The effect of race on the prognosis of the glioblastoma patient: a brief review

Investigating distinct clinical features and constructing a nomogram model for survival probability in adults with cerebellar high-grade gliomas

BACKGROUND

The clinical features of cerebellar high-grade gliomas (cHGGs) in adults have not been thoroughly explored. This large-scale, population-based study aimed to comprehensively outline these traits and construct a predictive model.

METHODS

Patient records diagnosed with gliomas were collected from various cohorts and analyzed to compare the features of cHGGs and supratentorial HGGs (sHGGs). Cox regression analyses were employed to identify prognostic factors for overall survival and to develop a nomogram for predicting survival probabilities in patients with cHGGs. Multiple machine learning methods were applied to evaluate the efficacy of the predictive model.

RESULTS

There were significant differences in prognosis, with SEER-cHGGs showing a median survival of 7.5 months and sHGGs 14.9 months (p < 0.001). Multivariate Cox regression analyses revealed that race, WHO grade, surgical procedures, radiotherapy, and chemotherapy were independent prognostic factors for cHGGs. Based on these factors, a nomogram was developed to predict 1-, 3-, and 5-year survival probabilities, with AUC of 0.860, 0.837, and 0.810, respectively. The model's accuracy was validated by machine learning approaches, demonstrating consistent predictive effectiveness.

CONCLUSIONS

Adult cHGGs are distinguished by distinctive clinical features different from those of sHGGs and are associated with an inferior prognosis. Based on these risk factors affecting cHGGs prognosis, the nomogram prediction model serves as a crucial tool for clinical decision-making in patient care.

Patients with glioblastoma: A tale of health care access and genetic ancestry

The incidence of glioblastoma, previously described as a disease predominantly affecting non‐Hispanic White patients, was higher among non‐White patients in the authors' recent study in which the racial/ethnical composition of the patients was representative of the overall population. These findings offer an opportunity to accurately redefine the patient population of patients with glioblastoma bearing the burden of this disease in the United States.

Racial Disparities in Glioblastoma Genomic Alterations: A Comprehensive Analysis of a Multi-Institution Cohort of 2390 Patients

BACKGROUND

Although molecular biomarkers have significantly advanced precision oncology in glioblastoma, the prevalence of these biomarkers by race remains underexplored. This study aims to characterize the genomic alterations in glioblastoma across Asian, Black, and White patients, offering insights into racial disparities that may influence treatment outcomes and disease progression.

METHODS

Analyzing data from the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange database V13.0, this study examined 2390 primary glioblastoma samples from unique patients. Genomic alterations in 566 cancer-related genes were assessed using targeted next-generation sequencing panels from 3 large cancer institutes. The patient cohort included 112 Asians, 67 Blacks, and 2211 Whites. Statistical significance of associations between genomic alterations and race was evaluated using the chi-squared test, with the Benjamini-Hochberg method applied to control for multiple testing adjustments.

RESULTS

Significant racial differences were observed in the frequency of genomic alterations. Asians exhibited a higher frequency of TP53 alterations (52.68%, P < 0.001), Blacks showed more frequent alterations in NRAS (7.46%, P < 0.001), MTOR (10.45%, P = 0.039), and TET2 (8.96%, P = 0.039), and Whites had a higher occurrence of PTEN alterations (48.67%, P = 0.045). Additionally, Black patients had an elevated rate of RET deletions (14.29%, P < 0.001).

CONCLUSIONS

This study identifies significant racial disparities in the alteration frequencies of 6 key glioblastoma genes: NRAS, TP53, MTOR, TET2, PTEN, and RET. These findings underscore the need for racial considerations in glioblastoma treatment strategies and highlight potential avenues for targeted therapeutic interventions. Further research is needed to explore the clinical implications of these genomic disparities.

The Emerging Role of Ubiquitin-Specific Protease 36 (USP36) in Cancer and Beyond

The balance between ubiquitination and deubiquitination is instrumental in the regulation of protein stability and maintenance of cellular homeostasis. The deubiquitinating enzyme, ubiquitin-specific protease 36 (USP36), a member of the USP family, plays a crucial role in this dynamic equilibrium by hydrolyzing and removing ubiquitin chains from target proteins and facilitating their proteasome-dependent degradation. The multifaceted functions of USP36 have been implicated in various disease processes, including cancer, infections, and inflammation, via the modulation of numerous cellular events, including gene transcription regulation, cell cycle regulation, immune responses, signal transduction, tumor growth, and inflammatory processes. The objective of this review is to provide a comprehensive summary of the current state of research on the roles of USP36 in different pathological conditions. By synthesizing the findings from previous studies, we have aimed to increase our understanding of the mechanisms underlying these diseases and identify potential therapeutic targets for their treatment.

Factors associated with longer survival among older medicare patients after diagnosis of supratentorial primary brain malignancies: a retrospective cohort study

OBJECTIVES

Despite recent advances, the prognosis for primary malignant brain tumors (PMBTs) remains poor. Some commonly prescribed medications may exhibit anti-tumor properties in various cancers, and neurodegenerative diseases may activate pathways that counteract gliomagenesis. Our study is focused on determining if there is a correlation between the use of metformin, beta-blockers, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs), or the presence of Parkinson's disease (PD), and the survival rates following a diagnosis of a PMBT.

METHODS

This analysis of the 100% Texas Medicare Database identified patients aged 66+ years diagnosed with a supratentorial PMBT from 2014-2017. Cox proportional hazards regression was employed to analyze survival following diagnosis and associations of survival with surgical intervention, radiation, PD diagnosis, and prescription of metformin, beta-blockers, ACEIs, or ARBs.

RESULTS

There were 1,943 patients who met study criteria, and the median age was 74 years. When medication utilization was stratified by none, pre-diagnosis only, post-diagnosis only, or both pre- and post-diagnosis (continuous), continuous utilization of metformin, beta-blockers, ACEIs, or ARBs was associated with prolonged survival compared to no utilization (hazard ratio [HR]:0.45, 95% CI:0.33-0.62; HR:0.71. 95% CI:0.59-0.86; HR:0.59, 95% CI:0.48-0.72; and HR:0.45, 95% CI:0.35-0.58 respectively). PD was also associated with longer survival (HR:0.59-0.63 across the four models).

