A prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches.

Background: Interactions among tumor, immune, and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Methods: Here, through computational genomics and proteomics approaches, we analyzed the functional and clinical relevance of CMP expression in GBM at bulk, single cell, and spatial anatomical resolution. Results: We identified genes encoding CMPs whose expression levels categorize GBM tumors into CMP expression-high (M-H) and CMP expression-low (M-L) groups. CMP enrichment is associated with worse patient survival, specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells, and immune checkpoint gene expression. Anatomical and single-cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative niches that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene CMP expression signature, termed Matrisome 17 (M17) signature that further refines the prognostic value of CMP genes. The M17 signature is a significantly stronger prognostic factor compared to MGMT promoter methylation status as well as canonical subtypes, and importantly, potentially predicts responses to PD1 blockade. Conclusion: The matrisome gene expression signature provides a robust stratification of GBM patients by survival and potential biomarkers of functionally relevant GBM niches that can mediate mesenchymal-immune cross talk. Patient stratification based on matrisome profiles can contribute to selection and optimization of treatment strategies.

Cost-effectiveness analysis of bevacizumab combined with lomustine in the treatment of progressive glioblastoma using a Markov model simulation analysis.

Background: Progressive glioblastoma (GBM) is a malignancy with extremely poor prognosis. Chemotherapy is one of the approved systemic treatment modalities. The aim of this study is to assess the cost-effectiveness of using bevacizumab (BEV) in combination with lomustine (LOM) regimen for the treatment of progressive glioblastoma in China. Methods: The estimation results are derived from a multicenter randomized phase III trial, which demonstrated improved survival in GBM patients receiving BEV+LOM combination therapy. To calculate the incremental cost-effectiveness ratio (ICER) from the perspective of Chinese society, a Markov model was established. Univariate deterministic analysis and probabilistic sensitivity analysis were employed to address the uncertainties within the model. Results: Compared to LOM monotherapy, the total treatment cost for BEV+LOM combination therapy increased from $2,646.70 to $23,650.98. The health-adjusted life years (QALYs) for BEV+LOM combination therapy increased from 0.26 QALYs to 0.51 QALYs, representing an increment of 0.25 QALYs. The incremental cost-effectiveness ratio (ICER) was $84,071.12. The cost-effectiveness curve indicates that within the willingness-to-pay (WTP) range of $35,906 per QALY, BEV+LOM combination therapy is not a cost-effective treatment option for unresectable malignant pleural mesothelioma patients. Conclusions: Taken as a whole, the findings of this study suggest that, from the perspective of payers in China, BEV+LOM combination therapy as a first-line treatment for GBM is not a cost-effective option. However, considering the survival advantages this regimen may offer for this rare disease, it may still be one of the clinical treatment options for this patient population.

Characterizing the relationship between MRI radiomics and AHR expression and deriving a predictive model for prognostic assessment in glioblastoma.

PURPOSE: Aryl hydrocarbon receptor (AHR), a crucial molecular marker associated with glioma, is a potential therapeutic target. We aimed to establish a non-invasive predictive model for AHR through radiomics. METHODS: Contrast-enhanced T1-weighted (T1W) MRI and the corresponding and clinical variables of glioblastoma patients from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) were obtained for analysis. KM curves and Cox regression analyses were used to assess the prognostic value of AHR expression. The radiomics features were screened by Max-Relevance and Min-Redundancy (mRMR) and recursive feature elimination (RFE), followed by the construction of two predictive models using logistic regression (LR) and a support vector machine (SVM). RESULTS: The expression levels of AHR in tumour patients were significantly higher than those in the control group, and higher AHR expression was associated with worse prognosis (P<0.05). AHR remained a risk factor for poor prognosis in glioblastoma after multivariate adjustment (HR: 1.61, 95% CI: 1.085-2.39, P<0.05). The radiomics models constructed using LR and SVM based on three selected features achieved area under the curve (AUC) values of 0.887 and 0.872, respectively. Radiomics score emerged as a key factor influencing overall survival (OS) after multivariate adjustment in the Cox model (HR: 3.931, 95% CI: 1.272-12.148, P < 0.05). CONCLUSION: The radiomics models could effectively distinguish the expression levels of AHR and predict prognosis in patients with glioblastoma, which may serve as a powerful tool to assist clinical assessment and precision treatment.

Assessment of silver nanoparticles' antitumor effects: Insights into cell number, viability, and morphology of glioblastoma and prostate cancer cells.

