Frequent concerted genetic mechanisms disrupt multiple components of the NRF2 inhibitor KEAP1/CUL3/RBX1 E3-ubiquitin ligase complex in thyroid cancer
Bibliographic record
Abstract
BACKGROUND: Reactive oxygen species contribute to normal thyroid function. The NRF2 oxidative response pathway is frequently and constitutively activated in multiple tumor types, including papillary thyroid carcinoma (PTC). Genetic mechanisms underlying NRF2 pathway activation in PTC are not fully understood. Thus, we aimed to determine whether inactivating patterns of DNA-level alterations affect genes encoding for individual NRF2 inhibitor complex components (CUL3/KEAP1/RBX1) occur in PTC. FINDINGS: Combined patterns of epi/genetic alterations for KEAP1/CUL3/RBX1 E3 ubiquitin-ligase complex components were simultaneously interrogated for a panel of 310 PTC cases and 40 adjacent non-malignant tissues. Data were obtained from The Cancer Genome Atlas project. Enrichment of NRF2 pathway activation was assessed by gene-set enrichment analysis using transcriptome data. Our analyses revealed that PTC sustain a strikingly high frequency (80.6%) of disruption to multiple component genes of the NRF2 inhibitor complex. Hypermethylation is the predominant inactivating mechanism primarily affecting KEAP1 (70.6%) and CUL3 (20%), while copy number loss mostly affects RBX1 (16.8%). Concordantly, NRF2-associated gene expression signatures are positively and significantly enriched in PTC. CONCLUSIONS: The KEAP1/CUL3/RBX1 E3-ubiquitin ligase complex is almost ubiquitously affected by multiple DNA-level mechanisms and downstream NRF2 pathway targets are activated in PTC. Given the importance of this pathway to normal thyroid function as well as to cancer; targeted inhibition of NRF2 regulators may impact strategies for therapeutic intervention involving this pathway.
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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 | 0.001 | 0.001 |
| 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".