Peritumoral edema shown by MRI predicts poor clinical outcome in glioblastoma

The apparent diffusion coefficient can serve as a predictor of survival in patients with gliomas

BACKGROUND AND PURPOSE

Magnetic resonance imaging is indispensable for the preoperative diagnosis of glioma. This study aimed to investigate the role of the apparent diffusion coefficient values as predictors of survival in patients with gliomas.

METHODS AND MATERIALS

A retrospective analysis was conducted on 101 patients with gliomas who underwent surgery between 2015 and 2020. Diffusion-weighted MRI was performed before the surgery. The regions of interest were categorized into parenchymal area, non-enhancing peritumoral area, and necrotic or cystic area. All the patients were divided into three subgroups: the parenchyma group, the non-enhancing peritumoral signal abnormality group, and the necrosis or cyst group. Univariate and multivariate analyses were performed using COX regression.

RESULTS

In the parenchymal group, Ki67, P53, IDH, and the high or low ADC values were identified as independent prognosticators for disease-free survival, while Ki67, IDH, and the high or low ADC values for overall survival. In the non-enhancing peritumoral signal abnormality group, Ki67, P53, IDH, and the ADC parenchymal area/ADC non-enhancing peritumoral area ratio were identified as independent prognostic factors for disease-free survival, while Ki67, IDH, and the ADC parenchymal area/ADC non-enhancing peritumoral area ratio for overall survival. In the necrosis or cyst group, Ki67 was significantly associated with disease-free survival, while Ki67 and the ADC value of the necrotic or cystic area for overall survival.

CONCLUSIONS

The ADC values, including the ADC value in the parenchymal area, the ADC parenchymal area/ADC non-enhancing peritumoral area ratio, and the ADC value in the necrotic or cystic area, can serve as an efficient and potential index for predicting the survival of patients with glioma.

Claudin and transmembrane receptor protein gene expressions are reversely correlated in peritumoral brain edema

INTRODUCTION

Peritumoral brain edema (PTBE) has been widely reported with many brain tumors, especially with glioma. Since the blood-brain barrier (BBB) is essential for maintaining minimal permeability, any alteration in the interaction of BBB components, specifically in astrocytes and tight junctions (TJ), can result in disrupting the homeostasis of the BBB and making it severely leaky, which subsequently generates edema.

OBJECTIVE

This study aimed to evaluate the functional gliovascular unit of the BBB by examining changes in the expression of claudin (CLDN) genes and the expression of transient receptor potential (TRP) membrane channels, additionally to define the correlation between their expressions. The evaluation was conducted using in vitro spheroid swelling models and tumor samples from glioma patients with PTBE.

RESULTS

The results of the spheroid model showed that the genes TRPC3, TRPC4, TRPC5, and TRPV1 were upregulated in glioma cells either wild-type isocitrate dehydrogenase 1 (IDH1) or the IDH1 R132H mutant, with or without NaCl treatment. Furthermore, TRP genes appeared to adversely correlate with the up regulation of CLDN1, CLDN3, and CLDN5 genes. Besides, the upregulation of TRPC1 and TRPC4 in IDH1mt-R132H glioma cells. On the other hand, the correlation analysis revealed different correlations between different proteins in PTBE. CLDN1 exhibits a slight positive correlation with CLDN3. Similarly, TRPV1 displays a slight positive correlation with TRPC1. In contrast, TRPC4 shows a slight negative correlation with TRPC5. On the other hand, TRPC3 demonstrates a slight positive correlation with TRPC5, while the non-PTBE analysis highlights a moderate positive correlation between CLDN1 and TRPM4 while CLDN3 exhibits a moderate negative correlation with TRPC4. Additionally, CLDN5 demonstrates a slight negative correlation with TRPC4 but a moderate positive correlation with TRPC3. Furthermore, TRPC1 have a slight negative correlation with TRPV1, TRPC3 exhibiting a slight positive correlation with TRPC4, and TRPV1 showing a slight negative correlation with TRPC5.

CONCLUSION

As a conclusion, the current study provided evidence of a slight negative correlation between TRPs and CLDN gene expression in PTBE patients and confirmatory results with some of the genes in cell model of edema.

Pleomorphic Xanthoastrocytoma: Multi-Institutional Evaluation of Stereotactic Radiosurgery

BACKGROUND AND OBJECTIVES

Pleomorphic xanthoastrocytoma (PXA) is a rare low-grade glial tumor primarily affecting young individuals. Surgery is the primary treatment option; however, managing residual/recurrent tumors remains uncertain. This international multi-institutional study retrospectively assessed the use of stereotactic radiosurgery (SRS) for PXA.

METHODS

A total of 36 PXA patients (53 tumors) treated at 11 institutions between 1996 and 2023 were analyzed. Data included demographics, clinical variables, SRS parameters, tumor control, and clinical outcomes. Kaplan-Meier estimates summarized the local control (LC), progression-free survival, and overall survival (OS). Secondary end points addressed adverse radiation effects and the risk of malignant transformation. Cox regression analysis was used.

RESULTS

A total of 38 tumors were grade 2, and 15 tumors were grade 3. Nine patients underwent initial gross total resection, and 10 received adjuvant therapy. The main reason for SRS was residual tumors (41.5%). The median follow-up was 34 months (range, 2-324 months). LC was achieved in 77.4% of tumors, with 6-month, 1-year, and 2-year LC estimates at 86.7%, 82.3%, and 77.8%, respectively. Younger age at SRS (hazard ratios [HR] 3.164), absence of peritumoral edema (HR 4.685), and higher marginal dose (HR 6.190) were significantly associated with better LC. OS estimates at 1, 2, and 5 years were 86%, 74%, and 49.3%, respectively, with a median OS of 44 months. Four patients died due to disease progression. Radiological adverse radiation effects included edema (n = 8) and hemorrhagic change (n = 1). One grade 3 PXA transformed into glioblastoma 13 months after SRS.

CONCLUSION

SRS offers promising outcomes for PXA management, providing effective LC, reasonable progression-free survival, and minimal adverse events.

A Monte Carlo simulation-based decision support system for radiation oncologists in the treatment of glioblastoma multiforme

In the present research, we have developed a model-based crisp logic function statistical classifier decision support system supplemented with treatment planning systems for radiation oncologists in the treatment of glioblastoma multiforme (GBM). This system is based on Monte Carlo radiation transport simulation and it recreates visualization of treatment environments on mathematical anthropomorphic brain (MAB) phantoms. Energy deposition within tumour tissue and normal tissues are graded by quality audit factors which ensure planned dose delivery to tumour site thereby minimising damages to healthy tissues. The proposed novel methodology predicts tumour growth response to radiation therapy from a patient-specific medicine quality audit perspective. Validation of the study was achieved by recreating thirty-eight patient-specific mathematical anthropomorphic brain phantoms of treatment environments by taking into consideration density variation and composition of brain tissues. Dose computations accomplished through water phantom, tissue-equivalent head phantoms are neither cost-effective, nor patient-specific customized and is often less accurate. The above-highlighted drawbacks can be overcome by using open-source Electron Gamma Shower (EGSnrc) software and clinical case reports for MAB phantom synthesis which would result in accurate dosimetry with due consideration to the time factors. Considerable dose deviations occur at the tumour site for environments with intraventricular glioblastoma, haematoma, abscess, trapped air and cranial flaps leading to quality factors with a lower logic value of 0. Logic value of 1 depicts higher dose deposition within healthy tissues and also leptomeninges for majority of the environments which results in radiation-induced laceration.

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics

Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.

Homeostatic status of thyroid hormones and brain water movement as determinant factors in biology of cerebral gliomas: a pilot study using a bioinformatics approach

Introduction

The expression and localization of the water channel transporters, aquaporins (AQPs), in the brain are substantially modified in gliomas during tumorigenesis, cell migration, edema formation, and resolution. We hypothesized that the molecular changes associated with AQP1 and AQP4 in the brain may potentially be anticancer therapeutic targets. To test this hypothesis, a bioinformatics analysis of publicly available data from international consortia was performed.

Methods

We used RNA-seq as an experimental strategy and identified the number of differential AQP1 and AQP4 transcript expressions in glioma tissue compared to normal brain tissue.