Silver nanoparticles (AgNPs) hold promise for cancer therapy. This study aimed to evaluate their impact on tumor and non-tumor cell number, viability, and morphology. Antitumor activity was tested on U-87MG (glioblastoma) and DU-145 (prostate cancer) cell lines. Treatment with AgNPs notably reached a reduction of U-87MG and DU-145 cell growth by 89.30% and 79.74%, respectively, resulting in slower growth rates. AgNPs induced DNA damage, evidenced by reduced nuclear area and DNA content via fluorescent image-based analyses. Conversely, HFF-1 non-tumor cells displayed no significant changes post-AgNPs exposure. Viability assays revealed substantial reductions in U-87MG and DU-145 cells (79% and 63% in MTT assays, 30% and 52.2% in high-content analyses), while HFF-1 cells exhibited lower sensitivity. Tumor cells had notably lower IC50 values than non-tumor cells, indicating selective susceptibility. Transmission electron microscopy (TEM) showed morphological changes post-AgNPs administration, including increased vacuoles, myelin figures, membrane ghosts, cellular extravasation, and membrane projections. The findings suggest the potential of AgNPs against glioblastoma and prostate cancer, necessitating further exploration across other cancer cell lines.

Application of Delta T1 maps for quantitative and objective assessment of extent of resection and survival prediction in glioblastoma.

Background and Objectives: Gross-total resection (GTR) and low residual tumor volume (RTV) have been associated with increased survival in glioblastoma. Largely due to the subjectivity involved, the determination of GTR and RTV remains difficult in the postoperative setting. In response, the objective of this study is to evaluate the clinical efficacy of an easy-to-use MRI metric, called delta T1 (dT1), to quantify extent of resection (EOR) and RTV, in comparison to radiologist impression, to predict overall survival (OS) in glioblastoma patients. Methods: 59 patients who underwent resection of glioblastoma were retrospectively identified. Delta T1 (dT1) images, automatically created from the difference between calibrated post- and pre-contrast T1-weighted images, were used to quantify EOR and RTV. Kaplan-Meier survival estimates were determined for EOR categories, an RTV cutoff of 5cm3 and radiologist interpretation of EOR. Multivariate Cox proportional hazard regression analysis was used to evaluate RTV and EOR along with effects related to sex, KPS, MGMT, and age on OS. Results: Kaplan-Meier analysis revealed a statistically significant difference in median OS for a dT1-determined RTV cutoff of 5 cm3 (P=.0024, HR=2.18 (1.232-3.856)), but not for radiological impression (P=0.666) or dT1-determined EOR (P=0.0803), which was limited to a comparison between partial and subtotal resections. Furthermore, when covariates were accounted for in multivariate Cox regression, significant differences in OS were retained for dT1-determined RTV. Additionally, a significantly strong yet short-term effect of MGMT methylation status on OS was revealed for each RTV and EOR model. Conclusion: The utility of dT1 maps to quantify EOR and RTV in glioblastoma and predict survival, suggests an emerging role for dT1s with relevance for intraoperative MRI, neuro-navigation and postoperative disease surveillance.

Hypofractionated radiotherapy for glioblastoma: A large institutional retrospective assessment of 2 approaches.

Background: Glioblastoma (GBM) poses therapeutic challenges due to its aggressive nature, particularly for patients with poor functional status and/or advanced disease. Hypofractionated radiotherapy (RT) regimens have demonstrated comparable disease outcomes for this population while allowing treatment to be completed more quickly. Here, we report our institutional outcomes of patients treated with 2 hypofractionated RT regimens: 40 Gy/15fx (3w-RT) and 50 Gy/20fx (4w-RT). Methods: A single-institution retrospective analysis was conducted of 127 GBM patients who underwent 3w-RT or 4w-RT. Patient characteristics, treatment regimens, and outcomes were analyzed. Univariate and multivariable Cox regression models were used to estimate progression-free survival (PFS) and overall survival (OS). The impact of chemotherapy and RT schedule was explored through subgroup analyses. Results: Median OS for the entire cohort was 7.7 months. There were no significant differences in PFS or OS between 3w-RT and 4w-RT groups overall. Receipt and timing of temozolomide (TMZ) emerged as the variable most strongly associated with survival, with patients receiving adjuvant-only or concurrent and adjuvant TMZ having significantly improved PFS and OS (P < .001). In a subgroup analysis of patients that did not receive TMZ, patients in the 4w-RT group demonstrated a trend toward improved OS as compared to the 3w-RT group (P = .12). Conclusions: This study demonstrates comparable survival outcomes between 3w-RT and 4w-RT regimens in GBM patients. Receipt and timing of TMZ were strongly associated with survival outcomes. The potential benefit of dose-escalated hypofractionation for patients not receiving chemotherapy warrants further investigation and emphasizes the importance of personalized treatment approaches.

