Transcriptional diversity of long-term glioblastoma survivors

Clinicopathological and molecular landscape of 5-year IDH-wild-type glioblastoma survivors: A multicentric retrospective study

Five-year glioblastoma (GBM) survivors (LTS) are the minority of the isocitrate dehydrogenase (IDH)-wild-type GBM patients, and their molecular fingerprint is still largely unexplored. This multicenter retrospective study analyzed a large LTS-GBM cohort from nine Italian institutions and molecularly characterized a subgroup of patients by mutation, DNA methylation (DNAm) and copy number variation (CNV) profiling, comparing it to standard survival GBM. Mutation scan allowed the identification of pathogenic variants in most cases, showing a similar mutational spectrum in both groups, and highlighted TP53 as the most commonly mutated gene in the LTS group. We confirmed DNAm as a valuable tool for GBM classification with a diagnostic refinement by using brain tumor classifier v12.5. LTS were more heterogeneous with more cases classified as diffuse pediatric high-grade glioma subtypes and having peculiar CNVs. We observed a global higher methylation in CpG islands and in gene promoters of LTS with methylation levels of distinct gene promoters correlating with prognosis.

Expression of STAT3 and hypoxia markers in long-term surviving malignant glioma patients

BACKGROUND

Glioblastoma is a malignant and aggressive type of central nevous system malignancy characterized by many distinct biological features including extensive hypoxia. Hypoxia in glioblatoma associates with complex signaling patterns including activation of several pathways such as MAPK, PI3K-AKT/mTOR and IL-6/JAK/STAT3 with the master regulator HIF-1, which in turn drive particular tumor behaviors determining, in the end, treatment outcomes and patients fate. Thus, the present study was designed to investigate the expression of selected hypoxia related factors including STAT3 in a small set of long-term surviving glioma patients.

METHODS

The expression of selected hypoxia related factors including STAT3 was evaluated in a time series of formalin fixed paraffin embedded and cryopreserved glioma samples from repeatedly resected patients. In addition, comparative studies were also conducted on primary glioma cells derived from original patient samples, stabilized glioma cell lines and tumor-xenograft mice model. Obtained data were correlated with clinical findings too.

RESULTS

Glioblastoma samples of the analyzed patients displayed heterogeneity in the expression of hypoxia- related and EMT markers with most interesting trend being observed in pSTAT3. This heterogeneity was subsequently confirmed in other employed models (primocultures derived from glioblastoma tissue resections, cryopreserved tumor specimens, stabilized glioblastoma cell line in vitro and in vivo) and concerned, in particular, STAT3 expression which remained stable. In addition, subsequent studies on the role of STAT3 in the context of glioblastoma hypoxia demonstrated opposing effects of its deletion on cell viability as well as the expression of hypoxia and EMT markers.

CONCLUSIONS

Our results suport the importance of STAT3 expression and activity in the context of hypoxia in malignant glioblastoma long-term surviving glioma patients while emphasizing heterogeneity of biological outcomes in varying employed tumor models.

Long-term survivors of glioblastoma: Tumor molecular, clinical, and imaging findings

Background

Glioblastoma (GBM) is the most aggressive primary brain malignancy with <45% living a year beyond diagnosis. Previously published investigations of long-term survivors (LTS) provided clinical data but rarely incorporated a comprehensive clinical and molecular analysis. Herein, we identify clinical, imaging, molecular, and outcome features for 23 GBM-LTS patients and compare them with a matched cohort of short-term survivors (STS).

Methods

Molecularly confirmed Isocitrate Dehydrogenase (IDH) wildtype GBM patients living ≥3 years post-diagnosis (NLTS = 23) or <3 years (NSTS = 75) were identified from our Natural History study. Clinical and demographic characteristics were compared. Tumor tissue was analyzed with targeted next generation sequencing (NGS) (NLTS = 23; NSTS = 74) and methylation analysis (NLTS = 18; NSTS = 28). Pre-surgical MRI scans for a subset of LTS (N = 14) and STS control (N = 28) matched on sex, age, and extent of resection were analyzed.

Results

LTS tended to be younger. Diagnostic MRIs showed more LTS with T1 tumor hypointensity. LTS tumors were enriched for MGMTp methylation and tumor protein 53 (TP53) mutation. Three patients with classic GBM histology were reclassified based on NGS and methylation testing. Additionally, there were LTS with typical poor prognostic molecular markers.

Conclusions

Our findings emphasize that generalized predictions of prognosis are inaccurate for individual patients and underscore the need for complete clinical evaluation including molecular work-up to confirm the diagnosis. Continued accrual of patients to LTS registries that containcomprehensive clinical, imaging, tumor molecular data, and outcomes measures may pro\vide important insights about individual patient prognosis.

Epithelial Membrane Protein-3 and Chitinase-3-like Protein-1 as New Prognostic Predictors of Glioma, a Two-Gene Study

BACKGROUND

Glioblastoma multiforme is the most common primary intracranial tumor, with a high degree of malignancy, poor therapeutic effect, and poor prognosis. According to previous studies, CHI3L1 and EMP3 are two independent tumor predictors that are of great significance for the prognostic prediction of other tumors, and their expression levels may be related to the prognosis of glioma patients.

METHODS

using Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Chinese Glioma Genome Atlas (CGGA), cBioPortal, LinkedOmics, and other databases, 693 glioma patients were screened to analyze the relationship between EMP3 and CHI3L1 expression and prognosis in glioma patients.

RESULTS

low-grade glioma patients with a low expression of EMP3/CHI3L1 had a better prognosis, and the combination of EMP3/CHI3L1 is a new predictor for glioma patients.

CONCLUSION

We used the TCGA and CGGA databases to analyze the effect of EMP3 and CHI3L1 expression on the prognosis of glioma patients and their correlation with gene expression using bioinformation analysis. The results showed that low-grade glioma patients with a low expression of EMP3 and CHI3L1 had a better prognosis, and EMP3 and CHI3L1 co-expression genes were correlated. The combination of these two factors could be a new prognostic index for glioma patients.

Adult IDH Wild-Type Glioblastoma Ultrastructural Investigation Suggests a Possible Correlation between Morphological Biomarkers and Ki-67 Index

Glioblastoma is an aggressive brain tumor with an average life expectancy between 14 and 16 months after diagnosis. The Ki-67 labeling index (LI), a measure of cellular proliferation, is emerging as a prognostic marker in GBM. In this study, we investigated the ultrastructure of glioblastoma tissue from 9 patients with the same molecular profile (adult IDH wild-type glioblastoma, wild-type ATRX, and positive for TP53 expression, GFAP expression, and EGFR overexpression) to find possible ultrastructural features to be used as biomarkers and correlated with the only parameter that differs among our samples, the Ki-67 LI. Our main results were the visualization of the anatomical basis of astrocyte-endothelial cells crosstalk; the ultrastructural in situ imaging of clusters of hyperactivated microglia cells (MsEVs); the ultrastructural in situ imaging of microglia cells storing lipid vesicles (MsLVs); the ultrastructural in situ imaging of neoplastic cells mitophagy (NCsM). The statistical analysis of our data indicated that MsEVs and MsLVs correlate with the Ki-67 LI value. We can thus assume they are good candidates to be considered morphological biomarkers correlating to Ki-67 LI. The role of NCsM instead must be further evaluated. Our study findings demonstrate that by combining ultrastructural characteristics with molecular information, we can discover biomarkers that have the potential to enhance diagnostic precision, aid in treatment decision-making, identify targets for therapy, and enable personalized treatment plans tailored to each patient. However, further research with larger sample sizes is needed to validate these findings and fully utilize the potential of ultrastructural analysis in managing glioblastoma.

