Impact of treatment on survival of patients with secondary glioblastoma

Proton beam therapy in a patient with secondary glioblastoma (32 years after postoperative irradiation of medulloblastoma): case report and literature review

OBJECTIVE

This report details the experience of a patient who developed a second primary glioblastoma (GB), offering insights into the treatment process and reviewing relevant literature.

CASE PRESENTATION

A male patient, who was diagnosed with medulloblastoma at age 9, received treatment with cobalt-60 craniospinal irradiation (CSI) (36 Gy/20 fractions) and a tumor bed boost (total of 56 Gy). After 32 years, at age 41, an MRI revealed a space-occupying mass in the left cerebellar hemisphere. Surgical resection was performed, and postoperative pathology confirmed a diagnosis of radiation-induced glioblastoma (RIGB). Given the history of irradiation and the current tolerability of brainstem doses, proton beam therapy (PBT) combined with Temozolomide (75 mg/m2) was chosen. The treatment plan included 60 Gy on the gross tumor bed and 54 Gy on the clinical target volume, delivered in 30 fractions. The patient underwent regular follow-up and achieved a complete response.

CLINICAL DISCUSSION

For childhood cancer survivors, the development of a second primary tumor significantly impacts prognosis. RIGB is a rare form of secondary tumor with distinct molecular characteristics compared to primary GB and recurrent secondary GB. Molecular markers such as IDH and MGMT status can help differentiate between primary GB, recurrent secondary GB, and radiation-induced secondary GB in patients with a history of prior radiation therapy. Surgical resection remains a primary treatment option, while PBT is preferred for postoperative treatment due to its superior protection of normal tissues and the ability to deliver high-dose irradiation.

CONCLUSION

RIGB is a rare second primary tumor that requires strategic molecular profiling and individualized management. Proton beam therapy provides effective high-dose irradiation in the postoperative phase and is the preferred treatment option for such cases.

Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics

PURPOSE

Glioblastoma Multiforme (GBM) represents the predominant aggressive primary tumor of the brain with short overall survival (OS) time. We aim to assess the potential of radiomic features in predicting the time-to-event OS of patients with GBM using machine learning (ML) algorithms.

MATERIALS AND METHODS

One hundred nineteen patients with GBM, who had T1-weighted contrast-enhanced and T2-FLAIR MRI sequences, along with clinical data and survival time, were enrolled. Image preprocessing methods included 64 bin discretization, Laplacian of Gaussian (LOG) filters with three Sigma values and eight variations of Wavelet Transform. Images were then segmented, followed by the extraction of 1212 radiomic features. Seven feature selection (FS) methods and six time-to-event ML algorithms were utilized. The combination of preprocessing, FS, and ML algorithms (12 × 7 × 6 = 504 models) was evaluated by multivariate analysis.

RESULTS

Our multivariate analysis showed that the best prognostic FS/ML combinations are the Mutual Information (MI)/Cox Boost, MI/Generalized Linear Model Boosting (GLMB) and MI/Generalized Linear Model Network (GLMN), all of which were done via the LOG (Sigma = 1 mm) preprocessing method (C-index = 0.77). The LOG filter with Sigma = 1 mm preprocessing method, MI, GLMB and GLMN achieved significantly higher C-indices than other preprocessing, FS, and ML methods (all p values < 0.05, mean C-indices of 0.65, 0.70, and 0.64, respectively).

CONCLUSION

ML algorithms are capable of predicting the time-to-event OS of patients using MRI-based radiomic and clinical features. MRI-based radiomics analysis in combination with clinical variables might appear promising in assisting clinicians in the survival prediction of patients with GBM. Further research is needed to establish the applicability of radiomics in the management of GBM in the clinic.

Risk of developing glioblastoma following non-CNS primary cancer: a SEER analysis between 2000 and 2018

BACKGROUND

Patients with a prior malignancy are at elevated risk of developing subsequent primary malignancies (SPMs). However, the risk of developing subsequent primary glioblastoma (SPGBM) in patients with a prior cancer history is poorly understood.

