Abstract B024: Single-chain traps targeting transforming growth factor-beta (TGF-beta) home to tumors and reduce tumor growth and metastasis by counteracting TGF-beta-mediated immunosuppression
Bibliographic record
Abstract
Abstract The TGF-beta superfamily includes a large number of ligands with physiological and pathological significance. In particular, elevated TGF-beta in the tumor microenvironment markedly augments cancer progression by inducing metastasis and angiogenesis and by suppressing the immune system. Therapeutic agents targeting TGF-beta, such as antibodies or IgG-Fc-fused receptor ectodomains, have been developed, however these agents are relatively large molecules, which may restrict tumor penetration. We have computationally designed single-chain traps that are comprised of tandemly-fused TGF-beta receptor domains. These traps are approximately one third the size of monoclonal antibodies which would potentially facilitate a better tumor penetration. The homobivalent TGF-beta RII-RII traps (i.e. T22d35 and T22d60) neutralize TGF-beta isoforms 1 and 3 and the heterovalent TGF-beta RI-RII based traps (i.e. T12d and T122bt) are pan-specific and neutralize all three isoforms (TGF-beta 1, 2 and 3). Both the T22d35 and T12d trap blocked TGF-beta 1 and 3, induced epithelial mesenchymal transition (EMT) and motility of mouse mammary tumor cells (JM01). Heterovalent T12d also blocked TGF-beta2 effects on these phenotypes. In vivo comparison of T22d35 trap and the pan-neutralizing TGF-beta antibody 1D11 indicated that T22d35 treatment but not 1D11 reduced the growth of established primary 4T1 mammary tumors, suggesting better neutralization of TGF-beta due to a better tumor penetration of the T22d35 trap (Mol. Cancer Ther. 11:1477, 2012). Trap treatment significantly increased T lymphocyte infiltration and cytotoxic activity within the tumors. Biodistribution studies demonstrated that the T22d35 trap, although eliminated rapidly from the circulating blood and other tissues (within 24 hours), localized and was retained within primary 4T1 tumors. Furthermore, a single injection of trap per week reduced 4T1 metastatic lesions by more than 80%, relative to saline controls, indicating that a short-term trap exposure in the host is sufficient to trigger long-lasting effects. Together, our results indicate that the TGF-beta traps readily home to tumors, antagonize immunosuppression and reduce metastatic spread. Citation Format: John Zwaagstra, Traian Sulea, Anne E.G. Lenferink, Jason Baardsnes, Catherine Collins, Christiane Cantin, Lucie Couture, Limei Tao, Yves Durocher, Maureen O'Connor-McCourt. Single-chain traps targeting transforming growth factor-beta (TGF-beta) home to tumors and reduce tumor growth and metastasis by counteracting TGF-beta-mediated immunosuppression. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr B024.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".