Results

AQPs genes are overexpressed in patients with glioma. Among the glioma subtypes, AQP1 and AQP4 were overexpressed in astrocytoma (low-grade glioma) and classical (high-grade glioma). Overall survival analysis demonstrated that both AQP genes can be used as prognostic factors for patients with low-grade glioma. Additionally, we observed a correlation between the expression of genes involved in the tyrosine and thyroid hormone pathways and AQPs, namely: PNMT, ALDH1A3, AOC2, HGDATP1B1, ADCY5, PLCB4, ITPR1, ATP1A3, LRP2, HDAC1, MED24, MTOR, and ACTB1 (Spearman's coefficient = geq 0.20 and p-value = ≤ 0.05).

Conclusion

Our findings indicate that the thyroid hormone pathways and AQPs 1 and 4 are potential targets for new anti-tumor drugs and therapeutic biomarkers for malignant gliomas.

Exploring prognostic factors and treatment strategies for long-term survival in pleomorphic xanthoastrocytoma patients

Pleomorphic xanthoastrocytomas (PXA) are rare, accounting for < 1% of all astrocytomas. Literature on the clinical course and treatment outcomes of PXAs is limited. The study aimed to determine prognosis and treatment strategies for PXAs. Patients who had PXAs surgery between 2000-2021 were retrospectively analyzed for demographics and radiological characteristics. Initial and salvage treatment outcomes were recorded. Overall, 40 and 9 patients had grade 2 and 3 PXAs; their 5-year progression-free survival (PFS) rates were 75.8% and 37.0%, respectively (p = 0.003). Univariate analysis revealed that strong T1 enhancement (p = 0.036), infiltrative tumor margins (p < 0.001), peritumoral edema (p = 0.003), WHO grade (p = 0.005), and gross total resection (p = 0.005) affected the PFS. Multivariate analysis revealed that the WHO grade (p = 0.010) and infiltrative tumor margins (p = 0.008) influenced the PFS. The WHO grade (p = 0.027) and infiltrative tumor margins (p = 0.027) also affected the overall survival (OS). Subgroup analysis for grade 2 PXAs revealed no significant associations between adjuvant radiation therapy and the PFS and OS. This study highlighted the heterogeneous nature of PXAs and its impact on patient prognosis. Infiltrative tumor margins emerged as a key prognostic factor. Our findings have emphasized the prognostic relevance of radiological features and the need for larger studies on comprehensive management.

The Impact of Extensive Surgical Resection of Butterfly Glioblastomas on Outcomes in the Presence of TERT Mutation and EGFR Amplification: A Retrospective Cohort Study

BACKGROUND AND OBJECTIVES

This study aimed to assess if extensive surgical resection enhances outcomes in wild-type Isocitrate Dehydrogenase (IDH) butterfly glioblastoma (B-GBM) patients, despite the presence of Telomerase Reverse Transcriptase (TERT) mutation and Epidermal Growth Factor Receptor (EGFR) amplification.

METHODS

The study, retrospectively conducted from 2014 to 2022, involved 723 GBM patients, 41 of whom met the criteria for IDH wild-type B-GBM. Exclusion criteria comprised prior diagnoses or treatments for low-grade glial tumors. Surgeons, employing two approaches-partial and extensive surgery-categorized patients based on age, sex, tumor location, corpus callosum involvement, and genetic characteristics. The interval between initial surgery and tumor recurrence/tumor-free period (TR/TFP) and overall survival (OS) were recorded and compared between the partial and extensive resection groups, analyzing the impact of resection width on TR/TFP and OS. Preoperative assessments utilized thin-section cranial computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI). Intraoperatively, tumor excision was guided by sodium fluorescein, and margins were delineated via neuronavigation. Genetic alterations (TERT mutations and EGFR amplifications) were correlated with surgical type, TR/TFP, and OS. Karnofsky Performance Scale (KPS) evaluations were performed pre- and post-operatively and at key intervals, comparing outcomes between surgical groups. Standard radiotherapy and chemotherapy regimens were administered to all patients.

RESULTS

Extensive resection yielded significantly longer TR/TFP compared to partial resection, despite TERT gene mutation and EGFR amplification being linked to shorter TR/TFP and OS. Its impact on OS, however, was not significant. KPS scores indicated a superior quality of life after extensive resection, with sustained improvement upon recurrence.

CONCLUSIONS

Extensive resection of B-GBM, even in the presence of adverse genetic alterations, may prolong TR/TFP, offering patients a period of improved comfort with minimal distress.

Expression and association of vascular endothelial growth factor, vascular endothelial growth factor receptor, and phosphorylated signal transducer and activator of transcription factor 3 in malignant gliomas

Objectives

Angiogenesis is one of the main characteristic features of malignant gliomas. Phosphorylated signal transducer and activator of transcription factor 3 (pSTAT3) is not only involved in glioma cell proliferation, anti-apoptosis, and immunosuppression but also plays a key role in cell migration and invasion. Constitutively, activated pSTAT3 induces expression of vascular endothelial growth factor (VEGF) and its receptor VEGFR, leading to endothelial cell proliferation and abnormal microvascular formation causing peritumoral edema (PTE). PTE is one of the significant contributors to mortality in malignant gliomas. Therefore, understanding the molecular mechanism involved in the evolution of gliomas is necessary. This study was to assess the level of expression of pSTAT3, VEGF, and VEGFR in malignant gliomas and analyze the extent of PTE and the extent of expression of one or more of these markers.

Materials and Methods

This study included 84 patients categorized as per the World Health Organization classification of central nervous system tumors into grade IV, III, and II gliomas to investigate the expression of pSTAT3, VEGF, and VEGFR by immunohistochemistry. Furthermore, the presence or absence of PTE was determined using magnetic resonance imaging/computed tomography scans in these patients.

Results

The association between the markers (pSTAT3, VEGFR, and VEGF) and the extent of PTE in these patients was statistically significant (P < 0.05).

Conclusion

The pSTAT3, VEGF-R, and VEGF signaling pathways could contribute to peritumoral edema and might be a regulatory mechanism during PTE formation during tumorigenesis and progression.

Evaluation of multimodal MR imaging for differentiating infiltrative versus reactive edema in brain gliomas

OBJECTIVE

To determine the border of glial tumors by diffusion weighted imaging (DWI), apparent diffusion co-efficient (ADC), magnetic resonance spectroscopy (MRS) and perfusion brain MRI.

PATIENTS AND METHODS

Ten patients with brain gliomas were enrolled [mean age: 35.3 ± 13.2, range: 20-62]. Conventional MRI was performed for all patients. Besides, tumor mapping based on Choline (Cho)/Creatine (Cr) color map in MRS, perfusion and diffusion color maps, were gathered. Different tumoral and peritumoral regions [normal tissue, reactive edema, infiltrative edema, and tumor core] were defined. MRI criteria were evaluated in areas targeted for biopsy and histopathologic evaluation was determined.

RESULTS

Tumor cell positive samples [one necrosis, 26 infiltrative and nine tumor cores] composed 36 (75%) of the 48 samples. Seven (19.4%) of the positive samples were interpreted as not tumor on MRI. Five were identified as reactive edema and two as normal tissue] [kappa: .67, p-value < .001]. Mean of ADC, median of N-acetylaspartate (NAA) and NAA/Cho were statistically different between positive and negative samples (p = .02 and p < .001, respectively). Mean ADC and median Cho/NAA were statistically different in missed tumor containing tissue presented as reactive edema compared to normal and correctly diagnosed reactive edema samples together (p-values < .05).

CONCLUSIONS

Multimodal MRI could define infiltrated borders of brain gliomas.

Transcranial Photosensitizer-Free Laser Treatment of Glioblastoma in Rat Brain

Over sixty years, laser technologies have undergone a technological revolution and become one of the main tools in biomedicine, particularly in neuroscience, neurodegenerative diseases and brain tumors. Glioblastoma is the most lethal form of brain cancer, with very limited treatment options and a poor prognosis. In this study on rats, we demonstrate that glioblastoma (GBM) growth can be suppressed by photosensitizer-free laser treatment (PS-free-LT) using a quantum-dot-based 1267 nm laser diode. This wavelength, highly absorbed by oxygen, is capable of turning triplet oxygen to singlet form. Applying 1267 nm laser irradiation for a 4 week course with a total dose of 12.7 kJ/cm2 firmly suppresses GBM growth and increases survival rate from 34% to 64%, presumably via LT-activated apoptosis, inhibition of the proliferation of tumor cells, a reduction in intracranial pressure and stimulation of the lymphatic drainage and clearing functions. PS-free-LT is a promising breakthrough technology in non- or minimally invasive therapy for superficial GBMs in infants as well as in adult patients with high photosensitivity or an allergic reaction to PSs.

