POS0322 GUSELKUMAB BINDING TO CD64+ IL-23–PRODUCING MYELOID CELLS ENHANCES POTENCY FOR NEUTRALIZING IL-23 SIGNALING
Bibliographic record
Abstract
Background: IL-23 is implicated in the pathogenesis of psoriasis (PsO), and myeloid cells that express FcγRI, known as CD64, have been identified as the primary cellular source of IL-23 in lesional PsO skin tissue.[1] The incidence and prevalence of psoriatic arthritis increases with the severity of PsO,[2] and joint disease activity is positively correlated with frequency of peripheral CD64+ monocytes.[3] Guselkumab (GUS) and risankizumab (RZB) are monoclonal antibodies (mAbs) specifically directed against the IL-23p19 subunit; however, GUS is a fully human IgG1 mAb with a native Fc region while RZB is a humanized IgG1 mAb with a mutated Fc region. Objectives: Here, we evaluated CD64 and IL-23 expression in PsO patient skin biopsies, binding of GUS and RZB to CD64, and the functional consequences of CD64 binding by IL-23p19 subunit mAbs, in in vitro assays. Methods: Expression of CD64, IL23p19 subunit, and IL23p40 subunit mRNA transcripts were analyzed from bulk and single-cell RNAseq datasets. Binding of mAbs to IFNγ-primed human monocytes, as well as binding to IL-23–secreting inflammatory monocytes and capture of endogenously secreted IL-23, were assessed by flow cytometry. Internalization of IL-23, GUS, and RZB within CD64+ macrophages was evaluated using live cell confocal imaging. Potency of GUS and RZB for inhibiting IL-23 signaling was determined in a co-culture of THP-1 cells (a CD64+ monocyte cell line activated to produce IL-23) and an IL-23 reporter cell line (measuring biologically active IL-23). Expression of IL23p19 mRNA transcript in the co-culture was measured by qPCR. Results: Analyses of RNAseq datasets showed increased expression of CD64, IL23p19, and IL23p40 mRNA transcripts in lesional versus non-lesional PsO skin, and myeloid cell types co-expressing CD64 and IL23p19 mRNA transcripts were increased in lesional skin. In in vitro assays, GUS, but not RZB, showed Fc-mediated binding to CD64 on IFNγ-primed monocytes. Moreover, CD64-bound GUS simultaneously captured IL-23 secreted from the same cells. GUS, but not RZB, bound to the surface of CD64+ macrophages and mediated internalization of IL-23 to low pH intracellular compartments. GUS and RZB demonstrated similar potency for inhibiting signaling by IL-23 present in THP-1–conditioned medium. However, in a co-culture of IL-23–producing THP-1 cells with an IL-23–responsive reporter cell line, GUS demonstrated enhanced potency compared to RZB for inhibiting IL-23 signaling. GUS did not alter expression of IL23p19 mRNA transcript in the co-culture. Conclusion: The results of our transcriptomic analysis were consistent with previous observations of CD64+ myeloid cells as a key source of IL-23 production in lesional PsO skin tissue. GUS binding to CD64 on IL-23–producing cells likely contributed to the enhanced functional potency of GUS compared to RZB for inhibition of IL-23 signaling in the co-culture assay. These in vitro data support a hypothesis for optimal localization of GUS in inflamed tissues, where CD64+ IL-23–producing myeloid cells are increased and in proximity to IL-23–responsive lymphoid cells, enhancing GUS neutralization of IL-23 at its source of production. REFERENCES: [1] Mehta, H. et al. J Invest Dermatol. 2021;141:1707-1718. [2] Merola, J. et al. J Am Acad Dermatol. 2022;86:748-757. [3] Matt, P. et al. Scand J Rheumatol. 