CD133+ brain tumor-initiating cells are dependent on STAT3 signaling to drive medulloblastoma recurrence
Bibliographic record
Abstract
Medulloblastoma (MB), the most common malignant paediatric brain tumor, is currently treated using a combination of surgery, craniospinal radiotherapy and chemotherapy. Owing to MB stem cells (MBSCs), a subset of MB patients remains untreatable despite standard therapy. CD133 is used to identify MBSCs although its functional role in tumorigenesis has yet to be determined. In this work, we showed enrichment of CD133 in Group 3 MB is associated with increased rate of metastasis and poor clinical outcome. The signal transducers and activators of transcription-3 (STAT3) pathway are selectively activated in CD133 + MBSCs and promote tumorigenesis through regulation of c-MYC, a key genetic driver of Group 3 MB. We screened compound libraries for STAT3 inhibitors and treatment with the selected STAT3 inhibitors resulted in tumor size reduction in vivo . We propose that inhibition of STAT3 signaling in MBSCs may represent a potential therapeutic strategy to treat patients with recurrent MB.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".