Type 2 Diabetes Mellitus and Glioblastoma Multiforme-Assessing Risk and Survival: Results of a Large Retrospective Study and Systematic Review of the Literature

Genetic association of type 2 diabetes mellitus and glycaemic factors with primary tumours of the central nervous system

Type 2 diabetes mellitus (T2DM) is a pivotal chronic disease with an increasing prevalence. Recent studies have found associations between T2DM and the development of central nervous system (CNS) tumours, a special class of solid tumours with an unclear pathogenesis. In this study, we aimed to explore the relationship between T2DM and certain glycaemic factors with common CNS tumours by using genetic data to conduct Mendelian randomization (MR) and co-localisation analysis. We found a causal relationship between T2DM and glioblastoma, fasting glucose and spinal cord tumours, glycated haemoglobin and spinal cord tumours, and insulin-like growth factor-1 and spinal cord tumours, pituitary tumours, and craniopharyngiomas. These results clarify the relationship between T2DM, glucose-related factors, and common CNS tumours, and they provide valuable insight into further clinical and basic research on CNS tumours, as well as new ideas for their diagnosis and treatment.

Structural and dynamical insights revealed the anti-glioblastoma potential of withanolides from Withania coagulans against vascular endothelial growth factor receptor (VEGFR)

CONTEXT

Glioblastoma (GBM), well known as grade 4 tumors due to its progressive malignant features such as vascular proliferation and necrosis, is the most aggressive form of primary brain tumor found in adults. Mutations and amplifications in the vascular endothelial growth factor receptor (VEGFR) contribute to almost 25% of GBM tumors. And thus, VEGFR has been declared the primary target in glioblastoma therapeutic strategies. However, many studies have been previously reported that include GBM as global therapeutics challenge, but they lack the molecular level insights that could help in understanding the biological function of a therapeutically important protein playing a major role in the disease and design the best strategies to develop the potential drugs.

METHODS

Therefore, to the best of our knowledge, the present study is the first time of kind, which involves multi-in silico approaches to predict the inhibition potential of withanolides from Withania coagulan against VEGFR. The study is actually based on determining the mode of action of five isolates: withanolide J, withaperuvin, 27-hydroxywithanolide I, coagule E, and coagule E, along with their respective binding energies. Molecular docking simulations revealed primarily four ligands, withanolide J (- 7.33 kJ/mol), 27-withanolide (- 7.01 kJ/mol), ajugine, withaperuvin (- 6.89 kJ/mol), and ajugine E (- 6.39 kJ/mol), to have significant binding potencies against the protein. Ligand binding was found to enhance the confirmational stability of the protein revealed through RMSD analysis, and RMSF assessment revealed the protein residues especially from 900-1000 surrounding the binding of the protein. Structural and dynamics of the protein via dynamics cross-correlation movement (DCCM) and principal component analysis (PCA) in both the unbound form and complexed with most potent ligand, withanolide J, reveal the ligand binding affecting the entire conformational integrity of the protein stabilized by hydrogen bonds and electrostatic attractions. Free energy of binding estimations by means of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) method further revealed the withanolide J to have maximum binding potency of the all ligands. Withanolide J in final was also found to have suitable molecular characterizations to cross the blood-brain barrier (BBB +) and reasonable human intestinal absorption ability determined by ADMET profiling via admetSAR tools.

Causal relationship between type 2 diabetes and glioblastoma: bidirectional Mendelian randomization analysis