METHODS

We used the Surveillance, Epidemiology, and End Results (SEER) database and identified patients diagnosed with non-CNS malignancy between 2000 and 2018. We calculated a modified standardized incidence ratio (M-SIR), defined as the ratio of the incidence of SPGBM among patients with initial non-CNS malignancy to the incidence of GBM in the general population, stratified by sex latency, and initial tumor location.

RESULTS

Of the 5,326,172 patients diagnosed with a primary non-CNS malignancy, 3559 patients developed SPGBM (0.07%). Among patients with SPGBM, 2312 (65.0%) were men, compared to 2,706,933 (50.8%) men in the total primary non-CNS malignancy cohort. The median age at diagnosis of SPGBM was 65 years. The mean latency between a prior non-CNS malignancy and developing a SPGBM was 67.3 months (interquartile range [IQR] 27-100). Overall, patients with a primary non-CNS malignancy had a significantly elevated M-SIR (1.13, 95% CI 1.09-1.16), with a 13% increased incidence of SPGBM when compared to the incidence of developing GBM in the age-matched general population. When stratified by non-CNS tumor location, patients diagnosed with primary melanoma, lymphoma, prostate, breast, renal, or endocrine malignancies had a higher M-SIR (M-SIR ranges: 1.09-2.15). Patients with lung cancers (M-SIR 0.82, 95% CI 0.68-0.99), or stomach cancers (M-SIR 0.47, 95% CI 0.24-0.82) demonstrated a lower M-SIR.

CONCLUSION

Patients with a history of prior non-CNS malignancy are at an overall increased risk of developing SPGBM relative to the incidence of developing GBM in the general population. However, the incidence of SPGBM after prior non-CNS malignancy varies by primary tumor location, with some non-CNS malignancies demonstrating either increased or decreased predisposition for SPGBM depending on tumor origin. These findings merit future investigation into whether these relationships represent treatment effects or a previously unknown shared predisposition for glioblastoma and non-CNS malignancy.

The Impact of ioMRI on Glioblastoma Resection and Clinical Outcomes in a State-of-the-Art Neuro-Oncological Setup

Intraoperative magnetic resonance imaging (ioMRI) aims to improve gross total resection (GTR) in glioblastoma (GBM) patients. Despite some older randomized data on safety and feasibility, ioMRI's actual impact in a modern neurosurgical setting utilizing a larger armamentarium of techniques has not been sufficiently investigated to date. We therefore aimed to analyze its effects on residual tumor, patient outcome, and progression-free survival (PFS) in GBM patients in a modern high-volume center. Patients undergoing ioMRI for resection of supratentorial GBM were enrolled between March 2018 and June 2020. ioMRI was performed in all cases at the end of resection when surgeons expected complete macroscopic tumor removal. Extent of resection (EOR) was performed by volumetric analysis, with GTR defined as an EOR ≥ 95%, respectively. Progression-free survival (PFS) was analyzed through univariate and multivariate Cox proportional regression analyses. In total, we enrolled 172 patients. Mean EOR increased from 93.9% to 98.3% (p < 0.0001) due to ioMRI, equaling an increase in GTR rates from 78.5% to 93.0% (p = 0.0002). Residual tumor volume decreased from 1.3 ± 4.2 cm³ to 0.6 ± 2.5 cm³ (p = 0.0037). Logistic regression revealed recurrent GBM as a risk factor leading to subtotal resection (STR) (odds ratio (OR) = 3.047, 95% confidence interval (CI) 1.165-7.974, p = 0.023). Additional resection after ioMRI led to equally long PFS compared to patients with complete tumor removal before ioMRI (hazard ratio (HR) = 0.898, 95%-CI 0.543-1.483, p = 0.67). ioMRI considerably reduces residual tumor volume and helps to achieve comparable PFS, even in patients with unexpected residual tumor after initial resection before ioMRI.

Prognostic and predictive factors of secondary gliosarcoma: A single-institution series of 18 cases combined with 89 cases from literature

Introduction

Secondary gliosarcomas (SGS) are rare malignancies that are diagnosed subsequent to pre-existing glioma. Clinical features and optimal treatment strategies for SGS have not been conclusively established. This study aimed to assess the clinicopathological features and outcomes of SGS.

