Survival Of Glioblastoma Patients Research Articles

Targeting ARNT attenuates chemoresistance through destabilizing p38α-MAPK signaling in glioblastoma

Glioblastoma (GBM) is the most aggressive and lethal brain tumor in adults. This study aimed to investigate the functional significance of aryl hydrocarbon receptor nuclear translocator (ARNT) in the pathogenesis of GBM. Analysis of public datasets revealed ARNT is upregulated in GBM tissues compared to lower grade gliomas or normal brain tissues. Higher ARNT expression correlated with the mesenchymal subtype and poorer survival in GBM patients. Silencing ARNT using lentiviral shRNAs attenuated the proliferative, invasive, and stem-like capabilities of GBM cell lines, while ARNT overexpression enhanced these malignant phenotypes. Single-cell RNA sequencing uncovered that ARNT is highly expressed in a stem-like subpopulation and is involved in regulating glycolysis, hypoxia response, and stress pathways. Mechanistic studies found ARNT activates p38 mitogen-activated protein kinase (MAPK) signaling to promote chemoresistance in GBM cells. Disrupting the ARNT/p38α protein interaction via the ARNT PAS-A domain restored temozolomide sensitivity. Overall, this study demonstrates ARNT functions as an oncogenic driver in GBM pathogenesis and represents a promising therapeutic target.

Profiling of Tumor-Infiltrating Immune Cells and Their Impact on Survival in Glioblastoma Patients Undergoing Immunotherapy with Dendritic Cells.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Cellular diversity through space and time: adding new dimensions to GBM therapeutic development.

The current median survival for glioblastoma (GBM) patients is only about 16 months, with many patients succumbing to the disease in just a matter of months, making it the most common and aggressive primary brain cancer in adults. This poor outcome is, in part, due to the lack of new treatment options with only one FDA-approved treatment in the last decade. Advances in sequencing techniques and transcriptomic analyses have revealed a vast degree of heterogeneity in GBM, from inter-patient diversity to intra-tumoral cellular variability. These cutting-edge approaches are providing new molecular insights highlighting a critical role for the tumor microenvironment (TME) as a driver of cellular plasticity and phenotypic heterogeneity. With this expanded molecular toolbox, the influence of TME factors, including endogenous (e.g., oxygen and nutrient availability and interactions with non-malignant cells) and iatrogenically induced (e.g., post-therapeutic intervention) stimuli, on tumor cell states can be explored to a greater depth. There exists a critical need for interrogating the temporal and spatial aspects of patient tumors at a high, cell-level resolution to identify therapeutically targetable states, interactions and mechanisms. In this review, we discuss advancements in our understanding of spatiotemporal diversity in GBM with an emphasis on the influence of hypoxia and immune cell interactions on tumor cell heterogeneity. Additionally, we describe specific high-resolution spatially resolved methodologies and their potential to expand the impact of pre-clinical GBM studies. Finally, we highlight clinical attempts at targeting hypoxia- and immune-related mechanisms of malignancy and the potential therapeutic opportunities afforded by single-cell and spatial exploration of GBM patient specimens.

Treatment, healthcare utilization and outcomes in patients with glioblastoma in Ontario: a 10-year cohort study.

Glioblastoma (GBM) is the most common malignant primary brain tumour in adults. Receipt of adjuvant therapies has been shown to exert a significant positive effect on patient survival. Little is known however about how changes in standards of care and healthcare system factors, such as access, affect real-world outcomes. In this study, we provide an overview of GBM in Ontario and examine elements of care, including treatment patterns, healthcare utilization, and overall survival, from 2010 to 2019, to interpret the impact of the changes in practice standards and expansion of the care network within this period. Using linked health-administrative databases from Ontario, Canada, we conducted a population-based cohort study to examine the clinical and biological characteristics, treatment, and healthcare utilization patterns of adult GBM patients diagnosed between 2010 and 2019. The primary outcomes were enrollment in adjuvant chemoradiation treatment and 1-, 2-, and 5-year survival. All analyses were performed using the Statistical Analysis Software (SAS). 5392 patients were diagnosed with GBM in Ontario from 2010 to 2019 (58% male, 42% female). The median age at diagnosis was 64. Receipt of adjuvant chemoradiation within one year of diagnosis increased from 51% in 2010 to 63% in 2019. 1-year, 2-year, and 5-year overall survival for all patients remained stable, ranging between 40 and 43%, 15-19%, and 5-7%, respectively. For patients above the age of 65, however, 1-year survival increased from 19% in 2010 to 26% in 2019. Regionalization enabled access to treatment closer to home for many patients. Over the last decade, receipt of adjuvant chemoradiation increased among elderly patients, but the improvement in 1-year overall survival over time was accounted for by sociodemographic and clinical covariates. Our findings support the efforts for regionalization of services to improve accessibility. This Ontario-based study provides insight into the effect of practice evolution and healthcare utilization on the overall survival of patients with GBM. Overall survival for most patients with glioblastoma has remained stagnant over the past decade. Changes in treatment standards and expansion of access to treating centres have been associated with prolonged survival in elderly glioblastoma patients.