Image-based assessment of natural killer cell activity against glioblastoma stem cells.

Glioblastoma (GBM) poses a significant challenge in oncology and stands as the most aggressive form of brain cancer. A primary contributor to its relentless nature is the stem-like cancer cells, called glioblastoma stem cells (GSCs). GSCs have the capacity for self-renewal and tumorigenesis, leading to frequent GBM recurrences and complicating treatment modalities. While natural killer (NK) cells exhibit potential in targeting and eliminating stem-like cancer cells, their efficacy within the GBM microenvironment is limited due to constrained infiltration and function. To address this limitation, novel investigations focusing on boosting NK cell activity against GSCs are imperative. This study presents two streamlined image-based assays assessing NK cell migration and cytotoxicity towards GSCs. It details protocols and explores the strengths and limitations of these methods. These assays could aid in identifying novel targets to enhance NK cell activity towards GSCs, facilitating the development of NK cell-based immunotherapy for improved GBM treatment.

Quantitative Assessment of Tumor Contact with Neurogenic Zones and Its Effects on Survival: Insights beyond Traditional Predictors.

So far, the cellular origin of glioblastoma (GBM) needs to be determined, with prevalent theories suggesting emergence from transformed endogenous stem cells. Adult neurogenesis primarily occurs in two brain regions: the subventricular zone (SVZ) and the subgranular zone (SGZ) of the hippocampal dentate gyrus. Whether the proximity of GBM to these neurogenic niches affects patient outcome remains uncertain. Previous studies often rely on subjective assessments, limiting the reliability of those results. In this study, we assessed the impact of GBM's relationship with the cortex, SVZ and SGZ on clinical variables using fully automated segmentation methods. In 177 glioblastoma patients, we calculated optimal cutpoints of minimal distances to the SVZ and SGZ to distinguish poor from favorable survival. The impact of tumor contact with neurogenic zones on clinical parameters, such as overall survival, multifocality, MGMT promotor methylation, Ki-67 and KPS score was also examined by multivariable regression analysis, chi-square test and Mann-Whitney-U. The analysis confirmed shorter survival in tumors contacting the SVZ with an optimal cutpoint of 14 mm distance to the SVZ, separating poor from more favorable survival. In contrast, tumor contact with the SGZ did not negatively affect survival. We did not find significant correlations with multifocality or MGMT promotor methylation in tumors contacting the SVZ, as previous studies discussed. These findings suggest that the spatial relationship between GBM and neurogenic niches needs to be assessed differently. Objective measurements disprove prior assumptions, warranting further research on this topic.

Response assessment of GBM during immunotherapy by delayed contrast treatment response assessment maps.

Introduction: Assessing the treatment response of glioblastoma multiforme during immunotherapy (IT) is an open issue. Treatment response assessment maps (TRAMs) might help distinguish true tumor progression (TTP) and pseudoprogression (PsP) in this setting. Methods: We recruited 16 naïve glioblastoma patients enrolled in a phase II trial consisting of the Stupp protocol (a standardized treatment for glioblastoma involving combined radiotherapy and chemotherapy with temozolomide, followed by adjuvant temozolomide) plus IT with dendritic cells. Patients were followed up till progression or death; seven underwent a second surgery for suspected progression. Clinical, immunological, and MRI data were collected from all patients and histology in case of second surgery. Patients were classified as responders (progression-free survival, PFS > 12 months), and non-responders (PFS ≤ 12), HIGH-NK (natural killer cells, i.e., immunological responders), and LOW-NK (immunological non-responders) based on immune cell counts in peripheral blood. TRAMs differentiate contrast-enhancing lesions with different washout dynamics into hypothesized tumoral (conventionally blue-colored) vs. treatment-related (red-colored). Results: Using receiver operating characteristic (ROC) curves, a threshold of -0.066 in VBlue/VCE (volume of the blue portion of tumoral area/volume of contrast enhancement) variation between values obtained in the MRI performed before PsP/TTP and at TTP/PSP allowed to discriminate TTP from PsP with a sensitivity of 71.4% and a specificity of 100%. Among HIGH-NK patients, at month 6 there was a significant reduction compared to baseline and month 2 in median "blue" volumes. Discussion: In conclusion, in our pilot study TRAMs support the discrimination between tumoral and treatment-related enhancing features in immunological responders vs. non-responders, the distinction between PsP and TTP, and might provide surrogate markers of immunological response.

