Anti-angiogenic and macrophage-based therapeutic strategies for glioma immunotherapy

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomarkers is crucial to enhance the prognostic assessment of glioma and to investigate more effective treatment options. In this research, we utilized multiple machine learning techniques to assess the significance of genes related to angiogenesis and epithelial-mesenchymal transition (EMT) in the context of prognosis and treatment for glioma patients. The random forest algorithm highlighted the significance of CALU, and further analysis indicated that the effect of CALU on glioma progression may be regulated by MYC. Different machine learning approaches were employed in our investigation to uncover crucial genes associated with angiogenesis and EMT in glioma. Our findings verify the connection between these genes and the prognosis of patients with glioma, as well as the results of immunotherapeutic interventions. Notably, through experimental verification, we identified CALU as a new prognostic marker for glioma, and inhibiting the expression of CALU can impede the progression of glioma.

An update to experimental and clinical aspects of tumor-associated macrophages in cancer development: hopes and pitfalls

Tumor-associated macrophages (TAMs) represent one of the most abundant tumor-infiltrating stromal cells, and their normal function in tumor microenvironment (TME) is to suppress tumor cells by producing cytokines which trigger both direct cell cytotoxicity and antibody-mediated immune response. However, upon prolonged exposure to TME, the classical function of these so-called M1-type TAMs can be converted to another type, "M2-type," which are recruited by tumor cells so that they promote tumor growth and metastasis. This is the reason why the accumulation of TAMs in TME is correlated with poor prognosis in cancer patients. Both M1- and M2-types have high degree of plasticity, and M2-type cells can be reprogrammed to M1-type for therapeutic purposes. This characteristic introduces TAMs as promising target for developing novel cancer treatments. In addition, inhibition of M2-type cells and blocking their recruitment in TME, as well as their depletion by inducing apoptosis, are other approaches for effective immunotherapy of cancer. In this review, we summarize the potential of TAMs to be targeted for cancer immunotherapy and provide an up-to-date about novel strategies for targeting TAMs.

Glioma hexokinase 3 positively correlates with malignancy and macrophage infiltration

BACKGROUND

Glioma is the main subtype of primary central nervous system (CNS) tumor with high malignancy and poor prognosis under current therapeutic approaches. Glycolysis and suppressive tumor microenvironment (TME) are key markers of glioma with great importance for aggressive features of glioma and inferior clinical outcomes. Hexokinase 3 (HK3) is an important rate-limiting enzyme in glycolysis, but its function in glioma remains unknown.

METHODS

This study comprehensively assessed the expression distribution and immunological effect of HK3 via pan-cancer analysis based on datasets from Genotype Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA). Furthermore, it explored the malignant phenotype and genomic landscape between low-HK3 and high-HK3 expression groups in gliomas from Chinese Glioma Genome Atlas (CGGA) and TCGA. Moreover, data from the TIMER website predicted the relationship between macrophage infiltration and HK3 expression. Also, single-cell sequencing data were used to validate the relationship.

RESULTS

For pan-cancer patients, HK3 was expressed in various cancers. The results showed that HK3 was highly expressed in gliomas and positively correlated with tumor-infiltrating immune cells (TIICs), immune checkpoints, immunomodulators, and chemokines. Meanwhile, HK3 expression was highest in normal immune cells and tissues. In gliomas, the expression of HK3 was found to be closely correlated with the malignant clinical characteristics and the infiltration of macrophages. Also, HK3 was proven to be positively associated with macrophage through single-cell sequencing data and immunohistochemistry techniques. Finally, it is predicted that samples with high HK3 expression are often malignant entities and also significant genomic aberrations of driver oncogenes.

CONCLUSIONS

This is the first comprehensive research to figure out the relationship between HK3 and TME characteristics in gliomas. HK3 is positively associated with macrophage infiltration and can induce the immunosuppressive TME and malignant phenotype of gliomas.

