Roles of c-Src and hDRR1 in glioma cell invasion
Bibliographic record
Abstract
Malignant glioma is the major brain tumor in adults, and has a poor prognosis. The failure to control invasive cell subpopulations may be the key reason for local glioma recurrence after radical tumor resection, and may contribute substantially to the failure of the other treatment modalities, such as radiation therapy and chemotherapy. As a model for this invasion, we have implanted spheroids from a human glioma cell line (U251) in three-dimensional collagen type I matrices which these cells readily invade. First, we observed that the Src family kinase specific pharmacological inhibitors PP2 and SU6656 significantly inhibited the invasion of the cells in this assay, which was then confirmed by expression of two inhibitors of Src family function, dominant inhibitory Src and CSK. Fluorescent time-lapse microscopy on U251 cells stably expressing a YFP-actin construct shows that PP2 caused the disappearance of peripheral membrane ruffles within minutes in monolayer cultures, and induced the loss of actin bursting at the leading tip of the invadopodium in three-dimensions. The inhibition of Src family activity is thus a potential therapeutic approach to treating highly invasive malignant glioma. In the second part, we analyze the role of a novel protein, hDRR1, which was cloned from a functional screen of genes involved in glioma cell hyperinvasion. We show that hDRR1 localizes endogenously and when overexpressed to the actin cytoskeleton, via two independent but homologous actin-localization domains. We also show that the C-terminus of hDRR1 can bind to the light chain of MAP1A and MAP1B, and that hDRR1 overexpression in invading glioma cells results in a decrease in the percentage of cells adopting a polarized morphology. These results suggest that hDRR1 represents a novel actin-tubulin bridging protein that plays important roles in cytoskeletal events.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.006 |
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".