Profiling of inhibitory immune checkpoints in glioblastoma: Potential pathogenetic players

Radiation-Triggered Selenium-Engineered Mesoporous Silica Nanocapsules for RNAi Therapy in Radiotherapy-Resistant Glioblastoma

Radiotherapy-resistant glioblastoma (rrGBM) remains a significant clinical challenge because of high infiltrative growth characterized by activation of antiapoptotic signal transduction. Herein, we describe an efficiently biodegradable selenium-engineered mesoporous silica nanocapsule, initiated by high-energy X-ray irradiation and employed for at-site RNA interference (RNAi) to inhibit rrGBM invasion and achieve maximum therapeutic benefit. Our radiation-triggered RNAi nanocapsule showed high physiological stability, good blood-brain barrier transcytosis, and potent rrGBM accumulation. An intratumoral RNAi nanocapsule permitted low-dose X-ray radiation-triggered dissociation for cofilin-1 knockdown, inhibiting rrGBM infiltration. More importantly, tumor suppression was further amplified by electron-affinity aminoimidazole products converted from metronidazole polymers under X-ray radiation-exacerbated hypoxia, which sensitized cell apoptosis to ionizing radiation by fixing reactive oxygen species-induced DNA lesions. In vivo experiments confirmed that our RNAi nanocapsule reduced tumor growth and invasion, prolonging survival in an orthotopic rrGBM model. Generally, we present a promising radiosensitizer that would effectively improve rrGBM-patient outcomes with low-dose X-ray irradiation.

Exploration of prognostic genes and risk signature in breast cancer patients based on RNA binding proteins associated with ferroptosis

Background: Breast cancer (BRCA) is a life-threatening malignancy in women with an unsatisfactory prognosis. The purpose of this study was to explore the prognostic biomarkers and a risk signature based on ferroptosis-related RNA-binding proteins (FR-RBPs). Methods: FR-RBPs were identified using Spearman correlation analysis. Differentially expressed genes (DEGs) were identified by the "limma" R package. The univariate Cox and multivariate Cox analyses were executed to determine the prognostic genes. The risk signature was constructed and verified with the training set, testing set, and validation set. Mutation analysis, immune checkpoint expression analysis in high- and low-risk groups, and correlation between risk signature and chemotherapeutic agents were conducted using the "maftools" package, "ggplot2" package, and the CellMiner database respectively. The Human Protein Atlas (HPA) database was employed to confirm protein expression trends of prognostic genes in BRCA and normal tissues. The expression of prognostic genes in cell lines was verified by Real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-meier (KM) plotter database analysis was applied to predict the correlation between the expression levels of signature genes and survival statuses. Results: Five prognostic genes (GSPT2, RNASE1, TIPARP, TSEN54, and SAMD4A) to construct an FR-RBPs-related risk signature were identified and the risk signature was validated by the International Cancer Genome Consortium (ICGC) cohort. Univariate and multivariate Cox regression analysis demonstrated the risk score was a robust independent prognostic factor in overall survival prediction. The Tumor Mutational Burden (TMB) analysis implied that the high- and low-risk groups responded differently to immunotherapy. Drug sensitivity analysis suggested that the risk signature may serve as a chemosensitivity predictor. The results of GSEA suggested that five prognostic genes might be related to DNA replication and the immune-related pathways. RT-qPCR results demonstrated that the expression trends of prognostic genes in cell lines were consistent with the results from public databases. KM plotter database analysis suggested that high expression levels of GSPT2, RNASE1, and SAMD4A contributed to poor prognoses. Conclusion: In conclusion, this study identified the FR-RBPs-related prognostic genes and developed an FR-RBPs-related risk signature for the prognosis of BRCA, which will be of great significance in developing new therapeutic targets and prognostic molecular biomarkers for BRCA.

The anterior gradient homologue 2 (AGR2) co-localises with the glucose-regulated protein 78 (GRP78) in cancer stem cells, and is critical for the survival and drug resistance of recurrent glioblastoma: in situ and in vitro analyses

BACKGROUND

Glioblastomas (GBs) are characterised as one of the most aggressive primary central nervous system tumours (CNSTs). Single-cell sequencing analysis identified the presence of a highly heterogeneous population of cancer stem cells (CSCs). The proteins anterior gradient homologue 2 (AGR2) and glucose-regulated protein 78 (GRP78) are known to play critical roles in regulating unfolded protein response (UPR) machinery. The UPR machinery influences cell survival, migration, invasion and drug resistance. Hence, we investigated the role of AGR2 in drug-resistant recurrent glioblastoma cells.

METHODS

Immunofluorescence, biological assessments and whole exome sequencing analyses were completed under in situ and in vitro conditions. Cells were treated with CNSTs clinical/preclinical drugs taxol, cisplatin, irinotecan, MCK8866, etoposide, and temozolomide, then resistant cells were analysed for the expression of AGR2. AGR2 was repressed using single and double siRNA transfections and combined with either temozolomide or irinotecan.

