MR Imaging Characteristics Associate with Tumor-Associated Macrophages in Glioblastoma and Provide an Improved Signature for Survival Prognostication

The FKBP51s Splice Isoform Predicts Unfavorable Prognosis in Patients with Glioblastoma

The primary treatment for glioblastoma (GBM) is removing the tumor mass as defined by MRI. However, MRI has limited diagnostic and predictive value. Tumor-associated macrophages (TAM) are abundant in GBM tumor microenvironment (TME) and are found in peripheral blood (PB). FKBP51 expression, with its canonical and spliced isoforms, is constitutive in immune cells and aberrant in GBM. Spliced FKBP51s supports M2 polarization. To find an immunologic signature that combined with MRI could advance in diagnosis, we immunophenotyped the macrophages of TME and PB from 37 patients with GBM using FKBP51s and classical M1-M2 markers. We also determined the tumor levels of FKBP51s, PD-L1, and HLA-DR. Tumors expressing FKBP51s showed an increase in various M2 phenotypes and regulatory T cells in PB, indicating immunosuppression. Tumors expressing FKBP51s also activated STAT3 and were associated with reduced survival. Correlative studies with MRI and tumor/macrophages cocultures allowed to interpret TAMs. Tumor volume correlated with M1 infiltration of TME. Cocultures with spheroids produced M1 polarization, suggesting that M1 macrophages may infiltrate alongside cancer stem cells. Cocultures of adherent cells developed the M2 phenotype CD163/FKBP51s expressing pSTAT6, a transcription factor enabling migration and invasion. In patients with recurrences, increased counts of CD163/FKBP51s monocyte/macrophages in PB correlated with callosal infiltration and were accompanied by a concomitant decrease in TME-infiltrating M1 macrophages. PB PD-L1/FKBP51s connoted necrotic tumors. In conclusion, FKBP51s identifies a GBM subtype that significantly impairs the immune system. Moreover, FKBP51s marks PB macrophages associated with MRI features of glioma malignancy that can aid in patient monitoring.

SIGNIFICANCE

Our research suggests that by combining imaging with analysis of monocyte/macrophage subsets in patients with GBM, we can enhance our understanding of the disease and assist in its treatment. We discovered a similarity in the macrophage composition between the TME and PB, and through association with imaging, we could interpret macrophages. In addition, we identified a predictive biomarker that drew more attention to immune suppression of patients with GBM.

Molecular diversity in isocitrate dehydrogenase-wild-type glioblastoma

In the dynamic landscape of glioblastoma, the 2021 World Health Organization Classification of Central Nervous System tumours endeavoured to establish biological homogeneity, yet isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma persists as a tapestry of clinical and molecular diversity. Intertumoural heterogeneity in IDH-wt glioblastoma presents a formidable challenge in treatment strategies. Recent strides in genetics and molecular biology have enhanced diagnostic precision, revealing distinct subtypes and invasive patterns that influence survival in patients with IDH-wt glioblastoma. Genetic and molecular biomarkers, such as the overexpression of neurofibromin 1, phosphatase and tensin homolog and/or cyclin-dependent kinase inhibitor 2A, along with specific immune cell abundance and neurotransmitters, correlate with favourable outcomes. Conversely, increased expression of epidermal growth factor receptor tyrosine kinase, platelet-derived growth factor receptor alpha and/or vascular endothelial growth factor receptor, coupled with the prevalence of glioma stem cells, tumour-associated myeloid cells, regulatory T cells and exhausted effector cells, signifies an unfavourable prognosis. The methylation status of O6-methylguanine-DNA methyltransferase and the influence of microenvironmental factors and neurotransmitters further shape treatment responses. Understanding intertumoural heterogeneity is complemented by insights into intratumoural dynamics and cellular interactions within the tumour microenvironment. Glioma stem cells and immune cell composition significantly impact progression and outcomes, emphasizing the need for personalized therapies targeting pro-tumoural signalling pathways and resistance mechanisms. A successful glioblastoma management demands biomarker identification, combination therapies and a nuanced approach considering intratumoural variability. These advancements herald a transformative era in glioblastoma comprehension and treatment.

