RRM2 Mediates the Anti-Tumor Effect of the Natural Product Pectolinarigenin on Glioblastoma Through Promoting CDK1 Protein Degradation by Increasing Autophagic Flux

Identification of Lower Grade Glioma Antigens Based on Ferroptosis Status for mRNA Vaccine Development

Purpose

mRNA vaccines represent a promising and innovative strategy within the realm of cancer immunotherapy. However, their efficacy in treating lower-grade glioma (LGG) requires evaluation. Ferroptosis exhibits close associations with the initiation, evolution, and suppression of cancer. In this study, we explored the landscape of the ferroptosis-associated tumor microenvironment to facilitate the development of mRNA vaccines for LGG patients.

Patients and Methods

Genomic and clinical data of the LGG patients was obtained from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Ferroptosis-related tumor antigens were identified based on differential expression, mutation status, correlation with antigen-presenting cells, and prognosis, relevance to immunogenic cell death (ICD). Antigen expression levels in LGG specimens and cell lines were validated using real time-polymerase chain reaction (RT-PCR). Consensus clustering was employed for patient classification. The immune landscapes of ferroptosis subtypes were further characterized, including immune responses, prognostic ability, tumor microenvironment, and tumor-related signatures.

Results

Five tumor antigens, namely, HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified in LGG. RT-PCR demonstrated higher expression of these genes in LGG compared to the control. Twelve gene modules and four ferroptosis subtypes (FS1-FS4) of LGG were defined. FS2 and FS4, characterized as "cold" tumors due to their decreased tumor mutation burden (TMB) and immune checkpoint proteins (ICPs), were deemed appropriate candidates for the mRNA vaccine.

Conclusion

HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified as promising candidate antigens for the development of an LGG mRNA vaccine, particularly offering potential benefits to FS2 and FS4 patients.

Synergistic Effect of a Combination of Proteasome and Ribonucleotide Reductase Inhibitors in a Biochemical Model of the Yeast Saccharomyces cerevisiae and a Glioblastoma Cell Line

Proteasome inhibitors are used in the therapy of several cancers, and clinical trials are underway for their use in the treatment of glioblastoma (GBM). However, GBM becomes resistant to chemotherapy relatively rapidly. Recently, the overexpression of ribonucleotide reductase (RNR) genes was found to mediate therapy resistance in GBM. The use of combinations of chemotherapeutic agents is considered a promising direction in cancer therapy. The present work aimed to evaluate the efficacy of the combination of proteasome and RNR inhibitors in yeast and GBM cell models. We have shown that impaired proteasome function results in increased levels of RNR subunits and increased enzyme activity in yeast. Co-administration of the proteasome inhibitor bortezomib and the RNR inhibitor hydroxyurea was found to significantly reduce the growth rate of S. cerevisiae yeast. Accordingly, the combination of bortezomib and another RNR inhibitor gemcitabine reduced the survival of DBTRG-05MG compared to the HEK293 cell line. Thus, yeast can be used as a simple model to evaluate the efficacy of combinations of proteasome and RNR inhibitors.

Targeting of RRM2 suppresses DNA damage response and activates apoptosis in atypical teratoid rhabdoid tumor

BACKGROUND

Atypical teratoid rhabdoid tumors (ATRT) is a rare but aggressive malignancy in the central nervous system, predominantly occurring in early childhood. Despite aggressive treatment, the prognosis of ATRT patients remains poor. RRM2, a subunit of ribonucleotide reductase, has been reported as a biomarker for aggressiveness and poor prognostic conditions in several cancers. However, little is known about the role of RRM2 in ATRT. Uncovering the role of RRM2 in ATRT will further promote the development of feasible strategies and effective drugs to treat ATRT.

METHODS

Expression of RRM2 was evaluated by molecular profiling analysis and was confirmed by IHC in both ATRT patients and PDX tissues. Follow-up in vitro studies used shRNA knockdown RRM2 in three different ATRT cells to elucidate the oncogenic role of RRM2. The efficacy of COH29, an RRM2 inhibitor, was assessed in vitro and in vivo. Western blot and RNA-sequencing were used to determine the mechanisms of RRM2 transcriptional activation in ATRT.

