"The PSA ranges are massive. It's a very heterogeneous thing," Jain said. "When we are talking about cancer, our point is that those variables should be personalized. Everyone's cancer grows differently.
"There are a lot of questions. If you take an intermittent therapy route, how do you decide the scheduling of treatment? Is it based solely on PSA levels? Shouldn't there be some incorporation of personal patient characteristics into these treatment decisions? Can you identify a subgroup of patients who are predicted to respond well to this, or are there conditions when one treatment vs. another could actually make things worse?"
Math offers some answers. The model's foundation is based on existing animal and human data on prostate cancer characteristics. Beyond that, the researchers have selected parameters to plug into the equations that more specifically detail what could be going on in an individual tumor: cancer cell growth rates, cancer cell death rates, the level of activation of PSA in tumor cells, and how quickly one person's PSA can travel from the prostate to the bloodstream.
The scientists even took into account the competitive power of individual types of cancer cells for example, some mutated cancer cells aren't as strong as their normal cancer cell counterparts. In those cases, the math model predicts, the best treatment option would be intermittent therapy because the stronger normal cancer cells would keep mutant cells in check during time off from the medication. With the cancer consistently dominated by cells that rely on the presence of testosterone, the treatment would
|Contact: Harsh Jain|
Ohio State University