Improving cancer therapy, says Joseph Nevins, comes down to figuring out two things: whom to treat and how to treat them. Nevins, who directs the Center for Applied Genomics & Technology within the Duke University Institute for Genome Science & Policy, says these are exactly the issues his team has addressed in two recent scientific papers. The first, which appeared in the August 10 issue of The New England Journal of Medicine (355:570-80), took up the “whom to treat” question. In it, the Duke investigators described a genomic tool to predict recurrence in patients with non-small-cell lung cancer (NSCLC), the most common lung cancer and one of the deadliest. The ability to identify Stage 1A patients who should be treated with chemo is only the first step in developing truly personalized cancer treatment. “In lung cancer,” Potti says, “we have four drugs that are considered to be ‘standard of care.’ But as a physician, I don’t know which of these drugs is best for any particular patient —it’s a trial-and-error process. We wind up exposing patients to months of chemotherapy that are potentially very toxic but may be of no benefit at all. We need a mechanism to match the right drug with the right patient.” The second paper from the Duke team, slated to appear in a forthcoming issue of the journal Nature Medicine, describes a strategy to develop a more rational approach to prescribing cancer drugs. It uses the same tool as the first paper—genomic signatures. In this case, however, the researchers went one step further and showed that the signatures could be used to predict not just who was at risk for recurrence, but who would respond to which cancer drugs. Thus, the study opens the door to providing the right drug to the right patient depending on the molecular profile or genomic signature of his or her tumor. For example, a lung cancer patient whose tumor expresses the genomic signature characteristic of tumors known to respond to the drug paclitaxel can be given that drug as first-line therapy. But another tumor might show a signature indicating resistance to paclitaxel; for these patients, the drug would likely show no benefit. Doctors would then look for a different signature that predicts sensitivity to another drug and administer that drug as first-line therapy. In both cases, say the Duke investigators, the frustrations of the trial-and-error approach can be avoided. Moreover, as cancer therapies today frequently rely on multiple drugs, these genomic signatures—obtained at the time of diagnosis—can be used to help guide physicians to determine the optimal combination of therapies for any given patient. In order to actually put these tools to use, the Nevins team has developed a series of clinical trials, each designed to evaluate the genomic signature approach. The immediate goal is to begin the process of actually deciding how to treat patients based on their genomic signatures. “Those will be the pivotal studies,” says Potti. “We are pretty confident that we will make a positive difference in these patients’ lives, but we still need to test what will happen if we prescribe drugs based on the genomic predictors.” Duke University Press Release http://www.askbig.org/archives/Articles/personalized_treatment Posted here 12/06 Remember we are NOT Doctors and have NO medical training. This site is like an Encylopedia - there are many pages, many links on many topics. Support our work with any size DONATION - see left side of any page - for how to donate. You can help raise awareness of CAM.