As the prevalence of Type 2 Diabetes Mellitus (T2DM) and Glioblastoma (GBM) rises globally, the relationship between T2DM and GBM remains controversial. This study aims to investigate whether genetically predicted T2DM is causally associated with GBM. We performed bidirectional Mendelian randomization (MR) analysis using data from genome-wide studies on T2DM (N = 62,892) and GBM (N = 218,792) in European populations. The results of the inverse-variance weighted (IVW) approach served as the primary outcomes. We applied Cochran's Q test and MR-Egger regression for heterogeneity assessment. Leave-one-out analysis was used to evaluate whether any single SNP significantly influenced the observed effect. Our findings reveal a significant causal association between T2DM and an increased risk of GBM (OR [95% CI] 1.70 [1.09, 2.65], P = 0.019). Conversely, the reverse association between T2DM and GBM was insignificant (OR [95% CI] 1.00 [0.99, 1.01], P = 0.408) (P > 0.40). Furthermore, the results from Cochran's Q-test and funnel plots in the MR-Egger method indicated no evidence of pleiotropy between the SNPs and GBM. Additionally, we mapped causal SNPs to genes and identified 10 genes, including MACF1, C1orf185, PTGFRN, NOTCH2, ABCB10, GCKR, THADA, RBMS1, SPHKAP, and PPARG, located on chromosomes 1, 2, and 3. These genes are involved in key biological processes such as the BMP signaling pathway and various metabolic pathways relevant to both conditions. This study provides robust evidence of a significant causal relationship between T2DM and an increased risk of GBM. The identified SNP-mapped genes highlight potential biological mechanisms underlying this association.

The need for paradigm shift: prognostic significance and implications of standard therapy-related systemic immunosuppression in glioblastoma for immunotherapy and oncolytic virotherapy

Despite significant advances in our knowledge regarding the genetics and molecular biology of gliomas over the past two decades and hundreds of clinical trials, no effective therapeutic approach has been identified for adult patients with newly diagnosed glioblastoma, and overall survival remains dismal. Great hopes are now placed on combination immunotherapy. In clinical trials, immunotherapeutics are generally tested after standard therapy (radiation, temozolomide, and steroid dexamethasone) or concurrently with temozolomide and/or steroids. Only a minor subset of patients with progressive/recurrent glioblastoma have benefited from immunotherapies. In this review, we comprehensively discuss standard therapy-related systemic immunosuppression and lymphopenia, their prognostic significance, and the implications for immunotherapy/oncolytic virotherapy. The effectiveness of immunotherapy and oncolytic virotherapy (viro-immunotherapy) critically depends on the activity of the host immune cells. The absolute counts, ratios, and functional states of different circulating and tumor-infiltrating immune cell subsets determine the net immune fitness of patients with cancer and may have various effects on tumor progression, therapeutic response, and survival outcomes. Although different immunosuppressive mechanisms operate in patients with glioblastoma/gliomas at presentation, the immunological competence of patients may be significantly compromised by standard therapy, exacerbating tumor-related systemic immunosuppression. Standard therapy affects diverse immune cell subsets, including dendritic, CD4+, CD8+, natural killer (NK), NKT, macrophage, neutrophil, and myeloid-derived suppressor cell (MDSC). Systemic immunosuppression and lymphopenia limit the immune system's ability to target glioblastoma. Changes in the standard therapy are required to increase the success of immunotherapies. Steroid use, high neutrophil-to-lymphocyte ratio (NLR), and low post-treatment total lymphocyte count (TLC) are significant prognostic factors for shorter survival in patients with glioblastoma in retrospective studies; however, these clinically relevant variables are rarely reported and correlated with response and survival in immunotherapy studies (e.g., immune checkpoint inhibitors, vaccines, and oncolytic viruses). Our analysis should help in the development of a more rational clinical trial design and decision-making regarding the treatment to potentially improve the efficacy of immunotherapy or oncolytic virotherapy.

Metabolic Syndrome and Survival in Glioblastoma Patients: Retrospective Cohort Study and Review of the Literature

