The SHORT Score for Preoperative Assessment of the Risk for Short-Term Survival in Glioblastoma

Classification of Glioblastoma Associated with Immune Checkpoints and Tumor Microenvironment based on Immunogenomic Profiling

BACKGROUND

Immune microenvironment is involved in tumor initiation and progression, and its effect on glioblastoma (GBM) is still unknown.

OBJECT

We sought to investigate the association between immune status and GBM.

METHODS

Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases, and we identified two immune subtypes based on 29 immune-associated gene sets.

RESULTS

Through single-sample gene set enrichment analysis (ssGSEA), we found that the high-immunity subtype had the most tumor-infiltrating immune cells and immune checkpoint molecules in GBM patients. Furthermore, we could more effectively identify immune signature pathways in GBM.

CONCLUSION

After validation with the GEO dataset, we conclude that the identified GBM high-immune subtypes may be amenable to the application of novel immune therapy for GBM.

Novel Immune-Related LncRNA Pairs are Associated with Immunol Infiltration and Survival Status in Glioblastoma

Background

Immune-related lncRNA is involved in tumor initiation and progression, while its effect in glioblastoma (GBM) is still unknown.

Objective

We sought to investigate the association between immune-related lncRNA (ir-lncRNA) and GBM.

Methods

Transcriptomic and clinical data were obtained from the TCGA dataset, and we found 2008 ir-lncRNA differentially expressed between GBM and adjacent brain tissues.

Results

Appling the univariate Cox and Lasso regression model, we found 30 prognosis-related ir-lncRNA pairs to construct a Cox regression risk model to associate the outcome of GBM patients. Furthermore, with this risk model, we can identify the tumor immune infiltration status, the expression of immunosuppressive biomarkers, and chemical sensitivity in GBM patients.

Conclusions

We constructed an immunologic risk model with lncRNA to associate the survival outcome of GBM patients, which can provide useful biomarkers.

Single-Cell Sequencing Reveals Necroptosis-Related Prognostic Genes of Glioblastoma

Background

Glioblastoma (GBM) is one of the most malignant forms of brain cancer, with the extremely lower survival rate. Necroptosis (NCPS) is also one of the most wide types of cell death, and its clinical importance in GBM is not clear.

Methods

We first identified necroptotic genes in GBM by single-cell RNA sequencing analysis of our surgical samples and weighted coexpression network analysis (WGNCA) from TCGA GBM data. The cox regression model with least absolute shrinkage and selection operator (LASSO) was used to construct the risk model. Then, KM plot and reactive operation curve (ROC) analysis were used to assess the prediction ability of the model. At last, the infiltrated immune cells and gene mutation profiling were investigated between the high- and low-NCPS groups as well.

Result

The risk model including ten necroptosis-related genes was identified as an independent risk factor for the outcome. In addition, we found that the risk model is correlated with the infiltrated immune cells and tumor mutation burden in GBM. NDUFB2 is identified to be a risk gene in GBM with bioinformatical analysis and in vitro experiment validation.

Conclusion

This risk model of necroptosis-related genes might provide clinical evidence for GBM interventions.

Unplanned intensive care unit readmission after surgical treatment in patients with newly diagnosed glioblastoma - forfeiture of surgically achieved advantages?

Postoperative intensive care unit (ICU) monitoring is an established option to ensure patient safety after resection of newly diagnosed glioblastoma. In contrast, secondary unplanned ICU readmission following complicating events during the initial postoperative course might be associated with severe morbidity and impair initially intended surgical benefit. In the present study, we assessed the prognostic impact of secondary ICU readmission and aimed to identify preoperatively ascertainable risk factors for the development of such adverse events in patients treated surgically for newly diagnosed glioblastoma. Between 2013 and 2018, 240 patients were surgically treated for newly diagnosed glioblastoma at the authors' neuro-oncological center. Secondary ICU readmission was defined as any unplanned admission to the ICU during initial hospital stay. A multivariable logistic regression analysis was performed to identify preoperatively measurable risk factors for unplanned ICU readmission. Nineteen of 240 glioblastoma patients (8%) were readmitted to the ICU. Median overall survival of patients with unplanned ICU readmission was 9 months compared to 17 months for patients without secondary ICU readmission (p=0.008). Multivariable analysis identified "preoperative administration of dexamethasone > 7 days" (p=0.002) as a significant and independent predictor of secondary unplanned ICU admission. Secondary ICU readmission following surgery for newly diagnosed glioblastoma is significantly associated with poor survival and thus may negate surgically achieved prerequisites for further treatment. This underlines the indispensability of precise patient selection as well as the importance of further scientific debate on these highly relevant aspects for patient safety.

