CD248 facilitates tumor growth via its cytoplasmic domain
Bibliographic record
Abstract
BACKGROUND: Stromal fibroblasts participate in the development of a permissive environment for tumor growth, yet molecular pathways to therapeutically target fibroblasts are poorly defined. CD248, also known as endosialin or tumor endothelial marker 1 (TEM1), is a transmembrane glycoprotein expressed on activated fibroblasts. We recently showed that the cytoplasmic domain of CD248 is important in facilitating an inflammatory response in a mouse model of arthritis. Others have reported that CD248 gene inactivation in mice results in dampened tumor growth. We hypothesized that the conserved cytoplasmic domain of CD248 is important in regulating tumor growth. METHODS: Mice lacking the cytoplasmic domain of CD248 (CD248CyD/CyD) were generated and evaluated in tumor models, comparing the findings with wild-type mice (CD248WT/WT). RESULTS: As compared to the response in CD248WT/WT mice, growth of T241 fibrosarcomas and Lewis lung carcinomas was significantly reduced in CD248CyD/CyD mice. Tumor size was similar to that seen with CD248-deficient mice. Conditioned media from CD248CyD/CyD fibroblasts were less effective at supporting T241 fibrosarcoma cell survival. In addition to our previous observation of reduced release of activated matrix metalloproteinase (MMP)-9, CD248CyD/CyD fibroblasts also had impaired PDGF-BB-induced migration and expressed higher transcripts of tumor suppressor factors, transgelin (SM22α), Hes and Hey1. CONCLUSIONS: The multiple pathways regulated by the cytoplasmic domain of CD248 highlight its potential as a therapeutic target to treat cancer.
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) | 0.002 | 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".