A very rare case report of long-term survival: A patient operated on in 1994 of glioblastoma multiforme and currently in perfect health

A Case of Long-Term Survival After Glioblastoma, IDH-Wild Type

INTRODUCTION

Glioblastoma is a uniformly lethal primary central nervous system neoplasm. Despite the increased understanding of its pathophysiology and treatment advancements, median overall survival for patients with glioblastoma, IDH-wild type remains 14 to 21 months from diagnosis.

CASE REPORT

We present the case of a 48-year-old female who presented with a focal seizure and was found to have a right frontal lobe mass on the brain magnetic resonance imaging. She underwent gross total resection and received a histological diagnosis of glioblastoma. She received radiotherapy and 6 cycles of carmustine (BCNU). Seventeen months later, she developed left hemiparesis. Imaging was concerning for tumor progression, and she was treated with 1 cycle of mechlorethamine, vincristine (oncovin), procarbazine, and prednisone (MOPP). Subsequent surveillance imaging demonstrated a therapeutic response. Twenty-seven years after her glioblastoma diagnosis, she developed status epilepticus and died from respiratory failure. Neuropathology on autopsy demonstrated extensive treatment-related changes but no evidence of recurrent glioblastoma. Genomic testing performed over 30 years after her original diagnosis revealed a profile diagnostic of glioblastoma, IDH-wild type per 2021 World Health Organization criteria.

CONCLUSIONS

This patient is one of the longest-known survivors of glioblastoma, IDH-wild type, with pathologic confirmation of glioblastoma at the time of her resection and no evidence of residual disease 26 years after her last treatment. She presented with multiple factors associated with long-term glioblastoma survivorship, including female sex, young age, high Karnofsky score, and multimodal therapy. This case shows that long-term survival after glioblastoma diagnosis is possible and likely mediated through a combination of individual, tumor, and treatment factors.

Investigating chromosomal instability in long-term survivors with glioblastoma and grade 4 astrocytoma

Background

Only a small group of patients with glioblastoma multiforme (GBM) survives more than 36 months, so-called long-term survivors. Recent studies have shown that chromosomal instability (CIN) plays a prognostic and predictive role among different cancer types. Here, we compared histological (chromosome missegregation) and bioinformatic metrics (CIN signatures) of CIN in tumors of GBM typical survivors (≤36 months overall survival), GBM long-term survivors and isocitrate dehydrogenase (IDH)-mutant grade 4 astrocytomas.

Methods

Tumor sections of all gliomas were examined for anaphases and chromosome missegregation. Further CIN signature activity analysis in the The Cancer Genome Atlas (TCGA)-GBM cohort was performed.

Results

Our data show that chromosome missegregation is pervasive in high grade gliomas and is not different between the 3 groups. We find only limited evidence of altered CIN levels in tumors of GBM long-term survivors relative to the other groups, since a significant depletion in CIN signature 11 relative to GBM typical survivors was the only alteration detected. In contrast, within IDH-mutant grade 4 astrocytomas we detected a significant enrichment of CIN signature 5 and 10 activities and a depletion of CIN signature 1 activity relative to tumors of GBM typical survivors.

Conclusions

Our data suggest that CIN is pervasive in high grade gliomas, however this is unlikely to be a major contributor to the phenomenon of long-term survivorship in GBM. Nevertheless, further evaluation of specific types of CIN (signatures) could have prognostic value in patients suffering from grade 4 gliomas.

WNT signaling at the intersection between neurogenesis and brain tumorigenesis

Neurogenesis and tumorigenesis share signaling molecules/pathways involved in cell proliferation, differentiation, migration, and death. Self-renewal of neural stem cells is a tightly regulated process that secures the accuracy of cell division and eliminates cells that undergo mitotic errors. Abnormalities in the molecular mechanisms controlling this process can trigger aneuploidy and genome instability, leading to neoplastic transformation. Mutations that affect cell adhesion, polarity, or migration enhance the invasive potential and favor the progression of tumors. Here, we review recent evidence of the WNT pathway’s involvement in both neurogenesis and tumorigenesis and discuss the experimental progress on therapeutic opportunities targeting components of this pathway.