Aggressiveness of Grade 4 Gliomas of Adults

Grade 4 adult gliomas are IDH-mutant astrocytomas and IDH-wildtype glioblastomas. They have a very high mortality rate, with survival at 5 years not exceeding 5%. We aimed to conduct a clinical imaging and morphogenetic characterization of them, as well as to identify the main negative prognostic factors that give them such aggressiveness. We conducted a ten-year retrospective study. We followed the clinical, imaging, and morphogenetic aspects of the cases. We analyzed immunohistochemical markers (IDH1, Ki-67, and nestin) and FISH tests based on the CDKN2A gene. The obtained results were analyzed using SPSS Statistics with the appropriate parameters. The clinical aspects representing negative prognostic factors were represented by patients’ comorbidities: hypertension (HR = 1.776) and diabetes mellitus/hyperglycemia (HR = 2.159). The lesions were mostly supratentorial, and the temporal lobe was the most affected. The mean volume was 88.05 cm3 and produced a midline shift with an average of 8.52 mm. Subtotal surgical resection was a negative prognostic factor (HR = 1.877). The proliferative index did not influence survival rate, whereas CDKN2A gene mutations were shown to have a major impact on survival. We identified the main negative prognostic factors that support the aggressiveness of grade 4 gliomas: patient comorbidities, type of surgical resection, degree of cell differentiation, and CDKN2A gene mutations.

RP11-552D4.1: a novel m6a-related LncRNA associated with immune status in glioblastoma

Glioblastoma (GBM) is the most malignant form of brain cancer in the world. Nevertheless, the survival rate of patients with GBM is extremely low. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) conduct important biological functions in patients’ survival status and the immunotherapeutic response. Here, m6A-related lncRNAs were identified by a co-expression method. Univariate and multivariate Cox regression together with LASSO were applied to establish the risk model. Kaplan-Meier and ROC analysis were applied to evaluate the prediction power of this risk model. Finally, the related immune profiling and chemical sensitivity targets were also investigated. The risk model holding three m6A-related lncRNAs was confirmed as an independent predictor for the prognosis. Furthermore, we found the risk model based on m6A-related lncRNAs is associated with the immune status, immunosuppressive biomarkers, and chemo-sensitivity in GBM patients. The RP11-552D4.1 is found to facilitate neuronal proliferation. This risk model consisted of m6A-related lncRNAs may be available for the clinical interventions in GBM patients.

Electrolyte and renal disorders in patients with newly diagnosed glioblastoma

Purpose: Disturbances of electrolytes and renal function have been linked to the prognosis of critically ill patients and recently also of cancer patients. This study aimed to assess electrolyte and renal disorders in glioblastoma patients and evaluate their prognostic effect. Methods: Medical records of patients with newly diagnosed glioblastoma between 2005 and 2018 were retrospectively reviewed for electrolyte and renal function parameters and for demographic, clinical and outcome parameters. Results: Electrolyte and renal function disorders were associated with poorer survival in univariate and Kaplan-Meier analysis. Multivariate analysis revealed hypochloremia as an independent prognostic factor for overall and 1-year survival. Conclusion: Only hypochloremia showed an association with glioblastoma prognosis, independent of other known prognostic factors, as age or molecular status.

How about Levetiracetam in Glioblastoma? An Institutional Experience and Meta-Analysis

Simple Summary

To date, there is a discrepancy regarding the role of antiepileptic drugs on glioblastoma survival. In the present study, based on large institutional cohort and enhanced with a meta-analysis of seven previously published studies, we show a robust association between the perioperative start of levetiracetam treatment with increased overall and progression-free survival in glioblastoma. Our results encourage the initiation of a prospective clinical trial to analyze the antitumor effect of levetiracetam in glioblastoma patients.

Abstract

Despite multimodal treatment, the prognosis of patients with glioblastoma (GBM) remains poor. Previous studies showed conflicting results on the effect of antiepileptic drugs (AED) on GBM survival. We investigated the associations of different AED with overall survival (OS) and progression-free survival (PFS) in a large institutional GBM cohort (n = 872) treated January 2006 and December 2018. In addition, we performed a meta-analysis of previously published studies, including this study, to summarize the evidence on the value of AED for GBM prognosis. Of all perioperatively administered AED, only the use of levetiracetam (LEV) was associated with longer OS (median: 12.8 vs. 8.77 months, p < 0.0001) and PFS (7 vs. 4.5 months, p = 0.001). In the multivariable analysis, LEV was independently associated with longer OS (aHR = 0.74, p = 0.017) and PFS (aHR = 0.68, p = 0.008). In the meta-analysis with 5614 patients from the present and seven previously published studies, outcome benefit for OS (HR = 0.83, p = 0.02) and PFS (HR = 0.77, p = 0.02) in GBM individuals with LEV was confirmed. Perioperative treatment with LEV might improve the prognosis of GBM patients. We recommend a prospective randomized controlled trial addressing the efficacy of LEV in GBM treatment.