DISCUSSION

Our study suggests that metformin, beta-blockers, ACEIs, ARBs, and comorbid PD are associated with a survival benefit among geriatric Medicare patients with supratentorial PMBTs.

A Retrospective Study to Evaluate Discrepancies in Urban Versus Rural Mortality Due to Brain Cancer in the United States

INTRODUCTION

The study aims to examine the disparities in mortality rates attributed to brain cancer between urban and rural areas over a 22-year period, totaling 315,538 deaths. This investigation serves as a crucial step in identifying areas within healthcare that require improvement. By pinpointing the variations in mortality rates between urban and rural settings, healthcare authorities can strategically implement necessary interventions.

METHODOLOGY

A retrospective study was conducted by analyzing the death certificate available on the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database from 1999 to 2020 to evaluate the mortality rate trends of brain cancer ( International Classification of Diseases (ICD)-10 C71.0-71.9).The data was grouped based on rural and urban death rates according to the 2013 urbanization classification and the variables that were used were age, gender and race. Data was analyzed using Microsoft Excel and R Studio 4.3.1. Significant associations between demographic variables and mortality rates were identified via Binomial tests.

RESULTS

From 1999 to 2020, urban areas recorded 259,402 deaths attributed to brain cancer, compared to 56,136 deaths in rural areas, indicating a higher mortality rate in urban settings. The mortality rate in both rural and urban areas exhibited an upward trend, except for a slight drop in 2010. The mortality rates were significantly higher in rural areas compared to urban areas for age groups 55-64 years and 65-74 years, males and caucasians.

CONCLUSIONS

Our research underscores the differences in death rates from brain cancer between urban and rural areas, specifically among individuals aged 55-64 and 65-74, males and those of caucasian ethnicity. Future research must adopt a multifaceted approach, integrating more recent datasets and embracing a finer granularity of individual-level information. Moreover, there is a pressing need to explore the interplay of various factors such as access to healthcare, treatment modalities, genetic predispositions, and socioeconomic determinants on mortality outcomes.

Principles in the Management of Glioblastoma

Glioblastoma, the most aggressive and common malignant primary brain tumour, is characterized by infiltrative growth, abundant vascularization, and aggressive clinical evolution. Patients with glioblastoma often face poor prognoses, with a median survival of approximately 15 months. Technological progress and the subsequent improvement in understanding the pathophysiology of these tumours have not translated into significant achievements in therapies or survival outcomes for patients. Progress in molecular profiling has yielded new omics data for a more refined classification of glioblastoma. Several typical genetic and epigenetic alterations in glioblastoma include mutations in genes regulating receptor tyrosine kinase (RTK)/rat sarcoma (RAS)/phosphoinositide 3-kinase (PI3K), p53, and retinoblastoma protein (RB) signalling, as well as mutation of isocitrate dehydrogenase (IDH), methylation of O6-methylguanine-DNA methyltransferase (MGMT), amplification of epidermal growth factor receptor vIII, and codeletion of 1p/19q. Certain microRNAs, such as miR-10b and miR-21, have also been identified as prognostic biomarkers. Effective treatment options for glioblastoma are limited. Surgery, radiotherapy, and alkylating agent chemotherapy remain the primary pillars of treatment. Only promoter methylation of the gene MGMT predicts the benefit from alkylating chemotherapy with temozolomide and it guides the choice of first-line treatment in elderly patients. Several targeted strategies based on tumour-intrinsic dominant signalling pathways and antigenic tumour profiles are under investigation in clinical trials. This review explores the potential genetic and epigenetic biomarkers that could be deployed as analytical tools in the diagnosis and prognostication of glioblastoma. Recent clinical advancements in treating glioblastoma are also discussed, along with the potential of liquid biopsies to advance personalized medicine in the field of glioblastoma, highlighting the challenges and promises for the future.

Association of county-level socioeconomic status with meningioma incidence and outcomes

BACKGROUND

Prior literature suggests that individual socioeconomic status (SES) may influence incidence, treatments, and survival of brain tumor cases. We aim to conduct the first national study to evaluate the association between US county-level SES and incidence, treatment, and survival in meningioma.

METHODS

The Central Brain Tumor Registry of the United States analytic dataset, which combines data from CDC's National Program of Cancer Registries (NPCR) and National Cancer Institute's Surveillance, Epidemiology, and End Results Program, was used to identify meningioma cases from 2006 to 2019. SES quintiles were created using American Community Survey data. Logistic regression models were used to evaluate associations between SES and meningioma. Cox proportional hazard models were constructed to assess the effect of SES on survival using the NPCR analytic dataset.

RESULTS

A total of 409 681 meningioma cases were identified. Meningioma incidence increased with higher county-level SES with Q5 (highest quintile) having a 12% higher incidence than Q1 (incidence rate ratios (IRR) = 1.12, 95%CI: 1.10-1.14; P < .0001). The Hispanic group was the only racial-ethnic group that had lower SES associated with increased meningioma incidence (Q5: age-adjusted incidence ratio (AAIR) = 9.02, 95%CI: 8.87-9.17 vs. Q1: AAIR = 9.33, 95%CI: 9.08-9.59; IRR = 0.97, 95%CI: 0.94-1.00; P = .0409). Increased likelihood of surgical treatment was associated with Asian or Pacific Islander non-Hispanic individuals (compared to White non-Hispanic (WNH)) (OR = 1.28, 95%CI: 1.23-1.33, P < .001) and males (OR = 1.31, 95%CI: 1.29-1.33, P < .001). Black non-Hispanic individuals (OR = 0.90, 95%CI: 0.88-0.92, P < .001) and those residing in metropolitan areas (OR = 0.96, 95%CI: 0.96-0.96, P < .001) were less likely to receive surgical treatment compared to WNH individuals. Overall median survival was 137 months, and survival was higher in higher SES counties (Q5 median survival = 142 months).

CONCLUSIONS

Higher county-level SES was associated with increased meningioma incidence, surgical treatment, and overall survival. Racial-ethnic stratification identified potential disparities within the meningioma population. Further work is needed to understand the underpinnings of socioeconomic and racial disparities for meningioma patients.

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.