Efficacy of Personalized Postoperative Epilepsy Management in Patients with Glioblastoma Utilizing IDH1 Gene Assessment.

Objective: We explored the correlation between the presence of isocitrate dehydrogenase-1 (IDH1) mutations and the incidence of postoperative epilepsy in patients with glioblastoma, as well as assessed the efficacy of preemptive administration of antiepileptic medications in mitigating the occurrence of postoperative epilepsy. Methods: Fifty-three patients who received a postoperative pathological diagnosis of glioblastoma, were enrolled in this study. Tumor specimens were subjected to IDH1 gene analysis. The patient cohort was stratified based on their IDH1 mutation status and the administration of prophylactic antiepileptic drugs during the postoperative phase. We subsequently conducted a comparative analysis of postoperative epileptic complications within each patient subgroup. Results: In the cohort of 53 patients under study, the occurrence of epilepsy was observed in 10 out of 21 patients carrying IDH1 mutations, while 5 out of 32 patients with wild-type IDH1 also experienced epilepsy, revealing a statistically significant difference (P < 0.05). Among the 27 patients who received prophylactic antiepileptic drugs, 6 of them developed epilepsy, whereas 9 out of 26 patients who did not receive prophylactic antiepileptic drugs exhibited concurrent epilepsy, with no statistically significant difference (P > 0.05). However, when performing a subgroup analysis, it was found that 3 out of 12 patients with IDH1 mutations who received prophylactic antiepileptic drugs experienced epilepsy, whereas 7 out of 9 patients who did not receive prophylactic antiepileptic drugs developed epilepsy, demonstrating a statistically significant difference (P < 0.05). Furthermore, within the group of 15 patients with wild-type IDH1, 3 patients who received prophylactic antiepileptic drugs developed epilepsy, while 2 cases of epilepsy occurred among the 17 patients who did not receive prophylactic antiepileptic drugs, with no statistically significant difference (P > 0.05). Conclusion: In individuals with IDH1 mutant glioblastoma who have undergone surgical resection, the implementation of preventive antiepileptic therapy demonstrates a potential to diminish the occurrence of postoperative epilepsy.

Personalized prognosis stratification of newly diagnosed glioblastoma applying a statistical decision tree model.

PURPOSE: Glioblastoma (GBM) is the most frequent glioma in adults with a high treatment resistance resulting into limited survival. The individual prognosis varies depending on individual prognostic factors, that must be considered while counseling patients with newly diagnosed GBM. The aim of this study was to elaborate a risk stratification algorithm based on reliable prognostic factors to facilitate a personalized prognosis estimation early on after diagnosis. METHODS: A consecutive patient cohort with confirmed GBM treated between 2010 and 2021 was retrospectively analyzed. Clinical, radiological, and molecular parameters were assessed and included in the analysis. Overall survival (OS) was the primary outcome parameter. After identifying the strongest prognostic factors, a risk stratification algorithm was elaborated with estimated odds of survival. RESULTS: A total of 462 GBM patients were analyzed. The strongest prognostic factors were Charlson Comorbidity Index (CCI), extent of tumor resection, and adjuvant treatment. Patients with CCI ≤ 1 receiving tumor resection had the highest survival odds (88% for 10 months). On the contrary, patients with CCI > 3 receiving no adjuvant treatment had the lowest survival odds (0% for 10 months). The 10-months survival rate in patients with CCI > 3 receiving adjuvant treatment was 56% for patients younger than 70 years and 22% for patients older than 70 years. CONCLUSION: A risk stratification algorithm based on significant prognostic factors allowed a personalized early prognosis estimation at the time of GBM diagnosis, that can contribute to a more personalized patient counseling.

High costs, low quality of life, reduced survival, and room for improving treatment: an analysis of burden and unmet needs in glioma.