RESULTS

Genomic and biological characterisations of the AGR2-expressed Jed66_GB and Jed41_GB recurrent glioblastoma tissues and cell lines showed features consistent with glioblastoma. Immunofluorescence data indicated that AGR2 co-localised with the UPR marker GRP78 in both the tissue and their corresponding primary cell lines. AGR2 and GRP78 were highly expressed in glioblastoma CSCs. Following treatment with the aforementioned drugs, all drug-surviving cells showed high expression of AGR2. Prolonged siRNA repression of a particular region in AGR2 exon 2 reduced AGR2 protein expression and led to lower cell densities in both cell lines. Co-treatments using AGR2 exon 2B siRNA in conjunction with temozolomide or irinotecan had partially synergistic effects. The slight reduction of AGR2 expression increased nuclear Caspase-3 activation in both cell lines and caused multinucleation in the Jed66_GB cell line.

CONCLUSIONS

AGR2 is highly expressed in UPR-active CSCs and drug-resistant GB cells, and its repression leads to apoptosis, via multiple pathways.

A Genomic Instability-Associated Prognostic Signature for Glioblastoma Patients

BACKGROUND

Genomic instability and aberrant tumor mutation burden are widely accepted hallmarks of cancer. Glioblastoma (GBM) is a common brain tumor in adults, and survival of patients with GBM is poor. This study aimed to investigate the prognostic value of genomic instability-derived genes in GBM.

METHODS

GBM data were downloaded from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Differential expression analysis of all samples with different tumor mutation burden was performed. Univariate Cox and LASSO Cox regression analyses were integrated to determine the optimal genes for constructing a risk score model. Multivariate Cox regression analysis and survival analysis determined independent prognostic indicators. Immune cell infiltration was analyzed by CIBERSORT algorithm.

RESULTS

In GMB patients with high and low tumor mutation burden, we identified 154 differentially expressed genes, which were significantly enriched in 47 Gene Ontology terms and 6 Kyoto Encyclopedia of Genes and Genomes pathways. To establish a risk score, 9 genes were further screened, including SDC1, CXCL1, CXCL6, RGS4, PCDHGB2, CA9, ZAR1, CHRM3, and SLN. High-risk patients had worse prognosis in two databases. The performance of a nomogram including prognostic factors (risk score and age) was good. Moreover, mast cells resting was significantly differentially infiltrated between high- and low-risk GBM samples.

CONCLUSIONS

The risk score constructed by 9 genomic instability-derived genes could reliably predict prognosis of GBM patients. The nomogram based on age and risk score also had a good prognostic predictive value.

Immunoglobulin-like transcript 2 blockade restores antitumor immune responses in glioblastoma

Glioblastoma stands as the most frequent primary brain tumor. Despite the multimodal therapy for glioblastoma patients, the survival rate is very low, highlighting the need for novel therapies that improve patient outcomes. Immune checkpoint blockade strategies are achieving promising results in a myriad of tumors and several studies have reported its efficacy in glioblastoma at a preclinical level. ILT2 is a novel immune checkpoint that exerts an inhibitory effect via the interaction with classical and non-classical HLA class-I molecules. Herein, we report that ILT2 blockade promotes antitumor responses against glioblastoma. In silico and immunohistochemical analyses revealed that the expression of ILT2 and its ligands HLA-A, -B, -C, and -E are highly expressed in patients with glioblastoma. Disruption of ILT2 with blocking monoclonal antibodies increased natural killer cell-mediated IFN-γ production and cytotoxicity against glioblastoma, partially reverting the immunosuppression linked to this malignancy. In addition, co-treatment with temozolomide strengthened the antitumor capacity of anti-ILT2-treated immune cells. Collectively, our results establish the basis for future studies regarding the clinical potential of ILT2 blockade alone or in combination regimens in glioblastoma.

Overexpression of GINS4 is associated with poor prognosis and survival in glioma patients

Background

GINS4, an indispensable component of the GINS complex, is vital for a variety of cancer. However, no known empirical research has focused on exploring relationships between GINS4 and glioma. Thus, this study aims to understand and explain the role of GINS4 in glioma.

Method

First, we used the data in the CGGA, TCGA, GEO, GEPIA, and HPA databases to explore the expression level of GINS4 in glioma, the correlation between GINS4 expression and the clinical features of glioma, its impact on the survival of glioma patients, and verified the analysis results through RT-qPCR, IHC, and meta-analysis. Subsequently, GSEA enrichment analysis is used to find the potential molecular mechanism of GINS4 to promote the malignant process of glioma and the anti-glioma drugs that may target GINS4 screened by CMap analysis. Moreover, we further explored the influence of the GINS4 expression on the immune microenvironment of glioma patients through the TIMER database.

Results

Our results suggested that GINS4 was elevated in glioma, and the overexpression of GINS4 was connected with a vast number of clinical features. The next, GINS4 as an independent prognostic factor, which can result in an unfavorable prognosis of glioma. Once more, GINS4 may be participating in the oncogenesis of glioma through JAK-STAT signaling pathways, etc. 6-thioguanine, Doxazosin, and Emetine had potential value in the clinical application of drugs targeting GINS4. Finally, the expression exhibited a close relationship with some immune cells, especially Dendritic cells.

Conclusion

GINS4 is an independent prognostic factor that led to a poor prognosis of glioma. The present study revealed the probable underlying molecular mechanisms of GINS4 in glioma and provided a potential target for improving the prognosis of glioma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00378-0.