Personalizing Melanoma Treatment Based on Patient Response

By monitoring for mutations in the circulating tumor DNA (ctDNA) of melanoma patients undergoing treatment, researchers at Cancer Research UK Manchester Institute are confident they can predict how patients will respond to their treatment and whether their disease would relapse.

Melanoma remains the most deadly form of skin cancer, according to the CDC, which predicts that the rates of disease incidence will rise over the next 15 years, with an estimate of 112,000 new cases in 2030 and $1.6 billion in treatment-related costs. Despite progress and revolutionizing treatments, nearly 10,000 people dies of the disease in 2012, according to the CDC. An important cause of these high rates of death are treatment resistance and disease relapse.

To this end, the scientists at Cancer Research UK analyzed 364 samples from 214 patients diagnosed with advanced melanoma and being treated with standard care, including chemotherapy, targeted therapy, and immunotherapy. Some of the patients were followed for over a year. The researchers developed individualized treatment decisions after whole-genome sequencing and analyzing their ctDNA, which help monitor patient response to treatment and the development of resistance. The circulating tumor cells were also used to grow patient-derived xenografts that were then tested to develop a personalized treatment for each patient.

In their paper published in Cancer Discovery, the authors describe the success of this approach through a prospective study in one of the patients being monitored. The patient with an advanced BRAF^V600R melanoma in the liver, hepatic, and peritoneal lymph nodes. While the new immunotherapy, ipilimumab, was ineffective in the patient, a dramatic response to the B-Raf/MEK inhibitor, dabrafenib/trametinib, was observed. “A ctDNA analysis on the patient helped predict response to predicted the failure of ipilimumab 1 week before the CT scan, and the response to dabrafenib/trametinib 6 weeks before the CT scan, whereas serum [lactate dehydrogenase] failed to predict these responses,” the authors write.

The study’s lead author, Richard Marais, PhD, has tremendous faith in using ctDNA to predict relapse and direct decisions. “Using our technique we hope that one day we will be able to spot when a patient’s disease is coming back at the earliest point and start treatment against this much sooner, hopefully giving patients more time with their loved ones. Our work has identified a way for us to do this but we still need to test the approach in further clinical trials before it reaches patients in the clinic,” Marais said in a statement.

Future studies, the authors write, are focused on optimizing this personalized care platform to deliver care to the broader population of patients.

Reference

Girotti MR, Gremel G, Lee R, et al. Application of sequencing, liquid biopsies, and patient-derived xenografts for personalized medicine in melanoma. Cancer Discov. 2016;6:286. doi: 10.1158/2159-8290.CD-15-1336.