Racial and socioeconomic disparities in glioblastoma outcomes: A single-center, retrospective cohort study

BACKGROUND

Glioblastoma (GBM) is the most common malignant primary brain tumor. Emerging reports have suggested that racial and socioeconomic disparities influence the outcomes of patients with GBM. No studies to date have investigated these disparities controlling for isocitrate dehydrogenase (IDH) mutation and O-6-methylguanine-DNA methyltransferase (MGMT) status.

METHODS

Adult patients with GBM were retrospectively reviewed at a single institution from 2008 to 2019. Univariable and multivariable complete survival analyses were performed. A Cox proportional hazards model was used to assess the effect of race and socioeconomic status controlling for a priori selected variables with known relevance to survival.

RESULTS

In total, 995 patients met inclusion criteria. Of these, 117 patients (11.7%) were African American (AA). The median overall survival for the entire cohort was 14.23 months. In the multivariable model, AA patients had better survival compared with White patients (hazard ratio [HR], 0.37; 95% confidence interval [CI], 0.2-0.69). The observed survival difference was significant in both a complete case analysis model and a multiple imputations model accounting for missing molecular data and controlling for treatment and socioeconomic status. AA patients with low income (HR, 2.17; 95% CI, 1.04-4.50), public insurance (HR, 2.25; 95% CI, 1.04-4.87), or no insurance (HR, 15.63; 95% CI, 2.72-89.67) had worse survival compared with White patients with low income, public insurance, or no insurance, respectively.

CONCLUSIONS

Significant racial and socioeconomic disparities were identified after controlling for treatment, GBM genetic profile, and other variables associated with survival. Overall, AA patients demonstrated better survival. These findings may suggest the possibility of a protective genetic advantage in AA patients.

PLAIN LANGUAGE SUMMARY

To best personalize treatment for and understand the causes of glioblastoma, racial and socioeconomic influences must be examined. The authors report their experience at the O'Neal Comprehensive Cancer Center in the deep south. In this report, contemporary molecular diagnostic data are included. The authors conclude that there are significant racial and socioeconomic disparities that influence glioblastoma outcome and that African American patients do better.

Defining subventricular zone involvement to predict the survival of patients in isocitrate dehydrogenase-wild type glioblastoma: validation in a prospective registry

OBJECTIVES

The prognostic value of subventricular zone distance (SVD) is unclear because of different definitions and lack of evaluation of clinical survival models. The aim of this study was to define SVD and evaluate its prognostic value in a survival nomogram for glioblastoma.

METHODS

This retrospective study included 158 (SVD biomarker) from historical glioblastoma patients and 187 (survival modeling) with IDH-wild type glioblastoma from a prospective registry (NCT02619890). SVD was assessed by two radiologists: definition 1, the distance between the tumor edge to subventricular zone (SVZ); definition 2, the distance between the tumor centroid to SVZ; definition 3, enhancement at the ventricular wall. The associations between SVD and overall survival (OS) were evaluated using multivariable Cox proportional hazards regression analysis. Performance of an updated SVD survival model was compared with that of the Radiation Therapy Oncology Group (RTOG) 0525 nomogram.

RESULTS

SVD according to both definition 1 (hazard ratio [HR]: 0.97, 95% CI: 0.94-0.99; p = .011) and definition 2 (HR: 0.96, 0.94-0.98, p < .001) was adversely associated with OS. Definition 1 was adversely associated with PFS (HR: 0.96, 0.94-0.99, p = .008) and showed the highest reproducibility (intraclass correlation coefficient, 0.90). The SVD-updated model showed similar to better performance than the RTOG model for predicting OS of up to 3 years (AUC: 0.735-0.738 vs. 0.687-0.708), with higher time-dependent specificity for 1-year (89.9% vs. 70.6%) and 3-year OS (93.3% vs. 80.0%).

CONCLUSION

SVZ distance is an independent adverse prognostic factor in patients with IDH-wild type glioblastoma. Updating the survival model with SVZ provides better time-dependent specificity and reproducibility.

KEY POINTS

• Subventricular zone distance (SVD) measurement from tumor edge showed high reproducibility. • Longer SVD was independently associated with longer overall survival. • Adding SVD improved time-dependent specificity for survival model in a prospective registry.

Deep Learning Approaches for Glioblastoma Prognosis in Resource-Limited Settings: A Study Using Basic Patient Demographic, Clinical, and Surgical Inputs

BACKGROUND

Glioblastoma (GBM) is the most common brain tumor in the United States, with an annual incidence rate of 3.21 per 100,000. It is the most aggressive type of diffuse glioma and has a median survival of months after treatment. This study aims to assess the accuracy of different novel deep learning models trained on a set of simple clinical, demographic, and surgical variables to assist in clinical practice, even in areas with constrained health care infrastructure.

METHODS

Our study included 37,095 patients with GBM from the SEER (Surveillance Epidemiology and End Results) database. All predictors were based on demographic, clinicopathologic, and treatment information of the cases. Our outcomes of interest were months of survival and vital status. Concordance index (C-index) and integrated Brier scores (IBS) were used to evaluate the performance of the models.

RESULTS

The patient characteristics and the statistical analyses were consistent with the epidemiologic literature. The models C-index and IBS ranged from 0.6743 to 0.6918 and from 0.0934 to 0.1034, respectively. Probabilistic matrix factorization (0.6918), multitask logistic regression (0.6916), and logistic hazard (0.6916) had the highest C-index scores. The models with the lowest IBS were the probabilistic matrix factorization (0.0934), multitask logistic regression (0.0935), and logistic hazard (0.0936). These models had an accuracy (1-IBS) of 90.66%; 90.65%, and 90.64%, respectively. The deep learning algorithms were deployed on an interactive Web-based tool for practical use available via https://glioblastoma-survanalysis.herokuapp.com/.

CONCLUSIONS

Novel deep learning algorithms can better predict GBM prognosis than do baseline methods and can lead to more personalized patient care regardless of extensive electronic health record availability.

