EGFRvIII tumorigenicity requires PDGFRA co-signaling and reveals therapeutic vulnerabilities in glioblastoma

Differential Expression of SRY-Related HMG-Box Transcription Factor 2, Oligodendrocyte Lineage Transcription Factor 2, and Zinc Finger E-Box Binding Homeobox 1 in Serum-Derived Extracellular Vesicles: Implications for Mithramycin Sensitivity and Targeted Therapy in High-Grade Glioma

Glioblastoma multiforme (GBM) is the most aggressive type of glioma and is often resistant to traditional therapies. Evidence suggests that glioma stem cells (GSCs) contribute to this resistance. Mithramycin (Mit-A) targets GSCs and exhibits antitumor activity in GBM by affecting transcriptional targets such as SRY-related HMG-box transcription factor 2 (SOX2), oligodendrocyte lineage transcription factor 2 (OLIG2), and zinc finger E-box binding homeobox 1 (ZEB1). However, its clinical use has been limited by toxicity. This study explored the diagnostic potential of serum extracellular vesicles (EVs) to identify Mit-A responders. Serum EVs were isolated from 70 glioma patients, and targeted gene expression was analyzed using qRT-PCR. Using chemosensitivity assay, we identified 8 Mit-A responders and 17 nonresponders among 25 glioma patients. The M-score showed a significant correlation (p = 0.045) with isocitrate dehydrogenase 1 mutation but not other clinical variables. The genes SOX2 (p = 0.005), OLIG2 (p = 0.003), and ZEB1 (p = 0.0281) were found to be upregulated in the responder EVs. SOX2 had the highest diagnostic potential (AUC = 0.875), followed by OLIG2 (AUC = 0.772) and ZEB1 (AUC = 0.632).The combined gene panel showed significant diagnostic efficacy (AUC = 0.956) through logistic regression analysis. The gene panel was further validated in the serum EVs of 45 glioma patients. These findings highlight the potential of Mit-A as a targeted therapy for high-grade glioma based on differential gene expression in serum EVs. The gene panel could serve as a diagnostic tool to predict Mit-A sensitivity, offering a promising approach for personalized treatment strategies and emphasizing the role of GSCs in therapeutic resistance.

Targeting glioblastoma tumor hyaluronan to enhance therapeutic interventions that regulate metabolic cell properties

Despite extensive advances in cancer research, glioblastoma (GBM) still remains a very locally invasive and thus challenging tumor to treat, with a poor median survival. Tumor cells remodel their microenvironment and utilize extracellular matrix to promote invasion and therapeutic resistance. We aim here to determine how GBM cells exploit hyaluronan (HA) to maintain proliferation using ligand-receptor dependent and ligand-receptor independent signaling. We use tissue engineering approaches to recreate the three-dimensional tumor microenvironment in vitro, then analyze shifts in metabolism, hyaluronan secretion, HA molecular weight distribution, as well as hyaluronan synthetic enzymes (HAS) and hyaluronidases (HYAL) activity in an array of patient derived xenograft GBM cells. We reveal that endogenous HA plays a role in mitochondrial respiration and cell proliferation in a tumor subtype dependent manner. We propose a tumor specific combination treatment of HYAL and HAS inhibitors to disrupt the HA stabilizing role in GBM cells. Taken together, these data shed light on the dual metabolic and ligand - dependent signaling roles of hyaluronan in glioblastoma.

Significance

The control of aberrant hyaluronan metabolism in the tumor microenvironment can improve the efficacy of current treatments. Bioengineered preclinical models demonstrate potential to predict, stratify and accelerate the development of cancer treatments.

Glioblastoma preclinical models: Strengths and weaknesses

Glioblastoma multiforme is a highly malignant brain tumor with significant intra- and intertumoral heterogeneity known for its aggressive nature and poor prognosis. The complex signaling cascade that regulates this heterogeneity makes targeted drug therapy ineffective. The development of an optimal preclinical model is crucial for the comprehension of molecular heterogeneity and enhancing therapeutic efficacy. The ideal model should establish a relationship between various oncogenes and their corresponding responses. This review presents an analysis of preclinical in vivo and in vitro models that have contributed to the advancement of knowledge in model development. The experimental designs utilized in vivo models consisting of both immunodeficient and immunocompetent mice induced with intracranial glioma. The transgenic model was generated using various techniques, like the viral vector delivery system, transposon system, Cre-LoxP model, and CRISPR-Cas9 approaches. The utilization of the patient-derived xenograft model in glioma research is valuable because it closely replicates the human glioma microenvironment, providing evidence of tumor heterogeneity. The utilization of in vitro techniques in the initial stages of research facilitated the comprehension of molecular interactions. However, these techniques are inadequate in reproducing the interactions between cells and extracellular matrix (ECM). As a result, bioengineered 3D-in vitro models, including spheroids, scaffolds, and brain organoids, were developed to cultivate glioma cells in a three-dimensional environment. These models have enabled researchers to understand the influence of ECM on the invasive nature of tumors. Collectively, these preclinical models effectively depict the molecular pathways and facilitate the evaluation of multiple molecules while tailoring drug therapy.