Revisiting prognostic factors of gliomatosis cerebri in adult-type diffuse gliomas.

There is lack of comprehensive analysis evaluating the impact of clinical, molecular, imaging, and surgical data on survival of patients with gliomatosis cerebri (GC). This study aimed to investigate prognostic factors of GC in adult-type diffuse glioma patients. Retrospective chart and imaging review was performed in 99 GC patients from adult-type diffuse glioma (among 1,211 patients; 6 oligodendroglioma, 16 IDH-mutant astrocytoma, and 77 IDH-wildtype glioblastoma) from a single institution between 2005 and 2021. Predictors of overall survival (OS) of entire patients and IDH-wildtype glioblastoma patients were determined. The median OS was 16.7months (95% confidence interval [CI] 14.2-22.2) in entire patients and 14.3months (95% CI 12.2-61.9) in IDH-wildtype glioblastoma patients. In entire patients, KPS (hazard ratio [HR] = 0.98, P = 0.004), no 1p/19q codeletion (HR = 10.75, P = 0.019), MGMTp methylation (HR = 0.54, P = 0.028), and hemorrhage (HR = 3.45, P = 0.001) were independent prognostic factors on multivariable analysis. In IDH-wildtype glioblastoma patients, KPS (HR = 2.24, P = 0.075) was the only independent prognostic factor on multivariable analysis. In subgroup of IDH-wildtype glioblastoma with CE tumors, total resection of CE tumor did not remain as a significant prognostic factor (HR = 1.13, P = 0.685). The prognosis of GC patients is determined by its underlying molecular type and patient performance status. Compared with diffuse glioma without GC, aggressive surgery of CE tumor in GC patients does not improve survival.

Factors associated with one-year survival in post-operative glioblastoma patients

Factors associated with one-year survival in post-operative glioblastoma patients

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics.

Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.

The Expression of Serglycin Is Required for Active Transforming Growth Factor β Receptor I Tumorigenic Signaling in Glioblastoma Cells and Paracrine Activation of Stromal Fibroblasts via CXCR-2.

Serglycin (SRGN) is a pro-tumorigenic proteoglycan expressed and secreted by various aggressive tumors including glioblastoma (GBM). In our study, we investigated the interplay and biological outcomes of SRGN with TGFβRI, CXCR-2 and inflammatory mediators in GBM cells and fibroblasts. SRGN overexpression is associated with poor survival in GBM patients. High SRGN levels also exhibit a positive correlation with increased levels of various inflammatory mediators including members of TGFβ signaling pathway, cytokines and receptors including CXCR-2 and proteolytic enzymes in GBM patients. SRGN-suppressed GBM cells show decreased expressions of TGFβRI associated with lower responsiveness to the manipulation of TGFβ/TGFβRI pathway and the regulation of pro-tumorigenic properties. Active TGFβRI signaling in control GBM cells promotes their proliferation, invasion, proteolytic and inflammatory potential. Fibroblasts cultured with culture media derived by control SRGN-expressing GBM cells exhibit increased proliferation, migration and overexpression of cytokines and proteolytic enzymes including CXCL-1, IL-8, IL-6, IL-1β, CCL-20, CCL-2, and MMP-9. Culture media derived by SRGN-suppressed GBM cells fail to induce the above properties to fibroblasts. Importantly, the activation of fibroblasts by GBM cells not only relies on the expression of SRGN in GBM cells but also on active CXCR-2 signaling both in GBM cells and fibroblasts.

Glioblastoma: Not Just Another Cancer.

This commentary urges a paradigm shift in how we approach research and drug development for glioblastoma, reimagining it as an aberrant brain-like organ, distinct from other cancers, to inspire innovative treatment strategies and interdisciplinary collaboration, addressing the minimal progress in extending glioblastoma patient survival despite years of research and investment.