ProJect: a powerful mixed-model missing value imputation method

Missing values (MVs) can adversely impact data analysis and machine-learning model development. We propose a novel mixed-model method for missing value imputation (MVI). This method, ProJect (short for Protein inJection), is a powerful and meaningful improvement over existing MVI methods such as Bayesian principal component analysis (PCA), probabilistic PCA, local least squares and quantile regression imputation of left-censored data. We rigorously tested ProJect on various high-throughput data types, including genomics and mass spectrometry (MS)-based proteomics. Specifically, we utilized renal cancer (RC) data acquired using DIA-SWATH, ovarian cancer (OC) data acquired using DIA-MS, bladder (BladderBatch) and glioblastoma (GBM) microarray gene expression dataset. Our results demonstrate that ProJect consistently performs better than other referenced MVI methods. It achieves the lowest normalized root mean square error (on average, scoring 45.92% less error in RC_C, 27.37% in RC_full, 29.22% in OC, 23.65% in BladderBatch and 20.20% in GBM relative to the closest competing method) and the Procrustes sum of squared error (Procrustes SS) (exhibits 79.71% less error in RC_C, 38.36% in RC full, 18.13% in OC, 74.74% in BladderBatch and 30.79% in GBM compared to the next best method). ProJect also leads with the highest correlation coefficient among all types of MV combinations (0.64% higher in RC_C, 0.24% in RC full, 0.55% in OC, 0.39% in BladderBatch and 0.27% in GBM versus the second-best performing method). ProJect's key strength is its ability to handle different types of MVs commonly found in real-world data. Unlike most MVI methods that are designed to handle only one type of MV, ProJect employs a decision-making algorithm that first determines if an MV is missing at random or missing not at random. It then employs targeted imputation strategies for each MV type, resulting in more accurate and reliable imputation outcomes. An R implementation of ProJect is available at https://github.com/miaomiao6606/ProJect.

Clinical characteristics and radiological features of glioblastoma, IDH-wildtype, grade 4 with histologically lower-grade gliomas

The 2021 World Health Organization (WHO) classification of central nervous system tumors applied molecular criteria and further integrated histological and molecular diagnosis of gliomas. This classification allows for the diagnosis of isocitrate dehydrogenase wild-type (IDHwt) glioblastoma (GBM), and WHO grade 4 with histologically lower-grade gliomas (LrGGs), even in the absence of high-grade histopathologic features, such as necrosis and/or microvascular proliferation. They contain at least one of the following molecular features: epidermal growth factor receptor amplification, chromosome 7 gain/10 loss, or telomerase reverse transcriptase promoter mutation. In the imaging features at the time of histological diagnosis, a gliomatosis cerebri growth pattern was frequently observed in these tumors. Furthermore, this growth pattern was significantly higher in IDHwt GBM, WHO grade 4, with histological grade II gliomas. Although the exact prognosis of IDHwt GBM, WHO grade 4, with histologically LGGs remains unknown, its OS was approximately 1-2 years similar to that of histologically IDHwt GBM, WHO grade 4, despite histopathological features similar to IDHmut LrGGs. These findings reinforce the need for the analysis of molecular features, regardless of presenting similar clinical characteristics and imaging features to IDHmut LrGGs.

Interaction of tumor-associated microglia/macrophages and cancer stem cells in glioma

Glioma is the most common tumor of the primary central nervous system, and its malignant phenotype has been shown to be closely related to glioma stem cells (GSCs). Although temozolomide has significantly improved the therapeutic outcome of glioma with a high penetration rate of the blood-brain barrier, resistance is often present in patients. Moreover, evidence has shown that the crosstalk between GSCs and tumor-associated microglia/macrophages (TAMs) affect the clinical occurrence, growth, and multi-tolerance of chemoradiotherapy in gliomas. Here, we highlight its vital roles in the maintenance of the stemness of GSCs and the ability of GSCs to recruit TAMs to the tumor microenvironment and promote their polarization into tumor-promoting macrophages, hence providing groundwork for future research into new treatment strategies of cancer.

Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping

Driven by multi-omics data, some multi-view clustering algorithms have been successfully applied to cancer subtypes prediction, aiming to identify subtypes with biometric differences in the same cancer, thereby improving the clinical prognosis of patients and designing personalized treatment plan. Due to the fact that the number of patients in omics data is much smaller than the number of genes, multi-view spectral clustering based on similarity learning has been widely developed. However, these algorithms still suffer some problems, such as over-reliance on the quality of pre-defined similarity matrices for clustering results, inability to reasonably handle noise and redundant information in high-dimensional omics data, ignoring complementary information between omics data, etc. This paper proposes multi-view spectral clustering with latent representation learning (MSCLRL) method to alleviate the above problems. First, MSCLRL generates a corresponding low-dimensional latent representation for each omics data, which can effectively retain the unique information of each omics and improve the robustness and accuracy of the similarity matrix. Second, the obtained latent representations are assigned appropriate weights by MSCLRL, and global similarity learning is performed to generate an integrated similarity matrix. Third, the integrated similarity matrix is used to feed back and update the low-dimensional representation of each omics. Finally, the final integrated similarity matrix is used for clustering. In 10 benchmark multi-omics datasets and 2 separate cancer case studies, the experiments confirmed that the proposed method obtained statistically and biologically meaningful cancer subtypes.

Survival Benefit of Supratotal Resection in a Long-term Survivor of IDH-wildtype Glioblastoma: A Case Report and Literature Review

Glioblastoma multiforme (GBM) is an aggressive cancer type, with fewer than 3–5% of patients surviving for more than 3 years. We describe a 48-year-old right-handed man who presented with generalized seizure attacks. Magnetic resonance imaging (MRI) revealed a heterogeneous gadolinium-enhancing lesion in the left inferior parietal lobule. The patient underwent awake surgery, and tumor resection included abnormalities on T2-weighted MRI, with subcortical mapping used to identify the deep functional boundaries. After supratotal resection, the tumor was diagnosed as GBM without isocitrate dehydrogenase (IDH) 1 and 2 mutations. At a follow-up evaluation, 9 years and 2 months after the surgery, the patient appeared healthy, and no relapse or recurrence was observed. We present the case of a long-term survivor of IDH-wildtype GBM. This case suggests that supratotal resection with intraoperative awake brain mapping can improve survival without impairing the patient’s neurological functions.

Identification of a novel metabolism-related gene signature associated with the survival of bladder cancer

Background

Bladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients.

Methods

First, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC.

Results

In the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability.

Conclusion

We successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09006-w.

A Novel Nomogram for Predicting the Risk of Short-Term Recurrence After Surgery in Glioma Patients

Objective

The aim of this study was to establish a nomogram model for predicting the risk of short-term recurrence in glioma patients.

Methods

The clinical data of recurrent glioma patients were summarized and analyzed in this study. Univariate and multivariate logistic regression analyses were performed to analyze the correlation between clinical data and the risk of short-term recurrence after operation. A nomogram was established based on the multivariate logistic regression model results.

Results

A total of 175 patients with recurrent glioma were enrolled, with 53 patients in the short-term recurrence (STR) group (recurrent time ≤6 months) and 122 patients in the long-term recurrence (LTR) group (recurrent time ≥36 months). Univariate analysis revealed that age at diagnosis, Karnofsky performance scores (KPSs), tumor location, glioma grade, glioma type, extent of resection (EOR), adjuvant chemotherapy (ad-CT), concurrent chemotherapy (co-CT), and isocitrate dehydrogenase (IDH) status were significantly associated with the short-term glioma recurrence. Multivariate analyses revealed that age at diagnosis, KPS, glioma grade, EOR, and IDH were independent risk factors for short-term glioma recurrence. A risk nomogram for the short-term recurrence of glioma was established, with the concordance index (C-index) of 0.971. The findings of calibration and receiver operating characteristic (ROC) curves showed that our nomogram model had good performance and discrimination to estimate short-term recurrence probability.

Conclusion

This nomogram model provides reliable information about the risk of short-term glioma recurrence for oncologists and neurosurgeons. This model can predict the short-term recurrence probability and give assistance to decide the interval of follow-up or formulate individualized treatment strategies based on the predicted results. A free online prediction risk tool for this nomogram is provided: https://rj2021.shinyapps.io/Nomogram_ recurrence-risk/.