Deciphering Glioblastoma: Fundamental and Novel Insights into the Biology and Therapeutic Strategies of Gliomas

Gliomas constitute a diverse and complex array of tumors within the central nervous system (CNS), characterized by a wide range of prognostic outcomes and responses to therapeutic interventions. This literature review endeavors to conduct a thorough investigation of gliomas, with a particular emphasis on glioblastoma (GBM), beginning with their classification and epidemiological characteristics, evaluating their relative importance within the CNS tumor spectrum. We examine the immunological context of gliomas, unveiling the intricate immune environment and its ramifications for disease progression and therapeutic strategies. Moreover, we accentuate critical developments in understanding tumor behavior, focusing on recent research breakthroughs in treatment responses and the elucidation of cellular signaling pathways. Analyzing the most novel transcriptomic studies, we investigate the variations in gene expression patterns in glioma cells, assessing the prognostic and therapeutic implications of these genetic alterations. Furthermore, the role of epigenetic modifications in the pathogenesis of gliomas is underscored, suggesting that such changes are fundamental to tumor evolution and possible therapeutic advancements. In the end, this comparative oncological analysis situates GBM within the wider context of neoplasms, delineating both distinct and shared characteristics with other types of tumors.

Correlation of tumor-associated macrophage infiltration in glioblastoma with magnetic resonance imaging characteristics: a retrospective cross-sectional study

Background

Glioblastoma (Gb) is the most common primary malignant tumor of brain with poor prognosis. Immune cells are the main factors affecting the prognosis of Gb, tumor-associated macrophages (TAMs) are the predominant infiltrating immune cell population in the immune microenvironment of Gb. Analyzing the relationship between magnetic resonance imaging (MRI) features and TAMs of Gb, and using imaging features to characterize the infiltration level of TAMs in tumor tissue may provide indicators for clinical decision-making and prognosis evaluation of Gb.

Methods

Data from 140 in patients with isocitrate dehydrogenase (IDH) wild-type Gb diagnosed via histopathology and molecular diagnosis in the Second Hospital of Lanzhou University from January 2018 to April 2022 were collected in this retrospective, cross-sectional study. MRI images were reviewed for lesion location, cyst, necrosis, hemorrhage, contrast-enhanced T1-weighted MRI signal intensity, average apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Immunohistochemical staining with anti-CD163 and anti-CD68 antibodies was employed for macrophage detection. The positive cell percentage was estimated in 9 microscopic fields at 400× magnification per whole-slide image with ImageJ software (National Institutes of Health). Additionally, the relationship between MRI features, molecular, states and the positive CD68 and CD163 expression was analyzed.

Results

Our study discovered that the mean or median values of CD68+ and CD163+ TAMs were 7.39% and 14.98%, respectively. There was an obvious correlation between CD163+ TAMs and CD68+ TAMs (r=0.497; P=0.000). CD68+ and CD163+ macrophage infiltration correlated with age at diagnosis in patients with Gb (CD68+: r=0.230, P=0.006; CD163+: r=0.172, P=0.042). The levels of Gb TAM infiltration in different tumor locations varied, with the temporal lobe having the highest CD163+ macrophage and CD68+ macrophage infiltration (18.58% and 9.46%, respectively). CD163+ macrophage infiltration was positively correlated with ADCmean (r=0.208; P=0.014). The infiltration of CD68+ macrophages differed significantly between groups with varying degrees of tumor enhancement (H =4.228; P=0.017). There was a significant difference in CD68+ TAMs and CD163+ TAMs between the wild-type and mutant-type telomerase reverse transcriptase (TERT) types (P=0.004 and P=0.031, respectively).

