New Technique May Help Predict Outcomes for Patients With Glioblastoma Multiforme
Researchers have developed a new method to quantitatively screen cell migration responses of glioma cells to PDGF.
Researchers at Yale University have developed a new method to quantitatively screen cell migration responses of glioma cells to platelet-derived growth factor (PDGF). They say this technique may be able to differentiate glioma cells into 2 groups (strong responders and weak responders), and help identify which glioblastoma patients are likely to relapse.1 This technique, furthermore, may be more sensitive and physiologically relevant than classical screening assays.
“We found that using a new nanotechnological platform mimicking the chemical and mechanical environment of the brain tissue allowed us to examine invasive migration patterns of cells derived from patients with glioblastoma at the time of surgery. We found that cell migration was predictive of time to tumor recurrence following surgery. The data relying on single cell measurements cannot be obtained from bulk tumor measurements used for genomic studies,” said study author Andre Levchenko, Eng ScD, professor of biomedical engineering and director of the Yale Systems Biology Institute at Yale University in New Haven, Connecticut.
The researchers conducted a study that provided time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface. This technique, which closely mimics in vivo 3D migration, was used as a platform to screen 14 patient-derived glioblastoma samples. They found that the migratory phenotype of a subset of cells in response to PDGF was highly predictive of tumor location and recurrence.
“Findings from these 14 patient samples showed that we can transfer this technique directly into the clinic. This is currently being pursued at Yale, Johns Hopkins University, and the Mayo Clinic, to improve the diagnostic and prognostic analyses of specific tumors. This can help manage and stage patients according to the expected time to recurrence and other prognostic features of the analyses. We are also working on using this technique to match individual patients with relevant therapeutic interventions,” Dr Levchenko told Cancer Therapy Advisor.
Dr Levchenko hopes that this advance in understanding migratory phenotypes will be a substantial leap; he and his team are planning clinical trials to gain the approval for its clinical use. They are adapting it for the precision medicine setting, in which they hope to match individual patients with current and new therapeutics. “This new technology holds great promise for treating patients with brain cancer, which is very important, given the paucity of effective techniques. We hope it can make a substantial difference in the quality of life and extension of life expectancy of these patients,” Dr Levchenko added.
The researchers contend that this newly proposed method may have several advantages over traditional protein expression assays. It is a simpler, more biomimetic, and informative method of gaining critical information about a patient's tumor and cell populations. Study investigator Alfredo Quinones-Hinojosa, MD, professor of neurosurgery and oncology, neuroscience and cellular and molecular medicine, and the director of the Brain Tumor Surgery Program at Johns Hopkins Bayview Hospital in Baltimore, Maryland, said this platform will allow oncologists and their patients to make better-informed decisions regarding treatment.
“I think this is a significant finding, because it tells us for the first time that the phenotype of a cell is important,” Dr Quinones-Hinojosa told Cancer Therapy Advisor. “This is the first time we have a tool that helps us to dissect a cell's migratory behavior in ways we were never able to do before, and it will open the doors to many more significant advances in the study of brain cancer.”
George Ansstas, MD, assistant professor of medicine at Siteman Cancer Center at Washington University in St. Louis, Missouri, said this is a novel approach and, if validated, may have a significant effect on patient outcomes. “A validation of such an approach will help practicing physicians to prognosticate outcomes of patients more accurately, given the shortcomings of genomic analysis and the overlook of tumor microenvironment,” Dr Ansstas told Cancer Therapy Advisor. “This technology will help to select the intensity of local therapy for those with high migratory phenotype. I envision that the radiation field and extent of surgery will be wider for patients with tumors that are more likely to migrate.”
1. Smith CL, Kilic O, Schiapparelli P, et al. Migration phenotype of brain-cancer cells predicts patient outcomes. Cell Rep. 2016 Jun 9. doi: 10.1016/j.celrep.2016.05.042 [Epub ahead of print]