Methods

We assessed the clinicopathological features and outcomes of SGS via retrospective analysis of data for SGS patients at Tangdu Hospital. Data from SGS patients in prior publications were also analyzed in accordance with PRISMA guidelines.

Results

Eighteen SGS patients who had been treated at Tangdu Hospital between 2013 and 2020 were enrolled in this study. Additional 89 eligible SGS patients were identified from 39 studies. The median age for the patients was 53 years old, and the most common location was the temporal lobe. The most common initial diagnosis was glioblastoma (GBM) (72.0%). Radiology revealed enhanced masses in 94.8% (73/77) of patients. Ten patients (10/107, 9.35%) had extracranial metastases at or after SGS diagnosis. Patients with initial diagnosis of non-GBM and who were younger than 60 years of age were significantly associated with a long duration of disease progression to SGS. After SGS diagnosis, patients with initial non-GBM diagnosis, gross total resection and chemoradiotherapy exhibited prolonged survival outcomes. Patients who had been initially diagnosed with GBM and received both chemoradiotherapy and active therapy after disease progression to SGS, had a significantly longer overall survival than patients who did not.

Conclusion

Initial diagnosis of GBM was a poor prognostic factor for SGS. Patients who underwent gross total resection and chemoradiation had better overall survival outcomes than those who did not. However, during treatment, clinicians should be cognizant of possible extracranial metastases.

Identification of serum exosomal miR-98-5p, miR-183-5p, miR-323-3p and miR-19b-3p as potential biomarkers for glioblastoma patients and investigation of their mechanisms

BACKGROUND

Exosomal miRNAs have attracted increasing interest as potential biomarkers and treatment targets for cancers, however, glioblastoma (GBM)-related exosomal miRNAs remain rarely reported. The study aimed to screen crucial serum exosomal miRNAs in GBM patients and explored their possible mechanisms.

METHODS

Serum exosomal miRNA profile datasets of GBM patients and normal controls were downloaded from the Gene Expression Omnibus database (GSE112462 and GSE122488). The differentially expressed miRNAs (DEMs) were identified using the limma method. Their diagnostic values were assessed by receiver operating characteristic (ROC) curve analysis. The target genes of DEMs were predicted by the miRwalk 2.0 database. Function enrichment analysis was performed using the DAVID database. The expression and prognosis of target genes were validated using TCGA sequencing data and immunohistochemistry.

RESULTS

Seven DEMs were shared in two datasets, among which hsa-miR-183-5p and hsa-miR-98-5p as well as has-miR-323-3p or has-miR-19b-3p constituted a diagnostic signature to distinguish GBM from controls, with the area under the ROC curve nearly approximate to 1. MAPK8IP1/FAM175B, OSMR/CASP3, PTPN2 and FBXO32 may be underlying targets for hsa-miR-183-5p, hsa-miR-98-5p, has-miR-323-3p and has-miR-19b-3p, respectively. Function analysis showed all of these target genes were involved in cell proliferation and related signaling pathways [positive regulation of cell proliferation (OSMR), negative regulation of transcription from RNA polymerase II promoter (PTPN2), cell division (FAM175B), regulation of transcription, DNA-templated (MAPK8IP1), hsa05200:Pathways in cancer (CASP3) and hsa04068:FoxO signaling pathway (FBXO32)]. The protein and (or mRNA) expression levels of OSMR, CASP3, PTPN2 and FBXO32 were validated to be upregulated, while MAPK8IP1 and FAM175B were downregulated in GBM tissues. Also, OSMR, CASP3, PTPN2 and FBXO32 were associated with patients' prognosis.

CONCLUSION

These findings suggest these four exosomal miRNAs may represent potential diagnostic biomarkers and therapeutic targets for GBM.