Conclusions

Age, location of the tumor, degree of tumor enhancement, ADC value, and TERT mutation status were associated with macrophage infiltration. These findings may serve as an effective tool for characterizing the tumor microenvironment in patients with Gb.

Glioblastoma masquerading as a cystic brain lesion: A case report and evidence-based review

INTRODUCTION AND IMPORTANCE

In adults, glioblastomas account for approximately 12-15 % of primary intracranial neoplasms. In current standard-of-care treatment, glioblastomas have a 5-year survival rate of ~7.5 % and a median survival of ~15 months. Glioblastoma exhibits a highly variable imaging appearance, but the thick and irregular ring enhancement surrounding a necrotic core with infiltrative growth is the most prevalent imaging pattern. Glioblastoma with a cystic component (also known as cystic glioblastoma) is a rare presentation that can be misleading and often mistaken for other cystic brain lesions.

CASE PRESENTATION

In this report, we present a case of a 43-year-old woman who presented to the emergency department with a 2-month history of progressive neurologic manifestations that was attributed to a right-sided cystic brain lesion detected on routine imaging studies, which was later characterized as a cystic glioblastoma based on specific imaging and molecular studies.

CLINICAL DISCUSSION

We highlight the importance of combining radiological and molecular modalities with clinical suspicion for a better characterization of cystic brain lesions and including glioblastoma in the list of potential diagnoses. Furthermore, we provide a comprehensive, evidence-based review of the entity of cystic glioblastoma and how the existence of the cystic component might affect the management and the overall prognosis.

CONCLUSION

Several characteristics make cystic glioblastoma unique. However, it is also capable of mimicking other benign cystic brain lesions, delaying definitive diagnosis and hence the most appropriate management plan.

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.

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.

Magnetic Resonance Imaging Correlates of Immune Microenvironment in Glioblastoma

Background

Glioblastoma (GBM) is the most commonly occurring primary malignant brain tumor, and it carries a dismal prognosis. Focusing on the tumor microenvironment may provide new insights into pathogenesis, but no clinical tools are available to do this. We hypothesized that the infiltration of different leukocyte populations in the tumoral and peritumoral brain tissues may be measured by magnetic resonance imaging (MRI).

Methods

Pre-operative MRI was combined with immune phenotyping of intraoperative tumor tissue based on flow cytometry of myeloid cell populations that are associated with immune suppression, namely, microglia and bone marrow-derived macrophages (BMDM). These cell populations were measured from the central and marginal areas of the lesion identified intraoperatively with 5-aminolevulinic acid-guided surgery. MRI features (volume, mean and standard deviation of signal intensity, and fractality) were derived from all MR sequences (T1w, Gd+ T1w, T2w, FLAIR) and ADC MR maps and from different tumor areas (contrast- and non-contrast-enhancing tumor, necrosis, and edema). The principal components of MRI features were correlated with different myeloid cell populations by Pearson's correlation.

Results

We analyzed 126 samples from 62 GBM patients. The ratio between BMDM and microglia decreases significantly from the central core to the periphery. Several MRI-derived principal components were significantly correlated (p <0.05, r range: [-0.29, -0.41]) with the BMDM/microglia ratio collected in the central part of the tumor.

Conclusions

We report a significant correlation between structural MRI clinical imaging and the ratio of recruited vs. resident macrophages with different immunomodulatory activities. MRI features may represent a novel tool for investigating the microenvironment of GBM.

Treatment Response and Prognosis Evaluation in High-Grade Glioma: An Imaging Review Based on MRI