Identification and validation of SOCS1/2/3/4 as potential prognostic biomarkers and correlate with immune infiltration in glioblastoma

Suppressor of cytokine signalling (SOCS) 1/2/3/4 are involved in the occurrence and progression of multiple malignancies; however, their prognostic and developmental value in patients with glioblastoma (GBM) remains unclear. The present study used TCGA, ONCOMINE, SangerBox3.0, UALCAN, TIMER2.0, GENEMANIA, TISDB, The Human Protein Atlas (HPA) and other databases to analyse the expression profile, clinical value and prognosis of SOCS1/2/3/4 in GBM, and to explore the potential development mechanism of action of SOCS1/2/3/4 in GBM. The majority of analyses showed that SOCS1/2/3/4 transcription and translation levels in GBM tissues were significantly higher than those in normal tissues. qRT-PCR, western blotting (WB) and immunohistochemical staining were used to verify that SOCS3 was expressed at higher mRNA and protein levels in GBM than in normal tissues or cells. High SOCS1/2/3/4 mRNA expression was associated with poor prognosis in patients with GBM, especially SOCS3. SOCS1/2/3/4 were highly contraindicated, which had few mutations, and were not associated with clinical prognosis. Furthermore, SOCS1/2/3/4 were associated with the infiltration of specific immune cell types. In addition, SOCS3 may affect the prognosis of patients with GBM through JAK/STAT signalling pathway. Analysis of the GBM-specific protein interaction (PPI) network showed that SOCS1/2/3/4 were involved in multiple potential carcinogenic mechanisms of GBM. In addition, colony formation, Transwell, wound healing and western blotting assays revealed that inhibition of SOCS3 decreased the proliferation, migration and invasion of GBM cells. In conclusion, the present study elucidated the expression profile and prognostic value of SOCS1/2/3/4 in GBM, which may provide potential prognostic biomarkers and therapeutic targets for GBM, especially SOCS3.

Angelica sinensis extract induces telomere dysfunction, cell cycle arrest, and mitochondria-mediated apoptosis in human glioblastoma cells

Glioblastoma (GB) is one of the most aggressive and malignant tumors of the central nervous system. Conventional treatment for GB requires surgical resection followed by radiotherapy combined with temozolomide chemotherapy; however, the median survival time is only 12-15 months. Angelica sinensis Radix (AS) is commonly used as a traditional medicinal herb or a food/dietary supplement in Asia, Europe, and North America. This study aimed to investigate the effect of AS-acetone extract (AS-A) on the progression of GB and the potential mechanisms underlying its effects. The results indicated that AS-A used in this study showed potency in growth inhibition of GB cells and reduction of telomerase activity. In addition, AS-A blocked the cell cycle at the G₀/G₁ phase by regulating the expression of p53 and p16. Furthermore, apoptotic morphology, such as chromatin condensation, DNA fragmentation, and apoptotic bodies, was observed in AS-A-treated cells, induced by the activation of the mitochondria-mediated pathway. In an animal study, AS-A reduced tumor volume and prolonged lifespans of mice, with no significant changes in body weight or obvious organ toxicity. This study confirmed the anticancer effects of AS-A by inhibiting cell proliferation, reducing telomerase activity, altering cell cycle progression, and inducing apoptosis. These findings suggest that AS-A has great potential for development as a novel agent or dietary supplement against GB.

The Influence of Ethnicity on Survival from Malignant Primary Brain Tumours in England: A Population-Based Cohort Study

BACKGROUND

In recent years, the completeness of ethnicity data in the English cancer registration data has greatly improved. Using these data, this study aims to estimate the influence of ethnicity on survival from primary malignant brain tumours.

METHODS

Demographic and clinical data on adult patients diagnosed with malignant primary brain tumour from 2012 to 2017 were obtained (n = 24,319). Univariate and multivariate Cox proportional hazards regression analyses were used to estimate hazard ratios (HR) for the survival of the ethnic groups up to one year following diagnosis. Logistic regressions were then used to estimate odds ratios (OR) for different ethnic groups of (1) being diagnosed with pathologically confirmed glioblastoma, (2) being diagnosed through a hospital stay that included an emergency admission, and (3) receiving optimal treatment.

RESULTS

After an adjustment for known prognostic factors and factors potentially affecting access to healthcare, patients with an Indian background (HR 0.84, 95% CI 0.72-0.98), Any Other White (HR 0.83, 95% CI 0.76-0.91), Other Ethnic Group (HR 0.70, 95% CI 0.62-0.79), and Unknown/Not Stated Ethnicity (HR 0.81, 95% CI 0.75-0.88) had better one-year survivals than the White British Group. Individuals with Unknown ethnicity are less likely be diagnosed with glioblastoma (OR 0.70, 95% CI 0.58-0.84) and less likely to be diagnosed through a hospital stay that included an emergency admission (OR 0.61, 95% CI 0.53-0.69).

CONCLUSION

The demonstrated ethnic variations associated with better brain tumour survival suggests the need to identify risk or protective factors that may underlie these differences in patient outcomes.

Chloroquine Supplementation for the Treatment of Glioblastoma: A Meta-analysis of Randomized Controlled Studies

INTRODUCTION

Chloroquine supplementation may show some potential in improving the efficacy for glioblastoma, and this meta-analysis aimed to identify the efficacy of chloroquine supplementation for patients with glioblastoma.

METHODS

Several databases including PubMed, Embase, Web of Science, EBSCO, and Cochrane Library databases have been systematically searched through August 2022, and we included randomized controlled trials assessing the efficacy of chloroquine supplementation for glioblastoma. This meta-analysis was performed using the random-effect model or fixed-effect model based on the heterogeneity.

RESULTS

Four randomized controlled trials were finally included in this meta-analysis. In comparison with control group for glioblastoma, chloroquine supplementation was associated with substantially decreased mortality (odd ratio [OR], 0.17; 95% confidence interval [CI], 0.06-0.53; P = 0.002), improved survival time (mean difference, 15.63; 95% CI, 2.27-28.99; P = 0.02), and remission (OR, 15.63; 95% CI, 2.27-28.99; P = 0.02), but unraveled no obvious impact on the incidence of adverse events (OR, 3.27; 95% CI, 0.29-36.44; P = 0.34) or seizure (OR, 2.57; 95% CI, 0.05-127.68; P = 0.64).

CONCLUSIONS

Chloroquine supplementation may be effective to improve the treatment efficacy for glioblastoma.