Competing Endogenous RNA Networks in Glioma

Gliomas are the most common and malignant primary brain tumors. Various hallmarks of glioma, including sustained proliferation, migration, invasion, heterogeneity, radio- and chemo-resistance, contribute to the dismal prognosis of patients with high-grade glioma. Dysregulation of cancer driver genes is a leading cause for these glioma hallmarks. In recent years, a new mechanism of post-transcriptional gene regulation was proposed, i.e., "competing endogenous RNA (ceRNA)." Long non-coding RNAs, circular RNAs, and transcribed pseudogenes act as ceRNAs to regulate the expression of related genes by sponging the shared microRNAs. Moreover, coding RNA can also exert a regulatory role, independent of its protein coding function, through the ceRNA mechanism. In the latest glioma research, various studies have reported that dysregulation of certain ceRNA regulatory networks (ceRNETs) accounts for the abnormal expression of cancer driver genes and the establishment of glioma hallmarks. These achievements open up new avenues to better understand the hidden aspects of gliomas and provide new biomarkers and potential efficient targets for glioma treatment. In this review, we summarize the existing knowledge about the concept and logic of ceRNET and highlight the emerging roles of some recently found ceRNETs in glioma progression.

Optimizing eligibility criteria and clinical trial conduct to enhance clinical trial participation for primary brain tumor patients

Building on an initiative to enhance clinical trial participation involving the Society for Neuro-Oncology, the Response Assessment in Neuro-Oncology Working Group, patient advocacy groups, clinical trial cooperative groups, and other partners, we evaluate the impact of eligibility criteria and trial conduct on neuro-oncology clinical trial participation. Clinical trials often carry forward eligibility criteria from prior studies that may be overly restrictive and unnecessary and needlessly limit patient accrual. Inclusion and exclusion criteria should be evaluated based on the goals and design of the study and whether they impact patient safety and/or treatment efficacy. In addition, we evaluate clinical trial conduct as a barrier to accrual and discuss strategies to minimize such barriers for neuro-oncology trials.

Long-term efficacy of surgical resection with or without adjuvant therapy for treatment of secondary glioblastoma in adults

Background

There are limited studies on treatment strategies and associated clinical outcomes in patients with secondary glioblastoma (sGBM). We sought to investigate the prognostic factors and treatment decisions in a retrospective cohort of patients with sGBM.

Methods

One hundred and seventy-one patients with sGBM who met the screening criteria were included in this study. Kaplan–Meier survival analysis and Cox survival analysis were used to detect prognostic factors. R (v3.5.0) and SPSS software (v25.0, IBM) were used to perform statistical analyses.

Results

The median overall survival was 303 days (range 23–2237 days) and the median progression-free survival was 229 days (range 33–1964 days) in patients with sGBM. When assessing the relationship between adjuvant treatment outcome and extent of resection (EOR), the results showed that patients underwent gross total resection can benefit from postoperative radiotherapy and chemotherapy, but not in patients underwent subtotal resection. In addition, we also found that aggressive adjuvant therapy can significantly improve clinical outcomes of IDH1-mutated patients but no significant prognostic value for IDH1-wildtyped patients. The univariate Cox regression analyses demonstrated that EOR, adjuvant therapy, and postoperative Karnofsky Performance Scores were prognostic factors for patients with sGBM, and multivariate COX analysis confirmed that adjuvant therapy and EOR were independent prognostic factors.

Conclusions

For patients with sGBM, aggressive postoperative adjuvant therapy after gross total resection was recommended. However, we did not detect a benefit in IDH1-wildtype patients in our cohort.

Valganciclovir as Add-On to Standard Therapy in Secondary Glioblastoma

Patients with glioblastoma have a very poor prognosis despite aggressive therapeutic strategies. Cytomegalovirus has been detected in >90% of glioblastoma tumors. This virus can affect tumor progression and may represent a novel glioblastoma therapy target. We report, here, a retrospective survival analysis of patients with secondary glioblastoma who were treated with the anti-viral drug valganciclovir at Karolinska University Hospital in Stockholm. We performed survival analyses of eight patients with secondary glioblastoma who were treated with a standard dose of valganciclovir as an add-on to second-line therapy after their disease progression to glioblastoma. Thirty-six patients with secondary glioblastoma admitted during the same time period who received similar treatment and care served as contemporary controls. The patients treated with valganciclovir showed an increased median overall survival after progression to glioblastoma compared with controls (19.1 versus 12.7 months, p = 0.0072). This result indicates a potential positive effect of valganciclovir in secondary glioblastoma, which is in agreement with our previous observation that valganciclovir treatment improves the outcomes of patients with newly diagnosed glioblastoma. Larger randomized studies are warranted to prove this hypothesis.