Modulation of the Complement System by Neoplastic Disease of the Central Nervous System

The complement system is a highly conserved component of innate immunity that is involved in recognizing and responding to pathogens. The system serves as a bridge between innate and adaptive immunity, and modulation of the complement system can affect the entire host immune response to a foreign insult. Neoplastic diseases have been shown to engage the complement system in order to evade the immune system, gain a selective growth advantage, and co-opt the surrounding environment for tumor proliferation. Historically, the central nervous system has been considered to be an immune-privileged environment, but it is now clear that there are active roles for both innate and adaptive immunity within the central nervous system. Much of the research on the role of immunological modulation of neoplastic disease within the central nervous system has focused on adaptive immunity, even though innate immunity still plays a critical role in the natural history of central nervous system neoplasms. Here, we review the modulation of the complement system by a variety of neoplastic diseases of the central nervous system. We also discuss gaps in the current body of knowledge and comment on future directions for investigation.

The Multifunctional Role of EMP3 in the Regulation of Membrane Receptors Associated with IDH-Wild-Type Glioblastoma

Epithelial membrane protein 3 (EMP3) is a tetraspan membrane protein overexpressed in isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma (GBM). Several studies reported high EMP3 levels as a poor prognostic factor in GBM patients. Experimental findings based on glioma and non-glioma models have demonstrated the role of EMP3 in the regulation of several membrane proteins known to drive IDH-wt GBM. In this review, we summarize what is currently known about EMP3 biology. We discuss the regulatory effects that EMP3 exerts on a variety of oncogenic receptors and discuss how these mechanisms may relate to IDH-wt GBM. Lastly, we enumerate the open questions towards EMP3 function in IDH-wt GBM.

Living with a central nervous system (CNS) tumor: findings on long-term survivorship from the NIH Natural History Study

Background

Primary central nervous system (CNS) tumors are often associated with high symptom burden and a poor prognosis from the time of diagnosis. The purpose of this study is to describe patient-reported outcomes (PRO) data from long-term survivors (LTS; ≥5-year survival post-diagnosis).

Methods

Clinical/treatment/molecular characteristics and PROs (symptom burden/interference (MDASI-BT/SP), perceived cognition (Neuro-QoL), anxiety/depression (PROMIS), and general health status (EQ-5D-3L)) were collected on 248 adult LTS between 9/2016 and 8/2019. Descriptive statistics and regression analysis were used to report results.

Results

Participants had a median age of 47 years (19-82) and were primarily White (83%) males (51%) with high-grade tumors (59%) and few mutations. Forty-two percent of the 222 brain tumor LTS reported no moderate-to-severe symptoms, whereas 45% reported three or more; most common symptoms were fatigue (40%), difficulty remembering (29%), and drowsiness (28%). Among spine tumor LTS (n = 42), nearly half reported moderate-to-severe weakness, pain, fatigue, and numbness/tingling, with 72% experiencing activity-related interference. Severe anxiety, depression, and cognitive symptoms were reported in up to 23% of the sample. Brain tumor LTS at higher risk for severe symptoms were more likely to be young, unemployed, and have poor KPS (Karnofsky Performance Status), whereas high symptom-risk spinal cord tumor LTS had poor KPS and received any tumor treatment.

Conclusions

Findings indicate LTS fall into distinct cohorts with no significant symptoms or very high symptom burden, regardless of tumor grade or mutational profile. These LTS data demonstrate the need for survivorship care programs and future studies to explore the symptom trajectory of all CNS tumor patients for prevention and early interventions.

Dissecting the mechanism of temozolomide resistance and its association with the regulatory roles of intracellular reactive oxygen species in glioblastoma

Glioblastoma is the most common primary malignant brain tumor that is usually considered fatal even with treatment. This is often a result for tumor to develop resistance. Regarding the standard chemotherapy, the alkylating agent temozolomide is effective in disease control but the recurrence will still occur eventually. The mechanism of the resistance is various, and differs in terms of innate or acquired. To date, aberrations in O⁶-methylguanine-DNA methyltransferase are the clear factor that determines drug susceptibility. Alterations of the other DNA damage repair genes such as DNA mismatch repair genes are also known to affect the drug effect. Together these genes have roles in the innate resistance, but are not sufficient for explaining the mechanism leading to acquired resistance. Recent identification of specific cellular subsets with features of stem-like cells may have role in this process. The glioma stem-like cells are known for its superior ability in withstanding the drug-induced cytotoxicity, and giving the chance to repopulate the tumor. The mechanism is complicated to administrate cellular protection, such as the enhancing ability against reactive oxygen species and altering energy metabolism, the important steps to survive. In this review, we discuss the possible mechanism for these specific cellular subsets to evade cancer treatment, and the possible impact to the following treatment courses. In addition, we also discuss the possibility that can overcome this obstacle.

Overcoming the Odds: Toward a Molecular Profile of Long-Term Survival in Glioblastoma

For over a century, gliomas were characterized solely by histologic features. With the publication of the WHO Classification of Tumours of the Central Nervous System, Revised 4th Edition in 2016, integrated histologic and molecular diagnosis became the norm, providing improved tumor grading and prognosis with IDH1/2 (isocitrate dehydrogenase 1 and 2) mutation being the most significant prognostic feature in all grades of adult diffuse glioma. Since then, much work has been done to identify additional molecular prognostic features, but the bulk of the progress has been made in defining aggressive features in lower grade astrocytoma. Although there have been several large case series of glioblastomas with long-term survival (LTS; overall survival ≥36 months), less is known about the clinical and molecular features of these cases. Herein, we review 19 studies examining LTS glioblastoma patients from 2009 to 2020 that include variable molecular analysis, including 465 cases with survival of 36 months or more (total n = 2328). These studies suggest that while there is no definitive molecular signature of long survival, younger age, IDH mutation, and MGMT (methyl guanine methyl transferase) promoter hypermethylation are associated with longer overall survival, and in IDH-wildtype tumors, chromosome 19/20 co-gain and lack of EGFR amplification, chromosome 7 gain/10 loss, and TERT promoter mutation are associated with LTS.

A novel gene signature based on five immune checkpoint genes predicts the survival of glioma

BACKGROUND

Glioma is the most common and fatal type of nerve neoplasm in the central nervous system. Several biomarkers have been considered for prognosis prediction, which is not accurate enough. We aimed to carry out a gene signature related to the expression of immune checkpoints which was enough for its performance in prediction.

METHODS

Gene expression of immune checkpoints in TGGA database was filtrated. The 5 selected genes underwent verification by COX and Lasso-COX regression. Next, the selected genes were included to build a novel signature for further analysis.

RESULTS

Patients were sub-grouped into high and low risk according to the novel signature. Immune response, clinicopathologic characters, and survival showed significant differences between those 2 groups. Terms including "naive," "effector," and "IL-4" were screened out by GSEA. The results showed strong relevance between the signature and immune response.

CONCLUSIONS

We constructed a gene signature with 5 immune checkpoints. The signature predicted survival effectively. The novel signature performed more functional than previous biomarkers.

Analysis of Factors Associated with Long-Term Survival in Patients with Glioblastoma

BACKGROUND

Some patients with glioblastoma multiforme (GBM) survive 3-5 years (or longer) after diagnosis. The goal of this study was to identify differences between the long-term survivors (LTS) and those who had a shorter overall survival (non-LTS groups).

METHODS

This study was a retrospective analysis of prospectively maintained surgical databases. All patients who underwent safe maximal resection for GBM were included. Demographic, clinical, radiologic, and pathologic data were obtained from electronic medical records. Values of the biomarkers of systemic inflammation were computed from the preoperative hemogram reports. Patients with an overall survival (OS) ≥36 months were defined as the LTS group and were compared with the non-LTS groups (OS<36 months).

RESULTS

Patients in the LTS group were younger, had a better baseline performance status, and were more likely to have undergone near- or gross-total resection. LTS was associated with lower Ki67 labeling, MGMT methylation, IDH mutation, and lack of p53 overexpression. Several novel findings were generated by this study. A longer pretreatment duration of symptoms was associated with a longer OS. Higher pretreatment levels of the absolute neutrophil count, neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, derived neutrophil-lymphocyte ratio and systemic index of inflammation, and lower levels of the absolute eosinophil count and eosinophil-lymphocyte ratio all correlated with a shorter OS.