Synthetic viability induces resistance to immune checkpoint inhibitors in cancer cells

BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized the treatment for multiple cancers. However, most of patients encounter resistance. Synthetic viability (SV) between genes could induce resistance. In this study, we established SV signature to predict the efficacy of ICI treatment for melanoma.

METHODS

We collected features and predicted SV gene pairs by random forest classifier. This work prioritized SV gene pairs based on CRISPR/Cas9 screens. SV gene pairs signature were constructed to predict the response to ICI for melanoma patients.

RESULTS

This study predicted robust SV gene pairs based on 14 features. Filtered by CRISPR/Cas9 screens, we identified 1,861 SV gene pairs, which were also related with prognosis across multiple cancer types. Next, we constructed the six SV pairs signature to predict resistance to ICI for melanoma patients. This study applied the six SV pairs signature to divide melanoma patients into high-risk and low-risk. High-risk melanoma patients were associated with worse response after ICI treatment. Immune landscape analysis revealed that high-risk melanoma patients had lower natural killer cells and CD8+ T cells infiltration.

CONCLUSIONS

In summary, the 14 features classifier accurately predicted robust SV gene pairs for cancer. The six SV pairs signature could predict resistance to ICI.

Driver Mutations Dictate the Immunologic Landscape and Response to Checkpoint Immunotherapy of Glioblastoma

The composition of the tumor immune microenvironment (TIME) is considered a key determinant of patients' response to immunotherapy. The mechanisms underlying TIME formation and development over time are poorly understood. Glioblastoma (GBM) is a lethal primary brain cancer for which there are no curative treatments. GBMs are immunologically heterogeneous and impervious to checkpoint blockade immunotherapies. Utilizing clinically relevant genetic mouse models of GBM, we identified distinct immune landscapes associated with expression of EGFR wild-type and mutant EGFRvIII cancer driver mutations. Over time, accumulation of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) was more pronounced in EGFRvIII-driven GBMs and was correlated with resistance to PD-1 and CTLA-4 combination checkpoint blockade immunotherapy. We determined that GBM-secreted CXCL1/2/3 and PMN-MDSC-expressed CXCR2 formed an axis regulating output of PMN-MDSCs from the bone marrow leading to systemic increase in these cells in the spleen and GBM tumor-draining lymph nodes. Pharmacologic targeting of this axis induced a systemic decrease in the numbers of PMN-MDSC, facilitated responses to PD-1 and CTLA-4 combination checkpoint blocking immunotherapy, and prolonged survival in mice bearing EGFRvIII-driven GBM. Our results uncover a relationship between cancer driver mutations, TIME composition, and sensitivity to checkpoint blockade in GBM and support the stratification of patients with GBM for checkpoint blockade therapy based on integrated genotypic and immunologic profiles.

Co-amplified with PDGFRA, IGFBP7 is a prognostic biomarker correlated with the immune infiltrations of glioma

BACKGROUND

A subgroup of glioma carry genetic 4q12 amplification including platelet derived growth factor receptor α (PDGFRA) and insulin like growth factor binding protein 7 (IGFBP7). However, the prognosis of PDGFRA and IGFBP7 in glioma is unclear.

METHODS

The prognosis of PDGFRA and IGFBP7 was determined using cox regression and Kaplan-Meier survival analysis. Pathways associated with IGFBP7 were analyzed through gene set enrichment analysis (GSEA). Immune profiling of glioma was determined using "ESTIMATE" and "TIMER" database.

RESULTS

PDGFRA amplification or expression was not correlated with the outcomes of glioblastoma (GBM). IGFBP7 but not PDGFRA was over-expressed in GBM. IGFBP7 over-expression was correlated with the unfavorable outcomes of GBM. In lower grade glioma (LGG), PDGFRA over-expression was not correlated with the unfavorable prognosis of LGG, while, IGFBP7 was a prognostic biomarker of LGG. LGG patients with IGFBP7 lower expressions had prolonged clinical overall survival. Combination of IDH mutation, LGG grade and IGFBP7 achieved even better prognostic effects in LGG. Moreover, IGFBP7 was over-expressed in glioma patients with wild type IDH or with high grades. IGFBP7 over-expression was correlated with the unfavorable outcomes of glioma. Furthermore, IGFBP7 was hypo-methylated in GBM or LGG patients without IDH mutations. IGFBP7 hyper-methylation was correlated with the lower overall survival of GBM or LGG. LGG patients with wild type IDH and with IGFBP7 hypo-methylation demonstrated even worse prognosis. IGFBP7 was associated with multiple immune-related signaling pathways in GBM or LGG. The stromal score, immune score and the infiltrations of immune cells were also correlated with IGFBP7 and the prognosis of LGG.

