Summary: A newly developed lab test can predict how quickly and aggressively glioblastoma brain cancer might lethally spread.
Source: Johns Hopkins Medicine.
Johns Hopkins Medicine researchers report they have developed an experimental laboratory test that accurately clocks the “speed” of human brain tumor cell movement along a small glass “track.” The assay, so far tested on the cells of 14 glioblastoma patients, has the potential, they say, to predict how quickly and aggressively a given cancer might lethally spread.
“After I remove a brain tumor from a patient, the patient always asks me, ‘Doc, how long do I have?’ I don’t have a reliable way to answer them,” says Alfredo Quinones-Hinojosa, M.D., director of the Brain Tumor Surgery Program and professor of neurosurgery at the Johns Hopkins University School of Medicine. “But we have taken a step to creating a possible way to provide useful updates, inform treatment choices and perhaps develop new treatments faster.”
According to the National Institutes of Health’s Cancer Genome Atlas, glioblastoma — an aggressive cancer of the glial cells of the brain — accounts for about 15 percent of all adult brain tumors in the U.S., and even with surgery and other treatment, only 3 to 5 percent of people with the tumor survive five years.
In a report on the newly developed assay, published online June 9 in Cell Reports, the Johns Hopkins researchers say their “racetrack” test using chemically primed glioblastoma cells from different tumors removed surgically lets them visualize which cancers most quickly move, mimicking the initial migration that leads to brain cancer invasion.
Quinones-Hinojosa says results of several experiments with the assay suggest that tumors with the fastest cells paralleled the quicker recurrence and other clinical outcomes of 14 glioblastoma patients at The Johns Hopkins Hospital. Further and larger studies are need to confirm the assay’s ability to determine the behavior of these cells, he cautions, but the research is a significant step because cell migration rates — and survival time — cannot be predicted using available genetic- or protein-based tests designed to predict treatment response.
The researchers designed the cell racetracks, which they described earlier in a 2012 PLOS Biology study, by engineering a glass slide with tiny plastic, parallel ridges going down its length. The ridges were designed to simulate the ridged surface of the brain, where migrating cancer cells move along the grooves of the white matter and blood vessels, following them like roadways, Quinones-Hinojosa says. For the new experiments, the researchers first identified a chemical way to start the cell’s engines and get them moving along the slide using platelet-derived growth factor (PDGF), which it’s known to stimulate rapid growth in gliomas.
They tested PDGF to see if it would prime the glioblastoma cells for movement rather than growth by growing the glioblastoma cells from two different tumors on the racetracks with 20 nanograms per milliliter of PDGF. When they placed these tumor cells on the slides for 24 hours, they took videos of the cells and measured their speed.
Some cells from one of the tumors — belonging to the fastest 25 percent of cells from that tumor — responded to the PDGF treatment by moving about two times faster than controls made up of untreated glioblastoma cells. Conversely, the slowest 25 percent of the cells in the tumors moved at the same slower pace as the control tumor cells, meaning that PDGF strongly affected the faster cells.
“We learned from this experiment that we couldn’t take the average of the fast and slow cells from each tumor because that would mask differences in the speedy outliers,” says Quinones-Hinojosa. “We had to pay attention to the cells moving very fast because these are the really bad cells that we believe are going to cause the tumor to spread.”
To see if their speed test had the potential to predict which brain tumors were the most aggressive, the scientists grew cells from 14 patient glioblastomas in PDGF, then placed them on the racetracks.
Timelapse photography shows a single glioblastoma cell migrating along a special slide.
Separately, they assessed 35 clinical factors in each of the patients, including measures of general health, tumor size, tumor shape, patient age, drug treatment and recurrence time after surgery.
When they compared the clinical data to the to the racetrack results, the researchers found that five patients with the fastest tumor cells had recurrence of their cancers within six months. The six patients with slower tumor cells had no recurrence between six and 22 months.
