CBIO-14TARGETING PROTEASOME ACTIVITY WITH MARIZOMIB AS A THERAPEUTIC PERSPECTIVE FOR GLIOMA PATIENTS
Bibliographic record
Abstract
Inhibition of the Ubiquitin-Proteasome pathway offers promise for the treatment of gliomas, but has yet to be tested because the approved drugs in this class don't penetrate the CNS. Marizomib is a novel second-generation proteasome inhibitor, with advantages over bortezomib and carfilzomib including irreversible inhibition of all three enzymatic activities of the proteasome and superior tolerability. While there are some promising data in preclinical models of solid tumors using proteasome inhibitors, only Marizomib has proven active in intracranial GBM xenografts, prompting the initiation of a Phase I trial in GBM in combination with bevacizumab. We aim to identify potential biomarkers predictive of response to Marizomib in GBM patients. Tumor tissues obtained from glioma patients at Toronto Western Hospital and utilized for proteasome activity assay. Glioma Stem Cells (GSC) isolated from freshly resected gliomas and used for in-vitro characterization of Marizomib treatment on GSCs. DNA and RNA were isolated from tumors of the patients (including those participating in the Phase I trial) for mutational analysis and expression of a cancer gene panel. Data shows significant increase in all three proteasome activities, Chymotrypsin-Like, Trypsin-Like and Caspase-Like, in GBM tumors compared to normal brain tissues, suggesting a role for the proteasome in GBM formation. Furthermore, progression of low-grade astrocytoma to GBM is associated with enhanced Chymotrypsin-Like and Trypsin-Like activities, indicating that targeting these subunits could potentially inhibit the progression of gliomas. In vitro analysis using GSC lines indicates that the GSC cells of proneural and mesenchymal origin differ in response to Marizomib, raising the possibility that molecular signatures associated with GBM subtypes could determine the therapeutic response to Marizomib in GBM patients. In conclusion, Marizomib represents as a potential therapeutic agent for GBM. Further investigation is necessary to assess the therapeutic benefits of Marizomib as a single agent or combined with other agents.
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 | 0.001 |
| 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".