In recent years, the development of advanced magnetic resonance imaging (MRI) technology and machine learning (ML) have created new tools for evaluating treatment response and prognosis of patients with high-grade gliomas (HGG); however, patient prognosis has not improved significantly. This is mainly due to the heterogeneity between and within HGG tumors, resulting in standard treatment methods not benefitting all patients. Moreover, the survival of patients with HGG is not only related to tumor cells, but also to noncancer cells in the tumor microenvironment (TME). Therefore, during preoperative diagnosis and follow-up treatment of patients with HGG, noninvasive imaging markers are needed to characterize intratumoral heterogeneity, and then to evaluate treatment response and predict prognosis, timeously adjust treatment strategies, and achieve individualized diagnosis and treatment. In this review, we summarize the research progress of conventional MRI, advanced MRI technology, and ML in evaluation of treatment response and prognosis of patients with HGG. We further discuss the significance of the TME in the prognosis of HGG patients, associate imaging features with the TME, indirectly reflecting the heterogeneity within the tumor, and shifting treatment strategies from tumor cells alone to systemic therapy of the TME, which may be a major development direction in the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 4.

Features of Visually AcceSAble Rembrandt Images: Interrater Reliability in Pediatric Brain Tumors

BACKGROUND AND PURPOSE

At present, no evidence-based lexicon exists for pediatric intracranial tumors. The Visually AcceSAble Rembrandt Images terminology describes reproducible MR imaging features of adult gliomas for prediction of tumor grade, molecular markers, and survival. Our aim was to assess the interrater reliability of the pre-resection features of Visually AcceSAble Rembrandt Images in pediatric brain tumors.

MATERIALS AND METHODS

Fifty consecutive pre-resection brain MR imaging examinations of pediatric intracranial neoplasms were independently reviewed by 3 neuroradiologists. The intraclass correlation coefficient for continuous variables and the Krippendorf alpha were used to evaluate the interrater agreement. Subgroup analysis was performed for 30 gliomas.

RESULTS

Parameters with almost perfect agreement (α > .8) included tumor location (F1) and proportion of enhancing tumor (F5). Parameters with substantial agreement (α = .61-.80) were side of tumor epicenter (F2), involvement of eloquent brain (F3), enhancement quality (F4), proportion of non-contrast-enhancing tumor (F6), and deep white matter invasion (F21). The other parameters showed either moderate (α = .41-.60; n = 11), fair (α = .21-.40; n = 5), or slight agreement (α = 0-.20; n = 1). Subgroup analysis of 30 gliomas showed almost perfect agreement for tumor location (F1), involvement of eloquent brain (F3), and proportion of enhancing tumor (F5); and substantial agreement for side of tumor epicenter (F2), enhancement quality (F4), proportion of noncontrast enhancing tumor (F6), cysts (F8), thickness of enhancing margin (F11), and deep white matter invasion (F21). The intraclass correlation coefficient for measurements in the axial plane was excellent in both the main group (0.984 [F29] and 0.982 [F30]) and the glioma subgroup (0.973 [F29] and 0.973 [F30]).

CONCLUSIONS

Nine features of Visually AcceSAble Rembrandt Images have an acceptable interrater agreement in pediatric brain tumors. For the subgroup of pediatric gliomas, 11 features of Visually AcceSAble Rembrandt Images have an acceptable interrater agreement. The low degree of reproducibility of the remainder of the features necessitates the use of features tailored to the pediatric age group and is likely related to the more heterogeneous imaging morphology of pediatric brain tumors.

MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma

PURPOSE

Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients.

METHODS

21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin.

RESULTS

Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor's enhancing zone and necrotic core and the L-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5).

CONCLUSIONS

This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

Prediction of H3K27M mutation status of diffuse midline gliomas using MRI features

BACKGROUND AND PURPOSE

Presurgical prediction of H3K27M mutation in diffuse midline gliomas (DMGs) on MRI is desirable. The purpose of this study is to elaborate conventional MRI (cMRI) features of H3K27M-mutant DMGs and identify features that could discriminate them from wild-type (WT) DMGs.

METHODS

CMRI features of 123 patients with DMG were evaluated conforming to the institutional research protocols. Multimodality MRI was performed on 1.5 or 3.0 Tesla MR Scanners with imaging protocol, including T1-weighted (w), T2w, fluid-attenuated inversion recovery, diffusion-weighted, susceptibility-weighted, and postcontrast T1w sequences. Pertinent cMRI features were annotated along the lines of Visually AcceSAble Rembrandt Images features, and Intra Tumoral Susceptibility Signal score (ITSS) was evaluated. R software was used for statistical analysis.

