Citations

ABSTRACT Glioblastoma (GBM) is universally lethal despite decades of research to find effective treatments. This highlights the need to identify druggable targets essential for sustaining the malignant phenotype but dispensable for normal tissue. We propose that the enzyme α-tubulin acetyl transferase ( ATAT1 ) meets these criteria. ATAT1 acetylates α-tubulin at lysine 40, which increases microtubule stability and promotes microtubule-based transport. While ATAT1 knockout mice have only a very mild phenotype, ATAT1 suppression in GBM has multiple therapeutic effects by reducing tumor invasion, proliferation, and therapeutic resistance. These translate not only into improved survival with ATAT1 targeting by itself, but also into synergy when ATAT1 deletion is combined with FDA approved therapies. This study strongly supports our conclusion that ATAT1 is a promising therapeutic target in GBM.

Abstract Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults with a poor prognosis of 15 months despite aggressive therapies. GBM malignancy is often driven by a high degree of inter- and intra-tumoral heterogeneity that is dynamic through time and regulated by interactions between tumor cells and their neural microenvironment. For instance, GBM tumors located near the lateral ventricles (LV) of the brain grow more aggressively and result in significantly worse patient survival, compared to tumors that grow far from the LV. This suggests that interactions between GBM and cells in the LV microenvironment may regulate tumor malignancy. Understanding the mechanisms underlying GBM malignancy near the LV is essential to determine if regulation of tumor biology is driven by the presence of healthy neural cells, and to ultimately develop therapeutic approaches that target GBM-LV interactions. Here, we tested the hypothesis that region-specific cellular identities and activation of unique transcriptional programs regulate GBM malignancy near the LV. Paired primary biopsies were collected from 14 GBM patients. Image-guided biopsies proximal and distal to the brain’s LV (LV-proximal GBM and LV-distal GBM, respectively) were processed for bulk RNA sequencing, single-nucleus RNA sequencing, and in situ spatial transcriptomic (Xenium) analyses. We found significant inter-patient and intra-tumoral transcriptional heterogeneity in GBM samples collected proximal and distal to the LV. After accounting for tumoral and patient heterogeneity, we found that proximal GBM tumors exhibit an increased immune-related gene signature, compared with tumors distal to the LV. Single-nucleus RNA sequencing and in situ spatial transcriptomic analyses showed no significant differences in the proportion of cellular states or identities between proximal and distal GBM samples. However, within each cellular identity, significant differences in gene expression were identified between proximal and distal GBM, suggesting that distinct cell-specific transcriptional pathways characterize regional differences in GBM biology. Our results suggest that GBM tumors near the LV have increased interactions with immune cells that lead to the enrichment of immune-related transcriptional pathways, compared to tumors growing far from the LV. This work will inform the development of therapies that target GBM-immune cell interactions to decrease tumor malignancy and improve individual patient outcomes. Citation Format: Maria F. Gonzalez-Aponte, Jhan C. Salazar, Aura Figueroa-Gonzalez, Emily S. Norton, Paola Suarez-Meade, Hugo Guerrero-Cazares. Integrating RNA sequencing and spatial transcriptomic analyses reveals drivers of glioblastoma malignancy near the brains’ lateral ventricles [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B035.

Abstract NF2-related schwannomatosis is a genetic condition characterized by mutation in the NF2 gene resulting in tumor formation throughout the nervous system. The most common tumors in these patients include bilateral vestibular schwannomas and multiple meningiomas which, despite their benign classification, lead to significant neurologic deficits including hearing loss, ataxia, hydrocephalus, and brainstem compression. Loss of NF2, which encodes the protein Merlin, is also the most common mutation in spontaneous meningiomas and schwannomas. Current treatment consists of resection followed by radiation for more aggressive tumors. Unfortunately, these treatments are not curative and are associated with significant risk due to tumor location, involvement of neurovasculature, cognitive impairment, and radiation-induced tumor induction. Therefore, identifying additional therapeutics for these patients is critical. Molecular profiling across large cohorts of sporadic meningiomas have identified molecular signatures associated with NF2 mutation, indicating upregulation of Wnt5a/b and the alternative Wnt5a/b-YAP/TAZ signaling pathway. In NF2 knock-out human arachnoid and Schwann cells, we find a significant upregulation of YAP in NF2-null lines compared to controls. Additionally, when stimulated with Wnt5a/b, controls upregulate both beta catenin (canonical Wnt) and YAP (alternative Wnt). However, in NF2-null lines only YAP is increased, indicating a preference for the alternative pathway in the absence of canonical Wnt signaling. In primary NF2-mutant meningioma lines, targeting this pathway via blocking Wnt secretion with the inhibitor LGK974 or YAP signaling with verteporfin, which is FDA approved, results in decreased cell viability and proliferation in vitro. These results indicate activation of the Wnt5a/b-YAP/TAZ alternative signaling pathway in NF2-mutant meningeal and Schwann cells, and a potential therapeutic effect of blocking this pathway in NF2-mutant meningiomas with a previously-FDA approved inhibitor. Additional research is needed on the receptors and molecular mediators playing a role in this pathway and how these drugs may have therapeutic benefits in vivo

