Addition of an Fc-IgG induces receptor clustering and increases the in vitro efficacy and in vivo anti-tumor properties of the thrombospondin-1 type I repeats (3TSR) in a mouse model of advanced stage ovarian cancer
Bibliographic record
Abstract
OBJECTIVES: Tumor vasculature is structurally abnormal, with anatomical deformities, reduced pericyte coverage and low tissue perfusion. As a result of this vascular dysfunction, tumors are often hypoxic, which is associated with an aggressive tumor phenotype, and reduced delivery of therapeutic compounds to the tumor. We have previously shown that a peptide containing the thrombospondin-1 type I repeats (3TSR) specifically targets tumor vessels and induces vascular normalization in a mouse model of epithelial ovarian cancer (EOC). However, due to its small size, 3TSR is rapidly cleared from circulation. We now introduce a novel construct with the 3TSR peptide fused to the C-terminus of each of the two heavy chains of the Fc region of human IgG1 (Fc3TSR). We hypothesize that Fc3TSR will have greater anti-tumor activity in vitro and in vivo compared to the native compound. METHODS: Fc3TSR was evaluated in vitro using proliferation and apoptosis assays to investigate differences in efficacy compared to native 3TSR. In light of the multivalency of Fc3TSR, we also investigate whether it induces greater clustering of its functional receptor, CD36. We also compare the compounds in vivo using an orthotopic, syngeneic mouse model of advanced stage EOC. The impact of the two compounds on changes to tumor vasculature morphology was also investigated. RESULTS: Fc3TSR significantly decreased the viability and proliferative potential of EOC cells and endothelial cells in vitro compared to native 3TSR. High-resolution imaging followed by image correlation spectroscopy demonstrated enhanced clustering of the CD36 receptor in cells treated with Fc3TSR. This was associated with enhanced downstream signaling and greater in vitro and in vivo cellular responses. Fc3TSR induced greater vascular normalization and disease regression compared to native 3TSR in an orthotopic, syngeneic mouse model of advanced stage ovarian cancer. CONCLUSION: The development of Fc3TSR which is greater in size, stable in circulation and enhances receptor activation compared to 3TSR, facilitates its translational potential as a therapy in the treatment of metastatic advanced stage ovarian cancer.
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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) | 0.001 | 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".