Does gender matter in glioblastoma?

Differences in Symptom Burden in Primary Brain Tumor Patients Based on Sex, Race, and Ethnicity: a Single-Center Retrospective Study

BACKGROUND

Symptom burden affects quality of life and prognosis in primary brain tumor (PBT) patients. Knowing whether symptom burden varies based on sex, race, or ethnicity may affect the interpretation of the relationship between symptoms and survival may reveal issues with applying the tools to measure symptom burden to different groups and may identify inequities in symptom management that need to be addressed at a system level. To determine whether symptoms in PBT patients vary across demographic groups, we conducted a retrospective chart review of symptom burden collected as part of routine care in a diverse population.

METHODS

Patient demographics and scores on the MD Anderson Symptom Inventory-Brain Tumor (MDASI-BT) module were extracted from the electronic medical record for patients seen in the Inova Neuro-oncology Clinic between March 2021 and June 2022. MDASI-BT scores were compared based on side of tumor, sex, race, and ethnicity for the entire population and for the subset with gliomas.

RESULTS

We included 125 people, of whom 85 had gliomas. For both the entire group and the subgroup with gliomas, about 40% were female and about 40% were non-White race. No differences in symptom burden were seen between males and females. Pain and numbness/tingling symptom burden were higher in both the entire population and the glioma subgroup for people of Hispanic/Latino/Spanish ethnicity and for people of races other than White or Middle Eastern self-identification.

CONCLUSIONS

Pain, weakness, and numbness/tingling varied significantly across racial and ethnic groups. Further research is needed to validate this finding in other populations and determine its cause.

Association between giant cell glioblastoma and glioblastoma multiforme in the United States: A retrospective cohort study

OBJECTIVES

The current study aims to find the differences between glioblastoma multiforme (GBM) and giant cell glioblastoma (GCG) regarding mortality and prognosis among adults and elderly patients in the U.S.

METHODS AND MATERIALS

This study is a historical cohort type of study and is conducted on adults and elderly individuals with GBM or GCG from the years 1985-2014 in the U.S. Data were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database. The study exposure was GBM or GCG and the outcome was mortality. The potential confounders were age, sex, race, ethnicity, year of diagnosis, primary site, brain overlap, and surgery. A chi-square test was used for categorical data. A univariate analysis was used for variables having a p-value <.05. Potential confounders were selected and evaluated using multivariate logistic regression models to calculate the odds ratio with stepwise selection.

RESULTS

The study sample was 25,117. The incidences of GBM and GCG were not similar in relation to age group. Also, Spanish-Hispanic ethnicity was independently protective of GBM and GCG as compared to Non-Spanish-Hispanic ethnicity patients with GBM have a higher mortality rate than do GCG patients. The mortality rate was higher among patients diagnosed before 2010.

CONCLUSION

GCG was not statistically significant in association to reduced mortality. Non-Spanish-Hispanics with GBM or GCG had a higher mortality rate than did Spanish-Hispanics. Factors such as being female, being age 59-65, and having a year of diagnosis before 2010 were independently associated with increased mortality.

Hydrogel Environment Supports Cell Culture Expansion of a Grade IV Astrocytoma

Malignant astrocytomas are aggressive cancers of glial origin that can develop into invasive brain tumors. The disease has poor prognosis and high recurrence rate. Astrocytoma cell lines of human origin are an important tool in the experimental pathway from bench to bedside because they afford a convenient intermediate system for in vitro analysis of brain cancer pathogenesis and treatment options. We undertook the current study to determine whether hydrogel culture methods could be adapted to support the growth of astrocytoma cell lines, thereby facilitating a system that may be biologically more similar to in vivo tumor tissue. Our experimental protocols enabled maintenance of Grade IV astrocytoma cell lines in conventional monolayer culture and in the extracellular matrix hydrogel, Geltrex™. Light and fluorescence microscopy showed that hydrogel environments promoted cellular reorganization from dispersed cells into multilayered aggregates. Transmission electron microscopy revealed the prevalence of autophagy and nuclear membrane distortions in both culture systems. Analysis of microarray Gene Expression Omnibus (GEO) DataSets highlighted expression of genes implicated in pathways for cancer progression and autophagy. A pilot quantitative polymerase chain reaction (qPCR) analysis of the autophagic biomarkers, Beclin 1 (BECN1) and microtubule-associated proteins 1A/1B light chain 3B (MAP1LC3B), with two reference genes (beta actin, ACTB; glyceraldehyde 3-phosphate dehydrogenase, GAPDH), uncovered a relative increase of BECN1 and LC3B in hydrogel cultures of astrocytoma as compared to the monolayer. Taken together, results establish that ultrastructural and molecular characteristics of autophagy are features of this astrocytoma cell line, and that hydrogel culture systems can afford novel opportunities for in vitro studies of glioma.

