Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Predicting immunotherapy treatment outcomes in melanoma patients (#434)

Jonathan Blackburn 1 , Jessica Da Gama Duarte 2 , Jonathan Cebon 2 , Andreas Behren 2
  1. University of Cape Town, Cape Town, WESTERN CAPE, South Africa
  2. Olivia Newton John Cancer Research Institute, Melbourne, Victoria, Australia

Background: Immunotherapies with checkpoint inhibitors have revolutionized the treatment of advanced melanomas. Nonetheless, not all patients benefit clinically from these immunotherapeutics and some develop immune-related adverse events (irAEs). Therefore, the ability to predict treatment outcomes in a non-invasive manner is of utmost value. The presence of tumour antigen-specific antibodies in circulation is indicative of immune engagement with the tumour, while an over-reactive autoantibody repertoire may predispose patients to develop irAEs. Thus, we aimed to determine the unique antibody repertoire of melanoma patients prior to undergoing immunotherapy with checkpoint inhibitors, to investigate if it may predict the likelihood of treatment success and the onset of irAEs.

Methods: Blood samples from 15 advanced melanoma patients were collected at baseline before treatment with anti-CTLA-4 or anti-PD-1 checkpoint inhibitors under HREC approved study protocol, with informed consent. Patients clinically developed high-grade, low-grade or no irAEs following treatment. Humoral immune responses were investigated using the Sengenics Immunome protein array, a high-content array with 1627 full-length, folded,  immobilized tumour and self-antigens that enabled the interrogation of the depth and breadth of the immune response.

Results: In patients treated with CTLA-4 or PD1 checkpoint blockade, the detection of antibodies against 10 to 60% of all antigen specificities on the array content at baseline was predictive of clinical response to treatment, including both partial and complete responses. In instances where clinical response was accompanied with the onset of irAEs, antibodies were detected against more than 80% of the array content. However, when patients progressed or developed irAEs without clinical benefit, antibodies were detected against less than 10% of the array content.  

Conclusions: Investigating humoral immunity may predict clinical responses and the onset of irAEs in patients treated with immunotherapies. Personalized therapeutic decisions will prevent patients from undergoing unnecessary treatments, while leading to improved clinical responses and outcomes.