RETROSPECTIVE EVALUATION OF MRI PATTERN OF GLIOBLASTOMA IN A TERTIARY HOSPITAL IN NIGERIA

Introduction

Malignant gliomas, especially glioblastomas, are among the most aggressive and devastating of cancers, commonly producing profound progressive disability and leading to death in most cases. Conventional magnetic resonance (MR) imaging with gadolinium-based contrast agents is the most widely established and most useful tool in the characterization of cerebral tumors including Glioblastomas. This study aims to describe the imaging characteristics of Glioblastoma in African patients using conventional MR imaging.

Methodology

This was a retrospective cross-sectional study carried out at a Nigerian tertiary hospital. The demographic data, MR images and reports of patients with imaging and histological diagnosis of Glioblastoma between January 2003 and September 2017 were retrieved and reviewed. All the recorded data were analyzed using simple proportion and descriptive statistics with the Statistical Package for Social Sciences (SPSS) version 20.0 software for Windows.

Results

One hundred and twenty-two (122) patients had brain tumors during the review period, out of which 14 (11.5%) had histologically confirmed glioblastoma. The male- to -female ratio was 2.5 to 1.0. The age ranged between 14 and 72 years with a mean age of 49.6 years SD ±16.3. Twelve (85.7%) patients had solitary tumors and 2 (14.3%) had multiple tumors. Six (42.9%) were found on the right hemisphere only, 5 (35.7%) were found on the left hemisphere while 3 (21.4%) traversed both hemispheres. All tumors showed inhomogeneous enhancement and significant midline shift to the contra-lateral side of greater than 3mm. Only 1 (7.1%) tumor showed evidence of intra-tumoral bleed detected on T2* sequence.

Conclusion

Glioblastoma is a known aggressive brain tumor with unique MR imaging characteristics. While midline shift is typical, intra-tumoral bleeding may be an uncommon finding at presentation in our center.

Magnetic Resonance Imaging Features of Zinc Finger Translocation Associated-RELA Fusion Ependymoma Compared to Its Wild-Type Counterpart

OBJECTIVE

To explore the predictive value of quantitative features extracted from conventional magnetic resonance imaging (MRI) in distinguishing Zinc Finger Translocation Associated (ZFTA)-RELA fusion-positive and wild-type ependymomas.

METHODS

Twenty-seven patients with pathologically confirmed ependymomas (17 patients with ZFTA-RELA fusions and 10 ZFTA-RELA fusion-negative patients) who underwent conventional MRI were enrolled in this retrospective study. Two experienced neuroradiologists who were blinded to the histopathological subtypes independently extracted imaging features using Visually Accessible Rembrandt Images annotations. The consistency between the readers was evaluated with the Kappa test. The imaging features with significant differences between the 2 groups were obtained using the least absolute shrinkage and selection operator regression model. Logistic regression analysis and receiver operating characteristic analysis were performed to analyze the diagnostic performance of the imaging features in predicting the ZFTA-RELA fusion status in ependymoma.

RESULTS

There was a good interevaluator agreement on the imaging features (kappa value range 0.601-1.000). Enhancement quality, thickness of the enhancing margin, and edema crossing the midline have high predictive performance in identifying ZFTA-RELA fusion-positive and ZFTA-RELA fusion-negative ependymomas (C-index = 0.862 and area under the curve= 0.8618).

CONCLUSIONS

Quantitative features extracted from preoperative conventional MRI by Visually Accessible Rembrandt Images provide high discriminatory accuracy in predicting the ZFTA-RELA fusion status of ependymoma.

Prognosis prediction for glioblastoma multiforme patients using machine learning approaches: Development of the clinically applicable model

BACKGROUND AND PURPOSE

We aimed to develop a clinically applicable prognosis prediction model predicting overall survival (OS) and progression-free survival (PFS) for glioblastoma multiforme (GBM) patients.

MATERIALS AND METHODS

All 467 patients treated with concurrent chemoradiotherapy at Yonsei Cancer Center from 2016 to 2020 were included in this study. We developed a conventional linear regression, Cox proportional hazards (COX), and non-linear machine learning algorithms, random survival forest (RSF) and survival support vector machine (SVM) based on 16 clinical variables. After backward feature selection and hyperparameter tuning using grid search, we repeated 100 times of cross-validations to combat overfitting and enhance the model performance. Harrell's concordance index (C-index) and integrated brier score (IBS) were employed as quantitative performance metrics.

RESULTS

In both predictions, RSF performed much better than COX and SVM. (For OS prediction: RSF C-index = 0.72 90%CI [0.71-0.72] and IBS = 0.12 90%CI [0.10-0.13]; For PFS prediction: RSF C-index = 0.70 90%CI [0.70-0.71] and IBS = 0.12 90%CI [0.10-0.14]). Permutation feature importance confirmed that MGMT promoter methylation, extent of resection, age, cone down planning target volume, and subventricular zone involvement are significant prognostic factors for OS. The importance of the extent of resection and MGMT promoter methylation was much higher than other selected input factors in PFS. Our final models accurately stratified two risk groups with root mean square errors less than 0.07. The sensitivity analysis revealed that our final models are highly applicable to newly diagnosed GBM patients.

CONCLUSION

Our final models can provide a reliable outcome prediction for individual GBM. The final OS and PFS predicting models we developed accurately stratify high-risk groups up to 5-years, and the sensitivity analysis confirmed that both final models are clinically applicable.

Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor

The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.

A clinical evaluation of cystic features in patients with newly diagnosed glioblastoma with IDH-wildtype

BACKGROUND

The prognostic significance of the presence of cystic features in patients with newly diagnosed glioblastoma (GB) is highly controversial. The purpose of this study was to determine whether cystic GB patients have a more favorable prognosis compared to non-cystic GB patients.

METHODS

The records of all GB patients diagnosed between August 2008 and December 2020 at Seoul St. Mary's Hospital were reviewed retrospectively. Out of 254 GB patients, we excluded patients with a confirmed isocitrate dehydrogenase (IDH) mutation or an unknown IDH mutation status. A total of 145 patients met our eligibility criteria.

RESULTS

Of the 145 patients we analyzed, 16 patients were classified as the cystic group, and 129 patients were classified into the non-cystic group. As there was a significant difference in the extent of resection between the two groups, 32 patients were matched according to propensity score matching. A Kaplan-Meier survival curve of the two groups indicated that the cystic group had better survival than the non-cystic group (28.6 months versus 18.8 months, respectively; p = 0.055). On multivariate analysis, the presence of cystic features (hazard ratio [HR]: 0.40, 95% confidence interval [CI]: 0.17-0.91, p = 0.029) was significantly related with a longer OS. Longer OS was also related with well-known prognostic factors, such as grossly total resection (HR: 0.05, CI: 0.01-0.31, respectively; p = 0.001) and lower European Cooperative Oncology Group (ECOG) score (HR: 3.67, CI: 1.56-9.02, respectively; p = 0.003).

CONCLUSION

Our results suggest that the presence of cystic features could be an independent prognostic factor suggesting better survival in GB patients. Further larger and prospective studies to validate our findings are needed.

Peritumoral ADC Values Correlate with the MGMT Methylation Status in Patients with Glioblastoma

Different results have been reported concerning the relationship of the apparent diffusion coefficient (ADC) values and the status of methylation as the promoter gene for the enzyme methylguanine-DNA methyltransferase (MGMT) in patients with glioblastomas (GBs). The aim of this study was to investigate if there were correlations between the ADC values of the enhancing tumor and peritumoral areas of GBs and the MGMT methylation status. In this retrospective study, we included 42 patients with newly diagnosed unilocular GB with one MRI study prior to any treatment and histopathological data. After co-registration of ADC maps with T1-weighted sequences after contrast administration and dynamic susceptibility contrast (DSC) perfusion, we manually selected one region-of-interest (ROI) in the enhancing and perfused tumor and one ROI in the peritumoral white matter. Both ROIs were mirrored in the healthy hemisphere for normalization. In the peritumoral white matter, absolute and normalized ADC values were significantly higher in patients with MGMT-unmethylated tumors, as compared to patients with MGMT-methylated tumors (absolute values p = 0.002, normalized p = 0.0007). There were no significant differences in the enhancing tumor parts. The ADC values in the peritumoral region correlated with MGMT methylation status, confirmed by normalized ADC values. In contrast to other studies, we could not find a correlation between the ADC values or the normalized ADC values and the MGMT methylation status in the enhancing tumor parts.