Cognitive Functions in Repeated Glioma Surgery

Low-grade gliomas (LGG) are slow-growing brain tumors infiltrating the central nervous system which tend to recur, often with malignant degeneration after primary treatment. Re-operations are not always recommended due to an assumed higher risk of neurological and cognitive deficits. However, this assumption is relatively ungrounded due to a lack of extensive neuropsychological testing. We retrospectively examined a series of 40 patients with recurrent glioma in eloquent areas of the left hemisphere, who all completed comprehensive pre- (T3) and post-surgical (T4) neuropsychological assessments after a second surgery (4-month follow up). The lesions were most frequent in the left insular cortex and the inferior frontal gyrus. Among this series, in 17 patients the cognitive outcomes were compared before the first surgery (T1), 4 months after the first surgery (T2), and at T3 and T4. There was no significant difference either in the number of patients scoring within the normal range between T3 and T4, or in their level of performance. Further addressing the T1-T4 evolution, there was no significant difference in the number of patients scoring within the normal range. As to their level of performance, the only significant change was in phonological fluency. This longitudinal follow-up study showed that repeated glioma surgery is possible without major damage to cognitive functions in the short-term period (4 months) after surgery.

Application of an Artificial Intelligence Algorithm to Prognostically Stratify Grade II Gliomas

(1) Background: Recently, it has been shown that the extent of resection (EOR) and molecular classification of low-grade gliomas (LGGs) are endowed with prognostic significance. However, a prognostic stratification of patients able to give specific weight to the single parameters able to predict prognosis is still missing. Here, we adopt classic statistics and an artificial intelligence algorithm to define a multiparametric prognostic stratification of grade II glioma patients. (2) Methods: 241 adults who underwent surgery for a supratentorial LGG were included. Clinical, neuroradiological, surgical, histopathological and molecular data were assessed for their ability to predict overall survival (OS), progression-free survival (PFS), and malignant progression-free survival (MPFS). Finally, a decision-tree algorithm was employed to stratify patients. (3) Results: Classic statistics confirmed EOR, pre-operative- and post-operative tumor volumes, Ki67, and the molecular classification as independent predictors of OS, PFS, and MPFS. The decision tree approach provided an algorithm capable of identifying prognostic factors and defining both the cut-off levels and the hierarchy to be used in order to delineate specific prognostic classes with high positive predictive value. Key results were the superior role of EOR on that of molecular class, the importance of second surgery, and the role of different prognostic factors within the three molecular classes. (4) Conclusions: This study proposes a stratification of LGG patients based on the different combinations of clinical, molecular, and imaging data, adopting a supervised non-parametric learning method. If validated in independent case studies, the clinical utility of this innovative stratification approach might be proved.

The Treatment of Gliomas in Adulthood

BACKGROUND

Gliomas are the most common intrinsic tumors of the brain, with an incidence of 6 per 100 000 persons per year. Recent years have seen marked changes in the diagnosis and treatment of gliomas, with molecular parameters now being an integral part of the diagnostic evaluation.

METHODS

This review is based on pertinent articles retrieved by a selective search in PubMed, with special attention to the new WHO glioma classification.