CONCLUSIONS

Several differences were identified between the LTS and non-LTS groups. These differences will likely be incorporated into future prognostic models. They may also aid in differentiation between recurrent disease and treatment-related changes.

Single-Cell RNA-Sequencing Shift in the Interaction Pattern Between Glioma Stem Cells and Immune Cells During Tumorigenesis

Glioblastoma is one of the most common neoplasms in the central nervous system characterized by limited immune response and unlimited expansion capability. Cancer stem cells (GSCs), a small fraction of the tumor cells, possess a pivotal regulation capability in the tumor microenvironment with a superior proliferation ability. We aimed to reveal the interaction between glioma stem cells (GSCs) and immune cells during tumorigenesis. Single-cell sequencing data from seven surgical specimens of glioblastoma patients and patient-derived GSCs cocultured with peripheral leukocytes were used for the analysis. Cell grouping and trajectory analysis were performed using Seurat and Monocle 3 packages in R software. The gene set of Cancer Genome Anatomy Project was used to define different cell types. Cells with the ability of proliferation and differentiation in glioblastoma tissue were defined as GSCs, which had a similar expression pattern to that in the GSCs in vitro. Astrocytes in glioblastoma were mainly derived from differentiated GSCs, while oligodendrocytes were most likely to be derived from different precursor cells. No remarkable evolutionary trajectory was observed among the subgroups of T cells in glioblastoma. The immune checkpoint interaction between GSCs and immune cells was changed from stimulatory to inhibitory during tumorigenesis. The patient-derived GSCs system is an ideal model for GSC research. The above research revealed that the interaction pattern between GSC glioma stem cells and immune cells during tumorigenesis provides a theoretical basis for GSC glioma stem cell-targeted immunotherapy.

MP-Pt(IV): A MAOB-Sensitive Mitochondrial-Specific Prodrug for Treating Glioblastoma

We have previously reported the in vitro and in vivo efficacy of N,N-bis(2-chloroethyl)-2-(1-methyl-1,2,3,6-tetrahydropyridin-4-yl)propenamide (MP-MUS), a prodrug that targeted the mitochondria of glioblastoma (GBM). The mitochondrial enzyme, monoamine oxidase B (MAOB), is highly expressed in GBM and oxidizes an uncharged methyl-tetrahydropyridine (MP-) moiety into the mitochondrially targeted cationic form, methyl-pyridinium (P⁺-). Coupling this MAOB-sensitive group to a nitrogen mustard produced a prodrug that damaged GBM mitochondria and killed GBM cells. Unfortunately, the intrinsic reactivity of the nitrogen mustard group and low solubility of MP-MUS precluded clinical development. In our second-generation prodrug, MP-Pt(IV), we coupled the MP group to an unreactive cisplatin precursor. The enzymatic conversion of MP-Pt(IV) to P⁺-Pt(IV) was tested using recombinant human MAOA and rhMAOB. The generation of cisplatin from Pt(IV) by ascorbate was studied optically and using mass spectroscopy. Efficacy toward primary GBM cells and tumors was studied in vitro and in an intracranial patient-derived xenograft mice GBM model. Our studies demonstrate that MP-Pt(IV) is selectively activated by MAOB. MP-Pt(IV) is highly toxic toward GBM cells in vitro MP-Pt(IV) toxicity against GBM is potentiated by elevating mitochondrial ascorbate and can be arrested by MAOB inhibition. In in vitro studies, sublethal MP-Pt(IV) doses elevated mitochondrial MAOB levels in surviving GBM cells. MP-Pt(IV) is a potent chemotherapeutic in intracranial patient-derived xenograft mouse models of primary GBM and potentiates both temozolomide and temozolomide-chemoradiation therapies. MP-Pt(IV) was well tolerated and is highly effective against GBM in both in vitro and in vivo models.

Preoperative Determination of Isocitrate Dehydrogenase Mutation in Gliomas Using Spectral Editing MRS: A Prospective Study

BACKGROUND

The edited magnetic resonance spectroscopy (MRS) technique has not yet been formally evaluated for the in vivo detection of 2-hydroxyglutarate (2-HG) in patients with gliomas of various grades.

PURPOSE

To evaluate the diagnostic accuracy of edited MRS in the preoperative identification of the isocitrate dehydrogenase (IDH) mutation status in patients with gliomas.

STUDY TYPE

Prospective.

POPULATION

Fifty-eight subjects (31 glioblastomas, 27 grade II and III gliomas).

FIELD STRENGTH/SEQUENCE

Mescher-Garwood (MEGA)-PRESS and routine clinical brain tumor MR sequences were used at 3T.

ASSESSMENT

Data were analyzed using an advanced method for accurate, robust, and efficient spectral fitting (AMARES) from jMRUI software. The amplitudes of the 2-HG, N-acetyl-aspartate (NAA), choline (Cho), and creatine/phosphocreatine (Cr) resonances were calculated with their associated Cramer-Rao lower bound (CRLB). The IDH1 R132H mutation status was assessed by immunohistochemistry for all patients. Patients with grades II and III gliomas with negative immunohistochemistry underwent DNA sequencing to further interrogate IDH mutation status.

STATISTICAL TEST

The differences in 2-HG amplitudes, 2-HG/NAA, 2-HG/Cho, and 2-HG/Cr between IDH-mutant and IDH-wildtype gliomas were assessed using Mann-Whitney U-tests. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic accuracy of each parameter.

RESULTS

The 2-HG amplitudes, 2-HG/NAA, and 2-HG/Cho were higher for IDH-mutant gliomas than IDH-wildtype gliomas (P < 0.007). Using a CRLB threshold <30%, a 2-HG cutoff greater than 0 had a sensitivity of 80% (95% confidence interval [CI]: 52-96%) and a specificity of 81% (95% CI: 54-96%) in identifying IDH-mutant gliomas. In the subset of patients with grades II and III gliomas, the sensitivity was 80% (95% CI: 52-96%) and specificity was 100% (95% CI: 40-100%). Among 2-HG ratios, the highest AUC for the identification of IDH mutant status was achieved using the 2-HG/NAA (AUC = 0.8, 95% CI 0.67-.89).

DATA CONCLUSION

Preoperative edited MRS appears to be able to help identify IDH-mutant gliomas with high specificity. Level of Evidence 1 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:416-426.

The influence of subventricular zone involvement in extent of resection and tumor growth pattern of glioblastoma

Objectives

Isocitrate dehydrogenase (IDH1/2) mutations and O6-alkylguanine DNA methyltransferase (MGMT) promoter methylations are acknowledged survival predictors in patients with glioblastoma (GB). Moreover, tumor growth patterns like multifocality and subventricular zone (SVZ) involvement seem to be associated with poorer outcomes. Here, we wanted to evaluate the influence of the SVZ involvement and the multifocal tumor growth on the extent of surgical resection and its correlation with overall survival (OS) and molecular characteristics of patients with GB.

Methods

Adult patients with primary GB who underwent surgery at our department between 2012 and 2014 were included. Preoperative magnetic resonance imaging findings were analyzed with regard to tumor location, presence of multifocality and SVZ involvement. The extent of surgical resection as well as clinical and molecular parameters was collected from electronic patient records. Univariate and multivariate analyses were performed.

Results

Two hundred eight patients were retrospectively analyzed, comprising 90 (43.3%) female individuals with a mean age of 62.9 (±12.26) years and OS of 10.2 months (±8.9). Unifocal tumor location was a predictor for better OS with a mean of 11.4 (±9.4) months (vs. 8.0 [±7.4] months, p=0.008). Affection of the SVZ was also associated with lower surgical resection rates (p<0.001). SVZ involvement revealed with 7.8 (±7.0) months a significant worse OS [vs. 13.9 (±10.1) months, p<0.001]. All six IDH1/2 wildtype tumors showed an unifocal location (p=0.066). MGMT promoter methylation was not associated with multifocal tumor growth (p=0.649) or SVZ involvement (p=0.348). Multivariate analysis confirmed independent association between the SVZ involvement and OS (p=0.001).

Conclusion

The involvement of the SVZ appears to have an influence on a lower resection rate of GB. This negative impact of SVZ on GB outcome might be related to lesser extent of resection, higher rates of multifocality and greater surgical morbidity but not inevitably to IDH1/2 mutation and MGMT promoter methylation status.