The role of angiogenic growth factors in the immune microenvironment of glioma

Angiogenic growth factors (AGFs) are a class of secreted cytokines related to angiogenesis that mainly include vascular endothelial growth factors (VEGFs), stromal-derived factor-1 (SDF-1), platelet-derived growth factors (PDGFs), fibroblast growth factors (FGFs), transforming growth factor-beta (TGF-β) and angiopoietins (ANGs). Accumulating evidence indicates that the role of AGFs is not only limited to tumor angiogenesis but also participating in tumor progression by other mechanisms that go beyond their angiogenic role. AGFs were shown to be upregulated in the glioma microenvironment characterized by extensive angiogenesis and high immunosuppression. AGFs produced by tumor and stromal cells can exert an immunomodulatory role in the glioma microenvironment by interacting with immune cells. This review aims to sum up the interactions among AGFs, immune cells and cancer cells with a particular emphasis on glioma and tries to provide new perspectives for understanding the glioma immune microenvironment and in-depth explorations for anti-glioma therapy.

A specific immune signature for predicting the prognosis of glioma patients with IDH1-mutation and guiding immune checkpoint blockade therapy

Isocitrate dehydrogenase (IDH1) is frequently mutated in glioma tissues, and this mutation mediates specific tumor-promoting mechanisms in glioma cells. We aimed to identify specific immune biomarkers for IDH1-mutation (IDH1mt) glioma. The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) were used to obtain RNA sequencing data and clinical characteristics of glioma tissues, while the stromal and immune scores of TCGA glioma tissues were determined using the ESTIMATE algorithm. Differentially expressed genes (DEGs), the protein–protein interaction(PPI) network, and least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were used to select hub genes associated with stroma and immune scores and the prognoses of patients and to construct the risk model. The practicability and specificity of the risk model in both IDH1mt and IDH1-wildtype (wtIDH1) gliomas in TCGA and CGGA were evaluated. Molecular mechanisms, immunological characteristics and benefits of immune checkpoint blockade therapy in glioma tissues with IDH1mt were analyzed using GSEA, immunohistochemical staining, CIBERSORT, and T-cell dysfunction and exclusion (TIDE) analysis. The overall survival rate for IDH1mt-glioma patients with high stroma/immune scores was lower than that for those with low stroma/immune scores. A total of 222 DEGs were identified in IDH1mt glioma tissues with high stroma/immune scores. Among them, 72 genes had interactions in the PPI network, while three genes, HLA-DQA2, HOXA3, and SAA2, were selected as hub genes and used to construct risk models classifying patients into high- and low-risk score groups, followed by LASSO and Cox regression analyses. This risk model showed prognostic value in IDH1mt glioma in both TCGA and CCGA; nevertheless, the model was not suitable for wtIDH1 glioma. The risk model may act as an independent prognostic factor for IDH1mt glioma. IDH1mt glioma tissues from patients with high-risk scores showed more infiltration of M1 and CD8 T cells than those from patients with low-risk scores. Moreover, TIDE analysis showed that immune checkpoint blockade(ICB) therapy was highly beneficial for IDH1mt patients with high-risk scores. The risk model showed specific potential to predict the prognosis of IDH1mt-glioma patients, as well as guide ICB, contributing to the diagnosis and therapy of IDH1mt-glioma patients.

NCAPG Promotes Tumor Progression and Modulates Immune Cell Infiltration in Glioma