Future generation of combined multimodal approach to treat brain glioblastoma multiforme and potential impact on micturition control

Glioblastoma remains lethal even when treated with standard therapy. This review aims to outline the recent development of various advanced therapeutics for glioblastoma and briefly discuss the potential impact of glioblastoma and some of its therapeutic approaches on the neurological function micturition control. Although immunotherapy led to success in treating hematological malignancies, but no similar success occurred in treatment for brain glioblastoma. Neither regenerative medicine nor stem cell therapy led to astounding success in glioblastoma. However, CRISPR Cas system holds potential in multiple applications due to its capacity to knock-in and knock-out genes, modify immune cells and cell receptors, which will enable it to address clinical challenges in immunotherapy such as CAR-T and regenerative therapy for brain glioblastoma, improving the precision and safety of these approaches. The studies mentioned in this review could indicate that glioblastoma is a malignant disease with multiple sophisticated barriers to be overcome and more challenges might arise in the attempt of researchers to yield a successful cure. A multimodal approach of future generation of refined and safe therapeutics derived from CRISPR Cas therapeutics, immunotherapy, and regenerative therapeutics mentioned in this review might prolong survival or even contribute towards a potential cure for glioblastoma.

Twenty Years After Glioblastoma Multiforme Diagnosis: A Case of Long-Term Survival

Glioblastoma multiforme (GBM) is an aggressive tumor that has a poor prognosis with a median survival of 15 months with treatment and 3-4 months without treatment. Subsets of patients are found to survive longer than two years, some survivors lived more than 10 years, and rare cases survived 20 years or more with treatment. Better prognosis has been found to be associated with many factors. Some of these factors are related to patients' characteristics, biological factors that impact tumor aggressiveness, and/or factors associated with treatment. However, the exact contribution for extended survival is still not known. Finding the factors that have a strong impact on the long survival is of high importance and can help give hope to better treat glioblastoma cases. In this report, we present a case of a glioblastoma patient who was diagnosed at the age of 47 years with more than 20-year survival. We further discuss the suggested factors that may have contributed to a better prognosis with a focus on the possible role of varicella-zoster infection in mediating long-term survival.

Survival prediction in glioblastoma on post-contrast magnetic resonance imaging using filtration based first-order texture analysis: Comparison of multiple machine learning models

OBJECTIVE

Magnetic resonance texture analysis (MRTA) is a relatively new technique that can be a valuable addition to clinical and imaging parameters in predicting prognosis. In the present study, we investigated the efficacy of MRTA for glioblastoma survival using T1 contrast-enhanced (CE) images for texture analysis.

METHODS

We evaluated the diagnostic performance of multiple machine learning models based on first-order histogram statistical parameters derived from T1-weighted CE images in the survival stratification of glioblastoma multiforme (GBM). Retrospective evaluation of 85 patients with GBM was performed. Thirty-six first-order texture parameters at six spatial scale filters (SSF) were extracted on the T1 CE axial images for the whole tumor using commercially available research software. Several machine learning classification models (in four broad categories: linear, penalized linear, non-linear, and ensemble classifiers) were evaluated to assess the survival prediction performance using optimal features. Principal component analysis was used prior to fitting the linear classifiers in order to reduce the dimensionality of the feature inputs. Fivefold cross-validation was used to partition the data iteratively into training and testing sets. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance.

RESULTS

The neural network model was the highest performing model with the highest observed AUC (0.811) and cross-validated AUC (0.71). The most important variable was the age at diagnosis, with mean and mean of positive pixels (MPP) for SSF = 0 being the second and third most important, followed by skewness for SSF = 0 and SSF = 4.

CONCLUSIONS

First-order texture features, when combined with age at presentation, show good accuracy in predicting GBM survival.

Present and Future of Anti-Glioblastoma Therapies: A Deep Look into Molecular Dependencies/Features

Glioblastoma (GBM) is aggressive malignant tumor residing within the central nervous system. Although the standard treatment options, consisting of surgical resection followed by combined radiochemotherapy, have long been established for patients with GBM, the prognosis is still poor. Despite recent advances in diagnosis, surgical techniques, and therapeutic approaches, the increased patient survival after such interventions is still sub-optimal. The unique characteristics of GBM, including highly infiltrative nature, hard-to-access location (mainly due to the existence of the blood brain barrier), frequent and rapid recurrence, and multiple drug resistance mechanisms, pose challenges to the development of an effective treatment. To overcome current limitations on GBM therapy and devise ideal therapeutic strategies, efforts should focus on an improved molecular understanding of GBM pathogenesis. In this review, we summarize the molecular basis for the development and progression of GBM as well as some emerging therapeutic approaches.