Molecular profiling of long-term IDH-wildtype glioblastoma survivors

BACKGROUND

Glioblastoma (GBM) represents an aggressive cancer type with a median survival of only 14 months. With fewer than 5% of patients surviving 5 years, comprehensive profiling of these rare patients could elucidate prognostic biomarkers that may confer better patient outcomes. We utilized multiple molecular approaches to characterize the largest patient cohort of isocitrate dehydrogenase (IDH)-wildtype GBM long-term survivors (LTS) to date.

METHODS

Retrospective analysis was performed on 49 archived formalin-fixed paraffin embedded tumor specimens from patients diagnosed with GBM at the Mayo Clinic between December 1995 and September 2013. These patient samples were subdivided into 2 groups based on survival (12 LTS, 37 short-term survivors [STS]) and subsequently examined by mutation sequencing, copy number analysis, methylation profiling, and gene expression.

RESULTS

Of the 49 patients analyzed in this study, LTS were younger at diagnosis (P = 0.016), more likely to be female (P = 0.048), and MGMT promoter methylated (UniD, P = 0.01). IDH-wildtype STS and LTS demonstrated classic GBM mutations and copy number changes. Pathway analysis of differentially expressed genes showed LTS enrichment for sphingomyelin metabolism, which has been linked to decreased GBM growth, invasion, and angiogenesis. STS were enriched for DNA repair and cell cycle control networks.

CONCLUSIONS

While our findings largely report remarkable similarity between these LTS and more typical STS, unique attributes were observed in regard to altered gene expression and pathway enrichment. These attributes may be valuable prognostic markers and are worth further examination. Importantly, this study also underscores the limitations of existing biomarkers and classification methods in predicting patient prognosis.

Does the expression of glial fibrillary acid protein (GFAP) stain in glioblastoma tissue have a prognostic impact on survival?

OBJECTIVE

Several parameters are known to predict the survival of glioblastoma (GB), including extent of resection and MGMT promotor methylation. Staining for glial fibrillary acidic protein (GFAP) is a common component of routine histological work-up, but its clinical utility in GB is unclear. The aim of the present study was to analyze the predictive value of quantitative GFAP measurements for survival of patients with GB.

METHODS

All subjects in our institutional database of patients with primary GB who underwent surgery between 2011 and 2014 with examination of immunohistochemical staining of GFAP were included. Percentage GFAP staining was measured in 5% increments (5-100%). Univariate and multivariate analyses were performed between GFAP values and survival data. Clinically relevant cut-offs for GFAP staining were identified by receiver operating characteristic (ROC) curves.

RESULTS

The final cohort consisted of 272GB patients with available quantitative GFAP measurements (mean age, 62 (±11.1) years, 117 females [43%]). Overall survival was 11.4 months (±8.6). Median GFAP value was 70% (range, 5-100%). The ROC curve showed the clinically relevant cut-off for GFAP at 75% (area under the curve: 0.691). Accordingly, GB patients with GFAP≥75% presented poorer survival on Kaplan-Meier survival estimation (P=0.021). Multivariate analysis adjusted for age, extent of resection, preoperative Karnofsky performance status scale, IDH1 mutation and MGMT methylation status confirmed the independent predictive value of GFAP≥75% for overall survival (P=0.032). Finally, patients with GFAP≥75% showed significantly poorer long-term survival than those with GFAP<75%: 5.8% vs. 15.2% (P=0.0183) and 0.8% vs. 8% (P=0.0076) for 2- and 3-year survival, respectively.

CONCLUSION

Quantitative immunohistochemical assessment of GFAP staining could provide a novel biomarker for overall and especially long-term survival of patients with GB. Prospective multi-center validation of the prognostic value of GFAP for GB survival is needed.

Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools

BACKGROUND

Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the ability of tumor cells to deeply infiltrate the surrounding tissue makes complete resection quite impossible, and, in consequence, the probability of tumor recurrence is high, and the prognosis is not positive. GBM is highly heterogeneous and adapts to treatment in most individuals. Nevertheless, these mechanisms of adaption are unknown.

RECENT FINDINGS

In this review, we will discuss the recent discoveries in molecular and cellular heterogeneity, mechanisms of therapeutic resistance, and new technological approaches to identify new treatments for GBM. The combination of biology and computer resources allow the use of algorithms to apply artificial intelligence and machine learning approaches to identify potential therapeutic pathways and to identify new drug candidates.

CONCLUSION

These new approaches will generate a better understanding of GBM pathogenesis and will result in novel treatments to reduce or block the devastating consequences of brain cancers.

Over ten years overall survival in glioblastoma: A different disease?

PURPOSE

The reasons why a specific subset of glioblastoma (GBM) patients survive longer than others is still unclear. This study analyzed a cohort of long-term and very-long-term GBM survivors to determine which genetic alterations or patient's characteristics influence survival time.

METHODS

We retrospectively reviewed a cohort of GBM patients treated at our institution over the last 20 years, stratifying patients in three groups: those with a survival time ≥ 36 months and < 120 months (LTS), ≥120 months (VLTS), and < 36 months, respectively. Clinical (age, sex, focality, resection degree, Karnofsky performance status), and immunohistochemical and molecular data (Ki-67 expression and multiple genes alterations) were collected. We then utilized principal component analysis, logistic regression, and Cox proportional hazard models to identify those variables associated with survival.

RESULTS

Younger age at presentation (HR = 0.36, 95% CI 0.21-0.67, p = .001), and MGMT promoter [(MGMTp), methylated, HR = 0.57, CI 0.34-0.96, p = .034) were associated with higher odds of VLTS survival. The multivariate analysis showed how the combination of younger age (< 50 years), Ki-67 < 10%, and the coexistence of TERTp not mutated, MGMTp methylated, and IDH1/2 mutated in the same patient are also associated with higher odds of survival (HR = 0.10, CI 0.01-0.74, p = .025).

CONCLUSIONS

We confirmed younger age at presentation and MGMTp methylation as the only independent factors associated with VLTS. The exceptional survival of our VLTS patients is probably associated with different, still understudied, gene mutations, or with the coexistence of multiple factors.

Molecular Study of Long-Term Survivors of Glioblastoma by Gene-Targeted Next-Generation Sequencing

Glioblastoma (GBM) is the most common malignant adult primary brain tumor. Despite its high lethality, a small proportion of patients have a relatively long overall survival (OS). Here we report a study of a series of 74 GBM samples from 29 long-term survivors ([LTS] OS ≥36 months) and 45 non-LTS. Using next-generation sequencing, we analyzed genetic alterations in the genes most frequently altered in gliomas. Approximately 20% of LTS had a mutation in the IDH1 or IDH2 (IDH) genes, denoting the relevance of this molecular prognostic factor. A new molecular group of GBMs harbored alterations in ATRX or DAXX genes in the absence of driver IDH or H3F3A mutations. These patients tended to have a slightly better prognosis, to be younger at diagnosis, and to present frontal or temporal tumors, and, morphologically, to present giant tumor cells. A significant fraction of LTS GBM patients had tumors with 1 or more alterations in the relevant GBM signaling pathways (RTK/PI3K, TP53 and RB1). In these patients, the PDGFRA alteration is suggested to be a favorable molecular factor. Our findings here are relevant for developing future targeted therapies and for identifying molecular prognostic factors in GBM patients.

