecular science may synergistically drive advances in personalised radiation therapy (RT) and optimise patient outcomes.

Optimal Combinations of Chemotherapy and Radiotherapy in Low-Grade Gliomas: A Mathematical Approach

Low-grade gliomas (LGGs) are brain tumors characterized by their slow growth and infiltrative nature. Treatment options for these tumors are surgery, radiation therapy and chemotherapy. The optimal use of radiation therapy and chemotherapy is still under study. In this paper, we construct a mathematical model of LGG response to combinations of chemotherapy, specifically to the alkylating agent temozolomide and radiation therapy. Patient-specific parameters were obtained from longitudinal imaging data of the response of real LGG patients. Computer simulations showed that concurrent cycles of radiation therapy and temozolomide could provide the best therapeutic efficacy in-silico for the patients included in the study. The patient cohort was extended computationally to a set of 3000 virtual patients. This virtual cohort was subject to an in-silico trial in which matching the doses of radiotherapy to those of temozolomide in the first five days of each cycle improved overall survival over concomitant radio-chemotherapy according to RTOG 0424. Thus, the proposed treatment schedule could be investigated in a clinical setting to improve combination treatments in LGGs with substantial survival benefits.

Fluorescence Lifetime Imaging and Spectroscopic Co-Validation for Protoporphyrin IX-Guided Tumor Visualization in Neurosurgery

Maximal safe resection is a key strategy for improving patient prognosis in the management of brain tumors. Intraoperative fluorescence guidance has emerged as a standard in the surgery of high-grade gliomas. The administration of 5-aminolevulinic acid prior to surgery induces tumor-specific accumulation of protoporphyrin IX, which emits red fluorescence under blue-light illumination. The technology, however, is substantially limited for low-grade gliomas and weakly tumor-infiltrated brain, where low protoporphyrin IX concentrations are outweighed by tissue autofluorescence. In this context, fluorescence lifetime imaging has shown promise to distinguish spectrally overlapping fluorophores. We integrated frequency-domain fluorescence lifetime imaging in a surgical microscope and combined it with spatially registered fluorescence spectroscopy, which can be considered a research benchmark for sensitive protoporphyrin IX detection. Fluorescence lifetime maps and spectra were acquired for a representative set of fresh ex-vivo brain tumor specimens (low-grade gliomas n = 15, high-grade gliomas n = 80, meningiomas n = 41, and metastases n = 35). Combining the fluorescence lifetime with fluorescence spectra unveiled how weak protoporphyrin IX accumulations increased the lifetime respective to tissue autofluorescence. Infiltration zones (4.1ns ± 1.8ns, p = 0.017) and core tumor areas (4.8ns ± 1.3ns, p = 0.040) of low-grade gliomas were significantly distinguishable from non-pathologic tissue (1.6ns ± 0.5ns). Similarly, fluorescence lifetimes for infiltrated and reactive tissue as well as necrotic and core tumor areas were increased for high-grade gliomas and metastasis. Meningioma tumor specimens showed strongly increased lifetimes (12.2ns ± 2.5ns, p = 0.005). Our results emphasize the potential of fluorescence lifetime imaging to optimize maximal safe resection in brain tumors in future and highlight its potential toward clinical translation.

5-ALA in Suspected Low-Grade Gliomas: Current Role, Limitations, and New Approaches

Radiologically suspected low-grade gliomas (LGG) represent a special challenge for the neurosurgeon during surgery due to their histopathological heterogeneity and indefinite tumor margin. Therefore, new techniques are required to overcome these current surgical drawbacks. Intraoperative visualization of brain tumors with assistance of 5-aminolevulinic acid (5-ALA) induced protoporphyrin IX (PpIX) fluorescence is one of the major advancements in the neurosurgical field in the last decades. Initially, this technique was exclusively applied for fluorescence-guided surgery of high-grade glioma (HGG). In the last years, the use of 5-ALA was also extended to other indications such as radiologically suspected LGG. Here, we discuss the current role of 5-ALA for intraoperative visualization of focal malignant transformation within suspected LGG. Furthermore, we discuss the current limitations of the 5-ALA technology in pure LGG which usually cannot be visualized by visible fluorescence. Finally, we introduce new approaches based on fluorescence technology for improved detection of pure LGG tissue such as spectroscopic PpIX quantification fluorescence lifetime imaging of PpIX and confocal microscopy to optimize surgery.