SREBP2/Rab11s/GLUT1/6 network regulates proliferation and migration of glioblastoma

Cholesterol serves a vital role in the occurrence and development of glioblastoma multiforme (GBM). Furthermore, cholesterol synthesis is regulated by sterol regulatory element-binding protein 2 (SREBP2), and certain glucose transporters (GLUTs) and Ras-related protein Rab11 (Rab11) small GTPase family members (Rab11s) may contribute to the process. The Cancer Genome Atlas was used to analyze the relationship between prognosis and GLUT gene expressions. To investigate the regulatory effect of Rab11s and SREBP2 on GLUTs during tumor progression, single cell RNA sequencing (scRNA-seq), western blotting and reverse transcription-quantitative PCR were performed on glioma tissues and the T98G GBM cell line. Cell viability and migration were assessed by performing MTT and wound healing assays, respectively. Moreover, the dual-luciferase reporter gene assay was conducted to predict the sterol regulatory elements in the promoter regions of the target genes. The results demonstrated that high SREBP2, GLUT1 and GLUT6 expression was associated with poor survival of patients with GBM. ScRNA-seq distinguished glioblastoma cells by EGFR and indicated the related lipid metabolism signaling pathways. Moreover, the results indicated that GLUT1 and GLUT6 were regulated by SREBP2 and Rab11s. Rab11s and SREBP2 also contributed to T98G cell viability and migration. Additionally, the results indicated that Rab11s, GLUT1 and GLUT6 were transcriptionally regulated by SREBP2. Therefore, the present study suggested that the SREBP2/Rab11/GLUT network promoted T98G cell growth, thus, identifying potential therapeutic targets for GBM.

Racial and ethnic disparities in brain tumour survival by age group and tumour type

PURPOSE

The extent to which racial/ethnic brain tumour survival disparities vary by age is not very clear. In this study, we assess racial/ethnic brain tumour survival disparities overall by age group and type.

METHODS

Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) 18 registries for US-based individuals diagnosed with a first primary malignant tumour from 2007 through 2016. Cox proportional hazards regression was used to compute adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the association between race/ethnicity and brain tumour survival, stratified by age group and tumour type.

RESULTS

After adjusting for sex, socioeconomic status, insurance status, and tumour type, non-Hispanic (NH) Blacks (HR: 1.26; 95% CI: 1.02-1.55), NH Asian or Pacific Islanders (HR: 1.29; 95% CI: 1.01-1.66), and Hispanics (any race) (HR: 1.28; 95% CI: 1.09-1.51) all showed a survival disadvantage compared with NH Whites for the youngest age group studied (0-9 years). Furthermore, NH Blacks (HR: 0.88; 95% CI: 0.91-0.97), NH Asian or Pacific Islanders (HR: 0.84; 95% CI: 0.77-0.92), and Hispanics (any race) (HR: 0.91; 95% CI: 0.85-0.97) all showed a survival advantage compared with NH Whites for the 60-79 age group. Tests for interactions showed significant trends, indicating that racial/ethnic survival disparities disappear and even reverse for older age groups (P < 0.001). This reversal appears to be driven by poor glioblastoma survival among NH Whites (P < 0.001).

CONCLUSION

Disparities in brain tumour survival among minorities exist primarily among children and adolescents. NH White adults show worse survival than their minority counterparts, which is possibly driven by poor glioblastoma biology.

Pediatric versus adult high grade glioma: Immunotherapeutic and genomic considerations

High grade gliomas are identified as malignant central nervous tumors that spread rapidly and have a universally poor prognosis. Historically high grade gliomas in the pediatric population have been treated similarly to adult high grade gliomas. For the first time, the most recent classification of central nervous system tumors by World Health Organization has divided adult from pediatric type diffuse high grade gliomas, underscoring the biologic differences between these tumors in different age groups. The objective of our review is to compare high grade gliomas in the adult versus pediatric patient populations, highlighting similarities and differences in epidemiology, etiology, pathogenesis and therapeutic approaches. High grade gliomas in adults versus children have varying clinical presentations, molecular biology background, and response to chemotherapy, as well as unique molecular targets. However, increasing evidence show that they both respond to recently developed immunotherapies. This review summarizes the distinctions and commonalities between the two in disease pathogenesis and response to therapeutic interventions with a focus on immunotherapy.

SPTSSA Is a Prognostic Marker for Glioblastoma Associated with Tumor-Infiltrating Immune Cells and Oxidative Stress

Background. SPTSSA encodes the small subunit A of serine palmitoyltransferase. It catalyzes the formation of sphingoid long-chain base backbone of sphingolipids. Its role in glioma prognosis and tumor-infiltrating immune cells remains unclear. Methods. We analyzed SPTSSA expression and association with clinical prognosis using GEPIA and CGGA database. Then, GSEA was performed to identify relevant biological functions of SPTSSA. The correlations between SPTSSA expression and tumor immune infiltrates were investigated using CIBERSORT and TIMER. Finally, IHC and IF were performed to confirm the value of prognosis and the correlation with immune infiltration. Results. SPTSSA expression was significantly upregulated in diffuse glioma compared to normal tissues and associated with poor survival in GEPIA and CGGA database. Then, we identified biological processes and signaling pathways associated with SPTSSA expression. The result showed that SPTSSA enriched in the GO term like oxidative stress. Finally, we showed that SPTSSA expression was significantly associated with tumor-infiltrating immune cells and overall survival via IHC. Conclusion. These findings suggest that SPTSSA expression might be used as a prognostic biomarker for glioma and potential target for novel glioma therapy.

Long-term time series forecasting and updates on survival analysis of glioblastoma multiforme, a 1975-2018 population-based study

OBJECTIVE

Glioblastomas(GBM) are the most common primary CNS tumors. Epidemiologic studies have investigated the effect of demographics on patient survival, but the literature remains inconclusive.

METHODS

This study included all adult patients with intracranial GBMs reported in the SEER-9 population database (1975-2018). The sample consisted of 32746 unique entries. We forecast the annual GBM incidence in the US population through the year of 2060 using time series analysis with autoregressive moving averages. A survival analysis of the GBM-specific time to death was also performed. Multivariate Cox Proportional Hazards(PH) regression revealed frank violations of the PH assumption for multiple covariates. Parametric models best described the GBM population's survival pattern; the results were compared to the semi-parametric analysis and the published literature.

