Pos0171 Metabolic Signature and Systemic Il-1/Il-17-Associated Cytokine Production as Biomarkers in a Predictive Model for the Outcome of Rheumatic Immune-Related Adverse Events in Patients With Non-Small Cell Lung Carcinoma

Background: Immune checkpoint-Inhibitors (ICIs) have significantly improved cancer outcome in several entities, including the non-small cell lung cancer (NSCLC). However, associated immune-related adverse events (irAEs) can be limiting for further ICI use. While most irAEs resolve after short-term glucocorticoid therapy, rheumatic irAEs - occurring frequently (5-15%) in ICI patients - tend to follow a chronic course with recurrent flares, thus posing a relevant challenge for both rheumatologists and oncologists.1 Objectives: The aim was to find serologic metabolic and cytokine biomarkers for the early identification of at-risk patients for development and chronification of rheumatic irAEs with (long-term) need of medication. Methods: Serum samples were analyzed for their metabolic and lipidomic signatures and IL-1-beta/IL-17-associated cytokine profiles at two times points: At Baseline before ICI initiation and at Follow-Up with irAE occurrence or if none occurred, at an at-risk timepoint with a mean of 110,7 days after therapy initiation. The NSCLC patients have been divided in three subgroups – with rheumatic irAEs under ICI-therapy (n=17), irAEs in other organ systems (n=19) and without any irAE (n=19). Furthermore, a control group with classical rheumatic diseases (n=20) and a healthy control group (n=40) have been recruited. The NMR spectra for the serum metabolome and lipidome were generated with a 700-MHz-Bruker-NMR-Spectrometer, the cytokine profiles were assessed by cytometric bead array. All patient records were analyzed regarding rheumatologically and oncologically relevant demographic, diagnostic, therapeutic and outcome parameters in a retro- and prospective manner. A Multi-Omics analysis with principal component analysis (PCA) has been performed to identify first differences between the groups. Results: In the PCA analysis the three NSCLC subgroups could be distinguished at both time points by significant differences in cytokine and metabolite concentration. At Baseline especially MCP-1 (p=0,0163) and histidine (p=0,0005) contributed to the difference. At Follow-Up several cytokines showed significant concentration differences between the subgroups, including IL-33, IL-10, IL12p70 and IL-1-beta. IL-1-beta showed the highest concentration in the cohort without irAE, counterintuitive to the clinical observation of high inflammation in patients with irAEs. The cytokine differences between the cohorts were underlined by concentration difference in the metabolites at Follow Up, especially histidine and glutamine. Interestingly, the differences both at Baseline and Follow-Up were mainly due to large differences between the rheumatic irAE cohort in comparison to the other cohorts, separating them from the irAEs in other organ systems as well. Conclusion: In summary, some promising biomarker candidates for early detection of at-risk ICI-patients were identified in the interim analysis. Moreover, we have observed changes in the cytokine and metabolite pools after the development of rheumatic irAEs, that differed from those seen in non-rheumatic irAEs. This suggests that different mechanisms might be behind the development of different types of irAEs. We are currently validating these data in a second cancer entity cohort. REFERENCES: 1 Gente K, Diekmann L, Daniello L, et al. Sex and anti-inflammatory treatment affect outcome of melanoma and non-small cell lung cancer patients with rheumatic immune-related adverse events. Journal for ImmunoTherapy of Cancer 2023;11:e007557. doi: 10.1136/jitc-2023-007557. Acknowledgements: NIL. Disclosure of Interests: Julia Will: None declared, Karolina Gente Abbvie, BMS, Gilead/Galapagos, Janssen, Lilly, MSD, Sandoz, UCB, Viatris, Abbvie, BMS, Gilead/Galapagos, Janssen, Lilly, MSD, Sandoz, UCB, Viatris, Medical faculty and Foundations commission of University of Heidelberg, Pfizer, Novartis, Junyan Lu: None declared, Rui Carvalho: None declared, Jürgen Graf: None declared, Petros Christopoulos Roche, Takeda, Gilead, AstraZeneca, Thermo Fisher, Janssen, Pfizer, Novartis, Pfizer, Chugai, Boehringer Ingelheim, Takeda, Novartis, AstraZeneca, MSD, Roche, Roche, Amgen, Boehringer Ingelheim, Takeda, Merck, AstraZeneca, Novartis, Hanns-Martin Lorenz Abbvie, Astra-Zeneca, Actelion, Alexion, Amgen, Bayer Vital, Baxter, Biogen, Boehringer Ingelheim, BMS, Celgene, Celltrion, Chugai, Fresenius, Galapagos, Genzyme, GSK, Gilead, Hexal, Janssen-Cilag, Lilly, Medac, MSD, Mundipharm, Mylan, Nordic, Novartis, octapharm, Pfizer, Roche, Sandoz, Sanofi, Shire, SOBI, Stada, Takeda, Thermo Fisher, UCB, Vifor, Abbvie, Astra-Zeneca, Actelion, Alexion, Amgen, Bayer Vital, Baxter, Biogen, Boehringer Ingelheim, BMS, Celgene, Celltrion, Chugai, Fresenius, Galapagos, Genzyme, GSK, Gilead, Hexal, Janssen-Cilag, Lilly, Medac, MSD, Mundipharm, Mylan, Nordic, Novartis, octapharm, Pfizer, Roche, Sandoz, Sanofi, Shire, SOBI, Stada, Takeda, Thermo Fisher, UCB, Vifor, Abbvie, Astra-Zeneca, Actelion, Alexion, Amgen, Bayer Vital, Baxter, Biogen, Boehringer Ingelheim, BMS, Celgene, Celltrion, Chugai, Fresenius, Galapagos, Genzyme, GSK, Gilead, Hexal, Janssen-Cilag, Lilly, Medac, MSD, Mundipharm, Mylan, Nordic, Novartis, octapharm, Pfizer, Roche, Sandoz, Sanofi, Shire, SOBI, Stada, Takeda, Thermo Fisher, UCB, Vifor, Abbvie, Astra-Zeneca, Actelion, Alexion, Amgen, Bayer Vital, Baxter, Biogen, Boehringer Ingelheim, BMS, Celgene, Celltrion, Chugai, Fresenius, Galapagos, Genzyme, GSK, Gilead, Hexal, Janssen-Cilag, Lilly, Medac, MSD, Mundipharm, Mylan, Nordic, Novartis, octapharm, Pfizer, Roche, Sandoz, Sanofi, Shire, SOBI, Stada, Takeda, Thermo Fisher, UCB, Vifor, Margarida Souto-Carneiro: None declared.