Abstract Background Glioblastoma (GBM) is the most common high-grade primary malignant brain tumor, characterized by a notably poor prognosis. Current treatments for GBM have shown limited effectiveness in improving patient survival, highlighting the urgent need for novel therapeutic strategies. Combination therapy offers significant potential in overcoming resistance by targeting multiple signaling pathways; however, it often comes with increased toxicity compared to monotherapy. Co-encapsulating multiple therapeutic agents into a tumor-targeted drug delivery platform holds promise for overcoming these limitations and improving treatment outcomes. Methods We developed a tumor-targeted liposomal nanoformulation (TTL) using phospholipids, cholesterol, DSPE-(PEG)2000-OMe, and a proprietary tumor-targeting peptide (TTP). The TTL was loaded with everolimus (TTL-E), vinorelbine (TTL-V), rapamycin (TTL-R), a combination (TTL-EV), or (TTL-RV). These formulations were tested in vivo on orthotopic GBM mice, combined with temozolomide and radiation. RNA sequencing was performed to identify molecular and transcriptome changes post-treatment. Results TTL demonstrated tumor-specific uptake, effectively delivering drugs to GBM tumors. TTL-EV and TTL-RV outperformed single-drug formulations. Radiation combined with TTL-EV/RV improved tumor growth inhibition and survival, while temozolomide provided minimal benefit. Transcriptome analysis revealed differentially expressed genes (DEGs) linked to DNA damage repair, cell cycle, metabolism, and extracellular matrix pathways. Conclusion TTL crossed the blood-brain barrier, targeting tumors effectively. Radiation plus TTL-EV/RV enhanced tumor suppression and survival in GBM models. Gene expression analysis identified DEGs related to DNA damage and cell death. Mechanistic studies suggest TTL-EV plus radiation inhibits mTOR/MAPK pathways and sensitizes tumors to radiation. These findings offer a potential approach for improving GBM treatment.

Abstract Extracellular matrix (ECM) stiffening correlates with tumor invasion in various cancer types, including glioblastoma (GBM). Increased matrix stiffness promotes a migratory phenotype through dysregulation of cell-ECM bidirectional communication. Exposure to stiffer environments is sensed by cells, which then adapt in ways that promote invasive behavior. These adaptive changes are imprinted onto the cells and persist even after they are placed in new, softer microenvironments via a process known as “mechanical memory.” Mechanical memory is believed to be driven by mechanosensitive transcription factor activity and epigenetic remodeling. Glioblastoma recurrence is linked to the ability of cells to disperse and infiltrate the surrounding healthy tissue. Extracellular matrix stiffness in GBM is heterogeneous; it starts with a softer tumor core and becomes progressively stiffer toward the tumor’s edges, potentially promoting sustained tumor invasion through mechanical memory. This review discusses the role of ECM stiffness in cancer cell behavior and the implications of ECM stiffening in GBM. We then describe the findings associated with mechanical memory and relay underlying mechanisms currently understood to drive the preservation of mechanically primed phenotypes. Finally, we discuss how matrix stiffness can drive migratory phenotypes in GBM cells and the potential role that progressive ECM dysregulation at the tumor periphery can link the formation of invasive tumor niches to the aggressive, resistant, and mesenchymal-like phenotypes present in GBM recurrent tumors.