Background Several studies point to metabolic syndrome as a risk factor for the development and progression of several types of cancer. Its association with glioblastoma has yet to be determined, and only two studies investigate the impact of metabolic syndrome on the survival of glioblastoma patients, indicating a trend toward decreased survival in patients with metabolic syndrome. The aim of this study was to determine whether patients with glioblastoma and metabolic syndrome had a worse clinical outcome. Methods We retrospectively reviewed the clinical records of 180 patients diagnosed with glioblastoma. Metabolic syndrome was defined according to the American Heart Association, as the presence of at least three of the following criteria: diabetes, hypertension, hyperlipidemia, and obesity. We analyzed the overall survival and progression-free survival of patients with and without metabolic syndrome. Results Of 180 patients, 20 (11.1%) met the diagnostic criteria for metabolic syndrome. The overall survival of patients with metabolic syndrome was 19.8 months, and without metabolic syndrome was 17.7 months (p-value=0.085). The progression-free survival of patients with metabolic syndrome was 9.9 months, and without metabolic syndrome was 7.9 months (p-value=0.076). Conclusion Our results showed no prognostic relevance of metabolic syndrome in patients with glioblastoma, although there was a trend towards increased overall survival and progression-free survival in patients with metabolic syndrome.

Associations between adiposity, diabetes, lifestyle factors and the risk of gliomas

Background

Despite numerous observational studies linking adiposity, diabetes, and lifestyle factors with gliomas, the causal associations between them remain uncertain.

Methods

This study aimed to use two-sample Mendelian randomization (MR) analysis to investigate whether these associations are causal. Specifically, independent genetic variants in body mass index (BMI), waist circumference (WC), type 2 diabetes (T2D), smoking, alcohol, and coffee consumption were extracted from the published genome-wide association studies (GWASs) with genome-wide significance. The corresponding summary-level data for gliomas were available from a GWAS of 1,856 cases and 4,955 controls of European descent from the GliomaScan consortium. Additionally, glioma pathogenesis-related protein 1 data were used for validation, and Radial MR analysis was conducted to examine the potential outlier single-nucleotide polymorphisms (SNPs).

Results

One standard deviation (SD) increase in BMI had an odds ratio (OR) of 1.392 (95% confidence interval (CI), 0.935-2.071) for gliomas, while one SD increase in WC had an OR of 0.967 (95% CI, 0.547-1.710). For T2D, a one-unit increase in log-transformed OR had an OR of 0.923 (95% CI, 0.754-1.129). The prevalence of smoking initiation had an OR of 1.703 (95% CI, 0.871-3.326) for gliomas, while the prevalence of alcohol intake frequency had an OR of 0.806 (95% CI, 0.361-1.083), and the prevalence of coffee intake had an OR of 0.268 (95% CI, 0.033-2.140) for gliomas.

Conclusion

This study provides evidence that adiposity, T2D, smoking, alcohol drinking, and coffee intake do not play causal roles in the development of gliomas. The findings highlight the importance of reconsidering causal relationships in epidemiological research to better understand the risk factors and prevention strategies for gliomas.

Modifiable risk factors for glioblastoma: a systematic review and meta-analysis

Glioblastoma (GBM) is the most common and aggressive glioma histological subtype, associated with high disability and poor survival. The etiology of this condition is still mostly unknown, and evidence about risk factors is elusive. The aim of this study is to identify modifiable risk factors for GBM. Electronic search was performed by two reviewers independently using the keywords and MeSH terms 'glioblastoma' OR 'glioma' OR 'brain tumor' AND 'risk factor'. The inclusion criteria were (1) observational studies or experimental studies on humans, (2) studies assessing the association between glioblastoma and exposure to modifiable conditions, and (3) studies published in English or Portuguese. Studies on the pediatric population or about exposure to ionizing radiation were excluded. A total of 12 studies were included. Seven were case-control studies, and five were cohort studies. The risk factors assessed included body mass index, alcohol consumption, exposure to magnetic fields, diabetes mellitus type 2 (DM2), and use of non-steroidal anti-inflammatory drugs (NSAID). No significant link was found between GBM incidence and DM2 or magnetic field exposure. On the other hand, higher BMI, alcohol consumption, and NSAID use demonstrated a protective effect on GMB risk. However, given the limited number of studies, it is not possible to obtain a behavioral recommendation; instead, these findings are relevant to guide future basic scientific studies on GBM oncogenesis.