Influence of insurance status on survival of adults with glioblastoma multiforme: A population-based study

BACKGROUND

To the authors' knowledge, the impact of insurance status on the survival time of patients with glioblastoma multiforme (GBM) has not been fully understood. The objective of the current study was to clarify the association between insurance status and survival of patients with GBM by analyzing population-based data.

METHODS

The authors performed a cohort study using data from the Surveillance, Epidemiology, and End Results program. They included adult patients (aged ≥18 years) with GBM as their primary diagnosis from the years 2007 to 2012. Patients without information regarding insurance status were excluded. A survival analysis between insurance status and GBM-related death was performed using an accelerated failure time model. Demographic and clinical variables were included to adjust for confounding effects.

RESULTS

Among the 13,665 adult patients in the study cohort, 558 (4.1%) were uninsured, 1516 (11.1%) had Medicaid coverage, and 11,591 (84.8%) had non-Medicaid insurance. Compared with patients who were uninsured, insured patients were more likely to be older, female, white, married, and with a smaller tumor size at diagnosis. Accelerated failure time analysis demonstrated that older age (hazard ratio [HR], 1.04; P<.001), male sex (HR, 1.08; P<.001), large tumor size at the time of diagnosis (HR, 1.26; P<.001), uninsured status (HR, 1.14; P =.018), and Medicaid insurance (HR, 1.10; P =.006) were independent risk factors for shorter survival among patients with GBM, whereas radiotherapy (HR, 0.40; P<.001) and married status (HR, 0.86; P<.001) indicated a better outcome. The authors discovered an overall yearly progressive improvement in survival in patients with non-Medicaid insurance who were diagnosed from 2007 through 2011 (P =.015), but not in uninsured or Medicaid-insured patients.

CONCLUSIONS

Variations existed in insurance status within the GBM population. Uninsured status and Medicaid insurance suggested shorter survival compared with non-Medicaid insurance among a population of patients with GBM. Cancer 2016;122:3157-65. © 2016 American Cancer Society.

Integrative and regularized principal component analysis of multiple sources of data

Integration of data of disparate types has become increasingly important to enhancing the power for new discoveries by combining complementary strengths of multiple types of data. One application is to uncover tumor subtypes in human cancer research in which multiple types of genomic data are integrated, including gene expression, DNA copy number, and DNA methylation data. In spite of their successes, existing approaches based on joint latent variable models require stringent distributional assumptions and may suffer from unbalanced scales (or units) of different types of data and non-scalability of the corresponding algorithms. In this paper, we propose an alternative based on integrative and regularized principal component analysis, which is distribution-free, computationally efficient, and robust against unbalanced scales. The new method performs dimension reduction simultaneously on multiple types of data, seeking data-adaptive sparsity and scaling. As a result, in addition to feature selection for each type of data, integrative clustering is achieved. Numerically, the proposed method compares favorably against its competitors in terms of accuracy (in identifying hidden clusters), computational efficiency, and robustness against unbalanced scales. In particular, compared with a popular method, the new method was competitive in identifying tumor subtypes associated with distinct patient survival patterns when applied to a combined analysis of DNA copy number, mRNA expression, and DNA methylation data in a glioblastoma multiforme study. Copyright © 2016 John Wiley & Sons, Ltd.

Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients

PURPOSE

The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type.

METHODS

The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis.

RESULTS

The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001).

CONCLUSION

A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM.

Increased 8-hydroxydeoxyguanosine in high-grade gliomas is associated with activation of autophagy

AIM OF THE STUDY

To understand the interaction between oxidative stress and autophagy in gliomas of different grades.

MATERIALS AND METHODS

In the present study, we analyzed levels of oxidative stress in 45 human glioma tumors, using the DNA oxidation marker 8-hydroxydeoxyguanosine (8-OHdG). In addition, we determined activation of autophagy in gliomas samples by assessing expression of microtubule-associated protein 1 light chain-3B (LC3B). To confirm our in vivo findings, in vitro studies using U87 cells were conducted.

RESULTS

It was determined that the grade of gliomas, that is, different malignant degrees according to WHO classification, significantly affected level of 8-OHdG. High levels of 8-OHdG were present in high-grade gliomas. This trend was significant in male patients and in young adult patients (<50 years old). Further study showed increased expression of LC3B in high-grade gliomas. In addition, levels of 8-OHdG and expression of LC3B were positively correlated. Reducing autophagic activity by 3-methyladenine resulted in significantly increased intracellular reactive oxygen species (ROS) in U87 cells.

CONCLUSIONS

Our study provides evidence that high levels of oxidative stress in high-grade gliomas are associated with autophagy activation that may play a protective role promoting the survival of high-grade gliomas under severe oxidative stress.