Defining Protein Pattern Differences Among Molecular Subtypes of Diffuse Gliomas Using Mass Spectrometry

Molecular characterization of diffuse gliomas has thus far largely focused on genomic and transcriptomic interrogations. Here, we utilized mass spectrometry and overlay protein-level information onto genomically defined cohorts of diffuse gliomas to improve our downstream molecular understanding of these lethal malignancies. Bulk and macrodissected tissues were utilized to quantitate 5,496 unique proteins over three glioma cohorts subclassified largely based on their IDH and 1p19q codeletion status (IDH wild type (IDHwt), n = 7; IDH mutated (IDHmt), 1p19q non-codeleted, n = 7; IDH mutated, 1p19q-codeleted, n = 10). Clustering analysis highlighted proteome and systems-level pathway differences in gliomas according to IDH and 1p19q-codeletion status, including 287 differentially abundant proteins in macrodissection-enriched tumor specimens. IDHwt tumors were enriched for proteins involved in invasiveness and epithelial to mesenchymal transition (EMT), while IDHmt gliomas had increased abundances of proteins involved in mRNA splicing. Finally, these abundance changes were compared with IDH-matched GBM stem-like cells (GSCs) to better pinpoint protein patterns enriched in putative cellular drivers of gliomas. Using this integrative approach, we outline specific proteins involved in chloride transport (e.g. chloride intracellular channel 1, CLIC1) and EMT (e.g. procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3, PLOD3, and serpin peptidase inhibitor clade H member 1, SERPINH1) that showed concordant IDH-status-dependent abundance differences in both primary tissue and purified GSC cultures. Given the downstream position proteins occupy in driving biology and phenotype, understanding the proteomic patterns operational in distinct glioma subtypes could help propose more specific, personalized, and effective targets for the management of patients with these aggressive malignancies.

Molecular profile of long-term survivors of glioblastoma: A scoping review of the literature

Molecular aberrations of malignancy are becoming widely recognized as important predictive and prognostic markers for treatment response and survival in oncology and have been linked to the discovery of novel treatment targets. This area of research in glioblastoma continues to evolve. The aim of this scoping review was to document the hallmark molecular characteristics of long-term survivors of glioblastoma. MEDLINE, Scopus and EMBASE were searched with core concepts: (1) glioblastoma, (2) long-term survivor and (3) molecular OR mutation. A thematic analysis was undertaken of the 18 included studies. Four main classes of characteristics were obtained: IDH mutation, MGMT methylation, other known characteristics and novel discoveries. While MGMT methylation or the combination with IDH mutation are suggested to be hallmark characteristics, there remains enough uncertainty to suggest further factors may be involved, such as CD34 expression. Further research is required to accurately describe hallmark molecular characteristics of long-term survivors to assist in defining these patients at diagnosis, preventing treatment complications and discovering novel treatments.

Long-term survival in patients with recurrent glioblastoma treated with bevacizumab: a multicentric retrospective study

PURPOSE

Recurrence of glioblastoma (GB) occurs in most patients after standard concomitant temozolomide-based radiochemotherapy (CTRC). Bevacizumab (BV), an anti-VEGF antibody, has an effect on progression-free survival (PFS) but not on overall survival (OS). However, a small part of the patients experience a survival, longer than expected. This retrospective study aims to characterize long responder (LR) patients treated with BV for a first or second GBM recurrence.

METHODS

Medical records from patients (814) who received BV for a first or second recurrence of primary glioblastoma between September 2010 and September 2015, and initially treated by CTRC were analyzed. Patients, who had at least a stable disease according to RANO criteria at 12 months from the start of BV, were included. Patients who had, a secondary GB, or received BV in neoadjuvant or adjuvant setting were excluded.

RESULTS

We focused on 65 LR patients without progression 12 months after the first injection of BV (8%). Median PFS was 21.7 months [95% CI (19.3; 27.2)] and median OS was 31.1 months [95% CI (24.3; 37.5)] from the start of BV. No prognostic factor was associated with OS in multivariate analysis. Karnofsky performance status, neurological status and corticosteroid dose were stable at 12 months.

CONCLUSIONS

Our results highlight that among patients receiving bevacizumab in first or second recurrence, one patient out of twelve could be classified as LR. A median OS of 31.1 months from the start of BV could be expected in this subpopulation. These findings reinforce the potential benefit of the use of BV in the situation of recurrence. 256 words.

Patterns of long-term survivorship following bevacizumab treatment for recurrent glioma: a case series

Aim:

Long-term survivors (LTS) after glioma recurrence while on bevacizumab (Bev) therapy are rarely reported in the current literature. The purpose of this case series is to confirm the existence of and describe a large cohort of recurrent glioma LTS treated with Bev (Bev-LTS).

Patients & methods:

We identified Bev-LTS as patients with post-Bev initiation survival times of ≥3 years among 1397 Bev treated recurrent glioma patients.

Results:

Among 962 grade-IV, 221 grade III, and 214 grade II Bev-treated glioma patients, we identified 28 (2.9%), 14 (6.3%) and 8 (3.7%) Bev-LTS patients, respectively. 45 Bev-LTS patients recurred on Bev, with 36 of those patients continuing therapy.

Conclusion:

Our study shows that a small portion of grade-IV, -III, and -II glioma patients can have long-term survival on Bev therapy even after Bev recurrence.

Diagnostic performance of clinical properties and conventional magnetic resonance imaging for determining the IDH1 mutation status in glioblastoma: a retrospective study

Background

Glioblastoma (GBM), the most malignant form of gliomas, is a relatively common primary brain tumor in adults. Preoperative identification of isocitrate dehydrogenase 1 (IDH1) mutations in GBM is of critical prognostic importance. The aim of the present study was to explore the feasibility and diagnostic performance of basic patient information combined with conventional magnetic resonance imaging (MRI) findings for determination of the IDH1 status (mutant vs wild type) in patients with GBM.

Methods

From January 1, 2016 to December 31, 2017, a consecutive series of 50 patients with GBM was retrospectively collected. The patients were divided into two group according to their IDH1 mutation status. Basic information and MRI features were analyzed for the establishment of a diagnostic prediction model using logistic regression. A receiver operating characteristic curve was used to evaluate the diagnostic performance.

Results

Patients with IDH1-mutant tumors were younger than those with IDH1-wild type tumors, and exhibited a larger tumor volume. The diagnostic predictive model established by combining age and the tumor size exhibited a sensitivity and specificity of 70% and 93%, respectively. The area under the curve was 0.88, which indicated high diagnostic performance.

Conclusion

Patient age and tumor volume can be used as indicators of IDH1 mutation status in patients with GBM, with high diagnostic performance for simple evaluations in clinical practice. The combined use of these two indicators can further enhance the diagnostic specificity.

Integrative analysis of DNA methylation suggests down-regulation of oncogenic pathways and reduced somatic mutation rates in survival outliers of glioblastoma

The study of survival outliers of glioblastoma can provide important clues on gliomagenesis as well as on the ways to alter clinical course of this almost uniformly lethal cancer type. However, there has been little consensus on genetic and epigenetic signatures of the long-term survival outliers of glioblastoma. Although the two classical molecular markers of glioblastoma including isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation and O6-methylguanine DNA methyltransferase (MGMT) promoter methylation are associated with overall survival rate of glioblastoma patients, they are not specific to the survival outliers. In this study, we compared the two groups of survival outliers of glioblastoma with IDH wild-type, consisting of the glioblastoma patients who lived longer than 3 years (n = 17) and the patients who lived less than 1 year (n = 12) in terms of genome-wide DNA methylation profile. Statistical analyses were performed to identify differentially methylated sites between the two groups. Functional implication of DNA methylation patterns specific to long-term survivors of glioblastoma were investigated by comprehensive enrichment analyses with genomic and epigenomic features. We found that the genome of long-term survivors of glioblastoma is differentially methylated relative to short-term survivor patients depending on CpG density: hypermethylation near CpG islands (CGIs) and hypomethylation far from CGIs. Interestingly, these two patterns are associated with distinct oncogenic aspects in gliomagenesis. In the long-term survival glioblastoma-specific sites distant from CGI, somatic mutations of glioblastoma are enriched with higher DNA methylation, suggesting that the hypomethylation in long-term survival glioblastoma can contribute to reduce the rate of somatic mutation. On the other hand, the hypermethylation near CGIs associates with transcriptional downregulation of genes involved in cancer progression pathways. Using independent cohorts of IDH1/2- wild type glioblastoma, we also showed that these two patterns of DNA methylation can be used as molecular markers of long-term survival glioblastoma. Our results provide extended understanding of DNA methylation, especially of DNA hypomethylation, in cancer genome and reveal clinical importance of DNA methylation pattern as prognostic markers of glioblastoma.

