Gene expression profiling of glioblastoma cell lines depending on TP53 status after tumor-treating fields (TTFields) treatment

Yeon-Joo Lee,Sang-Gu Hwang,Hyun Wook Seo,Eun Ho Kim,Sun Ha Lim,Jeong-Hwa Baek

doi:10.1038/s41598-020-68473-6

Abstract

Glioblastoma is frequently associated with TP53 mutation, which is linked to a worse prognosis and response to conventional treatments (chemoradiotherapy). Therefore, targeting TP53 is a promising strategy to overcome this poor therapeutic response. Tumor-treating fields (TTFields) are a recently approved treatment for newly diagnosed glioblastoma, which involves direct application of low-intensity, intermediate-frequency alternating electric fields to the tumor, thereby offering a local tumor-killing effect. However, the influence of TP53 mutation status on the effectiveness of TTFields is controversial. Here, we identified the key gene signatures and pathways associated with TTFields in four glioblastoma cell lines varying in TP53 mutation status using gene profiling and functional annotation. Overall, genes associated with the cell cycle, cell death, and immune response were significantly altered by TTFields regardless of TP53 status. TTFields appeared to exert enhanced anti-cancer effects by altering the immune system in the inflammatory environment and regulating cell cycle- and cell death-related genes, but the precise genes influenced vary according to TP53 status. These results should facilitate detailed mechanistic studies on the molecular basis of TTFields to further develop this modality as combination therapy, which can improve the therapeutic effect and minimize side effects of chemoradiotherapy.

Highlights

Glioblastoma (GBM) a histological subtype of glioma in which most patients survive for an average of 12–15 months[1]
To identify the effect of TTFields on various cellular responses according to TP53 status in GBM, we conducted microarray analysis using WT and MT TP53 GBM cell lines (Fig. 1b)
Numerous studies have shown that TP53 is a valuable prognostic biomarker in cancer and TP53 mutations alter the expression of various genes through point mutations[22,23]

Summary

Introduction

Glioblastoma (GBM) a histological subtype of glioma in which most patients survive for an average of 12–15 months[1]. Several researchers have suggested that TP53-based targeted therapy is a promising approach for treating GBM, but its value as a prognostic marker in the clinical field is unclear. Microarray analysis is a useful method for evaluating therapies for GBM to detect differential expression between normal and cancer cells following treatment with specific drugs or physical procedures[11,12]. TP53 has functional effects on the transcriptional profiles of genes in several cancer cell lines[13], but the impact of tumortreating fields (TTFields) on GBM according to the TP53 status remains unknown. We performed gene expression profiling during TTFields treatment in four GBM cell lines to explore effects of TTFields on diverse cellular responses in accordance with the TP53 status.

Methods

Results

Conclusion