RESULTS

We predicted an increasing GBM incidence, which demonstrated that by the year 2060, over 1800 cases will be reported annually in the SEER. All eight demographic variables were significant in the univariable analysis. The calendar year 2005 was the cutoff associated with an increased survival probability. A male survival benefit was eliminated in the year-adjusted Cox. The factors: infratentorial tumors, non-metropolitan areas, and White patient race were erroneously associated with survival in the multivariate Cox analysis. AFT lognormal regression was the best model to describe the survival pattern in our patient population, identifying age > 30 years old as a poor prognostic and patients > 70 years old as having the worst survival. Annual income > $75,000 and supratentorial tumors were good prognostics, while surgical intervention provided the strongest survival benefit.

CONCLUSIONS

Annual GBM incidence rates will continue to increase by almost 50% in the upcoming 30 years. Cox regression analysis should not be utilized for time-to-event predictions in GBM survival statistics. AFT lognormal distribution best describes the GBM specific survival pattern, and as an inherent population characteristic, it should be implemented by researchers for future studies. Surgical intervention provides the strongest survival benefit, while patient age > 70 years old is the worst prognostic. Based on our study, the demographics: gender, race, and county type should not be considered as meaningful prognostics when designing future trials.

Distinct survival and clinical profile of infantile glioblastoma: insights from a national database

BACKGROUND

The diagnosis of glioblastoma (GBM) in infants aged ≤ 1 year is extremely rare, and its comparability to the more common adult diagnosis is underexplored. Correspondingly, the objective of this study was to interrogate a national cancer database to elucidate the typical survival and clinical profile of this demographic.

METHODS

All GBM patients aged ≤ 1 year in the U.S. National Cancer Database (NCDB) between 2005 and 2016 were retrospectively reviewed. Data were summarized, and overall survival (OS) was modeled using Kaplan-Meier and Cox regression analyses.

RESULTS

A total of 86 patients satisfied criteria for entry into study, making up 0.08% of all GBM diagnoses in the database. There were 32 (37%) females and 54 (63%) males. Irrespective of treatment, median OS was 67.3 months (95% CI, 46-91), which was distinct from all other ages and pediatric age groups. There were 74 (86%) treated by surgery, 51 (59%) treated by chemotherapy, and 17 (20%) treated by radiation therapy. Multivariable analysis demonstrated that Hispanic status (HR = 3.41, P = 0.02) and the presence of comorbidity (HR = 3.24, P = 0.01) independently predicted shorter OS, whereas treatment with chemotherapy (HR = 0.18, P < 0.01) independently predicted longer OS. Neither extent of surgery nor radiation therapy demonstrated independent statistical significance.

CONCLUSION

Infantile GBM should be viewed as a distinct GBM entity with a longer OS than other pediatric and adult patients. Chemotherapy is a statistically significant component in the treatment of this demographic, and the value of surgical treatment is likely universal. Future studies into understanding the biological and genetic profile of infantile GBM are needed to advance both pediatric and adult fields.

Racial Disparities Affecting Postoperative Outcomes After Brain Tumor Resection

OBJECTIVE

To investigate racial disparities in 30-day postoperative outcomes of craniotomy for glioma resection.

METHODS

2006-2019 American College of Surgeons' National Surgical Quality Improvement Program files were queried for all patients who underwent a craniotomy for a supratentorial glioma resection. Racial disparities in preoperative variables were studied between the demographic cohorts of Asian, African Americans, Hispanics, and Caucasian. Fisher exact tests were used to examine association of preoperative variables with race. Multivariable logistic regression models, adjusted for all preoperative variables associated with race, were used to determine the odds ratios of postoperative outcomes for each demographic cohort in comparison with Caucasian patients.

RESULTS

A total of 12,544 patients were identified: 4% Asian, 5% African American, 7% Hispanic, and 85% Caucasian. African American patients had significantly higher adjusted odds than Caucasian patients of major adverse cardiovascular events (adjusted odds ratio [aOR]: 1.827, 95% confidence interval [CI]: 1.155-2.891, P = 0.01), pulmonary events (aOR: 1.683, 95% CI: 1.145-2.473, P = 0.008), and urinary tract infection (aOR: 2.016, 95% CI: 1.221-3.327, P = 0.006). Asian patients had significantly higher odds than Caucasian patients of requiring a transfusion (aOR: 2.094, 95% CI: 1.343-3.266, P = 0.001). All demographic cohorts had higher odds of having an extended length of stay than Caucasian patients.

CONCLUSIONS

African American patients who undergo a craniotomy for glioma resection have almost twice the odds of Caucasian patients of having a postoperative major cardiovascular complication, pulmonary complication, or urinary tract infection. All minority groups have higher odds of an extended length of stay as compared with Caucasian patients.

The Multifaceted Role of Extracellular Vesicles in Glioblastoma: microRNA Nanocarriers for Disease Progression and Gene Therapy

Glioblastoma (GB) is the most aggressive form of brain cancer in adults, characterized by poor survival rates and lack of effective therapies. MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression post-transcriptionally through specific pairing with target messenger RNAs (mRNAs). Extracellular vesicles (EVs), a heterogeneous group of cell-derived vesicles, transport miRNAs, mRNAs and intracellular proteins, and have been shown to promote horizontal malignancy into adjacent tissue, as well as resistance to conventional therapies. Furthermore, GB-derived EVs have distinct miRNA contents and are able to penetrate the blood-brain barrier. Numerous studies have attempted to identify EV-associated miRNA biomarkers in serum/plasma and cerebrospinal fluid, but their collective findings fail to identify reliable biomarkers that can be applied in clinical settings. However, EVs carrying specific miRNAs or miRNA inhibitors have great potential as therapeutic nanotools in GB, and several studies have investigated this possibility on in vitro and in vivo models. In this review, we discuss the role of EVs and their miRNA content in GB progression and resistance to therapy, with emphasis on their potential as diagnostic, prognostic and disease monitoring biomarkers and as nanocarriers for gene therapy.