Genetic secrets of long-term glioblastoma survivors

Glioblastomas are the most aggressive and lethal primary astrocytic tumors of the central nervous system. They account for 60% to 70% of all gliomas and the majority are diagnosed in Caucasian male patients at advanced age. Genetic analyses of glioblastoma show a great intra- and inter-tumor heterogeneity, which opens up a debate about its cellular origin. Different types of brain cells, including astrocytes, neural stem cells, oligodendrocyte precursor cells and glioblastoma stem cells are proposed to have a role in tumor initiation and spreading; however, data is still inconclusive. Due to short life expectancy, long-term glioblastoma survivors are defined as patients who live longer than two years post-diagnosis. Extreme survivors, living 10 years or more after diagnosis, comprise less than 1% of all patients. Molecular testing indicates genetic differences between short- and long-term survivors with glioblastoma. The most informative are IDH1/2 gene mutations and MGMT promoter methylation, which are associated with a better response to standard clinical care. Moreover, a decreased expression of the CHI3L1, FBLN4, EMP3, IGFBP2, IGFBP3, LGALS3, MAOB, PDPN, SERPING1 and TIMP1 genes has been associated with prolonged survival. In addition, emerging evidence suggests the role of different microRNAs in predicting patient survival. Other factors that may affect the survival of glioblastoma patients include clinical/demographic characteristics such as seizures at presentation, age at diagnosis, and the extent of surgical resection. Because of the small number of long-term survivors with glioblastoma, comparative studies on genetic differences between short- and long-term survivors are challenging. To improve patient management and clinical outcomes, a thorough "omics" approach is necessary for identifying differences between short- and long-term survivors with glioblastoma.

Genome-Wide Analysis of Glioblastoma Patients with Unexpectedly Long Survival

Glioblastoma (GBM), representing WHO grade IV astrocytoma, is a relatively common primary brain tumor in adults with an exceptionally dismal prognosis. With an incidence rate of over 10 000 cases in the United States annually, the median survival rate ranges from 10-15 months in IDH1/2-wildtype tumors and 24-31 months in IDH1/2-mutant tumors, with further variation depending on factors such as age, MGMT methylation status, and treatment regimen. We present a cohort of 4 patients, aged 37-60 at initial diagnosis, with IDH1-mutant GBMs that were associated with unusually long survival intervals after the initial diagnosis, currently ranging from 90 to 154 months (all still alive). We applied genome-wide profiling with a methylation array (Illumina EPIC Array 850k) and a next-generation sequencing panel to screen for genetic and epigenetic alterations in these tumors. All 4 tumors demonstrated methylation patterns and genomic alterations consistent with GBM. Three out of four cases showed focal amplification of the CCND2 gene or gain of the region on 12p that included CCND2, suggesting that this may be a favorable prognostic factor in GBM. As this study has a limited sample size, further evaluation of patients with similar favorable outcome is warranted to validate these findings.

MicroRNA-562 negatively regulated c-MET/AKT pathway in the growth of glioblastoma cells

Background

MicroRNA-562 (miR-562) has been found to possess anti-cancer function in certain tumors. However, the function of miR-562 in glioblastoma (GBM) is still not fully understood.

Purpose

The aim at present study is to analyze the function of miR-562 and its possible target in GBM cells.

Patients and methods

In the present study, a total of 80 GBM samples and 16 adjacent noncancerous tissues were used to examine the expression of miR-562 and c-MET. In order to gain a deep insight into the molecular network of miR-562 and c-MET in GBM, the miR-562 mimic and inhibitor were transfected into two GBM cell lines (U251 and U87), respectively. Meanwhile, lentiviral vector was used to mediate overexpression of c-MET. Cell proliferation was examined via Cell Counting Kit-8 (CCK-8) assays. Meanwhile, cell apoptosis was analyzed by Annexin V-FTTC/PI staining assay.

Results

Our results indicated that the level of miR-562 was downregulated in GBM tissues and the expression of c-MET was upregulated in tumors. Cell proliferation analysis indicated that miR-562 was an anti-proliferation effector in GBM cells. Moreover, cell apoptosis analysis suggested the pro-apoptosis function of miR-562 in GBM cells.

Conclusion

Our results demonstrated that miR-562 negatively regulated the c-MET/AKT signal pathway. In addition, caspase-3 might also serve as another target for miR-562 in GBM cells. This research not only obtained a deep understanding of miR-562 but also provided evidence in terms of developing new prognostic biomarker for GBM.

Integrated molecular characterization of IDH-mutant glioblastomas

AIMS

Mutations of isocitrate dehydrogenase (IDH)1/2 affect almost all astrocytomas of WHO grade II and III. A subset of IDH-mutant astrocytic tumours progresses to IDH-mutant glioblastoma or presents with the histology of a glioblastoma at first presentation. We set out here to assess the molecular spectrum of IDH-mutant glioblastomas.

METHODS

We performed an integrated molecular analysis of a mono-centric cohort (n = 97); assessed through genome-wide DNA methylation analysis, copy-number profiling and targeted next generation sequencing using a neurooncology-tailored gene panel.

RESULTS

Of these 97 IDH-mutant glioblastomas, 68 had a glioblastoma at first presentation ('de novo' IDH-mutant glioblastoma) and 29 emerged from a prior low-grade lesion ('evolved' IDH-mutant glioblastoma). Unsupervised hierarchical clustering of DNA methylation data disclosed that IDH-mutant glioblastoma ('de novo' and 'evolved') formed a distinct group separate from other diffuse glioma subtypes. Homozygous deletions of CDKN2A/B were found to be associated with shorter survival.

CONCLUSIONS

This study demonstrates DNA methylation patterns in IDH-mutant glioblastoma to be distinct from lower-grade astrocytic counterparts but homogeneous within de novo and evolved IDH-mutant glioblastomas, and identifies CDKN2A as a marker for possible genetic sub-stratification.

Potential targets of TMEM176A in the growth of glioblastoma cells

BACKGROUND

Human transmembrane protein 176A (TMEM176A) is upregulated in several tumors. Growing evidence has suggested the high clinical value of TMEM176A as a biomarker for early tumor diagnosis. However, less is known about the function of TMEM176A in glioblastomas (GBMs).

METHODS

In this study, we systematically analyzed the effect of TMEM176A knockdown and overexpression in GBM cells (U87, T98G and A172) on cell proliferation, cell cycle and cell apoptosis.

RESULTS

Our results indicated that TMEM176A acted as a tumor-promoting factor in GBM cells. Moreover, a specific ERK1/2 inhibitor, U0126, suppressed the function of TMEM176A in GBM cells. Therefore, we proposed that TMEM176A may be involved in a pathway including ERK1/2 in the regulation of the cell cycle. Moreover, we also found that TMEM176A affected the expression of Bcl2 and played a central role in apoptosis of GBM cells.

CONCLUSION

Taken together, our results not only elucidated the multiple functions of TMEM176A in GBM cells but also provided a deep insight into the potential targets of TMEM176A in the growth of GBM cells.

Extracellular matrix differences in glioblastoma patients with different prognoses

Glioblastoma is the most common malignant central nervous system tumor. Patient outcome remains poor despite the development of therapy and increased understanding of the disease in the past decades. Glioma cells invade the peritumoral brain, which results in inevitable tumor recurrence. Previous studies have demonstrated that the extracellular matrix (ECM) is altered in gliomas and serves a major role in glioma invasion. The present study focuses on differences in the ECM composition of tumors in patients with poor and improved prognosis. The mRNA and protein expression of 16 invasion-associated ECM molecules was determined using reverse trascription-quantitiative polymerase chain reaction and immunohistochemistry, respectively. Clinical factors of patients with different prognoses was also analyzed. It was determined that age and postoperative Karnofsky performance score were associated with patient survival. Furthermore, Fms-related tyrosine kinase 4/vascular endothelial growth factor receptor 3 (FLT4/VEGFR3), murine double minute 2 (MDM2) and matrix metallopeptidase 2 (MMP2) mRNA levels were significantly different between the two prognostic groups. Additionally, brevican, cluster of differentiation 44, hyaluronan mediated motility receptor, integrin-αV and -β1, and MDM2 protein expression were indicated to be significantly different in immunohistochemistry slides. Using the expression profile, including the invasion spectrum of the samples, it was possible to identify the prognostic group of the sample with high efficacy, particularly in cases with poor prognosis. In conclusion, it was determined that ECM components exhibit different expression levels in tumors with different prognoses and thus the invasion spectrum can be used as a prognostic factor in glioblastoma.