RESULTS

The classification of gliomas on the basis of additional molecular parameters enables more accurate prognostication and serves as a basis for therapeutic decision-making and treatment according to precisely specified algorithms. PET scanning with 18F-fluoroethyl tyrosine and 11C-methionine for the measurement of metabolic activity in gliomas has further refined the diagnostic evaluation. The median overall survival of patients with glioblastoma who have undergone resection of all tumor tissue with a disrupted blood-brain barrier (i.e., all contrast-enhancing tumor tissue) has been prolonged to up to 20 months. The 5-year survival of patients with WHO grade II gliomas is now as high as 97% after near-total resection. The surgical resection of all contrast-enhancing tumor tissue and subsequent radiotherapy and chemotherapy remain the key elements of treatment. New surgical strategies and new methods of planning radiotherapy have made these techniques safer and more effective. The percutaneous application of tumor-treating fields is a new therapeutic option that has gained a degree of acceptance. Accompanying measures such as psycho-oncology and palliative care are very important for patients and should be considered mandatory.

CONCLUSION

The consistent application of the existing multimodal treatment options for glioma has led in recent years to improved survival. Areas of important current and future scientific activity include immunotherapy and targeted and combined chemotherapy, as well as altered neurocognition, modern approaches to palliative care, and complementary therapies.

Identification of a Five-Pseudogene Signature for Predicting Survival and Its ceRNA Network in Glioma

Background: Glioma is the most common primary brain tumor with a dismal prognosis. It is urgent to develop novel molecular biomarkers and conform to individualized schemes. Methods: Differentially expressed pseudogenes between low grade glioma (LGG) and glioblastoma multiforme (GBM) were identified in the training cohort. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox proportional hazards regression analyses were used to select pseudogenes associated with prognosis of glioma. A risk signature was constructed based on the selected pseudogenes for predicting the survival of glioma patients. A pseudogene-miRNA-mRNA regulatory network was established and visualized using Cytoscape 3.5.1. Gene Oncology (GO) and signaling pathway analyses were performed on the targeted genes to investigate functional roles of the risk signature. Results: Five pseudogenes (ANXA2P2, EEF1A1P9, FER1L4, HILS1, and RAET1K) correlating with glioma survival were selected and used to establish a risk signature. Time-dependent receiver operating characteristic (ROC) curves revealed that the risk signature could accurately predict the 1, 3, and 5-year survival of glioma patients. GO and signaling pathway analyses showed that the risk signature was involved in regulation of proliferation, migration, angiogenesis, and apoptosis in glioma. Conclusions: In this study, a risk signature with five pseudogenes was constructed and shown to accurately predict 1-, 3-, and 5-year survival for glioma patient. The risk signature may serve as a potential target against glioma.

Glioblastoma in the setting of prior lower grade gliomas - insights from SEER database

Introduction

Secondary glioblastomas (GBs) constitute a small subset of all GBs and tend to arise after a lower grade glioma. Though knowledge regarding this subset has gained traction in recent years, its definition continues to evolve, complicating its clinical management. Investigation of epidemiology and survival patterns may help provide needed insights.

Results

The age at GB diagnosis is significantly lower (46.22 vs 60.25 years) for group B. The distribution among type of GB (glioblastoma, giant cell glioblastoma, or gliosarcoma) was significantly different, with no diagnosis of giant cell GB in Group B. Compared to Group A, Group B exhibited a higher proportion of females, not married, smaller tumors, no GTR, and no radiation (all p < 0.05). GB-related observed survivals were comparable. Cox regression with inclusion of co-variates reveal no significant influence of GB group on observed survival. Regarding group B, mean age was 40.197 for diagnosis of initial lower grade glioma. The most common initial ICD-O-3 pathology was oligodendroglioma, NOS; astrocytoma, NOS; astrocytoma, anaplastic; and mixed glioma.

Methods

The SEER-18 registry was queried for patients with GBs. Patients were further classified into two GB groups: Group A – those with GB as the only primary tumor, and Group B – those with GB as a 2^nd primary or subsequent tumor and with history of lower grade gliomas. Demographics and clinical factors were compared between group A and B. Appropriate statistics were employed to calculate incidences and differences among factors and GB-related survivals between the groups.

Conclusions

Overall, Group B develops GBs at an earlier age, but observed survival remains similar to those with GBs as the only primary. Moreover, this subset also exhibit different proportions of the types of GBs, and well as differences in other key clinical factors (namely, gender and tumor size at presentation). Prior treatments for lower grade gliomas likely explain some of the differences noted regarding management course after diagnosis of GB.