Chronically Radiation-Exposed Survivor Glioblastoma Cells Display Poor Response to Chk1 Inhibition under Hypoxia

A Human Adenovirus C Infection-Related Gene Panel for Predicting Survival and Treatment Responsiveness in Glioma Patients

BACKGROUND

Viruses are critical for the regulation of cancer development and for therapy. Human adenovirus C (HadVC) has been detected in central nervous system and glioma tissue. The objective of the present study was the development of a robust prognostic model based on HadVC infection (HadVCi)-relevant genes.

METHODS

The genome, transcriptome, and virome were systemically analyzed using The Cancer Genome Atlas dataset for training and 2 cohorts from the Chinese Glioma Genome Atlas and an immunotherapy trial cohort with 17 patients receiving anti-PD-1 treatment for validation. HadVCi-relevant gene selection from differentially expressed genes between HadVC-infected and non-HadVC-infected glioma patients using least absolute shrinkage and selection operator regression was followed by Cox regression modeling to establish a prognostic HadVCi score. Kaplan-Meier and receiver operating characteristic curve analyses were performed to estimate the predictive capacity of the HadVCi score. The χ2, Spearman, and Mann-Whitney U tests were used to identify the correlation with the clinicopathological parameters, treatment responsiveness, and immune landscape. Temozolomide-resistant glioma cells were established and analyzed at the transcriptional level using RNA sequencing data.

RESULTS

The HadVCi score was (-0.2526673∗TRPC6) + (-0.2244276∗RNF207) + (-0.0894468∗SEC31B) + (-0.0190214∗ZCRB1) + (-0.017122∗DNPH1) + (0.0495818∗CCDC34) + (0.1196349∗PURG) + (0.1778997∗LILRA5). The score possesses a strong ability to predict overall survival. Further analysis revealed a higher HadVCi score correlated with a malignant phenotype and poorer treatment responsiveness to temozolomide-based chemotherapy and combined therapies. Additionally, transcriptomic analysis showed malignancy-, stemness-, and radioresistant-related gene activation in the HadVCi group, which characterized the poor outcomes and limited sensitivity to standard therapy.

CONCLUSIONS

The HadVCi score could be an effective tool for survival prediction and treatment guidance for patients with glioma.

Impact of Ferroptosis Inducers on Chronic Radiation-exposed Survivor Glioblastoma Cells

INTRODUCTION

The median survival of patients diagnosed with glioblastoma is very poor, despite efforts to improve the therapeutic effects of surgery, followed by treatment with temozolomide (TMZ) and ionizing radiation (IR). The utilization of TMZ or IR survivor cell models has enhanced the understanding of glioblastoma biology and the development of novel therapeutic strategies. In this present study, naïve U373 and clinically relevant U373 IRsurvivor (Surv) cells were used, as the IR-Surv cell model mimics the chronic long-term exposure to standardized radiotherapy for patients with glioblastoma in the clinic. As the role of ferroptosis in the IR survivor cell model has not previously been reported, we aimed to clarify its involvement in the clinically relevant IR-Surv glioblastoma model.

METHODS

Transcriptomic alterations of ferroptosis-related genes were studied on naïve U373 and IR-Surv cell populations. To determine the effects of glutathione peroxidase inhibitors, ferroptosis-inducing agent 56 (FIN56) and Ras synthetic lethal 3 (RSL3), on the cells, several properties were assessed, including colony formation, cell viability and lipid peroxidation.

RESULTS

Results from the transcriptomic analysis identified ferroptosis as a critical mechanism after radiation exposure in glioblastoma. Our findings also identified the role of ferroptosis inducers (FINs) in IR-survivor cells and suggested using FINs to treat glioblastoma.

CONCLUSION

FINs serve an important role in radioresistant cells; thus, the results of the present study may contribute to improving survival in patients with glioblastoma.