Investigating Causal Genetic Effects on Overall Survival of Glioblastoma Patients using Normalizing Flow and Structural Causal Model.

Glioblastoma (GBM) is the most common and aggressive brain tumor with short overall survival (OS) of about 15 months. Understanding the causal factors affecting the patient survival is crucial for disease prognosis and treatment planning. Although previous efforts on survival prediction using multi-omics data has yielded useful predictive models, the causation of the correlated genetic risk factors has not been addressed. Recent advances in causal deep learning models enable the study of causality from complex dataset. In this paper, we leverage the recently proposed structural causal model (SCM) with normalizing flows parameterized by deep networks to perform the counterfactual query to investigate the causal relationship between gene mutation and OS with the presence of other confounders including sex, age and radiomics features. The query amounts to the question that what the survival days will be if the gene mutation status has been changed, i.e., from mutant to non-mutant and vice versa. The trained causal model will infer the counterfactual outcome given the intervention on specific gene mutation. We apply multivariate Cox-PH model to find the genes associated with survival, and investigate the causal genetic effect by comparing the original and counterfactual survival days in a bi-directional fashion. Particularly, the following two scenarios are considered: (1) intervention on a specific gene with non-mutant status to generate the counterfactual survival days as if the gene is mutant, with which the original survival days of the subjects with that mutant gene will be compared; (2) intervention on the gene with mutant status and perform the comparison with survival days of subjects with that non-mutant gene. Our experimental results show that no causation of two correlated genes (NF1, RB1) was revealed in the cohort (n=181), while their genetic effects on OS in terms of prolonging or shortening are generally in accordance with clinical findings.

The MDM2-p53 Axis Represents a Therapeutic Vulnerability Unique to Glioma Stem Cells.

The prevention of tumor recurrence by the successful targeting of glioma stem cells endowed with a tumor-initiating capacity is deemed the key to the long-term survival of glioblastoma patients. Glioma stem cells are characterized by their marked therapeutic resistance; however, recent evidence suggests that they have unique vulnerabilities that may be therapeutically targeted. We investigated MDM2 expression levels in glioma stem cells and their non-stem cell counterparts and the effects of the genetic and pharmacological inhibition of MDM2 on the viability of these cells as well as downstream molecular pathways. The results obtained showed that MDM2 expression was substantially higher in glioma stem cells than in their non-stem cell counterparts and also that the inhibition of MDM2, either genetically or pharmacologically, induced a more pronounced activation of the p53 pathway and apoptotic cell death in the former than in the latter. Specifically, the inhibition of MDM2 caused a p53-dependent increase in the expression of BAX and PUMA and a decrease in the expression of survivin, both of which significantly contributed to the apoptotic death of glioma stem cells. The present study identified the MDM2-p53 axis as a novel therapeutic vulnerability, or an Achilles' heel, which is unique to glioma stem cells. Our results, which suggest that non-stem, bulk tumor cells are less sensitive to MDM2 inhibitors, may help guide the selection of glioblastoma patients suitable for MDM2 inhibitor therapy.

494 Evaluating ERK1 2 Phosphorylation as a Predictive Biomarker for Survival in Recurrent Glioblastoma Patients: A REMARK Criteria-guided Analysis of a Clinical Trial Cohort Treated With Intracerebral PD-1 and CTLA-4 Blockade

INTRODUCTION: Glioblastoma patients exhibit variable clinical responses to anti-PD-1 immunotherapy. Our previous work identified ERK1/2 phosphorylation (p-ERK) in pre-treatment tumor samples as a predictive biomarker of overall survival in two independent cohorts of recurrent glioblastoma patients undergoing adjuvant anti-PD-1 therapy (Arrieta et al, Nat Cancer, 2021). This biomarker, however, has not yet been explored with alternative immune checkpoint blockade strategies nor assessed using REMARK criteria. METHODS: Adhering to REMARK criteria for biomarker validation, we investigated p-ERK as a predictor of survival in 24 evaluable recurrent glioblastoma patients from a clinical trial (NCT03233152; Duerinck J, et al, JITC, 2021). Patients underwent intracerebral administration of immune checkpoint inhibitors within a phase I clinical trial, receiving either ipilimumab (10 mg), or a combination of ipilimumab (5 mg) and nivolumab (10 mg), followed by postsurgical intravenous nivolumab (10 mg). We quantified p-ERK+ cell density in tumor regions and conducted a double-blinded statistical analysis of p-ERK’s association with survival outcomes, performed by an independent statistical team. RESULTS: Although analysis of the entire cohort revealed no statistically significant survival difference between patients with high and low p-ERK tumors (p = 0.29), a focused examination of wild-type IDH GBM patients demonstrated a significantly prolonged survival for those with high p-ERK tumors (median survival = 55.6 weeks, 95% CI 33.86-NA) compared to those with low p-ERK tumors (median OS of 30 weeks, 95% CI 16.14-NA; p = 0.036). CONCLUSIONS: Despite the limited sample size, this study highlights the promising predictive potential of p-ERK as a biomarker in a third independent prospective glioblastoma cohort treated with a novel immune checkpoint blockade administration approach, emphasizing the need for further investigation and validation in larger cohorts.

