Abstract 3919: Targeting urease to human VEGFR2 elicits antitumor activity in triple-negative breast cancer models
Bibliographic record
Abstract
Abstract Introduction: Vascular endothelial growth factor receptor type 2 (VEGFR2) expression is one of the most prominent biomarkers of the tumor-associated neovasculature. Moreover, VEGFR2 can be aberrantly expressed on the surface of tumor cells. We have previously described the development of V21-DOS47, an immunoconjugate composed of the VHH-portion of a camelid single domain anti-VEGFR2 antibody (V21H4) and jack bean urease, which converts endogenous urea into ammonia and hydroxyl ions. V21-DOS47 is the second in a class of antibody-urease drugs. The first, L-DOS47, is currently in clinical testing for non-small cell lung cancer. In this study, we identified tumor cells with VEGFR2 expression, tested V21-DOS47 binding to tumor cells, and investigated in vivo activity in both immunocompetent and immunodeficient mice. Methods: Flow cytometry experiments were performed with biotinylated V21H4 antibody and anti-biotin fluorochrome-conjugated secondary antibody. Detection of urease by flow cytometry was performed with an anti-urease antibody followed by incubation with a fluorochrome-conjugated secondary antibody. Western blotting was used for the assessment of protein expression. For in vivo experiments, VEGFR2-overexpressing derivatives of human MDA-MB-231 and murine 4T1 breast cancer cell lines were generated. Balb/c or nude mice were inoculated with tumor cells: 2.5 x 105 4T1 or 1x106 MDA-MB-231, respectively, on Day 0 of each experiment. Intravenous injections of V21-DOS47 at a dose of 10 µg/kg were started on Day 3 and continued on Days: 5, 7, 9 and 11. Results: After screening human tumor cell lines for VEGFR2 expression by RT-PCR and Western blotting, we determined that two triple-negative breast cancer cell lines (MDA-MB-231 and MDA-MB-468) expressed the highest levels of VEGFR2. Binding of V21H4 to the cell surface of both cell lines was confirmed by flow cytometry. In vivo studies were conducted using both immunodeficient (with human MDA-MB-231-hVEGFR2 cells) and immunocompetent (with murine 4T1-hVEGFR2 cells) mice. In the syngeneic/immunocompetent model of Balb/c mice implanted with 4T1-hVEGFR2 cells, but not wild-type 4T1 cells, the antitumor effect of V21-DOS47 was significant and long-lasting. However, the results obtained from the initial experiment in the MDA-MB-231-hVEGFR2 model suggest that the antitumor effect of V21-DOS47 is transient in immunodeficient mice. Conclusions: Our data show successful targeting of the DOS47 platform to human VEGFR2 expressed on tumor cells. Our in vivo data indicate that the antitumor activity of V21-DOS47 is enhanced in immunocompetent mice, which suggests that the immune system is a significant component of the antitumor activity of the V21-DOS47 immunoconjugate. Citation Format: Angelika Muchowicz, Anna Bujak, Beata Pyrzynska, Justyna Karolczak, Abdessamad Zerrouqi, Magdalena Ozga, Lukasz Szewczyk, Baomin Tian, Wah Wong, Marni Uger, Katarzyna Poplawska, Dorota Gierej, Pawel Wisniewski, Heman Chao, Magdalena Winiarska, Radoslaw Zagozdzon. Targeting urease to human VEGFR2 elicits antitumor activity in triple-negative breast cancer models [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 3919.
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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".