Glycomaterials to Investigate the Functional Role of Aberrant Glycosylation in Glioblastoma

Glycation Interferes with the Expression of Sialyltransferases and Leads to Increased Polysialylation in Glioblastoma Cells

Glioblastoma (GBM) is a highly aggressive brain tumor that often utilizes aerobic glycolysis for energy production (Warburg effect), resulting in increased methylglyoxal (MGO) production. MGO, a reactive dicarbonyl compound, causes protein alterations and cellular dysfunction via glycation. In this study, we investigated the effect of glycation on sialylation, a common post-translational modification implicated in cancer. Our experiments using glioma cell lines, human astrocytes (hA), and primary glioma samples revealed different gene expressions of sialyltransferases among cells, highlighting the complexity of the system. Glycation has a differential effect on sialyltransferase expression, upregulating ST8SIA4 in the LN229 and U251 cell lines and decreasing the expression in normal hA. Subsequently, polysialylation increased in the LN229 and U251 cell lines and decreased in hA. This increase in polysialylation could lead to a more aggressive phenotype due to its involvement in cancer hallmark processes such as immune evasion, resistance to apoptosis, and enhancing invasion. Our findings provide insights into the mechanisms underlying GBM aggressiveness and suggest that targeting glycation and sialylation could be a potential therapeutic strategy.

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

BACKGROUND

Gliomas are the most common brain tumours with the high-grade glioblastoma representing the most aggressive and lethal form. Currently, there is a lack of specific glioma biomarkers that would aid tumour subtyping and minimally invasive early diagnosis. Aberrant glycosylation is an important post-translational modification in cancer and is implicated in glioma progression. Raman spectroscopy (RS), a vibrational spectroscopic label-free technique, has already shown promise in cancer diagnostics.

METHODS

RS was combined with machine learning to discriminate glioma grades. Raman spectral signatures of glycosylation patterns were used in serum samples and fixed tissue biopsy samples, as well as in single cells and spheroids.

RESULTS

Glioma grades in fixed tissue patient samples and serum were discriminated with high accuracy. Discrimination between higher malignant glioma grades (III and IV) was achieved with high accuracy in tissue, serum, and cellular models using single cells and spheroids. Biomolecular changes were assigned to alterations in glycosylation corroborated by analysing glycan standards and other changes such as carotenoid antioxidant content.

CONCLUSION

RS combined with machine learning could pave the way for more objective and less invasive grading of glioma patients, serving as a useful tool to facilitate glioma diagnosis and delineate biomolecular glioma progression changes.

Meta-Analysis of RNA-Seq Datasets Identifies Novel Players in Glioblastoma

Glioblastoma is a devastating grade IV glioma with poor prognosis. Identification of predictive molecular biomarkers of disease progression would substantially contribute to better disease management. In the current study, we performed a meta-analysis of different RNA-seq datasets to identify differentially expressed protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs). This meta-analysis aimed to improve power and reproducibility of the individual studies while identifying overlapping disease-relevant pathways. We supplemented the meta-analysis with small RNA-seq on glioblastoma tissue samples to provide an overall transcriptomic view of glioblastoma. Co-expression correlation of filtered differentially expressed PCGs and lncRNAs identified a functionally relevant sub-cluster containing DANCR and SNHG6, with two novel lncRNAs and two novel PCGs. Small RNA-seq of glioblastoma tissues identified five differentially expressed microRNAs of which three interacted with the functionally relevant sub-cluster. Pathway analysis of this sub-cluster identified several glioblastoma-linked pathways, which were also previously associated with the novel cell death pathway, ferroptosis. In conclusion, the current meta-analysis strengthens evidence of an overarching involvement of ferroptosis in glioblastoma pathogenesis and also suggests some candidates for further analyses.