2015;44:464-473. Acknowledgements: NIL. Disclosure of Interests: Dennis McGonagle - Speakers bureau: AbbVie, Celgene, Janssen, Merck, Novartis, Pfizer, and UCB, Consultant: Abbvie, Celgene, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support: Abbvie, Celgene, Janssen, Merck, Pfizer, Novartis, Raja Atreya - Consultant: AbbVie, Amgen, Arena Pharmaceuticals, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Celltrion Healthcare, Dr. Falk Pharma, Ferring, Fresenius Kabi, Galapagos, Gilead, GlaxoSmithKline, InDex Pharmaceuticals, Janssen, Kliniksa Pharmaceuticals, Merk Sharp & Dohme, Novartis, Pfizer, Roche, Samsung Bioepsis, Stelic, Sterna Biologicals, Takeda, and Tillotts, Maria T. Abreu - Speakers bureau: Alimentiv, Janssen Pharmaceuticals, Prime CME, and WebMD Global LLC, Consultant and/or advisory board: AbbVie Inc, Arena Pharmaceuticals Inc (now Pfizer), Bristol Myers Squibb, Celsius Therapeutics, Eli Lilly and Company, Gilead Sciences Inc, Janssen Pharmaceuticals, Janssen Global Services, Pfizer Pharmaceutical, Prometheus Biosciences, and UCB Biopharma SRL, James G. Krueger - Consultant: AbbVie, Aclaris, Allergan, Almirall, Amgen, Arena, Aristea, Asana, Aurigene, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Escalier, Galapagos, Janssen, MoonLake, Nimbus, Novartis, Pfizer, Sanofi, Sienna, Sun, Target-Derm, UCB, Valeant, and Ventyx, Kilian Eyerich - Speakers bureau: AbbVie, Almirall, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Hexal, Janssen, Leo Pharma, Pfizer, Novartis, Sanofi, and UCB, Advisory board: AbbVie, Almirall, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Hexal, Janssen, LEO Pharma, Pfizer, Novartis, Sanofi, and UCB, Robert Bissonnette - Speakers bureau: AbbVie, Alumis, Amgen, AnaptysBio, Bausch Health, Boston, Bristol Myers Squibb, Celgene, Dermavant, Eli Lilly, Janssen, Leo Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio and Xencor, Shareholder: Innovaderm Research, Employee: Innovaderm Research, Consultant and/or advisory board: AbbVie, Alumis, Amgen, AnaptysBio, Bausch Health, Boston, Bristol Myers Squibb, Celgene, Dermavant, Eli Lilly, Janssen, Leo Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio and Xencor, Grant/research support: AbbVie, Alumis, Amgen, AnaptysBio, Bausch Health, Boston, Bristol Myers Squibb, Celgene, Dermavant, Eli Lilly, Janssen, Leo Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio and Xencor, Carrie Greving - Shareholder: Johnson & Johnson, Employee: Janssen, He (Hurley) Li - Shareholder: Johnson & Johnson, Employee: Janssen, Tom C. Freeman - Shareholder: Johnson & Johnson, Employee: Janssen, Amy Hart - Shareholder: Johnson & Johnson, Employee: Janssen, Brice Keyes - Shareholder: Johnson & Johnson, Employee: Janssen, Brian Stoveken - Shareholder: Johnson & Johnson, Employee: Janssen, John Hartman - Shareholder: Johnson & Johnson, Employee: Janssen, Kristin Leppard - Shareholder: Johnson & Johnson, Employee: Janssen, Joshua Wertheimer - Shareholder: Johnson & Johnson, Employee: Janssen, Indra Sarabia - Shareholder: Johnson & Johnson, Employee: Janssen, Janise Deming - Shareholder: Johnson & Johnson, Employee: Janssen, Kristen Kohler - Shareholder: Johnson & Johnson, Employee: Janssen, Christopher T. Ritchlin - Consultant: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB, Grant/research support: AbbVie, Amgen, and UCB, Iain B. Mc Innes - Shareholder: Causeway and Evelo Compugen, board member: NHS GGC, board of directors: Evelo, trustee: Versus Arthritis, Consultant: AbbVie, Amgen, Astra Zeneca, Bristol Myers Squibb, Cabaletta, Compugen, Eli Lilly, Gilead, Glaxo Smith Kline, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support: Amgen, Astra Zeneca, Bristol Myers Squibb, Eli Lilly, Glaxo Smith Kline, Janssen, Novartis, Roche, and UCB, Matthieu Allez - Speakers bureau: AbbVie, Amgen, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Celltrion, Ferring, Genentech, Gilead, IQVIA, Janssen, Novartis, Pfizer, Roche, Takeda, and Tillots, Consultant: AbbVie, Amgen, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Celltrion, Ferring, Genentech, Gilead, IQVIA, Janssen, Novartis, Pfizer, Roche, Takeda, and Tillots, Grant/research support: Genentech/Roche, Innate, Janssen and Takeda, Anne Fourie - Shareholder: Johnson & Johnson, Employee: Janssen, Kacey Sachen - Shareholder: Johnson & Johnson, Employee: Janssen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".