Significant Systemic Insulin Resistance is Associated With Unique Glioblastoma Multiforme Phenotype

Background

Some glioblastoma multiforme (GBM) are characterized by the presence of gemistocytes (GCs), a unique phenotype of reactive astrocytes. Certain GCs can be identified as neoplastic cells but these cells were also found to be associated with diabetes in non-neoplastic lesions of the central nervous system. Our aim was to find a correlation between insulin - resistance metabolic features and the presence of GCs in patients with newly diagnosed GBM.

Methods

Medical records from histologically confirmed GBM patients were retrospectively extracted for different systemic metabolic variables. A statistic-based comparison was made between GBM, diabetic patients with and without GC. Patients with poorly controlled diabetes (ie, hemoglobin A1C ⩾ 8.0) were also compared between the 2 groups.

Results

A total of 220 newly diagnosed GBM patients were included in our study. 58 (26.3%) patients had a history of diabetes mellitus type 2 (DM2) at the time of admission. The rate of poorly-controlled DM2 was nearly as twice in the GC-GBM group than in the non-GC GBM group (18.75% vs 9.5%; P = .130). In the DM2 cohort, the subgroup of GC-GBM was significantly associated with demographic and metabolic features related to insulin resistance such as male gender predominance (89% vs 50%, P = .073) and morbid obesity (weight ⩾85 kg: OR 6.16; P = .0019 and mean BMI: 34.1 ± 11.42 vs 28.7 ± 5.44; P = .034 for group with and without GCs, respectively). In the poorly-controlled DM2 group, none of the GC-GBM patients were using insulin prior to diagnosis, compared to 61.1% in the non-GC GBM patients (OR = 0.04, P = .045).

Conclusion

Systemic metabolic factors related to marked insulin resistance (DM2, morbid obesity, male gender) are associated with a unique histologic phenotype of GBM, characterized by the presence of GCs. This feature is prominent in poorly-controlled DM2 GBM patients who are not using synthetic insulin. This novel finding may add to the growing data on the relevance of glucose metabolism in astrocytes and in astrocytes associated with high-grade gliomas. In GBM patients, a correlation between patients' metabolic status, tumor's histologic phenotype, tumor's molecular changes, use of anti-diabetic drugs and the respective impact of these factor on survival warrants further investigation.

Downregulated CLIP3 induces radioresistance by enhancing stemness and glycolytic flux in glioblastoma

Background

Glioblastoma Multiforme (GBM) is a malignant primary brain tumor in which the standard treatment, ionizing radiation (IR), achieves a median survival of about 15 months. GBM harbors glioblastoma stem-like cells (GSCs), which play a crucial role in therapeutic resistance and recurrence.

Methods

Patient-derived GSCs, GBM cell lines, intracranial GBM xenografts, and GBM sections were used to measure mRNA and protein expression and determine the related molecular mechanisms by qRT-PCR, immunoblot, immunoprecipitation, immunofluorescence, OCR, ECAR, live-cell imaging, and immunohistochemistry. Orthotopic GBM xenograft models were applied to investigate tumor inhibitory effects of glimepiride combined with radiotherapy.

Results

We report that GSCs that survive standard treatment radiation upregulate Speedy/RINGO cell cycle regulator family member A (Spy1) and downregulate CAP-Gly domain containing linker protein 3 (CLIP3, also known as CLIPR-59). We discovered that Spy1 activation and CLIP3 inhibition coordinately shift GBM cell glucose metabolism to favor glycolysis via two cellular processes: transcriptional regulation of CLIP3 and facilitating Glucose transporter 3 (GLUT3) trafficking to cellular membranes in GBM cells. Importantly, in combination with IR, glimepiride, an FDA-approved medication used to treat type 2 diabetes mellitus, disrupts GSCs maintenance and suppresses glycolytic activity by restoring CLIP3 function. In addition, combining radiotherapy and glimepiride significantly reduced GBM growth and improved survival in a GBM orthotopic xenograft mouse model.

Conclusions

Our data suggest that radioresistant GBM cells exhibit enhanced stemness and glycolytic activity mediated by the Spy1-CLIP3 axis. Thus, glimepiride could be an attractive strategy for overcoming radioresistance and recurrence by rescuing CLIP3 expression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02077-4.