A hypoxia-dissociable siRNA nanoplatform for synergistically enhanced chemo-radiotherapy of glioblastoma

Glioblastoma (GBM), as the most aggressive adult brain tumor, seriously threatened people's lives with a low survival time. Standard postoperative treatment, chemotherapy combined with radiotherapy (RT), was the major therapeutic strategy for GBM. However, this therapeutic efficacy was hindered by chemoradiotherapy resistance of GBM. Herein, to sensitize temozolomide (TMZ)-based chemotherapy and RT, a hypoxia-radiosensitive nanoparticle for co-delivering TMZ and siMGMT (RDPP(Met)/TMZ/siMGMT) was synthesized in this study. Our nanoparticle could effectively release the encapsulated alkylating agent (TMZ) and small interfering O6-methylguanine-DNA-methyltransferase RNA (siMGMT) in the hypoxic GBM. DNA-damage repair was effectively inhibited by down-regulating MGMT expression and activating cell apoptosis, which obviously enhanced the sensitivity of TMZ as well as RT. In vitro and in vivo experiments showed that RDPP(Met)/TMZ/siMGMT could efficiently penetrate the blood-brain barrier (BBB), accurately target GBM cells and effectively inhibit GBM proliferation. Compared with traditional TMZ combined with RT, RDPP(Met)/TMZ/siMGMT remarkably improved the survival time of orthotopic GBM-bearing mice, which demonstrated that our nanoplatform was an efficient combinatorial GBM therapy.

Identification of glycogene signature as a tool to predict the clinical outcome and immunotherapy response in breast cancer

Background

Breast cancer is one of the most important diseases in women around the world. Glycosylation modification correlates with carcinogenesis and roles of glycogenes in the clinical outcome and immune microenvironment of breast cancer are unclear.

Methods

A total of 1297 breast cancer and normal cases in the TCGA and GTEx databases were enrolled and the transcriptional and survival information were extracted to identify prognostic glycogenes using Univariate Cox, LASSO regression, Multivariate Cox analyses and Kaplan-Meier method. The immune infiltration pattern was explored by the single sample gene set enrichment method. The HLA and immune checkpoint genes expression were also compared in different risk groups. The expressions of a glycogene MGAT5 as well as its products were validated by immunohistochemistry and western blotting in breast cancer tissues and cells.

Results

A 19-glycogene signature was identified to separate breast cancer patients into high- and low-risk groups with distinct overall survival rates (P < 0.001). Compared with the high-risk group, proportion of naive B cells, plasma cells and CD8⁺ T cells increased in the low-risk group (P < 0.001). Besides, expressions of HLA and checkpoint genes, such as CD274, CTLA4, LAG3 and TIGIT3, were upregulated in low-risk group. Additionally, highly expressed MGAT5 was validated in breast cancer tissues and cells. Downstream glycosylation products of MGAT5 were all increased in breast cancer.

Conclusions

We identified a 19-glycogene signature for risk prediction of breast cancer patients. Patients in the low-risk group demonstrated a higher immune infiltration and better immunotherapy response. The validation of MGAT5 protein suggests a probable pathway and target for the development and treatment of breast cancer.

Glycan-Lectin Interactions as Novel Immunosuppression Drivers in Glioblastoma

Despite diagnostic and therapeutic improvements, glioblastoma (GB) remains one of the most threatening brain tumor in adults, underlining the urgent need of new therapeutic targets. Lectins are glycan-binding proteins that regulate several biological processes through the recognition of specific sugar motifs. Lectins and their ligands are found on immune cells, endothelial cells and, also, tumor cells, pointing out a strong correlation among immunity, tumor microenvironment and vascularization. In GB, altered glycans and lectins contribute to tumor progression and immune evasion, shaping the tumor-immune landscape promoting immunosuppressive cell subsets, such as myeloid-derived suppressor cells (MDSCs) and M2-macrophages, and affecting immunoeffector populations, such as CD8⁺ T cells and dendritic cells (DCs). Here, we discuss the latest knowledge on the immune cells, immune related lectin receptors (C-type lectins, Siglecs, galectins) and changes in glycosylation that are involved in immunosuppressive mechanisms in GB, highlighting their interest as possible novel therapeutical targets.