RESULTS

RRM2 was found to be significantly overexpressed in multiple independent ATRT clinical cohorts through comprehensive bioinformatics and clinical data analysis in this study. The expression level of RRM2 was strongly correlated with poor survival rates in patients. In addition, we employed shRNAs to silence RRM2, which led to significantly decrease in ATRT colony formation, cell proliferation, and migration. In vitro experiments showed that treatment with COH29 resulted in similar but more pronounced inhibitory effect. Therefore, ATRT orthotopic mouse model was utilized to validate this finding, and COH29 treatment showed significant tumor growth suppression and prolong overall survival. Moreover, we provide evidence that COH29 treatment led to genomic instability, suppressed homologous recombinant DNA damage repair, and subsequently induced ATRT cell death through apoptosis in ATRT cells.

CONCLUSIONS

Collectively, our study uncovers the oncogenic functions of RRM2 in ATRT cell lines, and highlights the therapeutic potential of targeting RRM2 in ATRT. The promising effect of COH29 on ATRT suggests its potential suitability for clinical trials as a novel therapeutic approach for ATRT.

Identification of CDK1, PBK, and CHEK1 as an Oncogenic Signature in Glioblastoma: A Bioinformatics Approach to Repurpose Dapagliflozin as a Therapeutic Agent

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary brain tumor whose median survival is less than 15 months. The current treatment regimen comprising surgical resectioning, chemotherapy with Temozolomide (TMZ), and adjuvant radiotherapy does not achieve total patient cure. Stem cells' presence and GBM tumor heterogeneity increase their resistance to TMZ, hence the poor overall survival of patients. A dysregulated cell cycle in glioblastoma enhances the rapid progression of GBM by evading senescence or apoptosis through an over-expression of cyclin-dependent kinases and other protein kinases that are the cell cycle's main regulatory proteins. Herein, we identified and validated the biomarker and predictive properties of a chemoradio-resistant oncogenic signature in GBM comprising CDK1, PBK, and CHEK1 through our comprehensive in silico analysis. We found that CDK1/PBK/CHEK1 overexpression drives the cell cycle, subsequently promoting GBM tumor progression. In addition, our Kaplan-Meier survival estimates validated the poor patient survival associated with an overexpression of these genes in GBM. We used in silico molecular docking to analyze and validate our objective to repurpose Dapagliflozin against CDK1/PBK/CHEK1. Our results showed that Dapagliflozin forms putative conventional hydrogen bonds with CDK1, PBK, and CHEK1 and arrests the cell cycle with the lowest energies as Abemaciclib.

Warburg effect-related risk scoring model to assess clinical significance and immunity characteristics of glioblastoma

BACKGROUND

Glioblastoma (GBM), the most common primary malignant brain tumor, has a poor prognosis, with a median survival of only 14.6 months. The Warburg effect is an abnormal energy metabolism, which is the main cause of the acidic tumor microenvironment. This study explored the role of the Warburg effect in the prognosis and immune microenvironment of GBM.

METHODS

A prognostic risk score model of Warburg effect-related genes (Warburg effect signature) was constructed using GBM cohort data from The Cancer Genome Atlas. Cox analysis was performed to identify independent prognostic factors. Next, the nomogram was built to predict the prognosis for GBM patients. Finally, the drug sensitivity analysis was utilized to find the drugs that specifically target Warburg effect-related genes.

RESULTS

Age, radiotherapy, chemotherapy, and WRGs score were confirmed as independent prognostic factors for GBM by Cox analyses. The C-index (0.633 for the training set and 0.696 for the validation set) and area under curve (>0.7) indicated that the nomogram exhibited excellent performance. The calibration curve also indicates excellent consistency of the nomogram between predictions and actual observations. In addition, immune microenvironment analysis revealed that patients with high WRGs scores had high immunosuppressive scores, a high abundance of immunosuppressive cells, and a low response to immunotherapy. The Cell Counting Kit-8 assays showed that the drugs targeting Warburg effect-related genes could inhibit the GBM cells growth in vitro.

CONCLUSION

Our research showed that the Warburg effect is connected with the prognosis and immune microenvironment of GBM. Therefore, targeting Warburg effect-related genes may provide novel therapeutic options.