About this brain cancer research article
Additional authors include Chris Smith, Onur Kilic, Paula Schiapparelli, Hugo Guerrero-Cazares, Deok-Ho Kim, Neda Sedora-Roman, Saksham Gupta, Thomas O’Donnell, Kaisorn Chaichana, Fausto Rodriguez, Sara Abbadi, JinSeok Park and Andre Levchenko of The Johns Hopkins University.
Funding: Funding for the study was provided by grants from the National Institute of Neurological Disorders and Stroke (grant number NS070024), the Ford Foundation, the American Heart Association and the National Cancer Institute (grant numbers U01CA15578 and CA16359).
Source: Vanessa McMains – Johns Hopkins Medicine Image Source: This NeuroscienceNews.com image is adapted from the Johns Hopkins Medicine video. Video Source: Video is credited to Johns Hopkins Medicine. Original Research: Full open access research “Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes” by Chris L. Smith, Onur Kilic, Paula Schiapparelli, Hugo Guerrero-Cazares, Deok-Ho Kim, Neda I. Sedora-Roman, Saksham Gupta, Thomas O’Donnell, Kaisorn L. Chaichana, Fausto J. Rodriguez, Sara Abbadi, JinSeok Park, Alfredo Quiñones-Hinojosa, and Andre Levchenko in Cell Reports. Published online June 9 2016 doi:10.1016/j.celrep.2016.05.042
Cite This NeuroscienceNews.com Article
[cbtabs][cbtab title=”MLA”]Johns Hopkins Medicine. “Lab Test May Predict Glioblastoma Aggression and Spread.” NeuroscienceNews. NeuroscienceNews, 9 June 2016. <https://neurosciencenews.com/glioblastoma-test-aggression-cancer-4425/>.[/cbtab][cbtab title=”APA”]Johns Hopkins Medicine. (2016, June 9). Lab Test May Predict Glioblastoma Aggression and Spread. NeuroscienceNews. Retrieved June 9, 2016 from https://neurosciencenews.com/glioblastoma-test-aggression-cancer-4425/[/cbtab][cbtab title=”Chicago”]Johns Hopkins Medicine. “Lab Test May Predict Glioblastoma Aggression and Spread.” https://neurosciencenews.com/glioblastoma-test-aggression-cancer-4425/ (accessed June 9, 2016).[/cbtab][/cbtabs]
Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomess
Highlights •High-throughput analysis for tumor single-cell migration •More sensitive and physiologically relevant than classical screening assays •Glioma cells showing inter- and intra-patient differential sensitivity to PDGF •Glioma cell sensitivity to PDGF correlating with tumor recurrence and tumor location
Summary Glioblastoma multiforme is a heterogeneous and infiltrative cancer with dismal prognosis. Studying the migratory behavior of tumor-derived cell populations can be informative, but it places a high premium on the precision of in vitro methods and the relevance of in vivo conditions. In particular, the analysis of 2D cell migration may not reflect invasion into 3D extracellular matrices in vivo. Here, we describe a method that allows time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface that closely mimics in vivo 3D migration. We used this platform to screen 14 patient-derived glioblastoma samples. We observed that the migratory phenotype of a subset of cells in response to platelet-derived growth factor was highly predictive of tumor location and recurrence in the clinic. Therefore, migratory phenotypic classifiers analyzed at the single-cell level in a patient-specific way can provide high diagnostic and prognostic value for invasive cancers.
“Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes” by Chris L. Smith, Onur Kilic, Paula Schiapparelli, Hugo Guerrero-Cazares, Deok-Ho Kim, Neda I. Sedora-Roman, Saksham Gupta, Thomas O’Donnell, Kaisorn L. Chaichana, Fausto J. Rodriguez, Sara Abbadi, JinSeok Park, Alfredo Quiñones-Hinojosa, and Andre Levchenko in Cell Reports. Published online June 9 2016 doi:10.1016/j.celrep.2016.05.042