Proliferation of Human Glioblastoma Stem Cells Occurs Independently of Exogenous Mitogens
Bibliographic record
Abstract
Primary glial tumors of the central nervous system, most commonly glioblastoma multiforme (GBM), are aggressive lesions with a dismal prognosis. Despite identification and isolation of human brain tumor stem cells (BTSCs), characteristics that distinguish BTSCs from neural stem cells remain to be elucidated. We cultured cells isolated from gliomas, using the neurosphere culture system, to understand their growth requirements. Both CD133(+) and CD133(-) adult GBM BTSCs proliferated in the absence of exogenous mitogenic stimulation and gave rise to multipotent GBM spheres that were capable of self-renewal. Epidermal growth factor (EGF) and fibroblast growth factor-2 enhanced GBM BTSC survival, proliferation, and subsequent sphere size. Blockade of EGF receptor (EGFR) signaling reduced exogenous mitogen-independent GBM sphere growth. Implantation of as few as 10 exogenous mitogen-independent GBM BTSCs led to the formation of highly invasive intracranial tumors, which closely resembled human GBMs, in immunocompromised mice. These results demonstrate that exogenous mitogen independence, mediated in part through EGFR signaling, is one characteristic that distinguishes CD133(+) and CD133(-) GBM BTSCs from neural stem cells. This novel experimental system will permit the elucidation of additional constitutively activated mechanisms that promote GBM BTSC survival, self-renewal, and proliferation.
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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".