Current Cancer Drug Test Shown to be Ineffective
Proliferation assays are typically used to see how cancer cells respond to a drug, but this method may not be the most effective.
A recent study found that the main method used to test compounds for anti-cancer activity in cells is faulty.
Currently, researchers determine the efficacy of a compound through proliferation assays, or counting how many cancer cells are alive after 72 hours, but this does not take into account any bias from exponential cell proliferation and does not measure how many cells there are at a single point in time.
"Cells are not uniform; they all proliferate exponentially, but at different rates," said researcher Vito Quaranta, MD, in a press release. "At 72 hours, some cells will have doubled three times and others will not have doubled at all.
Also, according to the study published in Nature Methods, each cell can have a different reaction to the drug.
Researchers in this study developed a drug-induced proliferation (DIP) rate metric to evaluate a compound’s effect on cell proliferation, according to the study. They used a systems biology approach to analyze the time-dependent bias in static proliferation assays and develop time-independent DIP rate metric.
"Systems biology is what really makes the difference here," Dr. Quaranta said. "It's about understanding cells - and life - as dynamic systems."
The authors said their findings are important since efforts to create data sets, including how cell lines respond to compounds, have been amplified.
"The idea is to look for statistical correlations - these particular cell lines with this particular makeup are sensitive to these types of compounds - to use these large databases as discovery tools for new therapeutic targets in cancer," Dr. Quaranta said. "If the metric by which you've evaluated the drug sensitivity of the cells is wrong, your statistical correlations are basically no good."
Researchers observed the response of 4 different melanoma cell lines to vemurafenib with the standard metric and with the new DIP rate.
Researchers found a major discrepancy between the metrics in 1 melanoma cell line.
"The static metric says that the cell line is very sensitive to vemurafenib. However, our analysis shows this is not the case," said Leonard Harris, PhD, a systems biology postdoctoral fellow. "A brief period of drug sensitivity, quickly followed by rebound, fools the static metric, but not the DIP rate."
Their findings suggest that melanoma tumors that are treated with vemurafenib would be expected to come back due to the difference in metrics and now, DIP rate analyses could assist with better treatments.
DIP rates can also have the added benefit of being able to reveal which drugs are cytotoxic, the study concluded.