Abstract 746: Development of novel formats of anti-AXL ADCs
Bibliographic record
Abstract
Abstract AXL is a member of the Tyro3- AXL -Mer (TAM) receptor tyrosine kinase subfamily which has been associated with several cellular functions including growth, migration, aggregation, and anti-inflammation (Li Y et al., 2009) via activation through its ligand, Gas6. Originally identified as an oncogene in chronic myelogenous leukemia, expression of Axl has been reported to be upregulated in a variety of cancers including breast, gastric, prostate, ovarian, and lung. AXL expression has been shown to be negatively associated with patient survival and implicated in epithelial-to-mesenchymal transition, a process closely linked with invasive motility and metastasis of malignant cells. Several recent studies have reported that AXL is overexpressed during resistance to chemotherapy and other molecularly targeted therapies, as well as during hypoxia (Schoumacher M et al 2017). Consequently, Axl is promising therapeutic target for development into ADCs for the first or second line treatment of cancer. At the National Research Council (NRC) of Canada, we have selected mouse monoclonal (mAbs) or llama derived single domain antibodies (sdAbs) that are selective for the extracellular domain of human Axl and which have been shown to be internalized into Axl expressing cells for antibody drug conjugate (ADC) development using a surrogate ADC screen. These antibodies were also characterized based on their binding domains and ability to compete with Gas6, the extracellular ligand for Axl. A panel of Axl-specific ADCs was subsequently directly conjugated to maytansine, the microtubule disrupting agent through a noncleavable linker. Axl-DM1 ADCs were shown to efficiently induce cytotoxicity in vitro, in Axl expressing cells including breast (MDA-MB 231), lung (NCI-H292) and ovarian (SKOV3) cell lines with sub nM potencies achieved with both sdAb and conventional mAb-based ADCs. When tested in vivo using ovarian (SKOV3) and breast cancer (MDA-MB 231) xenograft models, Axl-DM1 ADCs were shown to have potent anti-tumor activity. Biparatopic antibodies (i.e. those which target two non-overlapping epitopes) directed against HER2 have been previously shown to induce target clustering and promote robust internalization, lysosomal trafficking, and degradation (LI JY et al 2016). Since these properties are important in the mechanism of action of ADCs, we have further tested anti-Axl antibodies in various configurations and have identified potent biparatopic antibodies for further development into ADCs. Citation Format: Maria L. Jaramillo, Myriam Banville, Alma Robert, Luc Meury, Maurizio Acchione, Anne Marcil, Christine Gadoury, Cunle Wu, Yves Fortin, Kevin Henry, Joseph Schrag, The-Minh Tu, Binbing (Erica) Ling, Jacqueline Slinn, Maria Moreno. Development of novel formats of anti-AXL ADCs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 746.
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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) | 0.003 | 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".