While high mutation load in metastatic melanoma is often associated with better responses to immune checkpoint inhibitors, researchers have found that loss of certain genomic regions in metastatic melanoma can bring about resistance to such therapies.
In addition, treatment with the anti-CTLA-4 Yervoy (ilipimumab), even if it fails, might prime the immune system to successfully respond to the anti-PD-1 therapy Opdivo (nivolumab).
The findings may help doctors predict who will benefit from immunotherapy and understand the mechanisms of therapeutic resistance to improve patient management and outcomes.
While immune checkpoint inhibitors like Yervoy or Opdivo induce strong responses in 20-30% of melanoma patients — some with long-lasting complete responses — other patients fail to respond to such treatments.
In an attempt to understand why these therapies work only for some, and looking for biomarkers that could predict response and resistance to immune checkpoint blockade, researchers examined the genome of tumor biopsies collected from 56 melanoma patients before, during and after treatment.
Patients were treated first with Yervoy, which blocks the CTLA-4 immune checkpoint. Then, if their tumor did not respond to Yervoy, they were given Opdivo.
The team found that tumors with large amounts of mutations, or with high mutational load, which provide targets for the immune system to detect, were more susceptible to immune checkpoint inhibitors. But the measure of mutational load could not predict response to treatment by itself, as the team found that tumors with a higher burden of copy number loss (when part of the genome is deleted and you lose one or more copies of a certain gene) had worse responses to immune checkpoint blockade.
“Combining mutational load and copy number loss could improve prediction of patient response,” co-senior author Jennifer Wargo, MD, associate professor of Surgical Oncology and Genomic Medicine at The University of Texas MD Anderson Cancer Center, said in a press release.
When the team classified patients by their mutation load and copy loss burden, they found that 11 out of 26 patients with high mutational load and low copy loss had clinical benefit. In contrast only four of 26 patients with low mutational load and high copy loss responded to treatment.
Looking at the genomes of nine biopsies collected from patients who did not respond to either drug, the team found that certain blocks of chromosomes 6, 10, and 11, were lost consistently. These regions harbored 13 known tumor-suppressor genes, which could explain the worse response to treatment. No patients who had responded to therapy had lost these regions.
The team also examined the genetic variability of the T-cell receptor, which allows T-cells to identify, attack, and remember an antigen found in a tumor cell. They found that while increased T-cell clonality, or a larger T-cell repertoire, a marker of T-cell response was not predictive of response to Yervoy, it was a biomarker for response to Opdivo. Importantly, all patients who responded to Opdivo had signs of T-cell response after Yervoy treatment, suggesting Yervoy primed the immune system.
“That’s evidence that anti-CTLA4 in some cases primes T-cells for the next step, anti-PD1 immunotherapy. It’s well known that if you don’t have T-cells in the tumor, anti-PD1 won’t do anything, it doesn’t bring T-cells into the tumor,” said co-senior author Andrew Futreal, PhD, professor, chair of Genomic Medicine and co-leader of MD Anderson’s Moon Shots Program.
“Developing an assay to predict response will take an integrated analysis, thinking about genomic signatures and pathways, to understand the patient when you start therapy and what happens as they begin to receive therapy,” Wargo said. “Changes from pretreatment to on-therapy activity will be important as well.”