Complementary Genomic, Bioinformatics, and Chemical Approaches Facilitate the Absolute Structure Assignment of Ionostatin, a Linear Polyketide from a Rare Marine-Derived Actinomycete

A new linear type-1 polyketide, ionostatin (1), has been fully defined using a combined genomic and bioinformatics approach coupled with confirmatory chemical analyses. The 41 carbon-containing polyether is the product of the 101 kbp ion biosynthetic cluster containing seven modular type-1 polyketide synthases. Ionostatin is composed of 15 chiral centers that were proposed using the stereospecificities installed by the different classes of ketoreductases and enoylreductases and confirmed by rigorous NMR analyses. Incorporated into the structure are two tetrahydrofuran rings that appear to be the product of stereospecific epoxidation, followed by stereospecific ring opening and cyclization. These transformations are proposed to be catalyzed by conserved enzymes analogous to those found in other bacterial-derived polyether biosynthetic clusters. Ionostatin shows moderate cancer cell cytotoxicity against U87 glioblastoma and SKOV3 ovarian carcinoma at 7.4 μg/mL.

The limitations of targeting MEK signalling in Glioblastoma therapy

Glioblastoma (GB) is a highly aggressive, difficult to treat brain tumour. Successful treatment, consisting of maximal safe tumour de-bulking, followed by radiotherapy and treatment with the alkylating agent Temozolomide (TMZ), can extend patient survival to approximately 15 months. Combination treatments based on the inhibition of the PI3K pathway, which is the most frequently activated signalling cascade in GB, have so far only shown limited therapeutic success. Here, we use the clinically approved MEK inhibitor Trametinib to investigate its potential use in managing GB. Trametinib has a strong anti-proliferative effect on established GB cell lines, stem cell-like cells and their differentiated progeny and while it does not enhance anti-proliferative and cell death-inducing properties of the standard treatment, i.e. exposure to radiation or TMZ, neither does MEK inhibition block their effectiveness. However, upon MEK inhibition some cell populations appear to favour cell-substrate interactions in a sprouting assay and become more invasive in the Chorioallantoic Membrane assay, which assesses cell penetration into an organic membrane. While this increased invasion can be modulated by additional inhibition of the PI3K signalling cascade, there is no apparent benefit of blocking MEK compared to targeting PI3K.

Long Term Survival in Patients Suffering from Glio-blastoma Multiforme: A Single-Center Observational Cohort Study

Background: Glioblastomas (GBM) are generally burdened, to date, by a dismal prognosis, although long term survivors have a relatively significant incidence. Our specific aim was to determine the exact impact of many surgery-, patient- and tumor-related variables on survival parameters. Methods: The surgical, radiological and clinical outcomes of patients have been retrospectively reviewed for the present study. All the patients have been operated on in our institution and classified according their overall survival in long term survivors (LTS) and short term survivors (STS). A thorough review of our surgical series was conducted to compare the oncologic results of the patients in regard to: (1) surgical-(2) molecular and (3) treatment-related features. Results: A total of 177 patients were included in the final cohort. Extensive statistical analysis by means of univariate, multivariate and survival analyses disclosed a survival advantage for patients presenting a younger age, a smaller lesion and a better functional status at presentation. From the histochemical point of view, Ki67 (%) was the strongest predictor of better oncologic outcomes. A stepwise analysis of variance outlines the existence of eight prognostic subgroups according to the molecular patterns of Ki67 overexpression and epidermal growth factor receptor (EGFR), p53 and isocitrate dehydrogenase (IDH) mutations. Conclusions: On the grounds of our statistical analyses we can affirm that the following factors were significant predictors of survival advantage: Karnofsky performance status (KPS), age, volume of the lesion, motor disorder at presentation and/or a Ki67 overexpression. In our experience, LTS is associated with a gross total resection (GTR) of tumor correlated with EGFR and p53 mutations with regardless of localization, and poorly correlated to dimension. We suppose that performing a standard molecular analysis (IDH, EGFR, p53 and Ki67) is not sufficient to predict the behavior of a GBM in regards to overall survival (OS), nor to provide a deeper understanding of the meaning of the different genetic alterations in the DNA of cancer cells. A fine molecular profiling is feasible to precisely stratify the prognosis of GBM patients.

The Role of SVZ Stem Cells in Glioblastoma

As most common primary brain cancer, glioblastoma is also the most aggressive and malignant form of cancer in the adult central nervous system. Glioblastomas are genetic and transcriptional heterogeneous tumors, which in spite of intensive research are poorly understood. Over the years conventional therapies failed to affect a cure, resulting in low survival rates of affected patients. To improve the clinical outcome, an important approach is to identify the cells of origin. One potential source for these are neural stem cells (NSCs) located in the subventricular zone, which is one of two niches in the adult nervous system where NSCs with the capacity of self-renewal and proliferation reside. These cells normally give rise to neuronal as well as glial progenitor cells. This review summarizes current findings about links between NSCs and cancer stem cells in glioblastoma and discusses current therapeutic approaches, which arise as a result of identifying the cell of origin in glioblastoma.