TGF-Beta Modulates the Integrity of the Blood Brain Barrier In Vitro, and Is Associated with Metabolic Alterations in Pericytes

The blood-brain barrier (BBB) is a selectively permeable boundary that separates the circulating blood from the extracellular fluid of the brain and is an essential component for brain homeostasis. In glioblastoma (GBM), the BBB of peritumoral vessels is often disrupted. Pericytes, being important to maintaining BBB integrity, can be functionally modified by GBM cells which induce proliferation and cell motility via the TGF-β-mediated induction of central epithelial to mesenchymal transition (EMT) factors. We demonstrate that pericytes strengthen the integrity of the BBB in primary endothelial cell/pericyte co-cultures as an in vitro BBB model, using TEER measurement of the barrier integrity. In contrast, this effect was abrogated by TGF-β or conditioned medium from TGF-β secreting GBM cells, leading to the disruption of a so far intact and tight BBB. TGF-β notably changed the metabolic behavior of pericytes, by shutting down the TCA cycle, driving energy generation from oxidative phosphorylation towards glycolysis, and by modulating pathways that are necessary for the biosynthesis of molecules used for proliferation and cell division. Combined metabolomic and transcriptomic analyses further underscored that the observed functional and metabolic changes of TGF-β-treated pericytes are closely connected with their role as important supporting cells during angiogenic processes.

MRI radiomic features of peritumoral edema may predict the recurrence sites of glioblastoma multiforme

Background and purpose

As one of the most aggressive malignant tumor in the central nervous system, the main cause of poor outcome of glioblastoma (GBM) is recurrence, a non-invasive method which can predict the area of recurrence pre-operation is necessary.To investigate whether there is radiological heterogeneity within peritumoral edema and identify the reproducible radiomic features predictive of the sites of recurrence of glioblastoma(GBM), which may be of value to optimize patients' management.

Materials and methods

The clinical information and MR images (contrast-enhanced T1 weighted and FLAIR sequences) of 22 patients who have been histologically proven glioblastoma, were retrospectively evaluated. Kaplan-Meier methods was used for survival analysis. Oedematous regions were manually segmented by an expert into recurrence region, non-recurrence region. A set of 94 radiomic features were obtained from each region using the function of analyzing MR image of 3D slicer. Paired t test was performed to identify the features existing significant difference. Subsequently, the data of two patients from TCGA database was used to evaluate whether these features have clinical value.

Results

Ten features with significant differences between the recurrence and non-recurrence subregions were identified and verified on two individual patients from the TCGA database with pathologically confirmed diagnosis of GBM.

Conclusions

Our results suggested that heterogeneity does exist in peritumoral edema, indicating that the radiomic features of peritumoral edema from routine MR images can be utilized to predict the sites of GBM recurrence. Our findings may further guide the surgical treatment strategy for GBM.

Correlation of EGFR mutation subtypes and survival in surgically treated brain metastasis from non-small-cell lung cancer

OBJECTIVE

Epidermal growth factor receptor (EGFR) mutation is a positive prognostic factor for survival in patients with non-small-cell lung cancer (NSCLC). In such patients, brain metastasis signifies negative outcomes. Patients with NSCLC brain metastasis that may benefit from neurosurgery is under investigation. We aim to investigate the impact of different mutation loci in surgically treated NSCLC brain metastasis patients.

METHODS

This retrospective cohort study included patients with NSCLC brain metastasis who underwent brain lesionectomy, followed by radiotherapy and chemotherapy or targeted therapy. Demographics and tumor characteristics were compared between the EGFR mutant type and wild type groups. Postoperative survival and risk factors were analyzed using log rank and Cox regression methods.

RESULTS

Overall, 101 patients were included, with 57 belonging to the EGFR mutant type group and 44 to the EGFR wild type group. The median postoperative survival was 17 months for the entire cohort, with the duration being 19 and 14 months for EGFR mutant type and wild type patients (p = 0.013), respectively. Multivariate analysis revealed that exon 19 del (p = 0.02) and a high Karnofsky Performance Scale score (p < 0.01) were independent positive prognostic factors to predict survival. The timing of development of the brain metastasis or the location of the intracranial metastasis was not associated with EGFR mutations.

CONCLUSION

EGFR mutations are associated with better survival outcomes in patients with NSCLC brain metastasis suitable for surgical treatment. This advantage was attributed to patients having a specific mutation of exon 19 deletion.

Cystic glioblastoma: A systematic review and meta-analysis of characteristics and outcomes

Introduction

Cystic glioblastoma is a well-recognised clinical entity but the characteristics and role of these cystic components in determining clinical outcome remains poorly understood.

Research question

To determine whether (1) there is a prognostic significance to a glioblastoma having a cystic component and (2) whether the presence of cyst, and its prognosis relative to non-cystic glioblastoma, relates to patient demographics and other tumour characteristics.

Material & methods

A systematic review and meta-analysis was conducted in accordance to PRISMA guidelines. Articles with histological and/or radiological diagnosis of cystic glioblastoma that reported on survival outcome and/or characteristics of cystic glioblastomas mentioned were included. Meta-analysis was performed and presented using random effect model.

Results

Twenty studies met the inclusion criteria, and nine studies were included in the meta-analysis (374 glioblastoma patients with cystic components and 2477 glioblastoma patients without cystic components above 18 years of age). Search result did not yield any Level I evidence. There is statistically significant survival benefit in cystic over non-cystic glioblastomas (HR ​= ​0.81, 95%CI 0.70-0.93, p ​= ​0.004, I2 ​= ​50%). Studies reported younger average patient age, larger tumor size and slower tumor growth velocity in cystic glioblastoma. No significant difference in gender ratio and IDH-1 and MGMT methylation status between cystic and non-cystic glioblastoma were reported.

Discussion & conclusion

Presence of cyst in glioblastoma tumor is associated with improved overall survival outcome. Etiology of cystic entities and why they might confer survival benefits remained to be determined, and future studies examining how to best treat cystic glioblastomas would be clinically valuable.

Factors Involved in Preoperative Edema in High-Grade Gliomas

Background Expansion of preoperative edema (PE) is an independent poor prognostic factor in high-grade gliomas. Evaluation of PE provides important information that can be readily obtained from magnetic resonance imaging (MRI), but there are few reports on factors associated with PE. The goal of this study was to identify factors contributing to PE in Grade 3 (G3) and Grade 4 (G4) gliomas. Methodology PE was measured in 141 pathologically proven G3 and G4 gliomas, and factors with a potential relationship with PE were examined in univariate and multivariate analyses. The following eight explanatory variables were used: age, sex, Karnofsky performance status (KPS), location of the glioma, tumor diameter, pathological grade, isocitrate dehydrogenase (IDH)-1-R132H status, and Ki-67 index. Overall survival (OS) and progression-free survival (PFS) were calculated in groups divided by PE (<1 vs. ≥1 cm) and by factors with a significant correlation with PE in multivariate analysis. Results In univariate analysis, age (p = 0.013), KPS (p = 0.012), pathology grade (p = 0.004), and IDH1-R132H status (p = 0.0003) were significantly correlated with PE. In multivariate analysis, only IDH1-R132H status showed a significant correlation (p = 0.036), with a regression coefficient of -0.42. The median follow-up period in survivors was 38.9 months (range: 1.2-131.7 months). The one-, two-, and three-year OS rates for PE <1 vs. ≥1 cm were 77% vs. 68%, 67% vs. 44%, and 63% vs. 24% (p = 0.0001), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 67%, 85% vs. 40%, and 81% vs. 21% (p < 0.0001), respectively. The one-, two-, and three-year PFS rates for PE <1 vs. ≥1 cm were 77% vs. 49%, 64% vs. 24%, and 50% vs. 18% (p = 0.0002), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 48%, 77% vs. 23%, and 73% vs. 14% (p < 0.0001), respectively. Conclusions IDH1-R132H status was found to be a significant contributor to PE. Cases with PE <1 cm and those with the IDH1-R132H mutation clearly had a better prognosis.

Standard clinical approaches and emerging modalities for glioblastoma imaging

Glioblastoma (GBM) is the most common primary adult intracranial malignancy and carries a dismal prognosis despite an aggressive multimodal treatment regimen that consists of surgical resection, radiation, and adjuvant chemotherapy. Radiographic evaluation, largely informed by magnetic resonance imaging (MRI), is a critical component of initial diagnosis, surgical planning, and post-treatment monitoring. However, conventional MRI does not provide information regarding tumor microvasculature, necrosis, or neoangiogenesis. In addition, traditional MRI imaging can be further confounded by treatment-related effects such as pseudoprogression, radiation necrosis, and/or pseudoresponse(s) that preclude clinicians from making fully informed decisions when structuring a therapeutic approach. A myriad of novel imaging modalities have been developed to address these deficits. Herein, we provide a clinically oriented review of standard techniques for imaging GBM and highlight emerging technologies utilized in disease characterization and therapeutic development.

