Powerful drugs known as BRAF-inhibitors have been crucial for melanoma patients, saving lives through their ability to turn off the BRAF protein’s power to spur cancer cell growth.
However, they often work for only a year or less. Scientists know some of the DNA mutations that cause the drug resistance, but they haven’t been able to determine the underlying cause of the resistance in as many as a third of these patients. As a result, identifying genomic-based follow-up therapies has been a challenge.
Researchers at MD Anderson Cancer Center have found that looking at unique “protein patterns” in melanoma patients may help predict who will benefit from genomic-based follow-up therapies.
“There are patients whose DNA doesn’t reveal how their melanomas became resistant to BRAF inhibitors,” said Lawrence Kwong, Ph.D., instructor in Genomic Medicine. “So we looked at patterns of changes in 150 proteins, which can give clues to the causes of resistance, even when DNA sequencing data is uninformative.”
Kwong is first author of a paper on the BRAF study, which appeared recently in the online edition of the Journal of Clinical Investigation (JCI).
“BRAF-inhibitors are effective in melanoma patients whose tumors have a ‘hot spot’ mutation in the BRAF cancer gene,” said Lynda Chin, M.D., chair of Genomic Medicine, and corresponding author on the JCI paper. “Unfortunately, almost uniformly, these patients develop resistance to the drug. Therefore, figuring out how melanoma gets around the drug is a critical first step in identifying an alternative therapy for these patients once resistance develops, or better yet, a way to treat these patients with combinations that prevent the emergence of resistance.”
Kwong and Chin’s team analyzed BRAF inhibitor resistance using a BRAF mouse melanoma model and human tumor biopsy samples. They found that such “proteome profiling” can provide a rapid view of BRAF-inhibitor resistance patterns in melanoma patients at a fraction of the cost of DNA or RNA sequencing.
In addition to these findings, the study also suggested the potential of using RNA and protein data as candidate “biomarkers” to help predict how long a patient will respond to BRAF inhibitor treatment so that combination or second-line therapies can be considered in a more personalized manner.
“These biomarkers include genes that track how fast the tumors are growing and how active the immune system is in the tumor,” said Kwong. “This raises the possibility that pre-treatment biopsies can be used to guide decisions on targeted agents or immunotherapies that may be most effective for that individual patient.”
The scientists caution that the study size was relatively small and will require additional analysis of much larger cohorts of patients.