Abstract 1759: PRO1160, a novel CD70-directed antibody-drug conjugate, demonstrates robust anti-tumor activity in mouse models of renal cell carcinoma and non-Hodgkin lymphoma
Bibliographic record
Abstract
Abstract PRO1160 is an antibody-drug conjugate directed toward CD70, an antigen that is aberrantly overexpressed in multiple hematologic malignancies and carcinomas with limited normal tissue expression. PRO1160 is comprised of a 1) human monoclonal antibody that selectively binds to CD70, 2) a cleavable, hydrophilic linker, and 3) exatecan, a topoisomerase 1 inhibitor. Upon binding to CD70 on the surface of malignant cells, PRO1160 is internalized and exatecan released through enzymatic cleavage of the linker. Exatecan blocks the ligation step of the cell cycle and generates DNA single- and double-strand breaks, which leads to cell death. PRO1160 demonstrated robust anti-tumor activity, in vitro and in vivo. In multiple cell-derived xenograft mouse models, PRO1160 demonstrated more potent tumor growth inhibition compared to an MMAE-conjugated ADC with the same parent antibody. PRO1160 was well tolerated in mice with no to minimal impact on body weight gain. The in vivo pharmacokinetics in rats showed that PRO1160 is stable in circulation. These nonclinical data suggest the potential for a broad therapeutic window and further development of PRO1160 is warranted. PRO1160 has the potential for an expanded therapeutic index. PRO1160 is being developed for the potential treatment of patients with CD70-expressing hematologic and solid tumor cancers. Citation Format: Lei Wang, Haidong Liu, Xiao Shang, Tae Han, Baiteng Zhao. PRO1160, a novel CD70-directed antibody-drug conjugate, demonstrates robust anti-tumor activity in mouse models of renal cell carcinoma and non-Hodgkin lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1759.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".