RESULTS

Sixty-one DMGs were H3K27M-mutant (mutant DMGs). The patients in the H3K27M-mutant DMG group were younger compared to the WT-DMG group (mean age 24.13 ± 13.13 years vs. 35.79±18.74 years) (p = 0.016). The two groups differed on five cMRI features--(1) enhancement quality (p = 0.032), (2) thickness of enhancing margin (p = 0.05), (3) proportion of edema (p = 0.002), (4) definition of noncontrast-enhancing tumor (NCET) margin (p = 0.001), and (5) cortical invasion (p = 0.037). The mutant DMGs showed greater enhancement and greater thickness of enhancing margin, while the WT DMGs exhibited significantly larger edema proportion with poorly defined NCET margins and cortical invasion. ITSS was not significantly different among the groups.

CONCLUSION

CMRI features like enhancement quality, the thickness of the enhancing margin, proportion of edema, definition of NCET margin, and cortical invasion can discriminate between the H3K27M-mutant and WT DMGs.

Macrophages/Microglia in the Glioblastoma Tumor Microenvironment

The complex interaction between glioblastoma and its microenvironment has been recognized for decades. Among various immune profiles, the major population is tumor-associated macrophage, with microglia as its localized homolog. The present definition of such myeloid cells is based on a series of cell markers. These good sentinel cells experience significant changes, facilitating glioblastoma development and protecting it from therapeutic treatments. Huge, complicated mechanisms are involved during the overall processes. A lot of effort has been dedicated to crack the mysterious codes in macrophage/microglia recruiting, activating, reprogramming, and functioning. We have made our path. With more and more key factors identified, a lot of new therapeutic methods could be explored to break the ominous loop, to enhance tumor sensitivity to treatments, and to improve the prognosis of glioblastoma patients. However, it might be a synergistic system rather than a series of clear, stepwise events. There are still significant challenges before the light of truth can shine onto the field. Here, we summarize recent advances in this field, reviewing the path we have been on and where we are now.

Neuroimaging in the Era of the Evolving WHO Classification of Brain Tumors, From the AJR Special Series on Cancer Staging

The inclusion of molecular and genetic information with histopathologic information defines the framework for brain tumor classification and grading. This framework is reflected in the major restructuring of the WHO brain tumor classification system in 2016 and in numerous subsequent proposed updates reflecting ongoing developments in understanding the impact of tumor genotype on classification and grading. This incorporation of molecular and genetic features improves tumor diagnosis and prediction of tumor behavior and response to treatment. Neuroimaging is essential for the noninvasive assessment of pretreatment tumor grading and for identification and determination of therapeutic efficacy. Use of conventional neuroimaging and physiologic imaging techniques, such as diffusion- and perfusion-weighted MRI, can increase diagnostic confidence before and after treatment. Although the use of neuroimaging to consistently determine tumor genetics is not yet robust, promising developments are on the horizon. Given the complexity of the brain tumor microenvironment, the development and implementation of a standardized reporting system can aid in conveying to radiologists, referring providers, and patients important information about brain tumor response to treatment. The purpose of this article is to review the current state and role of neuroimaging in this continuously evolving field.

