Differential expression of drug resistance genes and chemosensitivity in glial cell lineages correlate with differential response of oligodendrogliomas and astrocytomas to chemotherapy.
Bibliographic record
Abstract
The two principal subtypes of glial neoplasms, astrocytomas and oligodendrogliomas, exhibit striking differences in response to chemotherapy. This differential chemosensitivity might be explained by the specific genetic alterations causing gliomas but could also be attributable to specific properties intrinsic to the cells from which gliomas arise. To examine the possibility that chemosensitivity might be associated with lineage-specific properties of potential ancestors of these tumors, we explored: (a) the expression of drug resistance genes in rat glial cells; (b) the sensitivity of rat glial subtypes to the bifunctional alkylating agent, 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU); and (c) the effect of O6-methylguanine-DNA methyltransferase (MGMT) and glutathione modulation on resistance to BCNU. Astrocytes, O-2A progenitors, and oligodendrocytes each displayed a unique pattern of expression of six drug resistance genes: MGMT, GST mu, GST pi,p53, MDR, and MT. Oligodendrocytes were more sensitive to BCNU than either astrocytes or O-2A progenitors. The increased resistance of astrocytes in comparison to oligodendrocytes was modulated, at least in part, by both O6-benzylguanine (BG) and DL-buthionine-(S,R)-sulfoximine, suggesting a role for both MGMT and glutathione in the resistance of astrocytes to BCNU. The sensitivity of O-2A progenitors to BCNU following BG pretreatment is virtually indistinguishable from that of oligodendrocytes depleted of MGMT, suggesting that the down-regulation of MGMT is sufficient to account for the increased sensitivity of oligodendrocyte lineage cells to BCNU as they differentiate. These experiments provide support for the hypothesis that properties of glial cells retained in gliomas may contribute to the differential chemosensitivity of glial neoplasms.
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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 | 0.000 |
| 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".