Antibody-Based Formats to Target Glioblastoma: Overcoming Barriers to Protein Drug Delivery

Glioblastoma (GB) is recognized as the most aggressive form of primary brain cancer. Despite advances in treatment strategies that include surgery, radiation, and chemotherapy, the median survival time (∼15 months) of patients with GB has not significantly improved. The poor prognosis of GB is also associated with a very high chance of tumor recurrence (∼90%), and current treatment measures have failed to address the complications associated with this disease. However, targeted therapies enabled through antibody engineering have shown promise in countering GB when used in combination with conventional approaches. Here, we discuss the challenges in conventional as well as future GB therapeutics and highlight some of the known advantages of using targeted biologics to overcome these impediments. We also review a broad range of potential alternative routes that could be used clinically to administer anti-GB biologics to the brain through evasion of its natural barriers.

A Comparative and Summative Study of Radiomics-based Overall Survival Prediction in Glioblastoma Patients

PURPOSE

This study aimed to assess different machine learning models based on radiomic features, Visually Accessible Rembrandt Images features and clinical characteristics in overall survival prediction of glioblastoma and to identify the reproducible features.

MATERIALS AND METHODS

Patients with preoperative magnetic resonance scans were allocated into 3 data sets. The Least Absolute Shrinkage and Selection Operator was used for feature selection. The prediction models were built by random survival forest (RSF) and Cox regression. C-index and integrated Brier scores were calculated to compare model performances.

RESULTS

Patients with cortical involvement had shorter survival times in the training set (P = 0.006). Random survival forest showed higher C-index than Cox, and the RSF model based on the radiomic features was the best one (testing set: C-index = 0.935 ± 0.023). Ten reproducible radiomic features were summarized.

CONCLUSIONS

The RSF model based on radiomic features had promising potential in predicting overall survival of glioblastoma. Ten reproducible features were identified.

Classification of Gliomas and Germinomas of the Basal Ganglia by Transfer Learning

Background

Germ cell tumors (GCTs) are neoplasms derived from reproductive cells, mostly occurring in children and adolescents at 10 to 19 years of age. Intracranial GCTs are classified histologically into germinomas and non-germinomatous germ cell tumors. Germinomas of the basal ganglia are difficult to distinguish based on symptoms or routine MRI images from gliomas, even for experienced neurosurgeons or radiologists. Meanwhile, intracranial germinoma has a lower incidence rate than glioma in children and adults. Therefore, we established a model based on pre-trained ResNet18 with transfer learning to better identify germinomas of the basal ganglia.

Methods

This retrospective study enrolled 73 patients diagnosed with germinoma or glioma of the basal ganglia. Brain lesions were manually segmented based on both T1C and T2 FLAIR sequences. The T1C sequence was used to build the tumor classification model. A 2D convolutional architecture and transfer learning were implemented. ResNet18 from ImageNet was retrained on the MRI images of our cohort. Class activation mapping was applied for the model visualization.

Results

The model was trained using five-fold cross-validation, achieving a mean AUC of 0.88. By analyzing the class activation map, we found that the model's attention was focused on the peri-tumoral edema region of gliomas and tumor bulk for germinomas, indicating that differences in these regions may help discriminate these tumors.

Conclusions

This study showed that the T1C-based transfer learning model could accurately distinguish germinomas from gliomas of the basal ganglia preoperatively.

Radiomics Analysis Based on Magnetic Resonance Imaging for Preoperative Overall Survival Prediction in Isocitrate Dehydrogenase Wild-Type Glioblastoma

Purpose

This study aimed to develop a radiomics signature for the preoperative prognosis prediction of isocitrate dehydrogenase (IDH)-wild-type glioblastoma (GBM) patients and to provide personalized assistance in the clinical decision-making for different patients.

Materials and Methods

A total of 142 IDH-wild-type GBM patients classified using the new classification criteria of WHO 2021 from two centers were included in the study and randomly divided into a training set and a test set. Firstly, their clinical characteristics were screened using univariate Cox regression. Then, the radiomics features were extracted from the tumor and peritumoral edema areas on their contrast-enhanced T1-weighted image (CE-T1WI), T2-weighted image (T2WI), and T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) magnetic resonance imaging (MRI) images. Subsequently, inter- and intra-class correlation coefficient (ICC) analysis, Spearman’s correlation analysis, univariate Cox, and the least absolute shrinkage and selection operator (LASSO) Cox regression were used step by step for feature selection and the construction of a radiomics signature. The combined model was established by integrating the selected clinical factors. Kaplan–Meier analysis was performed for the validation of the discrimination ability of the model, and the C-index was used to evaluate consistency in the prediction. Finally, a Radiomics + Clinical nomogram was generated for personalized prognosis analysis and then validated using the calibration curve.

Results

Analysis of the clinical characteristics resulted in the screening of four risk factors. The combination of ICC, Spearman’s correlation, and univariate and LASSO Cox resulted in the selection of eight radiomics features, which made up the radiomics signature. Both the radiomics and combined models can significantly stratify high- and low-risk patients (p &lt; 0.001 and p &lt; 0.05 for the training and test sets, respectively) and obtained good prediction consistency (C-index = 0.74–0.86). The calibration plots exhibited good agreement in both 1- and 2-year survival between the prediction of the model and the actual observation.

Conclusion

Radiomics is an independent preoperative non-invasive prognostic tool for patients who were newly classified as having IDH-wild-type GBM. The constructed nomogram, which combined radiomics features with clinical factors, can predict the overall survival (OS) of IDH-wild-type GBM patients and could be a new supplement to treatment guidelines.

Machine Learning and Radiomic Features to Predict Overall Survival Time for Glioblastoma Patients

Glioblastoma is an aggressive brain tumor with a low survival rate. Understanding tumor behavior by predicting prognosis outcomes is a crucial factor in deciding a proper treatment plan. In this paper, an automatic overall survival time prediction system (OST) for glioblastoma patients is developed on the basis of radiomic features and machine learning (ML). This system is designed to predict prognosis outcomes by classifying a glioblastoma patient into one of three survival groups: short-term, mid-term, and long-term. To develop the prediction system, a medical dataset based on imaging information from magnetic resonance imaging (MRI) and non-imaging information is used. A novel radiomic feature extraction method is proposed and developed on the basis of volumetric and location information of brain tumor subregions extracted from MRI scans. This method is based on calculating the volumetric features from two brain sub-volumes obtained from the whole brain volume in MRI images using brain sectional planes (sagittal, coronal, and horizontal). Many experiments are conducted on the basis of various ML methods and combinations of feature extraction methods to develop the best OST system. In addition, the feature fusions of both radiomic and non-imaging features are examined to improve the accuracy of the prediction system. The best performance was achieved by the neural network and feature fusions.

Emerging therapeutic targets for cerebral edema

INTRODUCTION

Cerebral edema is a key contributor to death and disability in several forms of brain injury. Current treatment options are limited, reactive, and associated with significant morbidity. Targeted therapies are emerging based on a growing understanding of the molecular underpinnings of cerebral edema.

AREAS COVERED

We review the pathophysiology and relationships between different cerebral edema subtypes to provide a foundation for emerging therapies. Mechanisms for promising molecular targets are discussed, with an emphasis on those advancing in clinical trials, including ion and water channels (AQP4, SUR1-TRPM4) and other proteins/lipids involved in edema signaling pathways (AVP, COX2, VEGF, and S1P). Research on novel treatment modalities for cerebral edema [including recombinant proteins and gene therapies] is presented and finally, insights on reducing secondary injury and improving clinical outcome are offered.

EXPERT OPINION

Targeted molecular strategies to minimize or prevent cerebral edema are promising. Inhibition of SUR1-TRPM4 (glyburide/glibenclamide) and VEGF (bevacizumab) are currently closest to translation based on advances in clinical trials. However, the latter, tested in glioblastoma multiforme, has not demonstrated survival benefit. Research on recombinant proteins and gene therapies for cerebral edema is in its infancy, but early results are encouraging. These newer modalities may facilitate our understanding of the pathobiology underlying cerebral edema.