Combining Magnetic Resonance Imaging with Systemic Monocyte Evaluation for the Implementation of GBM Management

Magnetic resonance imaging (MRI) is the gold standard for glioblastoma (GBM) patient evaluation. Additional non-invasive diagnostic modalities are needed. GBM is heavily infiltrated with tumor-associated macrophages (TAMs) that can be found in peripheral blood. FKBP51s supports alternative-macrophage polarization. Herein, we assessed FKBP51s expression in circulating monocytes from 14 GBM patients. The M2 monocyte phenotype was investigated by qPCR and flow cytometry using antibodies against PD-L1, CD163, FKBP51s, and CD14. MRI assessed morphologic features of the tumors that were aligned to flow cytometry data. PD-L1 expression on circulating monocytes correlated with MRI tumor necrosis score. A wider expansion in circulating CD163/monocytes was measured. These monocytes resulted in a dramatic decrease in patients with an MRI diagnosis of complete but not partial surgical removal of the tumor. Importantly, in patients with residual tumor, most of the peripheral monocytes that in the preoperative stage were CD163/FKBP51s- had turned into CD163/FKBP51s+. After Stupp therapy, CD163/FKBP51s+ monocytes were almost absent in a case of pseudoprogression, while two patients with stable or true disease progression showed sustained levels in such circulating monocytes. Our work provides preliminary but meaningful and novel results that deserve to be confirmed in a larger patient cohort, in support of potential usefulness in GBM monitoring of CD163/FKBP51s/CD14 immunophenotype in adjunct to MRI.

The Role of Microglia in Glioblastoma

Glioblastoma (GB), the most aggressive malignant glioma, is made up of a large percentage of glioma-associated microglia/macrophages (GAM), suggesting that immune cells play an important role in the pathophysiology of GB. Under physiological conditions, microglia, the phagocytes of the central nervous system (CNS), are involved in various processes such as neurogenesis or axonal growth, and the progression of different conditions such as Alzheimer's disease. Through immunohistochemical studies, markers that enhance GB invasiveness have been shown to be expressed in the peritumoral area of ​​the brain, such as Transforming Growth Factor α (TGF-α), Stromal Sell-Derived Factor 1 (SDF1/CXCL12), Sphingosine-1-Phosphate (S1P) and Neurotrophic Factor Derived from the Glial cell line (GDNF), contributing to the increase in tumor mass. Similarly, it has also been described 17 biomarkers that are present in hypoxic periarteriolar HSC niches in bone marrow and in hypoxic periarteriolar GSC niches in glioblastoma. Interestingly, microglia plays an important role in the microenvironment that supports GB progression, being one of the most important focal points in the study of therapeutic targets for the development of new drugs. In this review, we describe the altered signaling pathways in microglia in the context of GB. We also show how microglia interact with glioblastoma cells and the epigenetic mechanisms involved. Regarding the interactions between microglia and neurogenic niches, some authors indicate that glioblastoma stem cells (GSC) are similar to neural stem cells (NSC), common stem cells in the subventricular zone (SVZ), suggesting that this could be the origin of GB. Understanding the similarities between SVZ and the tumor microenvironment could be important to clarify some mechanisms involved in GB malignancy and to support the discovering of new therapeutic targets for the development of more effective glioblastoma treatments.

Clinical Relevance of Alternative Lengthening of Telomeres in Cancer

The alternative lengthening of telomere (ALT) is a pathway responsible for cell immortalization in some kinds of tumors. Since the first description of ALT is relatively recent in the oncology field, its mechanism remains elusive, but recent works address ALT-related proteins or cellular structures as potential druggable targets for more specific and efficient antitumor therapies. Moreover, some new generation compounds for antitelomerase therapy in cancer were able to provoke acquisition of ALT phenotype in treated tumors, enhancing the importance of studies on this alternative lengthening of the telomere. However, ALT has been implicated in different - sometimes opposite - outcomes, according to the tumor type studied. Then, in order to design and develop new drugs for ALT+ cancer in an effective way, it is crucial to understand its clinical implications. In this review, we gathered works published in the last two decades to highlight the clinical relevance of ALT on oncology.

