Maintenance of primary tumor phenotype and genotype in glioblastoma stem cells
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
The clinicopathological heterogeneity of glioblastoma (GBM) and the various genetic and phenotypic subtypes in GBM stem cells (GSCs) are well described. However, the relationship between GSCs and the corresponding primary tumor from which they were isolated is poorly understood. We have established GSC-enriched neurosphere cultures from 15 newly diagnosed GBM specimens and examined the relationship between the histopathological and genomic features of GSC-derived orthotopic xenografts and those of the respective patient tumors. GSC-initiated xenografts recapitulate the distinctive cytological hallmarks and diverse histological variants associated with the corresponding patient GBM, including giant cell and gemistocytic GBM, and primitive neuroectodermal tumor (PNET)-like components. This indicates that GSCs generate tumors that preserve patient-specific disease phenotypes. The majority of GSC-derived intracerebral xenografts (11 of 15) demonstrated a highly invasive behavior crossing the midline, whereas the remainder formed discrete nodular and vascular masses. In some cases, GSC invasiveness correlated with preoperative MRI, but not with the status of PI3-kinase/Akt pathways or O(6)-methylguanine methyltransferase expression. Genome-wide screening by array comparative genomic hybridization and fluorescence in situ hybridization revealed that GSCs harbor unique genetic copy number aberrations. GSCs acquiring amplifications of the myc family genes represent only a minority of tumor cells within the original patient tumors. Thus, GSCs are a genetically distinct subpopulation of neoplastic cells within a GBM. These studies highlight the value of GSCs for preclinical modeling of clinically relevant, patient-specific GBM and, thus, pave the way for testing novel anti-GSC/GBM agents for personalized therapy.
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) | 0.000 | 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) | 0.000 | 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