Nrf2‐Keap1 pathway does not have an important role in cisplatin resistance in neuroblastoma (655.8)
Bibliographic record
Abstract
Drug resistance is one of the major causes of treatment failure in neuroblastoma (NB). Cisplatin is one of the key chemotherapeutic agents for NB. Nuclear factor erythroid 2‐like‐2 (Nrf2) is a transcription factor that regulates anti‐oxidative stress enzymes and drug transporters, negatively regulated by Keap1 (kelch‐like ECH‐associated protein 1). Loss‐of‐function mutations of Keap1 gene and subsequent Nrf2 activation have been shown to be a mechanism of cisplatin resistance in adult cancers. We conducted this study to clarify the role of Nrf2‐Keap1 pathway in cisplatin resistance in NB. We investigated the basal activity of Nrf2 in nine NB cell lines (IMR‐32, LAN5, CHLA‐15, SH‐SY5Y, CHLA‐20, SKN‐FI, SK‐N‐BE(2), BE(2)C, CHLA‐90) using Antioxidant Response Element luciferase reporter assay. No cell lines had high reporter activities. In order to evaluate whether cisplatin activates Nrf2, we analyzed the mRNA expression of Nrf2 and its target genes (Glutamate‐Cysteine Ligase, Modifier Subunit: GCLM and NAD(P)H Dehydrogenase, Quinone 1: NQO1) after 24h treatment with cisplatin. In this experiment, we identified CHLA‐90 as one of the 3 cell lines, which showed high induction of Nrf2 target genes upon cisplatin exposure. However, knockdown of Nrf2 expression by small interfering RNA did not improve MTT assay‐measured dose‐response survival rate of CHLA‐90 with cisplatin treatment. We conclude that the Nrf2‐Keap1 pathway does not necessarily play an important role in cisplatin resistance in NB cells. Grant Funding Source : Supporter by CIHR, TCCSG, and Joseph M. West Family Memorial Fund
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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) | 0.002 | 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".