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Updated: Sep 5, 2025
The Clinical Application of Tumor Treating Fields Therapy in Glioblastoma
Published on: April 16, 2019
Molecular alterations associated with improved outcome in patients with glioblastoma treated with Tumor-Treating
Manjari Pandey1, Joanne Xiu2, Sandeep Mittal3
1West Cancer Center and Research Institute, Memphis, Tennessee, USA.
Background:
The genomic and overall biologic landscape of glioblastoma (GB) has become clearer over the past 2 decades, as predictive and prognostic biomarkers of both de novo and transformed forms of GB have been identified. The oral chemotherapeutic agent temozolomide (TMZ) has been integral to standard-of-care treatment for nearly 2 decades. More recently, the use of non-pharmacologic interventions, such as application of alternating electric fields, called Tumor-Treating Fields (TTFields), has emerged as a complementary treatment option that increases overall survival (OS) in patients with newly diagnosed GB. The genomic factors associated with improved or lack of response to TTFields are unknown.
Methods:
We performed comprehensive genomic analysis of GB tumors resected from 55 patients who went on to receive treatment using TTFields, and compared results to 57 patients who received standard treatment without TTFields.
Results:
We found that molecular driver alterations in NF1, and wild-type PIK3CA and epidermal growth factor receptor (EGFR), were associated with increased benefit from TTFields as measured by progression-free survival (PFS) and OS. There were no differences when stratified by TP53 status. When NF1, PIK3CA, and EGFR status were combined as a Molecular Survival Score, the combination of the 3 factors significantly correlated with improved OS and PFS in TTFields-treated patients compared to patients not treated with TTFields.
Conclusions:
These results shed light on potential driver and passenger mutations in GB that can be validated as predictive biomarkers of response to TTFields treatment, and provide an objective and testable genomic-based approach to assessing response.
Insights
Genomic biomarkers, including NF1, PIK3CA, and EGFR, predict glioblastoma response to Tumor-Treating Fields (TTFields). These findings offer a genomic approach to assess TTFields treatment efficacy in glioblastoma patients.
Area of Science:
- Neuro-oncology
- Genomics
- Cancer Therapeutics
Background:
- Glioblastoma (GB) treatment has advanced with biomarkers and temozolomide (TMZ).
- Tumor-Treating Fields (TTFields), an electric field therapy, improve survival in newly diagnosed GB.
- Genomic predictors of TTFields response in glioblastoma remain unidentified.
Purpose of the Study:
- To identify genomic factors associated with glioblastoma response to TTFields.
- To compare genomic profiles of patients treated with TTFields versus standard care.
- To explore potential predictive biomarkers for TTFields efficacy.
Main Methods:
- Comprehensive genomic analysis of 55 glioblastoma tumors from patients receiving TTFields.
- Comparison of genomic data with 57 patients receiving standard treatment without TTFields.
- Correlation of molecular alterations with progression-free survival (PFS) and overall survival (OS).
Main Results:
- NF1 alterations and wild-type PIK3CA and EGFR were linked to improved PFS and OS with TTFields.
- No significant differences in response were observed based on TP53 status.
- A combined 'Molecular Survival Score' (NF1, PIK3CA, EGFR) significantly correlated with better outcomes in TTFields-treated patients.
Conclusions:
- Identified NF1, PIK3CA, and EGFR as potential predictive biomarkers for TTFields response in glioblastoma.
- These findings support a genomic-based approach for assessing TTFields treatment effectiveness.
- Further validation of these mutations may refine glioblastoma treatment strategies.