The role of systemic inflammatory cells in meningiomas

The aim of this review is to describe the inflammatory systemic cell infiltrate and its role in pathophysiology and prognostic implications of meningiomas. Articles from PubMed describing inflammation and immune cells in meningioma were systematically selected and reviewed. Infiltrating inflammatory cells are common in meningiomas and correlate with tumor behavior and peritumoral edema. The immune cell infiltrate mainly comprised macrophages, CD4 + T cells of the Th1 and Th2 subtype, CD8 + cytotoxic T cells, mast cells, and to a lesser degree B cells. The polarization of macrophages to M1 or M2 states, as well as the differentiation of T-helper cells to Th1 or Th2 subsets, is of prognostic value, but whether or not the presence of macrophages is associated with the degree of malignancy of the tumor is controversial. The best documented immunosuppressive and tumor-promoting mechanism is the expression of programmed cell death protein 1 (PD-1/PD-1L) which is found on both tumor cells and tumor-infiltrating immune cells. The immune cell infiltration varies between different meningiomas. It contributes to a microenvironment with potential contradictory effects on tumor growth and edema. The immune mechanisms are potential therapeutic targets provided that their effects can be comprehensively understood.

Peritumoral edema status of glioblastoma identifies patients reaching long-term disease control with specific progression patterns after tumor resection and high-dose proton boost

Background

Glioblastoma peritumoral edema (PE) extent is associated with survival and progression pattern after tumor resection and radiotherapy (RT). To increase tumor control, proton beam was adopted to give high-dose boost (> 90 Gy). However, the correlation between PE extent and prognosis of glioblastoma after postoperative high-dose proton boost (HDPB) therapy stays unknown. We intend to utilize the PE status to classify the survival and progression patterns.

Methods

Patients receiving HDPB (96.6 GyE) were retrospectively evaluated. Limited peritumoral edema (LPE) was defined as PE extent < 3 cm with a ratio of PE extent to tumor maximum diameter of < 0.75. Extended progressive disease (EPD) was defined as progression of tumors extending > 1 cm from the tumor bed edge.

Results

After long-term follow-up (median 88.7, range 63.6–113.8 months) for surviving patients with (n = 13) and without (n = 32) LPE, the median overall survival (OS) and progression-free survival (PFS) were 77.2 vs. 16.7 months (p = 0.004) and 13.6 vs. 8.6 months (p = 0.02), respectively. In multivariate analyses combined with factors of performance, age, tumor maximum diameter, and tumor resection extent, LPE remained a significant factor for favorable OS and PFS. The rates of 5-year complete response, EPD, and distant metastasis with and without LPE were 38.5% vs. 3.2% (p = 0.005), 7.7% vs. 40.6% (p = 0.04), and 0% vs. 34.4% (p = 0.02), respectively.

Conclusions

The LPE status effectively identified patients with relative long-term control and specific progression patterns after postoperative HDPB for glioblastoma.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-021-03765-6.

[Epidemiological, clinical, therapeutic and evolutionary features of patients with glioblastoma: series of cases managed in the Department of Hematology-Oncology at the Mohammed VI University Hospital Center in Marrakech in 2016 and 2017]

Glioblastoma is the most common primary malignant brain tumour. Despite advances in diagnostic and therapeutic treatments, it is still associated with poor outcome The purpose of this study of cases is to describe the epidemiological, clinical, therapeutic and evolutionary features of patients with glioblastoma admitted to the Department of Hematology-Oncology (DHO) in Marrakech in 2016 and 2017. We conducted a literature review of epidemiological, clinical, radiological, anatomopathological, therapeutic and evolutionary data from 40 patients. Glioblastoma accounted for 47.6% of treated intracranial tumours. The average age of patients was 52.4±12.3 years. Functional impotence and signs of intracranial hypertension were the main symptoms. Tumours mainly occurred in the parietal region (44%) and were large (57.5%). Aphasia was related to tumour size (p=0.042). Nine cases had glioblastomas-IDH1-wild and one case had glioblastoma-IDH1-mutant. On admission, patients had poor performance-status. This was due to a prolonged time between surgery and DHO admission (p= 0.034). Patients with sensory impairments were older (62.5±3 years) than those without sensory impairments (51.2±12 years) (p=0,045). In-patient women received chemoradiotherapy (1.5±1 month) earlier than men (2.3±1.2 months) (p=0.03). Survival was 13.6±5.3 months; it was unrelated to the time to surgery (p=0.076), the time to DHO (p=0.058), and the time to chemoradiotherapy (p=0.073). The epidemiological, clinical, radiological and evolutionary features of our sample were comparable to literature data. The molecular profiling was not systematically realized. Despite prolonged treatment times, no link to survival was detected.

The Prognostic Role of Peritumoral Edema in Patients with Newly Diagnosed Glioblastoma: A Retrospective Analysis

OBJECTIVE

Previous studies on glioblastomas (GBMs) have not reached a consensus on peritumoral edema (PTE)'s influence on survival. This study evaluated the PTE index's prognostic role in newly diagnosed GBMs using a well-designed method.

METHODS

Selected patients were reviewed after a rigorous screening process. Their general information was obtained from electronic medical records. The imaging metrics (MTD, TTM, TTE) representing tumor diameter, laterality, and PTE extent were obtained by manual measurement in Syngo FastView software. The PTE index was a ratio of TTE to MTD. Multiple variables were evaluated using analysis of variance and Cox regression model.

RESULTS

Of 143 patients, 62 were included in this study. MGMT promoter methylation and tumor laterality were both independent prognostic factors (p = 0.020, 0.042; HR = 0.272, 2.630). The lateral tumors' index was higher than that of the medial tumors (57.7% vs. 42.6%, p = 0.027). Low-index tumors were located in relatively medial positions compared with high-index tumors (TTM, 4.9 vs. 12.8, p = 0.032). This finding indicated that the PTE index tended to increase with tumor laterality. Moreover, the patients with low-index tumors had a significant survival disadvantage in the univariate analysis but not in the multivariate analysis (p = 0.023, 0.220). However, further analysis found that the combination of tumor laterality and PTE statistically stratified the survival outcome. The patients with lateral high-index tumors survived significantly longer (p = 0.022, HR = 1.927).

CONCLUSIONS

In contrast with the previous studies, this study recommends combining PTE and tumor laterality for survival stratification in newly diagnosed GBMs.

Prognostic Prediction Based on Dynamic Contrast-Enhanced MRI and Dynamic Susceptibility Contrast-Enhanced MRI Parameters from Non-Enhancing, T2-High-Signal-Intensity Lesions in Patients with Glioblastoma

Objective

Few attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM.

Materials and Methods

A total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival.

Results

The 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009).

Conclusion

The 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression.

Association of Isocitrate Dehydrogenase (IDH) Status With Edema to Tumor Ratio and Its Correlation With Immune Infiltration in Glioblastoma

Purpose

The extent of preoperative peritumoral edema in glioblastoma (GBM) has been negatively correlated with patient outcome. As several ongoing studies are investigating T-cell based immunotherapy in GBM, we conducted this study to assess whether peritumoral edema with potentially increased intracranial pressure, disrupted tissue homeostasis and reduced local blood flow has influence on immune infiltration and affects survival.

Methods

A volumetric analysis of preoperative imaging (gadolinium enhanced T1 weighted MRI sequences for tumor size and T2 weighted sequences for extent of edema (including the infiltrative zone, gliosis etc.) was conducted in 144 patients using the Brainlab® software. Immunohistochemical staining was analyzed for lymphocytic- (CD 3+) and myelocytic (CD15+) tumor infiltration. A retrospective analysis of patient-, surgical-, and molecular characteristics was performed using medical records.

Results

The edema to tumor ratio was neither associated with progression-free nor overall survival (p=0.90, p=0.74). However, GBM patients displaying IDH-1 wildtype had significantly higher edema to tumor ratio than patients displaying an IDH-1 mutation (p=0.01). Immunohistopathological analysis did not show significant differences in lymphocytic or myelocytic tumor infiltration (p=0.78, p=0.74) between these groups.

Conclusion

In our cohort, edema to tumor ratio had no significant correlation with immune infiltration and outcome. However, patients with an IDH-1wildtype GBM had a significantly higher edema to tumor ratio compared to their IDH-1 mutated peer group. Further studies are necessary to elucidate the underlying mechanisms.

