Scientists at the Perlmutter Cancer Center in the NYU Grossman School of Medicine have developed an experimental test based on a composite panel of autoantibody signatures that generates a score that can be used to predict the occurrence of severe side effects or the recurrence of cancer in melanoma patients who have received immune checkpoint blockade immunotherapies—a therapeutic modality that bolsters the patients own immune system to attack malignant cells.

“The composite panel of autoantibody signatures can allow for the simultaneous risk stratification of patients according to their likelihood of recurring and suffering severe toxicity,” the authors noted.

The development of the test was in the journal Clinical Cancer Research (“Baseline serum autoantibody signatures predict recurrence and toxicity in melanoma patients receiving adjuvant immune checkpoint blockade”).

Iman Osman, MD, professor of dermatology at the Perlmutter Cancer Center, is a senior author of the study.

“Our results show that the new research test, by predicting whether a patient will respond to a treatment or experience side effects, has the potential to help physicians make more precise treatment recommendations,” said Paul Johannet, MD, first author of the study, a postdoctoral fellow in the laboratory of Iman Osman, MD, professor of dermatology at the Perlmutter Cancer Center and a senior author of the study. “With further validation, this composite panel might help patients to better balance the chances of treatment success against severe side effects.”

In contrast to antibodies that recognize foreign microorganisms such as bacteria, viruses, and fungi, autoantibodies react to proteins in the body’s own cells to cause autoimmune disease. The current study suggests that the presence of a newly identified panel of autoantibodies in a patient’s bloodstream before immunotherapy can potentially predict the recurrence of cancer or autoimmune side effects due to the treatment.

Generally, normal cells of the body are not attacked by autoimmune antibodies since immune cells include “checkpoint” sensors. Immune cells selectively recognize tumor cells as abnormal, but cancer cells have developed devious mechanisms to hijack checkpoints and turn off immune attacks against themselves, including the immune checkpoint protein called PD-1 (programmed death receptor 1).

PD-1 inhibitor-based immunotherapies are effective against many cancers and are used as adjuvant therapy in patients with surgically removed melanomas. However, in some patients, cancer recurs following immunotherapy or they suffer severe adverse effects from the treatment regimen.

The authors of the current study hypothesized that undetected higher levels of key autoantibodies in some cancer patients before immunotherapy, trigger checkpoint inhibitors to cause greater adverse immune side effects in these patients. The researchers, therefore, identified a panel of autoantibody signatures that could predict immune-related adverse effects upon immunotherapy with two commonly used checkpoint inhibitors, nivolumab and ipilimumab, and their combination.

The study included 950 patients with advanced melanoma who received adjuvant checkpoint inhibitor immunotherapy as part of two Phase III randomized controlled trials: CheckMate 238 (ipilimumab vs nivolumab) and CheckMate 915 (nivolumab vs ipilimumab plus nivolumab). All patients included in the study had tumors surgically removed and blood samples collected before they received immunotherapy.

Judy Zhong, PhD, a professor of population health and environmental medicine at NYU Grossman School of Medicine, is co-senior author of the study.

Statistical modeling based on the detection of autoantibodies, enabled co-senior author Judy Zhong, PhD, a professor of population health and environmental medicine at NYU Grossman School of Medicine, and her colleagues, to develop a score-based prediction system for each immunotherapy regimen. They found patients with a higher autoantibody score for recurrence showed recurrence of cancer after a shorter interval following immunotherapy compared to patients with a lower score. Similarly, patients with higher pre-treatment autoantibody toxicity scores were more likely to experience severe adverse effects than those with lower scores.

“That we identified 283 autoantibody signals shows that the biological phenomena underlying recurrence and toxicity are complex and cannot be driven by one or two biomarkers,” said Osman. In future studies, her group will test the predictive power of the autoantibody test in patients with cancers other than melanoma, who have received immunotherapies.

This study was funded by the NYU Melanoma SPORE and NIH/NCI.