A Root in Synapsis and the Other One in the Gut Microbiome-Brain Axis: Are the Two Poles of Ketogenic Diet Enough to Challenge Glioblastoma?

Glioblastoma is the most frequent and aggressive brain cancer in adults. While precision medicine in oncology has produced remarkable progress in several malignancies, treatment of glioblastoma has still limited available options and a dismal prognosis. After first-line treatment with surgery followed by radiochemotherapy based on the 2005 STUPP trial, no significant therapeutic advancements have been registered. While waiting that genomic characterization moves from a prognostic/predictive value into therapeutic applications, practical and easy-to-use approaches are eagerly awaited. Medical reports on the role of the ketogenic diet in adult neurological disorders and in glioblastoma suggest that nutritional interventions may condition outcomes and be associated with standard therapies. The acceptable macronutrient distribution of daily calories in a regular diet are 45-65% of daily calories from carbohydrates, 20-35% from fats, and 10-35% from protein. Basically, the ketogenic diet follows an approach based on low carbohydrates/high fat intake. In carbohydrates starvation, body energy derives from fat storage which is used to produce ketones and act as glucose surrogates. The ketogenic diet has several effects: metabolic interference with glucose and insulin and IGF-1 pathways, influence on neurotransmission, reduction of oxidative stress and inflammation, direct effect on gene expression through epigenetic mechanisms. Apart from these central effects working at the synapsis level, recent evidence also suggests a role for microbiome and gut-brain axis induced by a ketogenic diet. This review focuses on rationales supporting the ketogenic diet and clinical studies will be reported, looking at future possible perspectives.

Sex-Specific Differences in Glioblastoma

Sex differences have been well identified in many brain tumors. Even though glioblastoma (GBM) is the most common primary malignant brain tumor in adults and has the worst outcome, well-established differences between men and women are limited to incidence and outcome. Little is known about sex differences in GBM at the disease phenotype and genetical/molecular level. This review focuses on a deep understanding of the pathophysiology of GBM, including hormones, metabolic pathways, the immune system, and molecular changes, along with differences between men and women and how these dimorphisms affect disease outcome. The information analyzed in this review shows a greater incidence and worse outcome in male patients with GBM compared with female patients. We highlight the protective role of estrogen and the upregulation of androgen receptors and testosterone having detrimental effects on GBM. Moreover, hormones and the immune system work in synergy to directly affect the GBM microenvironment. Genetic and molecular differences have also recently been identified. Specific genes and molecular pathways, either upregulated or downregulated depending on sex, could potentially directly dictate GBM outcome differences. It appears that sexual dimorphism in GBM affects patient outcome and requires an individualized approach to management considering the sex of the patient, especially in relation to differences at the molecular level.

Transcriptome Analysis of Subcutaneous Adipose Tissue from Severely Obese Patients Highlights Deregulation Profiles in Coding and Non-Coding Oncogenes

Obesity is a major risk factor for a large number of secondary diseases, including cancer. Specific insights into the role of gender differences and secondary comorbidities, such as type 2 diabetes (T2D) and cancer risk, are yet to be fully identified. The aim of this study is thus to find a correlation between the transcriptional deregulation present in the subcutaneous adipose tissue of obese patients and the oncogenic signature present in multiple cancers, in the presence of T2D, and considering gender differences. The subcutaneous adipose tissue (SAT) of five healthy, normal-weight women, five obese women, five obese women with T2D and five obese men were subjected to RNA-sequencing, leading to the identification of deregulated coding and non-coding RNAs, classified for their oncogenic score. A panel of DE RNAs was validated via Real-Time PCR and oncogene expression levels correlated the oncogenes with anthropometrical parameters, highlighting significant trends. For each analyzed condition, we identified the deregulated pathways associated with cancer, the prediction of possible prognosis for different cancer types and the lncRNAs involved in oncogenic networks and tissues. Our results provided a comprehensive characterization of oncogenesis correlation in SAT, providing specific insights into the possible molecular targets implicated in this process. Indeed, the identification of deregulated oncogenes also in SAT highlights hypothetical targets implicated in the increased oncogenic risk in highly obese subjects. These results could shed light on new molecular targets to be specifically modulated in obesity and highlight which cancers should receive the most attention in terms of better prevention in obesity-affected 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.

