Colorectal cancer cells express functional cell surface‐bound TGFβ
Bibliographic record
Abstract
Disruptions to the TGFbeta signaling pathway have been implicated in most human adenocarcinomas. In addition to its role in cancer cell migration and metastasis, TGFbeta has been implicated in tumor-mediated immunosuppression. Membrane-bound TGFbeta has previously been reported to be expressed on a subset of regulatory T cells and was shown to be critical to their immune suppressive function. In the present study, we document expression of a signaling competent, endogenously derived form of cell surface-bound TGFbeta on colorectal cancer cells. While antibodies against only the mature form of TGFbeta failed to label cells, surface-bound TGFbeta was clearly detected by antibodies specific for both the latent and mature forms of the cytokine. Confirming the notion that the surface TGFbeta was in latent form, brief acid pulsing of the cells increased the amount of detectable membrane-associated TGFbeta. In coculture assays, this cell-bound TGFbeta could be activated and utilized in a paracrine fashion both by other cancer cells and by CD8+ intraepithelial lymphocytes. This effect was abrogated by the use of a furin inhibitor which decreased the membranous expression of TGFbeta on the tumor cells. Signaling competent membrane-bound TGFbeta on cancer cells is thus likely to be a key player in regulating tumor cell interactions with each other as well as with other cells in their microenvironment.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".