Assessment of Prognostic Value of Cystic Features in Glioblastoma Relative to Sex and Treatment With Standard-of-Care

Glioblastoma (GBM) is the most aggressive primary brain tumor and can have cystic components, identifiable through magnetic resonance imaging (MRI). Previous studies suggest that cysts occur in 7–23% of GBMs and report mixed results regarding their prognostic impact. Using our retrospective cohort of 493 patients with first-diagnosis GBM, we carried out an exploratory analysis on this potential link between cystic GBM and survival. Using pretreatment MRIs, we manually identified 88 patients with GBM that had a significant cystic component at presentation and 405 patients that did not. Patients with cystic GBM had significantly longer overall survival and were significantly younger at presentation. Within patients who received the current standard of care (SOC) (N = 184, 40 cystic), we did not observe a survival benefit of cystic GBM. Unexpectedly, we did not observe a significant survival benefit between this SOC cystic cohort and patients with cystic GBM diagnosed before the standard was established (N = 40 with SOC, N = 19 without SOC); this significant SOC benefit was clearly observed in patients with noncystic GBM (N = 144 with SOC, N = 111 without SOC). When stratified by sex, the survival benefit of cystic GBM was only preserved in male patients (N = 303, 47 cystic). We report differences in the absolute and relative sizes of imaging abnormalities on MRI and the prognostic implication of cysts based on sex. We discuss hypotheses for these differences, including the possibility that the presence of a cyst could indicate a less aggressive tumor.

Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma

INTRODUCTION

Survival varies in patients with glioblastoma due to intratumoral heterogeneity and radiomics/imaging biomarkers have potential to demonstrate heterogeneity. The objective was to combine radiomic, semantic and clinical features to improve prediction of overall survival (OS) and O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation status from pre-operative MRI in patients with glioblastoma.

METHODS

A retrospective study of 181 MRI studies (mean age 58 ± 13 years, mean OS 497 ± 354 days) performed in patients with histopathology-proven glioblastoma. Tumour mass, contrast-enhancement and necrosis were segmented from volumetric contrast-enhanced T1-weighted imaging (CE-T1WI). 333 radiomic features were extracted and 16 Visually Accessible Rembrandt Images (VASARI) features were evaluated by two experienced neuroradiologists. Top radiomic, VASARI and clinical features were used to build machine learning models to predict MGMT status, and all features including MGMT status were used to build Cox proportional hazards regression (Cox) and random survival forest (RSF) models for OS prediction.

RESULTS

The optimal cut-off value for MGMT promoter methylation index was 12.75%; 42 radiomic features exhibited significant differences between high and low-methylation groups. However, model performance accuracy combining radiomic, VASARI and clinical features for MGMT status prediction varied between 45 and 67%. For OS predication, the RSF model based on clinical, VASARI and CE radiomic features achieved the best performance with an average iAUC of 96.2 ± 1.7 and C-index of 90.0 ± 0.3.

CONCLUSIONS

VASARI features in combination with clinical and radiomic features from the enhancing tumour show promise for predicting OS with a high accuracy in patients with glioblastoma from pre-operative volumetric CE-T1WI.

Intronic TP53 Polymorphisms Are Associated with Increased Δ133TP53 Transcript, Immune Infiltration and Cancer Risk

We investigated the influence of selected TP53 SNPs in exon 4 and intron 4 on cancer risk, clinicopathological features and expression of TP53 isoforms. The intron 4 SNPs were significantly over-represented in cohorts of mixed cancers compared to three ethnically matched controls, suggesting they confer increased cancer risk. Further analysis showed that heterozygosity at rs1042522(GC) and either of the two intronic SNPs rs9895829(TC) and rs2909430(AG) confer a 2.34-5.35-fold greater risk of developing cancer. These SNP combinations were found to be associated with shorter patient survival for glioblastoma and prostate cancer. Additionally, these SNPs were associated with tumor-promoting inflammation as evidenced by high levels of infiltrating immune cells and expression of the Δ133TP53 and TP53β transcripts. We propose that these SNP combinations allow increased expression of the Δ133p53 isoforms to promote the recruitment of immune cells that create an immunosuppressive environment leading to cancer progression.