Colen R, Zinn PO. MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift

Low-grade gliomas (LGGs) are tumors that affect mostly adults. These neoplasms are comprised mainly of oligodendrogliomas and diffuse astrocytomas. LGGs remain vexing to current management and therapeutic modalities although they exhibit more favorable survival rates compared with high-grade gliomas (HGGs). The specific genetic subtypes that these tumors exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of an LGG pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). The introduction of radiomics as a high throughput quantitative imaging technique that allows for improved diagnostic, prognostic and predictive indices has created more interest for such techniques in cancer research and especially in neurooncology (MRI-based classification of LGGs, predicting Isocitrate dehydrogenase (IDH) and Telomerase reverse transcriptase (TERT) promoter mutations and predicting LGG associated seizures). Radiogenomics refers to the linkage of imaging findings with the tumor/tissue genomics. Numerous applications of radiomics and radiogenomics have been described in the clinical context and management of LGGs. In this review, we describe the recently published studies discussing the potential application of radiomics and radiogenomics in LGGs. We also highlight the potential pitfalls of the above-mentioned high throughput computerized techniques and, most excitingly, explore the use of machine learning artificial intelligence technologies as standalone and adjunct imaging tools en route to enhance a personalized MRI-based tumor diagnosis and management plan design.

First-line antiepileptic drug treatment in glioma patients with epilepsy: Levetiracetam vs valproic acid

Objective

This study aimed at estimating the cumulative incidence of antiepileptic drug (AED) treatment failure of first‐line monotherapy levetiracetam vs valproic acid in glioma patients with epilepsy.

Methods

In this retrospective observational study, a competing risks model was used to estimate the cumulative incidence of treatment failure, from AED treatment initiation, for the two AEDs with death as a competing event. Patients were matched on baseline covariates potentially related to treatment assignment and outcomes of interest according to the nearest neighbor propensity score matching technique. Maximum duration of follow‐up was 36 months.

Results

In total, 776 patients using levetiracetam and 659 using valproic acid were identified. Matching resulted in two equal groups of 429 patients, with similar covariate distribution. The cumulative incidence of treatment failure for any reason was significantly lower for levetiracetam compared to valproic acid (12 months: 33% [95% confidence interval (CI) 29%–38%] vs 50% [95% CI 45%–55%]; P < .001). When looking at specific reasons of treatment failure, treatment failure due to uncontrolled seizures was significantly lower for levetiracetam compared to valproic acid (12 months: 16% [95% CI 12%–19%] vs 28% [95% CI 23%–32%]; P < 0.001), but no differences were found for treatment failure due to adverse effects (12 months: 14% [95% CI 11%–18%] vs 15% [95% CI 11%–18%]; P = .636).

Significance

Our results suggest that levetiracetam may have favorable efficacy compared to valproic acid, whereas level of toxicity seems similar. Therefore, levetiracetam seems to be the preferred choice for first‐line AED treatment in patients with glioma.

A New Epigenetic Model to Stratify Glioma Patients According to Their Immunosuppressive State

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

Risk Assessment by Pre-surgical Tractography in Left Hemisphere Low-Grade Gliomas

Background: Tracking the white matter principal tracts is routinely typically included during the pre-surgery planning examinations and has revealed to limit functional resection of low-grade gliomas (LGGs) in eloquent areas.

Objective: We examined the integrity of the Superior Longitudinal Fasciculus (SLF) and Inferior Fronto-Occipital Fasciculus (IFOF), both known to be part of the language-related network in patients with LGGs involving the temporo-insular cortex. In a comparative approach, we contrasted the main quantitative fiber tracking values in the tumoral (T) and healthy (H) hemispheres to test whether or not this ratio could discriminate amongst patients with different post-operative outcomes.

Methods: Twenty-six patients with LGGs were included. We obtained quantitative fiber tracking values in the tumoral and healthy hemispheres and calculated the ratio (H_IFOF–T_IFOF)/H_IFOF and the ratio (H_SLF–T_SLF)/H_SLF on the number of streamlines. We analyzed how these values varied between patients with and without post-operative neurological outcomes and between patients with different post-operative Engel classes.

Results: The ratio for both IFOF and SLF significantly differed between patient with and without post-operative neurological language deficits. No associations were found between white matter structural changes and post-operative seizure outcomes.

Conclusions: Calculating the ratio on the number of streamlines and fractional anisotropy between the tumoral and the healthy hemispheres resulted to be a useful approach, which can prove to be useful during the pre-operative planning examination, as it gives a glimpse on the potential clinical outcomes in patients with LGGs involving the left temporo-insular cortex.

Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Simple Summary

Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored.

Abstract

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.