Ketogenic Diet for Malignant Gliomas: a Review

PURPOSE OF REVIEW

In this review, we examine the postulated mechanisms of therapeutic effect of ketogenic diets in the treatment of gliomas, review the completed clinical trials, and discuss further directions in this field.

RECENT FINDINGS

Cancers including gliomas are characterized by derangements in cellular metabolism. In vitro and animal studies have revealed that dietary interventions to reduce glucose and glycolytic pathways in gliomas may have a therapeutic effect. Early trials in patients with malignant gliomas have shown feasibility, but are not robust enough yet to demonstrate clinical applicability. Therapies for malignant gliomas of the brain are increasingly using a multi-targeted approach. The use of ketogenic diets and its variants may offer a unique and promising anti-glioma treatment by exploiting metabolic alterations seen in cancers including gliomas seen at the cellular level, which may work in concert with other therapies.

Clinical Risk and Overall Survival in Patients with Diabetes Mellitus, Hyperglycemia and Glioblastoma Multiforme. A Review of the Current Literature

The relationship between type 2 diabetes mellitus (DM2) and hyperglycemia with cancer patients remains controversial also in the setting of patients with glioblastoma multiforme (GBM), the most common and aggressive form of astrocytoma with a short overall survival (OS) and poor prognosis. A systematic search of two databases was performed for studies published up to 19 August 2020, reporting the OS of patients with DM2 or high blood sugar level and GBM and the clinical risk of diabetic patients for development of GBM. According to PRISMA guidelines, we included a total of 20 papers reporting clinical data of patients with GBM and diabetes and/or hyperglycemia. The aim of this review was to investigate the effect of DM2, hyperglycemia and metformin on OS of patients with GBM. In addition, we evaluated the effect of these factors on the risk of development of GBM. This review supports accumulating evidence that hyperglycemia, rather than DM2, and elevated BMI are independent risk factors for poor outcome and shorter OS in patients with GBM. GBM patients with normal weight compared to obese, and diabetic patients on metformin compared to other therapies, seems to have a longer OS. Further studies are needed to understand better these associations.

Association of metabolic syndrome with glioblastoma: a retrospective cohort study and review

Background

Metabolic syndrome is identified as a risk factor for the development of several systemic cancers, but its frequency among patients with glioblastoma and its association with clinical outcomes have yet to be determined. The aim of this study was to investigate metabolic syndrome as a risk factor for and affecting survival in glioblastoma patients.

Methods

A retrospective cohort study, consisting of patients with diagnoses at a single institution between 2007 and 2013, was conducted. Clinical records were reviewed, and clinical and laboratory data pertaining to 5 metabolic criteria were extrapolated. Overall survival was determined by time from initial surgical diagnosis to date of death or last follow-up.

Results

The frequency of metabolic syndrome among patients diagnosed with glioblastoma was slightly greater than the frequency of metabolic syndrome among the general population. Within a subset of patients (n = 91) receiving the full schedule of concurrent radiation and temozolomide and adjuvant temozolomide, median overall survival was significantly shorter for patients with metabolic syndrome compared with those without. In addition, the presence of all 5 elements of the metabolic syndrome resulted in significantly decreased median survival in these patients.

Conclusions

We identified the metabolic syndrome at a slightly higher frequency in patients with diagnosed glioblastoma compared with the general population. In addition, metabolic syndrome with each of its individual components is associated with an overall worse prognosis in patients receiving the standard schedule of radiation and temozolomide after adjustment for age.

Hemoglobin A1c in Patients with Glioblastoma-A Preliminary Study

BACKGROUND

Glioblastomas are among the most common primary brain tumors with an abysmal prognosis. The significance of glucose metabolism in glioblastoma cell metabolism and proliferation is well-known. However, a significant correlation between the systemic metabolic status of the patient and the cellular proliferation of the glioblastoma has not yet been established.

