DDDR-32. A NEW IMMUNOMODULATORY FUNCTION OF PYRIDO-PYRIMIDINE DERIVATIVES TO IMPAIR METASTATIC GROUP 3 MEDULLOBLASTOMA IN VIVO
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is an embryonal tumor of the cerebellum constituting ~ 20% of pediatric brain tumors. To date, four MB molecular groups (further stratified in twelve subtypes) have been described. Among them, Groups 3 and Group 4 MB have the poorest prognosis due to their high metastatic potential. Recently, we have reported a metastatic axis driven by Prune1 overexpression in MB Group3 characterized by canonical TGF-β signaling enhancement and epithelial-mesenchymal transition. Here, we have developed a new not toxic pyrido-pyrimidine derivative with the ability to impair Prune-1-driven-axis, thus ameliorating the survival rate of a murine model of metastatic MB Group3 characterized by overexpression of human Prune1 gene in the cerebellum (under the control of MATH1 promoter). Of importance, this small molecule also is showing immunomodulatory functions thus inhibiting the conversion of tumor-infiltrating T lymphocytes (TILs) to immunosuppressive regulatory T cells (Tregs) in vivo via impairing the secretion of inflammatory cytokines from MB cells. Furthermore, this molecule can also act synergistically with the currently used modified-intensity chemotherapy (e.g. in PNET5 use of Vincristine) or potential in the combination with epigenetics drugs (e.g., LSD1/KDM1A inhibitors). Altogether these results are of importance for future targeted therapies of high-risk metastatic MB. Acknowledgments: We thank for funding support: the Italian Association for Cancer Research (AIRC) Grant IG no. 22129 (M.Z.) and Lazio Innova Grant n. 85-2017-14785 (FT; MZ)
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) | 0.002 | 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".