e13121 Background: Metastatic breast cancer remains a major clinical challenge, characterized by poor prognosis and limited therapeutic options. The incidence of metastatic female breast cancer increased from 5.8 to 7.9 per 100,000 females from 2001 to 2021. The Hippo pathway effector YAP1 plays a critical role in driving tumor growth and metastasis in many cancers including breast but little is known about the gene-specific changes that occur when breast cancers have metastasized. This study aimed to investigate the extent of genomic alterations, including copy number alterations (CNAs) and mutations, in YAP1 and its downstream genes in metastatic breast cancer compared to nonmetastatic breast cancer. Methods: Genomic data for the YAP1 gene and its downstream target genes (CTGF, Cyr61, MCL-1, TOP2A, FOSL2, and ANKRD1) were obtained from cBioPortal. This included mutation data and CNA data, considering both amplifications and deletions as CNA events. The chi-square test was performed using GraphPad Prism 10 to compare the frequencies of mutations and CNAs between metastatic and non-metastatic breast cancer cases. Results: A total of 2390 samples of metastatic breast cancer and 9289 samples of non-metastatic breast cancer were analyzed for mutations. Among them, a significantly higher percentage of mutations in the YAP1 (P ≤ 0.0001), ANKRD1 (P ≤ 0.0001), MCL-1 (P ≤ 0.0001), and TOP2A (P ≤ 0.0001) genes was observed in metastatic breast cancer compared to non-metastatic breast cancer. Evaluating CNAs in 2197 cases in the metastatic breast cancer group compared to 9289 cases in the non-metastatic breast cancer group demonstrated a significantly higher frequency of CNAs in the YAP1 ( P ≤ 0.0001), Cyr61 (P ≤ 0.0001), CTGF ( P ≤ 0.0001), ANKRD1 ( P ≤ 0.0001), TOP2A (P ≤ 0.0001) and FOSL2 (P ≤ 0.0001) genes among metastatic breast cancer. Conclusions: This study revealed significant genomic alterations in the YAP1 gene and its downstream genes in metastatic breast cancer. These findings highlight the importance of the YAP1 pathway in breast cancer metastasis and suggest that targeting this pathway may have therapeutic potential for primary and metastatic breast cancer. Frequency of mutations and copy number alterations (CNAs) in metastatic vs. non-metastatic breast cancer. Gene Metastatic Breast Cancer Mutation Frequency (%) Non-Metastatic Breast Cancer Mutation Frequency (%) P-value Metastatic Breast Cancer CNA Frequency (%) Non-Metastatic Breast Cancer CNA Frequency (%) P-value YAP1 0.75 0.17 <0.0001 5.1 1.18 <0.0001 CTGF 0.13 0.18 0.781 5.42 0.65 <0.0001 Cyr61 0.17 0.16 0.999 3.9 0.65 <0.0001 MCL-1 0.63 0.11 <0.0001 10.74 11.93 0.121 ANKRD1 1.17 0.09 <0.0001 1.96 0.25 <0.0001 TOP2A 0.96 0.18 <0.0001 8.06 3.6 <0.0001 FOSL2 0.17 0.1 0.317 3.64 0.62 <0.0001