METHODS

Our aim was to observe and analyze for a possible correlation between glioblastoma cellular proliferation and patients' glycated hemoglobin (HbA1c) levels as a marker of chronic systemic glycemia. We analyzed the data from 25 patients and compared their Ki-67 values with their preoperative HbA1c values.

RESULTS

We observed a statistically significant correlation (P < 0.03) between chronic glycemia (measured using HbA1c) and the cellular proliferation of glioblastoma (measured by cellular Ki-67 expression).

CONCLUSIONS

These results imply a possible positive correlation between glioblastoma cell proliferation and chronic systemic glycemia, a correlation that, to the best of our knowledge, has not yet been reported. Further research in this area could not only lead to a better understanding of glioblastoma but also have significant clinical applications in treating this devastating disease.

Comorbid Medical Conditions as Predictors of Overall Survival in Glioblastoma Patients

Glioblastoma (GBM) is an aggressive central nervous system tumor with a poor prognosis. This study was conducted to determine any comorbid medical conditions that are associated with survival in GBM. Data were collected from medical records of all patients who presented to VCU Medical Center with GBM between January 2005 and February 2015. Patients who underwent surgery/biopsy were considered for inclusion. Cox proportional hazards regression modeling was performed to assess the relationship between survival and sex, race, and comorbid medical conditions. 163 patients met inclusion criteria. Comorbidities associated with survival on individual-characteristic analysis included: history of asthma (Hazard Ratio [HR]: 2.63; 95% Confidence Interval [CI]: 1.24–5.58; p = 0.01), hypercholesterolemia (HR: 1.95; 95% CI: 1.09–3.50; p = 0.02), and incontinence (HR: 2.29; 95% CI: 0.95–5.57; p = 0.07). History of asthma (HR: 2.22; 95% CI: 1.02–4.83; p = 0.04) and hypercholesterolemia (HR: 1.99; 95% CI: 1.11–3.56; p = 0.02) were associated with shorter survival on multivariable analysis. Surgical patients with GBM who had a prior history of asthma or hypercholesterolemia had significantly higher relative risk for mortality on individual-characteristic and multivariable analyses.

The effect of diabetes mellitus on in-hospital hyperglycemia, length of stay and survival in patients with brain tumor receiving dexamethasone: A descriptive and comparative analysis

OBJECTIVES

To perform a comparative analysis on the impact of Type 2 Diabetes Mellitus (DM) on in-hospital hyperglycemia, length of stay (LOS) and survival of patients suffering from brain tumor who receive dexamethasone.

PATIENTS AND METHODS

Patients with brain tumor hospitalized in a Neurosurgery department between 2011 and 2018, were studied. Data referring to medical history, clinical characteristics and in-hospital survival was collected and analyzed. Morning plasma glucose levels (PGL) were obtained for seven consecutive days after the start of dexamethasone.

RESULTS

Fifty-six patients were identified. Of them, 21 (37.5%) were diabetic. During dexamethasone administration, a difference in morning PGL values during different days was noted (p = 0.003). No difference in glucose levels among different glucocorticoid doses was seen. DM was associated with higher average PGL (aMPGL), calculated as the mean of morning PGL values for the last six days (p = 0.001) and with higher rates of persistent hyperglycemia (p = 0.002). The change of aMPGL from the morning PGL value of day one did not differ between the two cohorts (p = 0.729). DM neither affected LOS nor in-hospital survival (p = 0.745 & p = 0.438, respectively).

CONCLUSION

Although morning glucose values were higher in diabetic, compared to non-diabetic patients, their change from day one was similar between the two cohorts. LOS and in-hospital survival were not affected by DM.

Positive correlation between blood glucose and radiotherapy doses to the central gustatory system in Glioblastoma Multiforme patients

BACKGROUND

The aim of this study was to assess the correlations between the levels of blood glucose (BG) and the dose of radiation therapy (RT) to the central gustatory system (GS) in glioblastoma multiforme (GBM) patients.