CONCLUSIONS

IGFBP7 but not PDGFRA served an ideal prognostic marker and therapeutic target of glioma.

WSD-0922, a novel brain-penetrant inhibitor of epidermal growth factor receptor, promotes survival in glioblastoma mouse models

Background

Although the epidermal growth factor receptor (EGFR) is a frequent oncogenic driver in glioblastoma (GBM), efforts to therapeutically target this protein have been largely unsuccessful. The present preclinical study evaluated the novel EGFR inhibitor WSD-0922.

Methods

We employed flank and orthotopic patient-derived xenograft models to characterize WSD-0922 and compare its efficacy to erlotinib, a potent EGFR inhibitor that failed to provide benefit for GBM patients. We performed long-term survival studies and collected short-term tumor, plasma, and whole-brain samples from mice treated with each drug. We utilized mass spectrometry to measure drug concentrations and spatial distribution and to assess the impact of each drug on receptor activity and cellular signaling networks.

Results

WSD-0922 inhibited EGFR signaling as effectively as erlotinib in in vitro and in vivo models. While WSD-0922 was more CNS penetrant than erlotinib in terms of total concentration, comparable concentrations of both drugs were measured at the tumor site in orthotopic models, and the concentration of free WSD-0922 in the brain was significantly less than the concentration of free erlotinib. WSD-0922 treatment provided a clear survival advantage compared to erlotinib in the GBM39 model, with marked suppression of tumor growth and most mice surviving until the end of the study. WSD-0922 treatment preferentially inhibited phosphorylation of several proteins, including those associated with EGFR inhibitor resistance and cell metabolism.

Conclusions

WSD-0922 is a highly potent inhibitor of EGFR in GBM, and warrants further evaluation in clinical studies.

Leveraging extrachromosomal DNA to fine-tune trials of targeted therapy for glioblastoma: opportunities and challenges

Glioblastoma evolution is facilitated by intratumour heterogeneity, which poses a major hurdle to effective treatment. Evidence indicates a key role for oncogene amplification on extrachromosomal DNA (ecDNA) in accelerating tumour evolution and thus resistance to treatment, particularly in glioblastomas. Oncogenes contained within ecDNA can reach high copy numbers and expression levels, and their unequal segregation can result in more rapid copy number changes in response to therapy than is possible through natural selection of intrachromosomal genomic loci. Notably, targeted therapies inhibiting oncogenic pathways have failed to improve glioblastoma outcomes. In this Perspective, we outline reasons for this disappointing lack of clinical translation and present the emerging evidence implicating ecDNA as an important driver of tumour evolution. Furthermore, we suggest that through detection of ecDNA, patient selection for clinical trials of novel agents can be optimized to include those most likely to benefit based on current understanding of resistance mechanisms. We discuss the challenges to successful translation of this approach, including accurate detection of ecDNA in tumour tissue with novel technologies, development of faithful preclinical models for predicting the efficacy of novel agents in the presence of ecDNA oncogenes, and understanding the mechanisms of ecDNA formation during cancer evolution and how they could be attenuated therapeutically. Finally, we evaluate the feasibility of routine ecDNA characterization in the clinic and how this process could be integrated with other methods of molecular stratification to maximize the potential for clinical translation of precision medicines.

Single-cell RNA sequencing reveals evolution of immune landscape during glioblastoma progression

Glioblastoma (GBM) is an incurable primary malignant brain cancer hallmarked with a substantial protumorigenic immune component. Knowledge of the GBM immune microenvironment during tumor evolution and standard of care treatments is limited. Using single-cell transcriptomics and flow cytometry, we unveiled large-scale comprehensive longitudinal changes in immune cell composition throughout tumor progression in an epidermal growth factor receptor-driven genetic mouse GBM model. We identified subsets of proinflammatory microglia in developing GBMs and anti-inflammatory macrophages and protumorigenic myeloid-derived suppressors cells in end-stage tumors, an evolution that parallels breakdown of the blood-brain barrier and extensive growth of epidermal growth factor receptor⁺ GBM cells. A similar relationship was found between microglia and macrophages in patient biopsies of low-grade glioma and GBM. Temozolomide decreased the accumulation of myeloid-derived suppressor cells, whereas concomitant temozolomide irradiation increased intratumoral GranzymeB⁺ CD8⁺T cells but also increased CD4⁺ regulatory T cells. These results provide a comprehensive and unbiased immune cellular landscape and its evolutionary changes during GBM progression.