MicroRNA-744-5p inhibits glioblastoma malignancy by suppressing replication factor C subunit 2

Glioblastoma (GBM) is the most common malignant primary brain tumor, accounting for ~57% of all gliomas and 48% of all malignant primary central nervous system tumors in the United States. Abnormal expression of the replication factor C subunit 2 (RFC2) gene and microRNA (miR)-744-5p is associated with tumorigenic characteristics, including cellular proliferation, migration and invasiveness. However, the mechanism underlying the interaction between miR-744-5p and RFC2 in GBM remains unknown. Reverse transcription-quantitative (RT-q) PCR analysis of RFC2 and miR-744-5p was performed using GBM tumor tissues and cells, and the association between miR-744-5p and RFC2 was determined by dual-luciferase reporter assay. Cell Counting Kit 8, 5-bromo-2-deoxyuridine (BrdU), wound-healing and cellular adhesion assays, as well as the detection of caspase-3 activity and western blotting were used to detect cellular proliferation, migration and adhesion, caspase-3 activity, and Bax and Bcl-2 protein expression, respectively, in GBM cells. The results of the present study demonstrated that RFC2 expression was increased in GBM tissues and cell lines. Overexpression of RFC2 promoted cellular proliferation, migration, adhesion and an increase in Bcl-2 protein levels, and suppressed cellular caspase-3 activity and Bax protein expression, while silencing RFC2 resulted in the opposite effect. The effects of miR-744-5p inhibition were similar to those of RFC2 overexpression. Moreover, miR-744-5p was found to target RFC2 in GBM cells, and inhibiting the expression of RFC2 suppressed GBM tumorigenesis. In conclusion, the present study demonstrated that miR-744-5p targets RFC2 and suppresses the progression of GBM by repressing cellular proliferation, migration and Bcl-2 protein expression, and effectively promoting caspase-3 activity and Bax protein expression. These findings suggest a new target for the clinical treatment and improved prognosis of patients with GBM in the future.

Receptor-Interacting Protein 140 Enhanced Temozolomide-Induced Cellular Apoptosis Through Regulation of E2F1 in Human Glioma Cell Lines

Glioblastoma (GBM), a grade IV glioma, is responsible for the highest years of potential life lost among cancers. The poor prognosis is attributable to its high recurrence rate, caused in part by the development of resistance to chemotherapy. Receptor-interacting protein 140 (RIP140) is a very versatile coregulator of nuclear receptors and transcription factors. Although many of the pathways regulated by RIP140 contribute significantly to cancer progression, the function of RIP140 in GBM remains to be determined. In this study, we found that higher RIP140 expression was associated with prolonged survival in patients with newly diagnosed GBM. Intracellular RIP140 levels were increased after E2F1 activation following temozolomide (TMZ) treatment, which in turn modulated the expression of E2F1-targeted apoptosis-related genes. Overexpression of RIP140 reduced glioma cell proliferation and migration, induced cellular apoptosis, and sensitized GBM cells to TMZ. Conversely, knockdown of RIP140 increased TMZ resistance. Taken together, our results suggest that RIP140 prolongs the survival of patients with GBM both by inhibiting tumor cell proliferation and migration and by increasing cellular sensitivity to chemotherapy. This study helps improve our understanding of glioma recurrence and may facilitate the development of more effective treatments.

Racial/ethnic disparities in treatment pattern and time to treatment for adults with glioblastoma in the US

PURPOSE

Race/ethnicity have been previously shown to significantly affect survival after diagnosis with glioblastoma, but the cause of this survival difference is not known. The aim of this study was to examine variation in treatment pattern and time to treatment by race/ethnicity, and the extent to which this affects survival.

METHODS

Data were obtained from the National Cancer Database (NCDB) for adults ≥ 40 with glioblastoma from 2004 to 2016 (N = 68,979). Treatment patterns and time to treatment by race/ethnicity were compared using univariable and multivariable logistic and linear regression models, respectively, and adjusted for known prognostic factors and factors potentially affecting health care access.

RESULTS

Black non-Hispanics (BNH) and Hispanics were less likely to receive radiation and less likely to receive chemotherapy as compared to White non-Hispanics (WNH). Time to radiation initiation was ~ 2 days longer and time to chemotherapy initiation was ~ 4 days longer in both groups in comparison to WNH.

CONCLUSION

Both race/ethnicity and treatment timing significantly affected survival time, and this association remained after adjustment for known prognostic factors. Additional research is necessary to disentangle the specific causal factors, and the mechanism with which they affect survival.

Impact of race on care, readmissions, and survival for patients with glioblastoma: an analysis of the National Cancer Database

Background

The objective of this study was to explore racial/ethnic factors that may be associated with survival in patients with glioblastoma by querying the National Cancer Database (NCDB).

Methods

The NCDB was queried for patients diagnosed with glioblastoma between 2004 and 2014. Patient demographic variables included age at diagnosis, sex, race, ethnicity, Charlson-Deyo score, insurance status, and rural/urban/metropolitan location of zip code. Treatment variables included surgical treatment, extent of resection, chemotherapy, radiation therapy, type of radiation, and treatment facility type. Outcomes included 30-day readmission, 30- and 90-day mortality, and overall survival. Multivariable Cox regression analyses were performed to evaluate variables associated with race and overall survival.

Results

A total of 103 652 glioblastoma patients were identified. There was a difference in the proportion of patients for whom surgery was performed, as well as the proportion receiving radiation, when stratified by race (P < .001). Black non-Hispanics had the highest rates of unplanned readmission (7.6%) within 30 days (odds ratio [OR]: 1.39 compared to White non-Hispanics, P < .001). Asian non-Hispanics had the lowest 30- (3.2%) and 90-day mortality (9.8%) when compared to other races (OR: 0.52 compared to White non-Hispanics, P = .031). Compared to White non-Hispanics, we found Black non-Hispanics (hazard ratio [HR]: 0.88, P < .001), Asian non-Hispanics (HR: 0.72, P < .001), and Hispanics (HR: 0.69, P < .001) had longer overall survival.

Conclusions

Differences in treatment and outcomes exist between races. Further studies are needed to elucidate the etiology of these race-related disparities and to improve outcomes for all patients.