Impact of Multifocality and Molecular Markers on Survival of Glioblastoma

OBJECTIVE

Several parameters like extent of resection and MGMT promotor methylation in glioblastoma (GBM) are known to influence survival. Other elements like multifocality and proliferation indices are not commonly used. The aim of the present study was to analyze routinely and not routinely assessed prognostic markers for survival of patients suffering from GBM in a single center.

METHODS

Adult cases with GBM operated at our institution were included in this survey. The association of age, Karnofsky performance status (KPS), MGMT promotor methylation, Ki67 proliferation index, IDH1/2 mutational status, and multifocality on overall survival (OS) was analyzed in univariate and multivariate cox regression models.

RESULTS

We analyzed 565 patients with a mean age of 62.2 (18-84) years. Median OS was 12.5 months. MGMT promoter methylation and IDH 1/2 mutation were associated with significant better OS (P < 0.01). In 48 cases (8.5%), the tumor was localized in both hemispheres, which was associated with a significant worse OS than tumor infiltration of 1 hemisphere (P = 0.039). Mean Ki67 proliferation index increased to 18% when both hemispheres were infiltrated. Multivariate analysis for OS revealed IDH 1/2 wildtype (adjusted odds ratio [aOR] 4.3), higher age (aOR 4.2), unmethylated MGMT promotor (aOR 3.5), preoperative KPS score <70 (aOR 1.9), and multifocality (aOR 2.1) as independent parameters for worse survival.

CONCLUSIONS

This study confirms well-known parameters like MGMT promoter methylation, IDH 1/2 mutational status, KPS, and age as independent prognostic factors for survival and reveals multifocality as further independent prognostic marker for survival. The dismal prognosis of multifocal involvement is associated with an increasing Ki67 proliferation index.

Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma

Glioblastoma (GBM) is the most common type of malignant tumor of the central nervous system. The prognosis of patients with GBM is very poor, with a survival time of ~15 months. GBM is highly heterogeneous and highly aggressive. Surgical removal of intracranial tumors does provide a good advantage for patients as there is a high rate of recurrence. The understanding of this type of cancer needs to be strengthened, and the aim of the present study was to identify gene signatures present in GBM and uncover their potential mechanisms. The gene expression profiles of GSE15824 and GSE51062 were downloaded from the Gene Expression Omnibus database. Normalization of the data from primary GBM samples and normal samples in the two databases was conducted using R software. Then, joint analysis of the data was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the protein‑protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Identification of prognostic biomarkers was conducted using UALCAN. In total, 9,341 DEGs were identified in the GBM samples, including 9,175 upregulated genes and 166 downregulated genes. The top 1,000 upregulated DEGs and all of the downregulated DEGs were selected for GO, KEGG and prognostic biomarker analyses. The GO results showed that the upregulated DEGs were significantly enriched in biological processes (BP), including immune response, cell division and cell proliferation, and the downregulated DEGs were also significantly enriched in BP, including cell growth, intracellular signal transduction and signal transduction by protein phosphorylation. KEGG pathway analysis showed that the upregulated DEGs were enriched in circadian entrainment, cytokine‑cytokine receptor interaction and maturity onset diabetes of the young, while the downregulated DEGs were enriched in the TGF‑β signaling pathway, MAPK signaling pathway and pathways in cancer. All of the downregulated genes and the top 1,000 upregulated genes were selected to establish the PPI network, and the sub‑networks revealed that these genes were involved in significant pathways, including olfactory transduction, neuroactive ligand‑receptor interaction and viral carcinogenesis. In total, seven genes were identified as good prognostic biomarkers. In conclusion, the identified DEGs and hub genes contribute to the understanding of the molecular mechanisms underlying the development of GBM and they may be used as diagnostic and prognostic biomarkers and molecular targets for the treatment of patients with GBM in the future.

GPR56/ADGRG1 Inhibits Mesenchymal Differentiation and Radioresistance in Glioblastoma

A mesenchymal transition occurs both during the natural evolution of glioblastoma (GBM) and in response to therapy. Here, we report that the adhesion G-protein-coupled receptor, GPR56/ADGRG1, inhibits GBM mesenchymal differentiation and radioresistance. GPR56 is enriched in proneural and classical GBMs and is lost during their transition toward a mesenchymal subtype. GPR56 loss of function promotes mesenchymal differentiation and radioresistance of glioma initiating cells both in vitro and in vivo. Accordingly, a low GPR56-associated signature is prognostic of a poor outcome in GBM patients even within non-G-CIMP GBMs. Mechanistically, we reveal GPR56 as an inhibitor of the nuclear factor kappa B (NF-κB) signaling pathway, thereby providing the rationale by which this receptor prevents mesenchymal differentiation and radioresistance. A pan-cancer analysis suggests that GPR56 might be an inhibitor of the mesenchymal transition across multiple tumor types beyond GBM.

Clinical and immunological correlates of long term survival in glioblastoma

Glioblastoma (GBM) is the most common and most aggressive type of primary brain tumour in adults. It represents 54% of all gliomas and 16% of all brain tumours (Ostrom et al. 2016). Despite surgery and treatment with radiotherapy plus an oral alkylating agent, temozolomide (TMZ), tumours invariably recur, and the patient survival is an average of ~14–16 months. In this review we summarise the current understanding of multiple factors that may affect survival of patients with GBMs. In particular, we discuss recent advancements in surgery and detection of genomic-based markers with prognostic values, such as IDH1/2 mutations, MGMT gene promoter methylation, and TERT gene promoter alterations. We address the issue of tumour heterogeneity and evolution that may result in different parts of the same tumour exhibiting different GBM subtypes and in subtype switching, which may restrict the usefulness of the expression-based classification as a prognostic marker before relapse. The determinants of long-term survival in patients with IDH1/2wt GBM, beyond MGMT promoter methylation, remain to be identified, and even the absence of both IDH1/2 mutations and MGMT promoter methylation does not preclude long-term survival. These findings suggest that host-derived factors, such as immune system responsiveness may contribute to long-term survival in such patients. We report the results of high-throughput approaches, suggesting links between long-term survival and enhanced immune-related gene expression. The further search for new gene candidates, promoter methylation status, and specific features of host immunity should provide prognostic biomarkers for the evaluation of survival of IDH1 wild-type/non-G-CIMP GBMs.

A novel gene signature based on five glioblastoma stem-like cell relevant genes predicts the survival of primary glioblastoma

PURPOSE

Primary glioblastoma (pGBM) is the most common and lethal type of neoplasms in the central nervous system, while the existing biomarkers, lacking consideration on the stemness changes of GBM cells, are not specific enough to predict the complex prognosis respectively. We aimed to build a high-efficiency prediction gene signature related to GBM cell stemness and investigate its prognostic value in primary glioblastoma.

METHODS

Differentially expressed genes were screened in GSE23806 database. The selected genes were then verified by univariate Cox regression in 591 patients from four enormous independent databases, including the Chinese Glioma Genome Atlas (CGGA), TCGA, REMBRANDT and GSE16011. Finally, the intersected genes were included to build the gene signature. GO analysis and GSEA were carried out to explore the bioinformatic implication.

RESULTS

The novel five-gene signature was used to identify high- and low-risk groups in the four databases, and the high-risk group showed notably poorer prognosis (P < 0.05). Gene ontology (GO) terms including "immune response", "apoptotic process", and "angiogenesis" were picked out by GO analysis and GSEA, which revealed that the gene signature was highly possibly related to the stemness of GSCs and predicting the prognosis of GBM effectively.

CONCLUSION

We built a gene signature with five glioblastoma stem-like cell (GSC) relevant genes, and predicted the survival in four independent databases effectively, which is possibly related to the stemness of GSCs in pGBM. Several GO terms were investigated to be correlated to the signature. The signature can predict the prognosis of glioblastoma efficiently.