P.106 Thrombospondin 1 mediates transforming growth factor beta induced premature senescence in primary glioblastoma cells
Bibliographic record
Abstract
Background: Glioblastoma is the most common primary malignant brain tumor. Primary Glioblastoma (PriGO) cells are key drivers of glioblastoma. Senescence is the irreversible growth arrest of cells with continued metabolic activity. Recently, I discovered PriGO cells undergo premature senescence in response to Fetal Bovine Serum (FBS). Determining the underlying molecular mechanisms may allow development of novel therapeutic strategies to decrease the malignant potential of glioblastoma. Methods: Global gene expression changes in PriGO cells treated with serum were analyzed and compared to untreated cells. Senescence was determined by the Senescence-Associated-Beta-Galactosidase (SA-B-Gal) assay. Results: PriGO cells treated with serum demonstrated increased expression of genes in the Transforming Growth Factor Beta (TGF-B) pathway, such as Thrombospondin 1 (TSP1), compared to untreated cells. TGF-B treatment of PriGO cells significantly increased senescence compared to untreated cells. Treatment of PriGO cells with serum and the TGF-B inhibitor SB431542 led to a decrease in senescence compared to serum only treated cells. Treatment of PriGO cells with serum and the TSP1 inhibitor LSKL led to a reduction in senescence compared to serum only treated cells. Conclusions: Our data identifies TGF-B as an important component of serum responsible for inducing senescence in PriGO cells. Furthermore, TGF-B induced senescence in PriGO cells is in part mediated by TSP1.
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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 | 0.001 |
| 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".