Abstract The extracellular matrix (ECM) plays a critical role in cancer progression, with its biophysical properties influencing cancer behavior. ECM stiffness can induce long-lasting adaptations in cancer cells, promoting sustained invasion through a process known as “mechanical memory” (MM). Glioblastoma (GBM) exhibits spatial heterogeneity in stiffness, with stiffer ECM found at the tumor periphery where invasive cells reside and promote recurrence. We hypothesize that increased stiffness at the tumor periphery primes GBM cells for sustained invasion through MM. METHODS Cell lines were established from image-guided human GBM samples from tumor margin and core (n=10 patients, 20 cell lines). Cells from random locations were conditioned in physiologically relevant extracellular matrices for two weeks. Human organotypic assay (n=3), Migration Assays, Atomic Force Microscopy (AFM), Immunocytochemistry, Western Blot, and RNA-sequencing (n=6) were performed. RESULTS GBM cells at higher stiff surfaces displayed increased migration (p&lt;0.01). Magnetic Resonance Elastography (n=9) confirmed GBM heterogeneity, with softer cores (0.2-0.5kPa) transitioning to stiffer margins (&gt;2kPa). Organotypic scaffolds mimicking the tumor margin promoted enhanced migration of GFP-labeled GBM cells. Margin cells and cells conditioned on stiffer matrices demonstrated higher migratory potential compared to their core and soft-conditioned counterparts (p&lt;0.05). These trends persist over time and across multiple passages. ECM stiffness exposure causes nanomechanical, cytoskeletal, and transcriptional adaptations. AFM shows that cells from the margin (n=6) are softer (p&lt;0.01) and more deformable (p&lt;0.01). RNAseq identified upregulation of MM-specific genes in GBM margin cells. The mechanosensitive transcription factor YAP1 emerged as a key driver of MM. Notably, YAP1 is targetable by the FDA-approved drug Verteporfin. YAP1 expression was elevated in margin and stiff-conditioned cells (p&lt;0.05). Stiff-conditioned cells and margin cells displayed increased sensitivity to Verteporfin treatment (p&lt;0.05), with treatment significantly reducing margin migration compared to the core (p&lt;0.001). CONCLUSION Stiffer GBM margins promote the formation of aggressive phenotypes through MM. Targeting YAP1 with Verteporfin, a readily available drug, presents a promising strategy to halt GBM invasion and improve patient outcomes.

OBJECTIVE Chordomas are rare tumors of the skull base and spine believed to arise from the vestiges of the embryonic notochord. These tumors are locally aggressive and frequently recur following resection and adjuvant radiotherapy. Proton therapy has been introduced as a tissue-sparing option because of the higher level of precision that proton-beam techniques offer compared with traditional photon radiotherapy. This study aimed to compare recurrence in patients with chordomas receiving proton versus photon radiotherapy following resection by applying tree-based machine learning models. METHODS The clinical records of all patients treated with resection followed by adjuvant proton or photon radiotherapy for chordoma at Mayo Clinic were reviewed. Patient demographics, type of surgery and radiotherapy, tumor recurrence, and other variables were extracted. Decision tree classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS Fifty-three patients with a mean ± SD age of 55.2 ± 13.4 years receiving surgery and adjuvant proton or photon therapy to treat chordoma were identified; most patients were male. Gross-total resection was achieved in 54.7% of cases. Proton therapy was the most common adjuvant radiotherapy (84.9%), followed by conventional or external-beam radiation therapy (9.4%) and stereotactic radiosurgery (5.7%). Patients receiving proton therapy exhibited a 40% likelihood of having recurrence, significantly lower than the 88% likelihood observed in those treated with nonproton therapy. This was confirmed on logistic regression analysis adjusted for extent of tumor resection and tumor location, which revealed that proton adjuvant radiotherapy was associated with a decreased risk of recurrence (OR 0.1, 95% CI 0.01–0.71; p = 0.047) compared with photon therapy. The decision tree algorithm predicted recurrence with an accuracy of 90% (95% CI 55.5%–99.8%), with the lowest risk of recurrence observed in patients receiving gross-total resection with adjuvant proton therapy (23%). CONCLUSIONS Following resection, adjuvant proton therapy was associated with a lower risk of chordoma recurrence compared with photon therapy. The described machine learning models were able to predict tumor progression based on the extent of tumor resection and adjuvant radiotherapy modality used.

