Faculty, Staff and Student Publications
Publication Date
3-21-2024
Journal
JCI Insight
Abstract
Spinal metastases can result in severe neurologic compromise and decreased overall survival. Despite treatment advances, local disease progression is frequent, highlighting the need for novel therapies. Tumor treating fields (TTFields) impair tumor cell replication and are influenced by properties of surrounding tissue. We hypothesized that bone's dielectric properties will enhance TTFields-mediated suppression of tumor growth in spinal metastasis models. Computational modeling of TTFields intensity was performed following surgical resection of a spinal metastasis and demonstrated enhanced TTFields intensity within the resected vertebral body. Additionally, luciferase-tagged human KRIB osteosarcoma and A549 lung adenocarcinoma cell lines were cultured in demineralized bone grafts and exposed to TTFields. Following TTFields exposure, the bioluminescence imaging (BLI) signal decreased to 10%-80% of baseline, while control cultures displayed a 4.48- to 9.36-fold increase in signal. Lastly, TTFields were applied in an orthotopic murine model of spinal metastasis. After 21 days of treatment, control mice demonstrated a 5-fold increase in BLI signal compared with TTFields-treated mice. TTFields similarly prevented tumor invasion into the spinal canal and development of neurologic symptoms. Our data suggest that TTFields can be leveraged as a local therapy within minimally conductive bone of spinal metastases. This provides the groundwork for future studies investigating TTFields for patients with treatment-refractory spinal metastases.
Keywords
Animals, Humans, Mice, Spinal Neoplasms, Cell Line, Tumor, Lung Neoplasms, Cell Proliferation, Disease Models, Animal, Osteosarcoma, Female, A549 Cells, Xenograft Model Antitumor Assays, Bone biology, Neuroscience, Neurological disorders, Orthopedics
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Neurology Commons, Neurosciences Commons, Oncology Commons, Orthopedics Commons
Comments
Supplementary Materials
PMID: 38512420