METHODS

Thirty-seven GBM patients with regular blood glucose measurements were investigated retrospectively. 59.5% were female and 40.5% male with a median age of 64.3 years (range 27.4-85.6). Diabetes mellitus type 2 (DM2) history, BG levels and dexamethasone (DEXA) medication were assessed. The analyzed central gustatory structures were: solitary tract and nucleus, ventral posteromedial nucleus of the thalamus, sensory tongue area of the postcentral gyrus, anterior part of the insula, frontal operculum, amygdala, hypothalamus. These structures were delineated on magnetic resonance tomographies (MRIs) registered to planning-CTs. All GS doses were transformed in equivalent doses in 2 Gy fraction (EQD2).

RESULTS

Twenty one patients (56.8%) had at least one BG values over 200 mg/dl during RT. There was a difference between average BG in DM2: 192.8 mg/dl (±24.4) and non-DM2 patients: 145.7 mg/dl (±39.5; p = 0.01) but no significant difference in daily DEXA medication - DM2 patients: 7.9 mg/d (±1.9) vs. non-DM2: 9.3 mg/dl (±5.7; p = 0.29). The EQD2 Dmean to the total GS was 36.0Gy (±8.6 Gy). There was a tendency for a higher increase in maximum BG values with more radiation dose to the total GS (b = 1.9, R2 = 0.103, p = 0.06).

CONCLUSION

BG levels in GBM patients are in direct correlation to the dose of RT applied to the central GS. GBM patients that undergo RT should thus be closely monitored for changes in BG levels during and after the radiation.

Does diabetes decrease the risk of glioma? A systematic review and meta-analysis of observational studies

PURPOSE

Increasing epidemiologic evidence suggests that diabetes mellitus (DM) may be associated with a decreased risk of glioma. This systematic review assessed whether DM was associated with glioma risk.

METHODS

Electronic searches were performed in PubMed, Web of Science, EMBASE, and Cochrane Library databases up to August 30, 2018. A random-effects model was performed to calculate summary effect size with corresponding 95% confidence intervals (CIs).

RESULTS

In total, 10 studies (eight case-control studies and two cohort studies) matched the inclusion criteria. Meta-analyses of case-control studies showed that DM decreased the risk of glioma by 23% (odds ratio: 0.77, 95% CI: 0.61-0.96; P = .02, I2 = 82.0%). However, no such effect was observed in cohort studies (relative risk: 0.71, 95% CI: 0.10-4.80; P = .72, I2 = 61.6%). In the subgroup analyses, DM was associated with a decreased risk of glioma in Caucasians but not in Asians; the inverse association was slightly higher in males than in females.

CONCLUSIONS

Our results indicate that DM decreases the risk of glioma, but the inverse association may vary in subgroups. The present conclusions should be confirmed with further studies.

Tanshinone IIA improves diabetes mellitus via the NF-κB-induced AMPK signal pathway

Diabetes mellitus (DM) is a systemic metabolic disease. Tanshinone IIA (Tan-IIA) presents potential benefits for DM. The purpose of this study was to investigate the efficacy of Tan-IIA in type 2 DM rats and explore its potential mechanism in renal cells. A type 2 DM rat model was established and administered with Tan-IIA or PBS. It was demonstrated that Tan-IIA treatment significantly reduced levels of total cholesterol, non-esterified fatty acids, total triglyceride and low-density lipoprotein cholesterol in experimental DM rats compared with the control group. The results indicated that Tan-IIA treatment significantly decreased levels of interleukin (IL)-8, tumor necrosis factor-α, C-reactive protein and IL-6. It was identified that Tan-IIA treatment significantly decreased nuclear factor-κB levels and significantly elevated 5' adenosine monophosphate-activated protein kinase levels. Western blot analysis indicated that Tan-IIA elevated immunocyte precipitation in renal cells. Furthermore, Tan-IIA treatment improved lipid metabolism, glucose metabolism, insulin resistance and body weight of type 2 DM rats. In conclusion, Tan-IIA administration may inhibit inflammatory cytokines and alleviate type 2 DM symptoms in experimental rats.