Precursor States of Brain Tumor Initiating Cell Lines Are Predictive of Survival in Xenografts and Associated with Glioblastoma Subtypes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In glioblastoma multiforme (GBM), brain-tumor-initiating cells (BTICs) with cancer stem cell characteristics have been identified and proposed as primordial cells responsible for disease initiation, recurrence, and therapeutic resistance. However, the extent to which individual, patient-derived BTIC lines reflect the heterogeneity of GBM remains poorly understood. Here we applied a stem cell biology approach and compared self-renewal, marker expression, label retention, and asymmetric cell division in 20 BTIC lines. Through cluster analysis, we identified two subgroups of BTIC lines with distinct precursor states, stem- or progenitor-like, predictive of survival after xenograft. Moreover, stem and progenitor transcriptomic signatures were identified, which showed a strong association with the proneural and mesenchymal subtypes, respectively, in the TCGA cohort. This study proposes a different framework for the study and use of BTIC lines and provides precursor biology insights into GBM.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it