GLIMPSE: a glioblastoma prognostication model using ensemble learning-a surveillance, epidemiology, and end results study

Purpose

Glioblastoma is one of the most common and aggressive brain tumors in the world with a poor prognosis. A glioblastoma prognostication model has the potential to improve the cancer's standard of care. No other paper has looked at using ensemble learning with a population database to predict multiple binary glioblastoma survival outcomes.

Methods

We utilized ensemble learning to design, build, and test a prognostication system for glioblastoma for short-, intermediate- and long-term survival, based on various clinical features. We used the population database SEER which covers 17 different registries. The most important prognostic features were identified and used as a clinical feature set. The statistical feature set was determined using Random Forests. The accuracy, sensitivity, specificity, area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were reported.

Results

Statistically-determined feature sets had the best performance. All the top models for short, intermediate, and long-term survival were random forests. With regards to short-term survival, top model had metrics AUROC = 0.937, accuracy = 86%, specificity = 88%, sensitivity = 85%, NPV = 85%, and PPV = 87%. For long-term survival, the top model had AUROC = 0.893, accuracy = 81%, specificity = 79%, sensitivity = 83%, NPV = 82%, and PPV = 79%. The top intermediate-term survival prediction had AUROC ≥ 0.780 and the other metrics were at least 70%.

Conclusions

Our ensemble models were high-performing and achieved AUROCs as high as 0.94, highlighting the importance of balancing, using ensemble techniques and statistical feature selection. Our models can potentially be used by clinicians after external validation.

PRL1 Promotes Glioblastoma Invasion and Tumorigenesis via Activating USP36-Mediated Snail2 Deubiquitination

Regenerating liver phosphatase 1 (PRL1) is an established oncogene in various cancers, although its biological function and the underlying mechanisms in glioblastoma multiforme (GBM) remain unclear. Here, we showed that PRL1 was significantly upregulated in glioma tissues and cell lines, and positively correlated with the tumor grade. Consistently, ectopic expression of PRL1 in glioma cell lines significantly enhanced their tumorigenicity and invasion both in vitro and in vivo by promoting epithelial-mesenchymal transition (EMT). Conversely, knocking down PRL1 blocked EMT in GBM cells, and inhibited their invasion, migration and tumorigenic growth. Additionally, PRL1 also stabilized Snail2 through its deubiquitination by activating USP36, thus revealing Snail2 as a crucial mediator of the oncogenic effects of PRL1 in GBM pathogenesis. Finally, PRL1 protein levels were positively correlated with that of Snail2 and predicted poor outcome of GBMs. Collectively, our data support that PRL1 promotes GBM progression by activating USP36-mediated Snail2 deubiquitination. This novel PRL1/USP36/Snail2 axis may be a promising therapeutic target for glioblastoma.

Identification of three glioblastoma subtypes and a six-gene prognostic risk index based on the expression of growth factors and cytokines

Glioblastoma multiforme (GBM) is the most common and invasive tumor of the central nervous system. Growth factors and cytokines (GFCKs) play a crucial role in tumor invasion. In the present study, GFCK expression profiles from GBM patients in the Chinese Glioma Genome Atlas were used to perform sample clustering with nonnegative matrix factorization. Three GBM subtypes were identified based on differences in GFCK expression, and the subtypes differed in characteristics and prognosis. A prognostic risk index (RI) comprising six GFCKs (BMP2, CCN3, GKN1, LIF, MDK, and SEMA3G) was defined using univariate Cox hazard analysis and multivariate stepwise Cox regression. The RI was validated in two independent data sets and may be independent of some known prognostic factors. Our results suggest that GBM occurs as different subtypes expressing different patterns of GFCKs and that these expression patterns can be captured in an RI that can predict prognosis.

Combating Glioblastoma by Codelivering the Small-Molecule Inhibitor of STAT3 and STAT3siRNA with α5β1 Integrin Receptor-Selective Liposomes

Glioblastoma multiforme (GBM) is one of the most aggressive tumors with a median survival of only 15 months. Effective therapeutics need to overcome the formidable challenge of crossing the blood-brain barrier (BBB). Receptors and transporters overexpressed on BCECs are being used for designing liposomes, polymers, polymeric micelles, peptides, and dendrimer-based drug carriers for combating brain tumors. Herein, using the orthotopic mouse glioblastoma model, we show that codelivering a small-molecule inhibitor of the JAK/STAT pathway (WP1066) and STAT3siRNA with nanometric (100-150 nm) α5β1 integrin receptor-selective liposomes of RGDK-lipopeptide holds therapeutic promise in combating glioblastoma. Rh-PE (red)-labeled liposomes of RGDK-lipopeptide were found to be internalized in GL261 cells via integrin α5β1 receptors. Intravenously administered near-infrared (NIR)-dye-labeled α5β1 integrin receptor-selective liposomes of RGDK-lipopeptide were found to be accumulated preferentially in the mouse brain tumor tissue. Importantly, we show that iv injection of WP1066 (a commercially sold small-molecule inhibitor of the JAK/STAT pathway) and STAT3siRNA cosolubilized within the liposomes of RGDK-lipopeptide leads to significant inhibition (>350% compared to the untreated mice group) of orthotopically growing mouse glioblastoma. The present strategy may find future use in combating GBM.

Involvement of Phosphatase and Tensin Homolog in Cyclin-Dependent Kinase 4/6 Inhibitor-Induced Blockade of Glioblastoma

Dysregulation of retinoblastoma (Rb) signaling pathway have been established as a requirement for glioblastoma (GBM) initiation and progression, which suggests that blockade of CDK4/6-Rb signaling axis for GBM treatment. Palbociclib, a selective inhibitor of the cyclin-dependent kinases CDK4/6, has been applied for breast cancer treatment. However, its efficacy against glioblastoma has not been well clarified. Here, effects of CDK4/6 inhibitors on various kinds of GBM cell lines are investigated and the functional mechanisms are identified. Data showed that cells with diverse PTEN status respond to palbociclib differently. Gain-of-function and loss-of-function studies indicated that PTEN enhanced the sensitivity of GBM cells to palbociclib in vitro and in vivo, which was associated with suppressions of Akt and ERK signaling and independent of Rb signaling inhibition. Hence, our findings support that palbociclib selectively