Shared Expression of CD93 and Other Antigens By AML and Endothelial Cells Highlights a Need for Rational Combinatorial Targeting
Bibliographic record
Abstract
Introduction: Acute myeloid leukemia (AML) is the most prevalent acute leukemia in the United States, accounting for more than 11,000 deaths each year and with a 5-year overall survival rate of less than 30%. With the exception of Gemtuzumab ozogamycin, an anti-CD33 antibody drug conjugate, the landmark success of immunotherapy in other hematologic malignancies has not translated to AML. Chimeric antigen receptor (CAR) T cell therapy, in which T cells are engineered with redirected tumor specificity, holds promise for the treatment of AML, but optimal antigens for CAR targeting of AML remain to be defined. We identified CD93 as a novel target for AML CAR therapy given high expression on many AML samples and an important role in leukemia stem cell (LSC) biology. Here, we describe anti-leukemic efficacy of CD93 CAR T cells both in vitro and in murine xenograft models. Consistent with predictions based on CD93 expression within the hematopoietic compartment, we demonstrate minimal CAR T cell toxicity to hematopoietic progenitors. However, we identify endothelial cell toxicity as a significant on-target, off-tumor toxicity. We also analyze endothelial expression of other common AML targets including CD123 and CD38 at baseline and in an inflammatory microenvironment and propose a strategy to incorporate endothelial expression considerations into rational design of combinatorial CAR T cells for AML. Results/Methods: CD93 was expressed to some degree on 24/25 (96%) of primary AML specimens, and was homogeneously expressed in 17/25 (68%). T cells were engineered to express second generation CD93 CARs based on the scFv of a humanized monocloncal CD93 antibody (F11) linked to CD28-CD3ζ or 4-1BB-CD3ζ intracellular domains (CD93-28z and CD93-BBz, respectively). CD93-28z and CD93-BBz CAR T cells incubated in vitro with target cells demonstrated AML-specific cytokine production measured by ELISA and cytotoxicity measured by IncucyteTM assay. CD93 CAR T cell treatment of NOD-SCID-IL2Rγc-/- (NSG) mice engrafted with the human AML line THP-1 resulted in improved leukemic control in comparison to mock-treated mice. In a patient derived xenograft model of primary AML, CD93 CAR T cell treatment resulted in significantly improved leukemic clearance, T cell expansion, and prolonged survival compared to mock-treated mice. CD93 CAR T cells were incubated with cord-blood derived CD34+ cells to evaluate CD93 CAR recognition of hematopoietic stem cells (HSCs) and other hematopoietic progenitors. In an ELISA, CD93 CAR T cells did not produce cytokines against the bulk CD34+ population, in contrast to a positive control of AML. Additionally, after a 24h co-culture, CD93 CAR T cells did not kill any hematopoietic progenitor cells as assessed by flow cytometry. Furthermore, a methycellulose based colony forming assay confirmed that CD93 CAR T cells do not impact hematopoietic progenitor multipotent functional ability. We analyzed CD93 expression by immunohistochemistry of a tissue microarray of normal tissues. H-scores of all tissues analyzed were <100, generally accepted to signify low or no expression. However, we discovered strong staining of endothelial cells throughout multiple organ systems. CD93 expression was confirmed on endothelial cell lines iHUVEC and TIME, and CD93 CAR T cells produced cytokines when co-cultured with these endothelial cells. Hematopoietic cells and endothelial cells have a common developmental origin, and other AML CAR targets have been described as expressed on endothelial cells either at baseline or in the presence of inflammatory cytokines. A targeted analysis of CD123, CD38, and CD33 revealed that CD123 and CD38 are also expressed on endothelial cells, especially when cells are pretreated with IFN𝛾 and TNF⍺. Conclusion: Progress in generating effective CAR T cells for acute myeloid leukemia (AML) has been hampered the paucity of AML cell surface antigens that are not expressed on vital tissues. Combinatorial antigen targeting will likely play a major role in advancing CAR T cell therapy for AML. Our data support that endothelial expression at baseline and in an inflammatory microenvironment should be considered as a factor in any rational combinatorial targeting strategy, and that creative CAR engineering will be necessary for certain AML targets, including CD93, to circumvent endothelial toxicity. Disclosures Richards: Stanford University: Patents & Royalties: pending patent application for CD93 CAR. Sotillo:Lyell Immunopharma: Consultancy, Other: Consultancy. Hong:Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Majzner:Zai Lab: Consultancy; Xyphos Biopharma: Consultancy; Aprotum Group: Consultancy; GammaDelta Therapeutics: Membership on an entity's Board of Directors or advisory committees; Illumina Radiopharmaceuticals: Consultancy; Lyell Immunopharma: Consultancy. Majeti:CircBio Inc.: Research Funding; Gilead Sciences, Inc.: Patents & Royalties: inventor on patents related to CD47 cancer immunotherapy; Stanford University: Patents & Royalties: pending patent application on CD93 CAR ; BeyondSpring Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Forty-Seven Inc.: Divested equity in a private or publicly-traded company in the past 24 months; Coherus BioSciences: Membership on an entity's Board of Directors or advisory committees; Zenshine Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Kodikaz Therapeutic Solutions Inc.: Membership on an entity's Board of Directors or advisory committees. Mackall:Lyell Immunopharma: Consultancy, Current equity holder in private company; BMS: Consultancy; Allogene: Current equity holder in publicly-traded company; Apricity Health: Consultancy, Current equity holder in private company; Nektar Therapeutics: Consultancy; NeoImmune Tech: Consultancy.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".