Abstract Glioblastoma remains as one of the deadliest malignancies with most cases likely to recur. Recent work has focused on characterizing not only glioma cells, but the tumor microenvironment via single-cell and spatial transcriptomic technologies. This has improved our understanding of the high heterogeneity of this disease and described potential tumor domains. However, there is still a need to further understand the changes that occur between the primary and the recurrent lesion. We propose that a spatial, multi-omic characterization of matched primary and recurrent glioblastoma can yield insights into recurrence mechanisms occurring throughout the tumor microenvironment. We collected 22 IDH-WT glioblastoma samples from 12 patients (11 primary, 11 recurrent, 10 matched pairs) from the Mayo Clinic Neuroscience Biobank. We performed single-nucleus RNA sequencing (15 samples, 10 patients, 5 matched pairs) and proteomics (16 samples, 6 matched pairs) from fresh-frozen tissue, as well as spatial transcriptomics with 10x Visium (14 samples, 8 patients, 6 matched pairs) and 10x Xenium in-situ molecular imaging (6 samples, 2 matched pairs). Using spatial transcriptomics data, we identified regional subsets present in different proportions and distributions between primary and recurrent glioblastoma. These clusters were characterized with gene set and gene ontology analysis, identifying regions enriched with known glioma subtypes and cellular activity. Spatial-based cluster genes were consistent with significantly differentially expressed proteins. We used single-nucleus RNAseq and in-situ molecular imaging data from matched tissue samples to further interrogate relevant cell populations and location in the tumor micro-environment. We identified regions with enriched extra cellular matrix interaction and remodeling signatures to be highly expressed in recurrent glioblastoma. Primary glioblastoma was enriched with oligodendrocyte-like regions with high cell communication and extracellular vesicle signatures. This study will further our understanding of the changes in the mechanisms at play in the complex ecosystem of glioblastoma as it recurs. Citation Format: Jean R. Clemenceau, Paola Suarez-Meade, Alfredo Quiñones-Hinojosa, Tae Hyun Hwang. Spatial and multi-omic interrogation of the primary and recurrent glioblastoma microenvironment [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 5482.

Abstract Differences in clonality, genomic and epigenetic alterations are known to occur between primary Glioblastoma (pGBM) and recurrent (rGBM), but this has been insufficient to yield a promising therapeutic approach. Recent studies show that the GBM tumor microenvironment (TME), composed of reactive glial cells, microglial subtypes, neuronal activity, myeloid cells, lymphocytes, etc., plays a crucial role in the invasiveness and evolution of the glioma cells. Nevertheless, how the spatial architecture and interplay among these cells facilitates GBM resurgence is largely unknown. To this point, we developed a pipeline for characterizing the TME changes using single nucleus and spatial transcriptomics (ST). We retrospectively collected matched, fresh-frozen, IDH-wildtype pGBM and rGBM samples (n=14, 7 patients) from the Mayo Clinic Neuroscience Biobank. Single nucleus RNA sequencing was performed using the 10x Chromium platform. Matched FFPE blocks from 8 samples were collected from the Mayo Clinic pathology department for 4 of the 7 patients. A region of interest was identified from the corresponding histopathology slide by a pathologist, avoiding areas of necrosis and hemorrhage. The region was collected from the block using a 5mm biopsy punch. The tissue was re-paraffinized, and a 5µm thick section was used to perform ST with the 10x Visium for FFPE platform. We performed transcriptomic and image texture-based clustering of capture dots along with differential gene expression analysis. Based on gene expression, we identified and characterized conserved regions across samples. We used single nucleus data to infer cell composition. Spatial correlation and autocorrelation statistics were calculated on features, such as gene expression, gene set scores, cell type prediction, and antibody capture. The features’ relative spatial changes were compared between pGBM and rGBM. Our analyses showed high heterogeneity within and across samples, but we found higher molecular and textural heterogeneity in rGBM samples compared to pGBM. We found higher androgen response activity (p &lt; 0.001) presents diffusely (I: 0.09) throughout rGBM tissue but localized to mesenchymal-like regions in pGBM (I: 0.15). KRAS signaling signature was decreased in pGBM (p &lt; 0.01) and increased in rGBM (p &lt; 0.01). This increase was significantly overexpressed in cluster 0 for rGBM (p=0.02), which is an area characterized by neural progenitor signature. No significant difference in KRAS or EGFR magnitude or distribution of expression was present for either GBM type, indicating an independent mechanism for pGBM. We established a pipeline for assessing the spatio-temporal changes of the GBM TME. We found evidence indicating differences in the type of growth signaling, the cells bing targeted, and their distribution across the TME between pGBM and rGBM. Our work suggests how ST can help us better understand the intricate dynamics of GBM. Citation Format: Jean R. Clemenceau, Paola Suarez Meade, Mark E. Jentoft, Alfredo Quiñones-Hinojosa, Tae Hyun Hwang. Spatial transcriptomic landscape of the primary and recurrent glioblastoma tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 144.