DRES-04. CHARACTERIZATION OF A MODEL OF TEMOZOLOMIDE RESISTANCE IN GLIOBLASTOMA
Bibliographic record
Abstract
Despite the discovery and widespread use of the chemotherapeutic drug temozolomide (TMZ), glioblastoma (GBM) remains a fatal cancer. TMZ, a DNA alkylating agent, provides a moderate survival benefit to patients whose tumours do not express the O6-methylguanine-methyltransferase (MGMT) gene. However, even these TMZ-sensitive GBMs recur and upon doing so, many are resistant to TMZ. The development of TMZ resistance is commonly associated with mutations in mismatch repair (MMR) and the re-expression of MGMT. Upregulation of homologous recombination (HR) and base excision repair (BER) have also been implicated as mechanisms of acquired TMZ resistance. To better characterize these mechanisms and to develop strategies to prevent or overcome resistance, our laboratory has implemented an in vitro model of inducible resistance in which frequent exposure to TMZ (100µM) yields multiple resistant colonies in the MGMT-methylated GBM cell line U251N (Yip et. al). These colonies displayed varying methods of resistance to TMZ, including those that have been clinically observed in recurrent, TMZ-treated GBMs. Several colonies harboured mutations in MMR genes MSH6, MSH2, and MLH1 with low or absent expression of their respective proteins. In addition, some MMR wild-type colonies had increased expression of poly-ADP ribose (a polymer required for the recognition of DNA breaks by the BER machinery), suggesting that upregulation of BER may be driving resistance. Furthermore, Western Blot analysis revealed that occasional colonies re-expressed MGMT. Interestingly, a few colonies did not possess these alterations, suggesting that their resistance may result from further downstream modifications of MMR or BER, or by mutations in HR. With a more comprehensive characterization of these U251 colonies, we hope to learn more about TMZ resistance in GBM, and refine treatments or preventative therapies for molecularly distinct, TMZ-resistant, recurrent tumours.
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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 | 0.001 |
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".