Glioma is one of the most deadly types of brain cancer. As it is highly invasive, the prognosis for glioma patients remains dismal, with median survival rarely exceeding 16 months. Thus, developing a new prognostic biomarker for glioma and investigating its molecular mechanisms is necessary for the development of an efficient treatment strategy. In this study, we analyzed a cohort of 1,131 glioma patients using RNA-seq data from The Cancer Genome Atlas (TCGA project) and Gene Expression Omnibus (GSE4290 and GSE16011 datasets), and validated the results using the RNA-seq data of 1,018 gliomas from the Chinese Glioma Genome Atlas (CGGA project). We used the R language as the main tool for statistical analysis and data visualization. We found that NCAPG, a mitosis-associated chromosomal condensing protein, is highly expressed in glioma tissues. Furthermore, the expression of NCAPG increased significantly with the increase in tumor grade, and high NCAPG expression was found to be a predictor of poor overall survival in glioma patients (P < 0.001). This result shows that NCAPG expression could be an independent prognostic factor. Importantly, when the expression of NCAPG was knocked down, the CCK-8 assay revealed that the proliferation of glioma cells (LN-229 and T98G cell lines) decreased significantly compared with the control group. In addition, the healing rates of these cells were significantly lower in the si-NCAPG group than in the control group (P < 0.001). We then used the CIBERSORT algorithm to analyze the expression levels of 22 subpopulations of immune cells and found that NCAPG was significantly negatively correlated with natural killer cell activation. In addition, it was positively correlated with MHC-I molecules and ADAM17. Our study is first in comprehensively describing the high expression of NCAPG in glioma. It also shows that NCAPG can function as an independent prognostic predictor of glioma, and that targeting NCAPG can be a new strategy for the treatment of glioma patients.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

LncRNA CDKN2B-AS1 contributes to glioma development by regulating the miR-199a-5p/DDR1 axis

BACKGROUND

Although cyclin-dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1) is upregulated in glioma, its function and potential mechanism in glioma remain unclear.

METHODS

CDKN2B-AS1 level in glioma tissues and cell lines LN229, U251, and U87 was measured by qRT-PCR. Loss-of-function assays using short hairpin RNA for CDKN2B-AS1 (sh-CDKN2B-AS1) were performed to evaluate the effect of CDKN2B-AS1 on cell invasion, migration, proliferation, and apoptosis. The relationship among CDKN2B-AS1, miR-199a-5p, and DDR1 was determined by bioinformatics analysis and luciferase reporter assay. Rescue experiments were conducted to explore the function of CDKN2B-AS1 and miR-199a-5p in glioma. An in vivo animal model of lentivirally transduced U87 glioma xenografts in mice was established to confirm the role of CDKN2B-AS1.

RESULTS

CDKN2B-AS1 is significantly upregulated in glioma tissues and cell lines. CDKN2B-AS1 knockdown significantly inhibits cell proliferation, invasion, and migration, while promoting apoptosis of glioma cell lines U251 and U87. Further, a miR-199a-5p inhibitor attenuates the inhibitory effects of sh-CDKN2B-AS1 on these cell phenotypes. CDKN2B-AS1 positively regulates DDR1 expression by directly sponging miR-199a-5p. Moreover, CDKN2B-AS1 knockdown efficiently inhibits U87 tumor xenograft growth in mice.

CONCLUSION

Our study reveals that CDKN2B-AS1 promotes glioma development by regulating the miR-199a-5p/DDR1 axis, suggesting that this lncRNA might be a potential therapeutic target.

Identification of Immune Cell Infiltration Landscape and Their Prognostic Significance in Uveal Melanoma

Uveal melanoma (UVM) is the most common primary intraocular cancer in adults. Increasing evidence has demonstrated that immune cell infiltration (ICI) is crucial in predicting patient outcomes and therapeutic efficacy. Thus, describing the immune cell infiltrative landscape of UVM tumors may yield a novel prognostic marker and provide direction for immunotherapeutic selection. In this study, the gene expression data and clinical information of UVM patients were obtained from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases. The ICI landscape of UVM was analyzed using the CIBERSORT and ESTIMATE algorithms. Two ICI phenotypes were defined, and the ICI scores were calculated by using principal component analysis algorithms. We found that a subtype with high ICI scores had poorer prognosis and increased expression levels of immune checkpoint-related genes. This study demonstrates that ICI scores are an independent prognostic biomarker and highlights their value in predicting immunotherapeutic outcomes.