Dexamethasone in Patients with Glioblastoma: A Systematic Review and Meta-Analysis.

Glioblastomas are the most common primary central nervous system (CNS) tumors. Although modern management strategies have modestly improved overall survival, the prognosis remains dismal, with treatment side effects often impinging on the clinical course. Glioblastomas cause neurological dysfunction by infiltrating CNS tissue and via perifocal oedema formation. The administration of steroids such as dexamethasone is thought to alleviate symptoms by reducing oedema. However, despite its widespread use, the evidence for the administration of dexamethasone is limited and conflicting. Therefore, we aimed to review the current evidence concerning the use and outcomes of dexamethasone in patients with glioblastoma. We performed a systematic review and meta-analysis according to the PRISMA-P guidelines. We performed a restricted search using the keywords "Dexamethasone" and "Glioblastoma" on PubMed, Web of Science, Cochrane Library, and Academic Search Premier. We included studies reporting on overall survival (OS) and progression-free survival (PFS) in glioblastoma patients receiving higher or lower dexamethasone doses. The risk of bias was assessed using ROBINS-I. We performed a meta-analysis using a random effects model for OS and PFS. Twenty-two retrospective studies were included. Higher doses of dexamethasone were associated with poorer OS (hazard ratio 1.62, confidence interval 1.40-1.88) and PFS (1.49, 1.23-1.81). OS remained worse even when studies corrected for clinical status (1.52, 1.38-1.67). Despite the widespread use of dexamethasone in glioblastoma patients, its use is correlated with worse long-term outcomes. Consequently, Dexamethasone administration should be restricted to selected symptomatic patients. Future prospective studies are crucial to confirm these findings.

Sarcopenia is associated with chemoradiotherapy discontinuation and reduced progression-free survival in glioblastoma patients.

Sarcopenia may complicate treatment in cancer patients. Herein, we assessed whether sarcopenia measurements derived from radiation planning computed tomography (CT) were associated with complications and tumor progression during radiochemotherapy for glioblastoma. Consecutive patients undergoing radiotherapy planning for glioblastoma between 2010 and 2021 were analyzed. Retrocervical muscle cross-sectional area (CSA) was measured via threshold-based semi-automated radiation planning CT analysis. Patients in the lowest sex-specific quartile of muscle measurements were defined as sarcopenic. We abstracted treatment characteristics and tumor progression from the medical records and performed uni- and multivariable time-to-event analyses. We included 363 patients in our cohort (41.6% female, median age 63years, median time to progression 7.7months). Sarcopenic patients were less likely to receive chemotherapy (p < 0.001) and more likely to be treated with hypofractionated radiotherapy (p = 0.005). Despite abbreviated treatment, they more often discontinued radiotherapy (p = 0.023) and were more frequently prescribed corticosteroids (p = 0.014). After treatment, they were more often transferred to inpatient palliative care treatment (p = 0.035). Finally, progression-free survival was substantially shorter in sarcopenic patients in univariable (median 5.1vs. 8.4months, p < 0.001) and multivariable modeling (hazard ratio 0.61 [confidence interval 0.46-0.81], p = 0.001). Sarcopenia is astrong risk factor for treatment discontinuation and reduced progression-free survival in glioblastoma patients. We propose that sarcopenic patients should receive intensified supportive care during radiotherapy and during follow-up as well as expedited access to palliative care.