Gliomas are a group of heterogeneous tumors that account for substantial morbidity, mortality, and costs to patients and healthcare systems globally. Survival varies considerably by grade, histology, biomarkers, and genetic alterations such as IDH mutations and MGMT promoter methylation, and treatment, but is poor for some grades and histologies, with many patients with glioblastoma surviving less than a year from diagnosis. The present review provides an introduction to glioma, including its classification, epidemiology, economic and humanistic burden, as well as treatment options. Another focus is on treatment recommendations for IDH-mutant astrocytoma, IDH-mutant oligodendroglioma, and glioblastoma, which were synthesized from recent guidelines. While recommendations are nuanced and reflect the complexity of the disease, maximum safe resection is typically the first step in treatment, followed by radiotherapy and/or chemotherapy using temozolomide or procarbazine, lomustine, and vincristine. Immunotherapies and targeted therapies currently have only a limited role due to disappointing clinical trial results, including in recurrent glioblastoma, for which the nitrosourea lomustine remains the de facto standard of care. The lack of treatment options is compounded by frequently suboptimal clinical practice, in which patients do not receive adequate therapy after resection, including delayed, shortened, or discontinued radiotherapy and chemotherapy courses due to treatment side effects. These unmet needs will require significant efforts to address, including a continued search for novel treatment options, increased awareness of clinical guidelines, improved toxicity management for chemotherapy, and the generation of additional and more robust clinical and health economic evidence.

The intersection of race and social determinants of health on clinical outcome of glioblastoma patients.

OBJECTIVE: Resection, chemotherapy, radiation therapy, and tumor treating fields significantly increase the overall survival (OS) of glioblastoma (GBM) patients. Yet, cost and healthcare disparities might limit access. Multiple studies have attributed more than 80% of the GBM disease burden to White patients. The aim of this study was to explore the intersections of race and social determinants of health (SDoH) with healthcare access and outcomes of GBM patients in a large metropolitan area. METHODS: In this retrospective single-center study, the tumor registry at the authors' institution (2011-2019) was queried to identify a GBM cohort according to the updated WHO criteria. Data were supplemented by electronic health records to include demographics, outcome, National Cancer Institute Comorbidity Index (NCI-CI), and the Agency for Healthcare Research and Quality (AHRQ) socioeconomic status (SES) index. RESULTS: A total of 276 unique patients met the study inclusion criteria; 46% of the cohort was female, and 45% was non-White. This racial proportion differs from previous reports indicating that 80% of patients with GBM are White. The proportion of non-White patients in this study was similar to that of the general US population and significantly lower than that of New York City (p < 0.05). Non-White patients predominantly composed the lowest AHRQ SES index quartile, while White patients constituted the highest quartile (p < 0.001). White patients were older at diagnosis compared with non-White patients (63 vs 58 years, p = 0.001). Older age (p = 0.03), higher NCI-CI (p = 0.0006), and lack of insurance (p = 0.03) reduced the odds of a home discharge. Private insurance (p = 0.005), younger age (p = 0.02), and the highest ("wealthiest") AHRQ SES index quartile (p = 0.02) predicted a lower hospital length of stay (LOS). Patients who underwent gross-total resection had greater OS than those who received a subtotal resection or biopsy, independent of race and SDoH (1.68 vs 1.4 years, p = 0.022). CONCLUSIONS: This study is the first to report on race and SDoH of a cohort using the latest WHO criteria for GBM classification. In contrast to previous literature, the study cohort exhibits a higher proportion of non-White patients with GBM, similar to the representation of non-White individuals in the general US population. This study corroborates the impact of SDoH and not race on LOS and discharge location. Initiatives to identify and address these barriers are crucial for enhancing the care of all GBM patients.

Real-world cost- effectiveness analysis: Tumor Treating Fields for newly diagnosed glioblastoma in China.