Targeting Tumor Associated Macrophages to Overcome Conventional Treatment Resistance in Glioblastoma

Glioblastoma (GB) is the most common and devastating form of brain cancer. Despite conventional treatments, progression or recurrences are systematic. In recent years, immunotherapies have emerged as an effective treatment in a number of cancers, leaving the question of their usefulness also faced with the particular case of brain tumors. The challenge here is major not only because the brain is the seat of our consciousness but also because of its isolation by the blood-brain barrier and the presence of a unique microenvironment that constitutes the central nervous system (CNS) with very specific constituent or patrolling cells. Much of the microenvironment is made up of immune cells or inflammation. Among these, tumor-associated macrophages (TAMs) are of significant interest as they are often involved in facilitating tumor progression as well as the development of resistance to standard therapies. In this review, the ubiquity of TAMs in GB will be discussed while the specific case of microglia resident in the brain will be also emphasized. In addition, the roles of TAMs as accomplices in the progression of GB and resistance to treatment will be presented. Finally, clinical trials targeting TAMs as a means of treating cancer will be discussed.

MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas

PURPOSE

To identify significant prognostic magnetic resonance imaging (MRI) features and their prognostic value when added to clinical features in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas.

MATERIALS AND METHODS

Preoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS.

RESULTS

The presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735).

CONCLUSION

MRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features.

KEY POINTS

• Comprehensive analysis of MRI features conveys prognostic information in patients with isocitrate dehydrogenase wild-type lower-grade gliomas. • Presence of cysts, pial invasion, and cortical involvement of the tumor were favorable prognostic factors. • Radiological phenotypes derived from MRI independently predict survival and have the potential to improve survival prediction when added to clinical features.

Alternative Lengthening of Telomeres (ALT) in Tumors and Pluripotent Stem Cells

A telomere consists of repeated DNA sequences (TTAGGG)n as part of a nucleoprotein structure at the end of the linear chromosome, and their progressive shortening induces DNA damage response (DDR) that triggers cellular senescence. The telomere can be maintained by telomerase activity (TA) in the majority of cancer cells (particularly cancer stem cells) and pluripotent stem cells (PSCs), which exhibit unlimited self-proliferation. However, some cells, such as telomerase-deficient cancer cells, can add telomeric repeats by an alternative lengthening of the telomeres (ALT) pathway, showing telomere length heterogeneity. In this review, we focus on the mechanisms of the ALT pathway and potential clinical implications. We also discuss the characteristics of telomeres in PSCs, thereby shedding light on the therapeutic significance of telomere length regulation in age-related diseases and regenerative medicine.

Elevation of the TP53 isoform Δ133p53β in glioblastomas: an alternative to mutant p53 in promoting tumor development

As tumor protein 53 (p53) isoforms have tumor‐promoting, migration, and inflammatory properties, this study investigated whether p53 isoforms contributed to glioblastoma progression. The expression levels of full‐length TP53α (TAp53α) and six TP53 isoforms were quantitated by RT‐qPCR in 89 glioblastomas and correlated with TP53 mutation status, tumor‐associated macrophage content, and various immune cell markers. Elevated levels of Δ133p53β mRNA characterised glioblastomas with increased CD163‐positive macrophages and wild‐type TP53. In situ‐based analyses found Δ133p53β expression localised to malignant cells in areas with increased hypoxia, and in cells with the monocyte chemoattractant protein C‐C motif chemokine ligand 2 (CCL2) expressed. Tumors with increased Δ133p53β had increased numbers of cells positive for macrophage colony‐stimulating factor 1 receptor (CSF1R) and programmed death ligand 1 (PDL1). In addition, cells expressing a murine ‘mimic’ of Δ133p53 (Δ122p53) were resistant to temozolomide treatment and oxidative stress. Our findings suggest that elevated Δ133p53β is an alternative pathway to TP53 mutation in glioblastoma that aids tumor progression by promoting an immunosuppressive and chemoresistant environment. Adding Δ133p53β to a TP53 signature along with TP53 mutation status will better predict treatment resistance in glioblastoma. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.