FBXO22 promotes glioblastoma malignant progression by mediating VHL ubiquitination and degradation

Glioblastoma (GBM) is the most common malignant primary brain tumor. Despite comprehensive treatment with traditional surgery, radiotherapy, and chemotherapy, the median survival rate is <14.6% and the 5-year survival rate is only 5%. FBXO22, a substrate receptor of the SCF ubiquitin ligases, has been reported to play a promoting role in melanoma, liver cancer, cervical cancer, and other cancers. However, the function of FBXO22 in GBM has not been reported. In the present study, we demonstrate that FBXO22 is highly expressed in glioma and is positively correlated with worse pathological features and shorter survival of GBM patients. We revealed that FBXO22 promotes GBM cell proliferation, angiogenesis, migration, and tumorigenesis in vitro and in vivo. In terms of mechanism, we reveal that FBXO22 decreases VHL expression by directly mediating VHL ubiquitination degradation, which ultimately increases HIF-1α and VEGFA expression. In addition, our data confirm that there are positive correlations among FBXO22, HIF-1α, and VEGFA expression, and there is a negative correlation between FBXO22 and VHL protein expression in glioma patients. Our study strongly indicates that FBXO22 is a promising diagnostic marker and therapeutic target for glioma patients.

Abstract 4392: Neuropeptide Y system in glioblastoma

Abstract Gliomas constitute the most common primary cerebral tumors of the central nervous system (CNS), with glioblastoma (GBM) representing the most aggressive subtype. Neurotransmitters are important players in maintaining physiological processes in CNS and abnormal levels of their expression is pathogenic, leading to different processes, including neoplasia. Neuropeptide Y (NPY) is one of the neurotransmitters that is found to play a pivotal role in several malignancies. NPY, acting via its cognate receptors Y1, Y2 and Y5 (Y1R, Y2R and Y5R), has been shown to stimulate cancer cell proliferation, migration, invasiveness and dissemination, as well as tumor vascularization in various malignancies including neuroblastoma, Ewing sarcoma, colon, breast, prostate and liver cancers. Thus, the goal of this study was to determine if the NPY system is involved in glioma biology. Our immunohistochemistry staining of NPY, Y1R, Y2R, and Y5R in human GBM tissues revealed positive staining for NPY and Y2R in GBM cells. No expression of Y1R and Y5R was detected in GBM neoplastic population. To further elucidate the association between NPY and its receptors with GBM tumor stage and patients' survival, we used the available clinical data from the Cancer Genome Atlas Program (TCGA) database to analyze the gene expression of the NPY system. Y2R expression was increased in high-grade gliomas, while mRNA levels of NPY, Y1R and Y5R inversely correlated with the degree of glioma malignancy. Moreover, high Y2R expression was associated with worse survival in GBM patients. Importantly, endothelial Y2R is also responsible for angiogenic effects of NPY, suggesting its role in GBM vascularization. Altogether, these data suggest the involvement of NPY/Y2R axis in glioma progression toward more aggressive phenotype. Further functional studies are required to determine the role of the Y2R axis in this process. Citation Format: Nouran Abualsaud, Jason Tilan, Bahauddeen M. Alrfaei, Harrison Glor, Taylor Polk, Ewa Izycka-Swieszewska, Joanna Kitlinska. Neuropeptide Y system in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4392.

Abstract 2508: EMP2 is a targetable biomarker in GBM tumors resistant to anti-angiogenic therapies