BACKGROUND: Glioblastoma (GBM) stands as the most aggressive and prevalent primary brain malignancy. Tumor Treating Fields (TTFields), an innovative therapy complementing chemotherapy for GBM treatment, which can significantly enhance overall survival, disease progression-free survival, and patient's quality of life. However, there is a dearth of health economics evaluation on TTFields therapy both domestically and internationally. OBJECTIVE: The study aims to assess the cost-effectiveness of TTFields + temozolomide (TMZ) in comparison to TMZ alone for newly diagnosed GBM patients. The intent is to provide robust economic evidence to serve as a foundation for policymaking and decision-making processes in GBM treatment. METHODS: We estimated outcomes for newly diagnosed GBM patients over a lifetime horizon using a partitioned survival model with three states: Progression-Free Survival, Progression Disease, and Death. The survival model was derived from a real-world study in China, with long-term survival data drawn from GBM epidemiology literature. Adverse event rates were sourced from the EF-14 trial data. Cost data, validated by expert consultation, was obtained from public literature and databases. Utility values were extracted from published literature. Using Microsoft Excel, we calculated expected costs and quality-adjusted life years (QALYs) over 15 years from a health system perspective. The willingness-to-pay threshold was set at three times the Chinese per capita Gross Domestic Product (GDP) in 2022, amounting to CN¥242,928 (US$37,655) /QALY. A 5% discount rate was applied to costs and utilities. Results underwent analysis through single factor and probability sensitivity analyses. RESULTS: TTFields + TMZ demonstrated a mean increase in cost by CN¥389,326 (US$57,859) and an increase of 2.46 QALYs compared to TMZ alone. The incremental cost-effectiveness ratio (ICER) was CN¥157,979 (US$23,474) per QALY gained. The model exhibited heightened sensitivity to changes in the discount rate. Probability sensitivity analysis indicates that, under the existing threshold, the probability of TTFields + TMZ being economical is 95.60%. CONCLUSIONS: This cost-effectiveness analysis affirms that incorporating TTFields into TMZ treatment proves to be cost-effective, given a threshold three times the Chinese per capita GDP.

Maximal cardiopulmonary exercise testing in glioblastoma patients undergoing chemotherapy: assessment of feasibility, safety, and physical fitness status.

PURPOSE: Maximal cardiopulmonary exercise testing (max. CPET) provides the most accurate measurement of cardiorespiratory fitness. However, glioblastoma (GBM) patients often undergo less intensive tests, e.g., 6-min walk test or self-rating scales. This study aims to demonstrate feasibility and safety of max. CPET in GBM patients, concurrently evaluating their physical fitness status. METHODS: Newly diagnosed GBM patients undergoing adjuvant chemotherapy were offered participation in an exercise program. At baseline, max. CPET assessed cardiorespiratory fitness including peak oxygen consumption (VO2peak), peak workload, and physical work capacity (PWC) at 75% of age-adjusted maximal heart rate (HR). Criteria for peak workload were predefined based on threshold values in HR, respiratory quotient, respiratory equivalent, lactate, and rate of perceived effort. Data were compared to normative values. Adverse events were categorized according to standardized international criteria. Further, self-reported exercise data pre- and post-diagnosis were gathered. RESULTS: All 36 patients (median-aged 60; 21 men) met the predefined criteria for peak workload. Mean absolute VO2peak was 1750 ± 529 ml/min, peak workload averaged 130 ± 43 W, and mean PWC was 0.99 ± 0.38 W/kg BW, all clinically meaningful lower than age- and sex-predicted normative values (87%, 79%, 90%, resp.). Only once (3%) a minor, transient side effect occurred (post-test dizziness, no intervention needed). Self-reported exercise decreased from 15.8 MET-h/week pre-diagnosis to 7.2 MET-h/week post-diagnosis. CONCLUSION: Max. CPET in this well-defined population proved feasible and safe. GBM patients exhibit reduced cardiorespiratory fitness, indicating the need for tailored exercise to enhance health and quality of life. CPET could be essential in establishing precise exercise guidelines.

Real-time glioblastoma tumor microenvironment assessment by SpiderMass for improved patient management.

Glioblastoma is a highly heterogeneous and infiltrative form of brain cancer associated with a poor outcome and limited therapeutic effectiveness. The extent of the surgery is related to survival. Reaching an accurate diagnosis and prognosis assessment by the time of the initial surgery is therefore paramount in the management of glioblastoma. To this end, we are studying the performance of SpiderMass, an ambient ionization mass spectrometry technology that can be used in vivo without invasiveness, coupled to our recently established artificial intelligence pipeline. We demonstrate that we can both stratify isocitrate dehydrogenase (IDH)-wild-type glioblastoma patients into molecular sub-groups and achieve an accurate diagnosis with over 90% accuracy after cross-validation. Interestingly, the developed method offers the same accuracy for prognosis. In addition, we are testing the potential of an immunoscoring strategy based on SpiderMass fingerprints, showing the association between prognosis and immune cell infiltration, to predict patient outcome.

Gold standard assessment of immunogenic cell death induced by photodynamic therapy: From in vitro to tumor mouse models and anti-cancer vaccination strategies.