Matrix Stiffness Modulates Patient-Derived Glioblastoma Cell Fates in Three-Dimensional Hydrogels

Cancer progression is known to be accompanied by changes in tissue stiffness. Previous studies have primarily employed immortalized cell lines and 2D hydrogel substrates, which do not recapitulate the 3D tumor niche. How matrix stiffness affects patient-derived cancer cell fate in 3D remains unclear. In this study, we report a matrix metalloproteinase-degradable poly(ethylene-glycol)-based hydrogel platform with brain-mimicking biochemical cues and tunable stiffness (40-26,600 Pa) for 3D culture of patient-derived glioblastoma xenograft (PDTX GBM) cells. Our results demonstrate that decreasing hydrogel stiffness enhanced PDTX GBM cell proliferation, and hydrogels with stiffness 240 Pa and below supported robust PDTX GBM cell spreading in 3D. PDTX GBM cells encapsulated in hydrogels demonstrated higher drug resistance than 2D control, and increasing hydrogel stiffness further enhanced drug resistance. Such 3D hydrogel platforms may provide a valuable tool for mechanistic studies of the role of niche cues in modulating cancer progression for different cancer types.

Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in glioblastoma

BACKGROUND

Recent epidemiological studies have suggested that sexual dimorphism influences treatment response and prognostic outcome in glioblastoma (GBM). To this end, we sought to (i) identify distinct sex-specific radiomic phenotypes-from tumor subcompartments (peritumoral edema, enhancing tumor, and necrotic core) using pretreatment MRI scans-that are prognostic of overall survival (OS) in GBMs, and (ii) investigate radiogenomic associations of the MRI-based phenotypes with corresponding transcriptomic data, to identify the signaling pathways that drive sex-specific tumor biology and treatment response in GBM.

METHODS

In a retrospective setting, 313 GBM patients (male = 196, female = 117) were curated from multiple institutions for radiomic analysis, where 130 were used for training and independently validated on a cohort of 183 patients. For the radiogenomic analysis, 147 GBM patients (male = 94, female = 53) were used, with 125 patients in training and 22 cases for independent validation.

RESULTS

Cox regression models of radiomic features from gadolinium T1-weighted MRI allowed for developing more precise prognostic models, when trained separately on male and female cohorts. Our radiogenomic analysis revealed higher expression of Laws energy features that capture spots and ripple-like patterns (representative of increased heterogeneity) from the enhancing tumor region, as well as aggressive biological processes of cell adhesion and angiogenesis to be more enriched in the "high-risk" group of poor OS in the male population. In contrast, higher expressions of Laws energy features (which detect levels and edges) from the necrotic core with significant involvement of immune related signaling pathways was observed in the "low-risk" group of the female population.

CONCLUSIONS

Sexually dimorphic radiogenomic models could help risk-stratify GBM patients for personalized treatment decisions.

Prognostic and Predictive Value of Integrated Qualitative and Quantitative Magnetic Resonance Imaging Analysis in Glioblastoma

Simple Summary

Glioblastoma (GBM) is the most malignant primary brain tumor, for which improving patient outcome is limited by a substantial amount of tumor heterogeneity. Magnetic resonance imaging (MRI) in combination with machine learning offers the possibility to collect qualitative and quantitative imaging features which can be used to predict patient prognosis and relevant tumor markers which can aid in selecting the right treatment. This study showed that combining these MRI features with clinical features has the highest prognostic value for GBM patients; this model performed similarly in an independent GBM cohort, showing its reproducibility. The prediction of tumor markers showed promising results in the training set but not could be validated in the independent dataset. This study shows the potential of using MRI to predict prognosis and tumor markers, but further optimization and prospective studies are warranted.

Abstract

Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase (IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64–0.78) and used to stratify Kaplan–Meijer curves in two survival groups (p-value < 0.001). The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582–8.25) and MGMT-methylation (AUC 0.667, 95% CI 0.522–0.82) but not for IDH-mutation (AUC 0.695, 95% CI 0.436–0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted.

Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients

Background: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. Methods: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. Results: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. Conclusions: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.

Reuse of Molecules for Glioblastoma Therapy

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumor. The current standard of care for GBM is the Stupp protocol which includes surgical resection, followed by radiotherapy concomitant with the DNA alkylator temozolomide; however, survival under this treatment regimen is an abysmal 12-18 months. New and emerging treatments include the application of a physical device, non-invasive 'tumor treating fields' (TTFs), including its concomitant use with standard of care; and varied vaccines and immunotherapeutics being trialed. Some of these approaches have extended life by a few months over standard of care, but in some cases are only available for a minority of GBM patients. Extensive activity is also underway to repurpose and reposition therapeutics for GBM, either alone or in combination with the standard of care. In this review, we present select molecules that target different pathways and are at various stages of clinical translation as case studies to illustrate the rationale for their repurposing-repositioning and potential clinical use.

Peritumoral edema in preoperative magnetic resonance imaging is an independent prognostic factor for hepatocellular carcinoma

BACKGROUND

Peritumoral edema is an independent prognostic risk factor for malignant tumors. Therefore, assessment of peritumoral edema in preoperative magnetic resonance imaging (MRI) may provide better prognostic information in patients with hepatocellular carcinoma (HCC).

AIM

To determine whether peritumoral edema in preoperative MRI is a prognostic factor for HCC.

METHODS

A retrospective analysis of 90 patients with HCC confirmed by surgical pathology was performed. All patients' peritumoral edema in preoperative MRI was reviewed by two radiologists. The association of disease recurrence with peritumoral edema and clinicopathological features was assessed using the Cox proportional hazards model. Interobserver agreement for evaluating peritumoral edema was determined using Cohen's κ coefficient.

RESULTS

Recurrence and non-recurrence after an average 20.8 month follow-up was 25.6% (23/90) and 74.4% (67/90), respectively. The ratio of peritumoral edema of 90 patients with HCC in preoperative MRI was 35.6% (32/90). In univariate Cox regression analysis, peritumoral edema [hazard ratio (HR) 11.08, P < 0.001], tumor diameter (HR 4.12, P = 0.001), microvascular invasion (HR 2.78, P = 0.020), gender (HR 0.29, P = 0.006), cirrhosis (HR 2.45, P = 0.049), ascites syndrome (HR 2.83, P = 0.022), aspartate aminotransferase(AST)/alanine aminotransferase(ALT) (HR 5.07, P = 0.003) were indicators for HCC recurrence. In multivariate Cox regression analysis, the tumor diameter (HR 2.53, P = 0.032) and peritumoral edema (HR 8.71, P < 0.001) were independent prognostic factors of HCC. The sensitivity, specificity, positive predictive value and negative predictive value of peritumoral edema and tumor diameter were 82.6%&60.9%, 80.6%&77.6%, 59.4%&48.3%, and 93.1%&85.3%, respectively.

CONCLUSION

Peritumoral edema in preoperative MRI may be considered as a biomarker of prognostic information for patients with HCC.

Prognostic relevance of CSF and peri-tumoral edema volumes in glioblastoma

BACKGROUND

We conducted a segmental volumetric analysis of pre-operative brain magnetic resonance images (MRIs) of glioblastoma patients to identify brain- and tumor-related features that are prognostic of survival.

METHODS

Using a dataset of 210 single-institutional adult glioblastoma patients, total volumes of the following tumor- and brain-related features were quantified on pre-operative MRIs using a fully automated segmentation tool: tumor enhancement, tumor non-enhancement, tumor necrosis, peri-tumoral edema, grey matter, white matter, and cerebrospinal fluid (CSF). Their association with survival using Cox regression models, adjusting for the well-known predictors of glioblastoma survival. The findings were verified in a second dataset consisting of 96 glioblastoma patients from The Cancer Imaging Archive and The Cancer Genome Atlas (TCIA/TCGA).

RESULTS

CSF volume and edema were independently and consistently associated with overall survival of glioblastoma patients in both datasets. Greater edema was associated with increased hazard or decreased survival [adjusted hazard ratio (aHR) with 95% confidence interval (CI): 1.34 [1.08-1.67], p = 0.008 (institutional dataset); and, 1.44 [1.08-1.93], p = 0.013 (TCIA/TCGA dataset)]. Greater CSF volume also correlated with increased hazard or decreased survival [aHR 1.27 [1.02-1.59], p = 0.035 (institutional dataset), and 1.42 [1.03-1.95], p = 0.032 (TCIA/TCGA dataset)].

CONCLUSIONS

Higher brain CSF volume and higher edema levels at diagnosis are independently associated with decreased survival in glioblastoma patients. These results highlight the importance of a broader, quantitative brain-wide radiological analyses and invite investigations to understand tumor-related causes of increased edema and possibly increased CSF volume.