Abstract Background: Glioblastoma (GBM) is characterized as the most aggressive and lethal primary brain tumor. One of the hallmarks of GBM tumor growth and progression lies within the proangiogenic tumor microenvironment. Current anti-angiogenic drugs such as the anti-VEGF antibody take effect by inducing tumor cell starvation, leading to a functional normalization of the tumor vasculature. However, the survival benefits of anti-angiogenic drugs have been very limited. To this end, we hypothesized that the tetraspan Epithelial Membrane Protein-2 (EMP2) may help mediate resistance. Objective: We hypothesize that Epithelial Membrane Protein-2 may serve as a targetable biomarker for anti-VEGF resistance. We further explored the effectiveness of combination therapy in SB28 and GL261 GBM mouse models using anti-VEGF drug, Aflibercept, with a novel anti-EMP2 monoclonal antibody (mAb). Results: Tumor tissue was collected prospectively from patients undergoing surgery for suspected glioblastoma and stained for EMP2 and HIF2a using standard immunohistochemistry. Patients had banked tumor tissue both prior to and after bevacizumab treatment with 3 months of clinical and radiologic follow-up available. Bevacizumab treatment increased EMP2 protein expression. This increase in EMP2 correlated with reduced mean survival time post-bevacizumab therapy. Similarly, HIF-2a showed increased expression post-bevacizumab treatment and showed expression in both tumor and stromal cells. Limited animal models exist for anti-VEGF therapy for GBM. To establish syngeneic models, 10 week-old mice were subcutaneously implanted with murine SB28 or GL261 GBM cells. Treatment with either polyclonal sera to VEGF or Aflibercept failed to reduce tumor load or provide a therapeutic benefit. To next investigate if this model could recapitulate the response obtained patients tumors, formalin fixed paraffin embedded tissue was analyzed for both EMP2 and HIF-2a expression. Both markers were significantly upregulated in Aflibercept treated samples compared to the control.To next investigate if combination treatment could produce a significant reduction in tumor load, animals were treated with a combination treatment with Aflibercept and anti-EMP2 mAb. The combination therapy significantly reduced tumor volume and weight in comparison to control-treated tumors. Combination treatment in SB28 tumors resulted in a two fold reduction in tumor load and 50% reduction in tumor weight. Moreover, tumors showed reduced Ki67 expression. Similarly, treated GL261 tumors produced a 2.3 fold reduction in tumor size and ~2.7 fold reduction in tumor weight. Our results suggest that EMP2 can be a promising new target therapeutic target that can be combined with anti-VEGF treatment to potentially increase overall survival in GBM patients. Citation Format: Brian Aguirre, Mahlet Mekonnen, Riddhi Mehta, Meera Suresh, Anubhav Chandla, Karam Han, Isaac Yang, Madhuri Wadehra. EMP2 is a targetable biomarker in GBM tumors resistant to anti-angiogenic therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2508.

Abstract 5439: Metastasis-enhancing protein KITENIN confers temozolomide resistance in glioblastoma with unmethylated MGMT via upregulation of cancer stem cell makers

Abstract Background: Elevated expression of cancer stem cell (CSC) markers is linked with progression, poor survival, and treatment resistance in glioblastoma (GBM). Our prior work identified KAI1 COOH-terminal interacting tetraspanin (KITENIN) as key to GBM progression. We investigated its influence on temozolomide (TMZ) resistance in GBM through modulation of CSC markers. Methods: We examined KITENIN and CSC markers in TMZ-resistant GBM cells and patient-derived GBM cells, and assessed therapeutic responses to TMZ in mice implanted with KITENIN-modulated GBM cells. The correlation of these markers with clinical outcomes was analyzed using our cohort and The Cancer Genome Atlas (TCGA) data. Results: High KITENIN expression correlated positively with elevated CSC marker levels in human GBM samples and KITENIN-modulated GBM cells. Inhibition of KITENIN using usnic acid reduced tumor progression by decreasing CSC marker expression. Our data and TCGA analyses linked co-directional increase of these factors with tumor recurrence and shorter survival in GBM patients with unmethylated MGMT. This increase was also observed in TMZ-resistant cell lines with unmethylated MGMT. Implantation of KITENIN-overexpressing cells led to TMZ resistance in our mouse model, associated with co-directionally increased CD44 and ALDH1A1 expression. The link between KITENIN and CD44/ALDH1A1 could be inhibited by DKC2511, a novel KITENIN inhibitor, and T5244, a c-Fos/AP-1 inhibitor. Conclusion: KITENIN might contribute to TMZ resistance in GBM patients with unmethylated MGMT, potentially through AP-1 activation and subsequent upregulation of CSC markers. Hence, targeting KITENIN could provide a novel strategy to overcome TMZ resistance in GBM patients with unmethylated MGMT. Citation Format: Eun-Jeong Ahn, Yeong Jin Kim, Tae-Young Jung, Jae-Hyuk Lee, Joon Haeng Rhee, Kyung-Keun Kim, Sung Sun Kim, Nah Ihm Kim, Hangun Kim, Kyung-Sub Moon, Kyung-Hwa Lee. Metastasis-enhancing protein KITENIN confers temozolomide resistance in glioblastoma with unmethylated MGMT via upregulation of cancer stem cell makers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5439.

