Checkpoint inhibition is an effective treatment in patients with metastatic melanoma (MM). T cell activation can induce tumor rejection but also possibly severe autoimmune side effects (irAE). Autoantibody biomarkers from serum have potential to predict irAEs such as an ipilimumab-induced colitis.
We use a cancer immunotherapy array consisting of 850 human protein antigens from 4 classes: 1. Tumor-associated antigens (TAA), 2. cancer pathway proteins, 3. autoimmune antigens, 4. cytokines/interleukins. Protein antigens were covalently coupled to magnetic beads and serum AABs were analyzed by Luminex FlexMap 3D. First, we screened pre-immunotherapy sera from 142 patients with MM (Heidelberg Cohort: 82 Ipilimumab (Ipi) treated; 11 Ipi/Nivolumab (Nivo); 40 Pembrolizumab (Pembro), 119 healthy controls (HC)). In this cohort, 41.5% (n = 59) experienced irAEs of any grade and 7% (n = 10) had colitis of grade 3 or 4. In a second study, 200 MM patients from 5 European sites (53 Ipi/Nivo; 111 Pembro, 100 HC) were analyzed. 25.6% (n = 42) had grade 3 or 4 irAEs, 12.8% (n = 21) had diarrhea or colitis of any grade and 9.8% (n = 16) had grade 3 or 4 colitis.
40 different AABs were significantly more prevalent in MM compared to HC including NY-ESO1, NY-ESO 2 and other TAAs, cytokines, and nuclear proteins. Significant correlations of AABs were seen in Ipi-treated patients who experienced irAEs, both in mono- but also in combination therapy, allowing to dichotomize MM in risk groups. Also different sets of AABs were seen in Pembro-treated patients with irAEs. The protein antigens represent a variety of biological processes: they are involved in melanoma progression including transcription factors or components of the E3 ubiquitin ligase complex, cytokeratins, and proteins involved in cell adhesion.
In MM, screening of AABs prior to start of Checkpoint inhibition holds potential to predict risk for irAEs such as colitis. As irAEs are especially frequent in Ipi-based treatment regimes, AABs presented here may serve as useful biomarkers for a risk-based treatment decision.
Clinical trial identification
Legal entity responsible for the study
Jessica C. Hassel and Protagen AG.
J.C. Hassel: Consulting role: Merck, Amgen; Honoraria: Bristol-Myers Squibb, Merck, Novartis, Roche and Pfizer; Science projects support: BMS. J. Mangana: Temporary advisory relationship and receives travel support: MSD, Merck. C. Pföhler: Consulting role: Merck Serono, Novartis, Roche, Amgen, BMS; Honoraria: Merck Serono, Novartis, Roche, Amgen, BMS. B. Weide: Consulting role: Curevac, Philogen, BMS; Honoraria: MSD, BMS, Roche, Amgen, Philogen; Science projects support: BMS, Philogen. L. Hakim-Meibodi: Travel grants: BMS. F. Meier: Honoraria: Roche, BMS, GSK, Novartis, MSD; Travel support: Roche, BMS; Research funding: Wyeth/Pfizer, Merck-Serono, Novartis. H.-D. Zucht, P. Budde; M. Tuschen: Employee: Protagen AG. P. Schulz-Knappe: Board member and chair holder: Protagen AG. All other authors have declared no conflicts of interest.