Impact of Peritumoral Edema During Tumor Treatment Field Therapy: A Computational Modelling Study

BACKGROUND

Tumor treatment fields (TTFie-lds) are an approved adjuvant therapy for glioblastoma (GBM). The magnitude of applied electrical field has been shown to be related to the anti-tumoral response. However, peritumoral edema may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we systematically address this issue with computational simulations.

METHODS

Finite element models are created of a human head with varying amounts of peritumoral edema surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results.

RESULTS

The inclusion of peritumoral edema decreased the average magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥6 mm of peritumoral edema decreased the electric field by 52%. In the patient specific models, peritumoral edema decreased the electric field magnitude within the tumor by an average of 26%. The effect of peritumoral edema on the electric field distribution was spatially heterogenous, being most significant at the tissue interface between edema and tumor.

CONCLUSIONS

The inclusion of peritumoral edema during TTFields modelling may have a dramatic effect on the predicted electric field magnitude within the tumor. Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and when planning TTField therapy.

Emerging Pharmacological Treatments for Cerebral Edema: Evidence from Clinical Studies

Cerebral edema, a common and often fatal companion to most forms of acute central nervous system disease, has been recognized since the time of ancient Egypt. Unfortunately, our therapeutic armamentarium remains limited, in part due to historic limitations in our understanding of cerebral edema pathophysiology. Recent advancements have led to a number of clinical trials for novel therapeutics that could fundamentally alter the treatment of cerebral edema. In this review, we discuss these agents, their targets, and the data supporting their use, with a focus on agents that have progressed to clinical trials.

Personalized Multimodal Demarcation of Peritumoral Tissue in Glioma

PURPOSE

Gliomas are life-threatening brain tumors, and the extent of surgical resection is one of the strongest influences on survival rate. However, the proper distinction of infiltrated tissue remains elusive. The aim of this study was to use multimodal analyses to demarcate peritumoral tissue (PT) from tumoral (TT) and healthy tissue (HT).

METHODS

A total of 40 patients with histologically confirmed glioma were recruited. We analyzed resting-state functional magnetic resonance imaging (rs-fMRI) using the voxel-based mean blood-oxygen-level-dependent (BOLD) signal and the corresponding structural MRI (s-MRI) alongside RNA sequencing, whole-exome sequencing, and histology results of biopsy samples obtained from PT, HT, and TT.

RESULTS

We demarcated a functionally defined PT area where the mean BOLD signal gradually decreased near the edge of the tumor and extended beyond the TT borders (as defined by s-MRI), which was confirmed on a case-by-case basis. Correspondingly, genetic analyses showed a gene expression pattern and mutational landscape of the PT that were distinct from that seen in HT and TT. The genetic characterization of PT relative to HT and TT converged with the MRI-defined PT zones. This was confirmed in three individual cases after additional histologic analysis. A wider PT was associated with a longer progression-free survival, which suggests PT might act as an intermediate area between TT and HT.

CONCLUSION

Combined multimodal imaging and genetic analyses can allow for an objective demarcation of the PT in glioma and a robust classification of the degree of infiltration of the PT. These findings could help improve both neurosurgical resection and radio-oncologic therapy.

Depressive and anxiety disorders worsen the prognosis of glioblastoma

Glioblastoma multiforme (GBM) is one of the most malignant tumors. Depressive and anxiety disorders may co-exist with GBM. We investigated whether depression and anxiety influenced the outcomes of GBM. The Patient Health Questionnaire 9-item (PHQ-9) and Generalized Anxiety Disorder 7-item (GAD-7) scales were used to investigate the mental condition of GBM patients in our department, and the overall survival times of these patients were monitored. The scores on both scales were higher in GBM patients than in healthy controls. For each scale, GBM patients were divided into high- and low-score groups based on the average score. The prognosis was poorer for GBM patients in the high-score groups than for those in the low-score groups. Moreover, magnetic resonance imaging revealed that tumor necrosis was more prevalent among high-scored GBM patients. Cellular experiments were performed on primary GBM cells from patients with either high or low scores on both scales. Sphere formation, EdU and wound healing assays revealed greater proliferation and invasion capacities in GBM cells from patients with high scores on both scales. Western blotting assay revealed significantly different expression of epithelial and mesenchymal markers between the two groups. Thus, our analysis revealed a clinically important correlation between depression/anxiety and GBM prognosis.

Anti-neoplastic Potential of Flavonoids and Polysaccharide Phytochemicals in Glioblastoma

Clinically, gliomas are classified into four grades, with grade IV glioblastoma multiforme being the most malignant and deadly, which accounts for 50% of all gliomas. Characteristically, glioblastoma involves the aggressive proliferation of cells and invasion of normal brain tissue, outcomes as poor patient prognosis. With the current standard therapy of glioblastoma; surgical resection and radiotherapy followed by adjuvant chemotherapy with temozolomide, it remains fatal, because of the development of drug resistance, tumor recurrence, and metastasis. Therefore, the need for the effective therapeutic option for glioblastoma remains elusive. Previous studies have demonstrated the chemopreventive role of naturally occurring pharmacological agents through preventing or reversing the initiation phase of carcinogenesis or arresting the cancer progression phase. In this review, we discuss the role of natural phytochemicals in the amelioration of glioblastoma, with the aim to improve therapeutic outcomes, and minimize the adverse side effects to improve patient's prognosis and enhancing their quality of life.

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Purpose:

Accurate differential diagnosis between glioblastoma and brain metastasis is important. We aimed to differentiate these tumors by evaluation of the perienhancing area.

Materials and Methods:

Thirty patients with glioblastoma and solitary brain metastasis were included. The diameters of perienhancing and enhancing areas were measured, and the percentage of enhancing area was calculated. We measured Apparent diffusion coefficient (ADC) of perienhancing and enhancing areas. Intratumoral necrotic areas were measured.

Results:

The enhancing area of glioblastoma was 56.61% and metastasis was 42.55% (p = 0.08). The ADC values of the perienhancing part of GBM was 0.7 and metastasis was 0.79 (p = 0.052). The ADC value of the enhancing part of the GBM was 0.82 and metastasis was 0.8 (p-value = 0.72). The intratumoral necrotic area of glioblastoma (152.25 mm³) was higher than in metastasis (0 mm³) (p-value = 0.003) with a cutoff area of 11.8 mm².

Conclusion:

The ADC values of the perienhancing area were lower in glioblastoma with a near-significant p-value. Other perienhancing parameters demonstrated no significant difference between both tumors. The intratumoral necrotic area of glioblastoma is larger than metastasis.

The predominant expression of cancer stem cell marker ALDH1A3 in tumor infiltrative area is associated with shorter overall survival of human glioblastoma

Background

ALDH1A3 is a cancer stem cell marker in neoplasms including glioblastoma (GBM). However, the comprehensive role of ALDH1A3 in GBM remains unclear. This study attempted to investigate the expression of ALDH1A3 in human GBM tissues and its association with clinical parameters.

Methods

Thirty primary GBM and 9 control were enrolled in this study. ALDH1A3 mRNA and protein expression levels were detected by RT²-PCR and western blot, respectively. Immunohistochemistry and immunofluorescence staining were performed to evaluate the regional and cellular expression manner of ALDH1A3. The association of ALDH1A3 expression with multiple clinical parameters was analyzed.

Results

ALDH1A3 protein level, but not mRNA level, in a subgroup of GBM was significantly higher than that in the control group. ALDH1A3 immunoreactivity was detected heterogeneously in individual GBMs. Fifteen of 30 cases showed a positive of ALDH1A3 immunoreactivity which was predominantly observed in the tumor infiltrative area (TI). Double immunofluorescence staining revealed a co-localization of ALDH1A3 with GFAP in glial-shaped cells and in tumor cells. ALDH1A3 immunoreactivity was often merged with CD44, but not with CD68. Moreover, ALDH1A3 expression was positively associated with the tumor edema grade and inversely with overall survival (OS) (median OS: 16 months vs 10 months), but with neither MGMT promoter methylation status nor Ki67 index in GBM. An upregulation of ALDH1A3 was accompanied by a reduced expression of STAT3β and p-STAT3β.

Conclusions

Inter- and intra-tumoral heterogeneous expression of ALDH1A3 was exhibited in GBMs. A high immunoreactivity of ALDH1A3 in tumor infiltrative area was associated with shorter OS, especially in patients with MGMT promoter methylation. Our findings propose ALDH1A3 not only as a predictive biomarker but also as a potential target for personalized therapy of GBM.