Abstract 7395: Histology-based prognosis prediction using deep learning outperforms and is independent of the MGMT methylation status in patients with glioblastoma

Abstract Introduction: MGMT gene promoter methylation status is today the only biomarker of survival for GBM patients and predicts favorable response to temozolomide (TMZ). Here we propose a deep learning-based model using histology data (H&amp;E slides) to predict the prognosis of patients with Glioblastoma (GBM) treated by standard of care (SOC). Methods: We included TCGA GBM patients and selected only patients treated after 2005 (Stupp protocol start); compliant to WHO 2021 classification; treated by surgery and adjuvant therapy; with a follow-up superior to median overall survival (OS) (14.5 months). Short and long survivor labels were defined based on median OS cut-off. A deep learning pipeline was trained to predict these labels from the H&amp;E slides (baseline surgery samples). First, the slides were automatically segmented into tissue and background, divided into a regular grid of tiles (112 × 112µm), and tiles were vectorized using a vision transformer-based feature extractor trained on H&amp;E slides of 5,500 patients with 16 cancer subtypes (GBM excluded). In the second step, ABMIL deep learning model was trained to predict the survival category using the bag of tile features available from step 1 for each patient. The cohort was divided into five folds with even numbers of short and long survivors. For each fold, 50 ABMIL models were trained on the remaining folds and ensembled to predict the category of the patients in the fold. Training hyperparameters were tuned on a separated cohort excluding GBM patients. Results: After filtering, we analyzed n = 192 TCGA GBM patients including 154 patients with a known MGMT promoter methylation status. Our histology-based model had an accuracy of 0.661 and a ROC AUC of 0.706. It stratified the population into short and long survivors with an Hazard Ratio (HR) of 0.48 (95% CI 0.34-0.69). Our model outperformed the MGMT methylation status that had an HR of 0.57 (95% CI 0.40-0.83). Moreover, our model was independent of MGMT methylation status and the combination of both was able to further improve prognosis prediction: we applied our model independently to the 91 patients with an unmethylated MGMT status (predicted: 43 low, 48 high) and to the 63 patients with a methylated MGMT status (predicted: 30 low, 33 high), and obtained HR of 0.42 (95% CI 0.27-0.67) and 0.49 (95% CI 0.28-0.86) respectively. Conclusion: Having selected patients treated by the latest SOC and classified as GBM by the latest WHO criteria, we propose a model predicting survival based on histological specimens available in routine care, which outperformed the current unique biomarker MGMT methylation status. The combination of this status and our model improves prognosis predictions compared to each strategy alone. Citation Format: Lucas Fidon, Celine Thiriez, Alexandre Grimaldi, Omar Darwiche Domingues, Charles Maussion, Caroline Hoffmann. Histology-based prognosis prediction using deep learning outperforms and is independent of the MGMT methylation status in patients with glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7395.

EGFR amplification and EGFRvIII predict and participate in TAT-Cx43266-283 antitumor response in preclinical glioblastoma models.

Glioblastoma (GBM) commonly displays epidermal growth factor receptor (EGFR) alterations (mainly amplification and EGFRvIII) and TAT-Cx43266-283 is a Src-inhibitory peptide with antitumor properties in preclinical GBM models. Given the link between EGFR and Src, the aim of this study was to explore the role of EGFR in the antitumor effects of TAT-Cx43266-283. The effect of TAT-Cx43266-283, temozolomide (TMZ) and erlotinib (EGFR inhibitor) was studied in patient-derived GBM stem cells (GSCs) and murine neural stem cells (NSCs) with and without EGFR alterations, in vitro and in vivo. EGFR alterations were analyzed by Western blot (WB) and Fluorescence In Situ Hybridization (FISH) in these cells, and compared with Src activity and survival in GBM samples from TCGA. The effect of TAT-Cx43266-283 correlated with EGFR alterations in a set of patient-derived GSCs and was stronger than that exerted by TMZ and erlotinib. In fact, TAT-Cx43266-283 only affected NSCs with EGFR alterations, but not healthy NSCs. EGFR alterations correlated with Src activity and poor survival in GBM patients. Finally, tumors generated from NSCs with EGFR alterations, showed a decrease in growth, invasiveness and vascularization after treatment with TAT-Cx43266-283, which enhanced the survival of immunocompetent mice. Clinically relevant EGFR alterations are predictors of TAT-Cx43266-283 response and part of its mechanism of action, even in TMZ- and erlotinib-resistant GSCs. TAT-Cx43266-283 targets NSCs with GBM-driver mutations, including EGFR alterations, in an immunocompetent GBM model in vivo, suggesting a promising effect on GBM recurrence. Together, this study represents an important step towards the clinical application of TAT-Cx43266-283.