The discovery of the concept of immunogenic cell death (ICD) is a cornerstone in the development of novel anti-cancer immunotherapeutic approaches. Induction of the ICD pathway by specific anti-cancer therapeutic regimens can eliminate cancer cells by directly killing them during therapy and by activation of strong and specific anti-cancer immunity, leading to a long-lasting immunological memory that prevents cancer recurrence. ICD encompasses different forms of regulated cell death and can be triggered by many anti-cancer treatment modalities, including photodynamic therapy (PDT). PDT is a multistep procedure involving the accumulation of a light-sensitive dye known as a photosensitizer (PS) in tumor cells, followed by its activation by irradiation with a light of an appropriate wavelength. In the presence of molecular oxygen, the irradiated PS leads to the generation of cytotoxic reactive oxygen species, which can lead to ICD induction in the cancer cells. Here, we first describe in vitro methods to help optimize the PDT procedure for a specific PS. We also provide a collection of protocols and techniques for assessing ICD in vitro, including analysis of the emission of damage associated molecular patterns (DAMPs), efferocytosis, and the maturation and activation state of antigen presenting cells. Next, we describe in detail protocols for diverse tumor mouse models for assessing and characterizing ICD in vivo, such as murine tumor vaccination models. Finally, as an immunotherapeutic vaccine, we suggest using either PDT-induced dead cancer cells, preferably undergoing ICD, or dendritic cells loaded with lysates of PDT-induced cancer cells in a syngeneic orthotopic glioma model. Overall, this methodological article provides a quantitative, comprehensive set of validated tools that can be successfully used, with some adaptations, to identify, optimize and validate novel PSs in vitro and in vivo for the efficient induction of ICD during photodynamic treatment.

Choreographed expansion of services results in decreased patient burden without compromise of outcomes: An assessment of the Ontario experience.

Background: Neuro-oncology care in Ontario, Canada has been historically centralized, at times requiring significant travel on the part of patients. Toward observing the goal of patient-centered care and reducing patient burden, 2 additional regional cancer centres (RCC) capable of neuro-oncology care delivery were introduced in 2016. This study evaluates the impact of increased regionalization of neuro-oncology services, from 11 to 13 oncology centers, on healthcare utilization and travel burden for glioblastoma (GBM) patients in Ontario. Methods: We present a cohort of GBM patients diagnosed between 2010 and 2019. Incidence of GBM and treatment modalities were identified using provincial health administrative databases. A geographic information system and spatial analysis were used to estimate travel time from patient residences to neuro-oncology RCCs. Results: Among the 5242 GBM patients, 79% received radiation as part of treatment. Median travel time to the closest RCC was higher for patients who did not receive radiation as part of treatment than for patients who did (P = .03). After 2016, the volume of patients receiving radiation at their local RCC increased from 62% to 69% and the median travel time to treatment RCCs decreased (P = .0072). The 2 new RCCs treated 35% and 41% of patients within their respective catchment areas. Receipt of standard of care, surgery, and chemoradiation (CRT), increased by 11%. Conclusions: Regionalization resulted in changes in the healthcare utilization patterns in Ontario consistent with decreased patient travel burden for patients with GBM. Focused regionalization did not come at the cost of decreased quality of care, as determined by the delivery of a standard of care.

Computational Assessment of Spectral Heterogeneity within Fresh Glioblastoma Tissue Using Raman Spectroscopy and Machine Learning Algorithms.

Understanding and classifying inherent tumor heterogeneity is a multimodal approach, which can be undertaken at the genetic, biochemical, or morphological level, among others. Optical spectral methods such as Raman spectroscopy aim at rapid and non-destructive tissue analysis, where each spectrum generated reflects the individual molecular composition of an examined spot within a (heterogenous) tissue sample. Using a combination of supervised and unsupervised machine learning methods as well as a solid database of Raman spectra of native glioblastoma samples, we succeed not only in distinguishing explicit tumor areas-vital tumor tissue and necrotic tumor tissue can correctly be predicted with an accuracy of 76%-but also in determining and classifying different spectral entities within the histomorphologically distinct class of vital tumor tissue. Measurements of non-pathological, autoptic brain tissue hereby serve as a healthy control since their respective spectroscopic properties form an individual and reproducible cluster within the spectral heterogeneity of a vital tumor sample. The demonstrated decipherment of a spectral glioblastoma heterogeneity will be valuable, especially in the field of spectroscopically guided surgery to delineate tumor margins and to assist resection control.

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.