NRF3 suppresses squamous carcinogenesis, involving the unfolded protein response regulator HSPA5
Bibliographic record
Abstract
Epithelial skin cancers are extremely common, but the mechanisms underlying their malignant progression are still poorly defined. Here, we identify the NRF3 transcription factor as a tumor suppressor in the skin. NRF3 protein expression is strongly downregulated or even absent in invasively growing cancer cells of patients with basal and squamous cell carcinomas (BCC and SCC). NRF3 deficiency promoted malignant conversion of chemically induced skin tumors in immunocompetent mice, clonogenic growth and migration of human SCC cells, their invasiveness in 3D cultures, and xenograft tumor formation. Mechanistically, the tumor-suppressive effect of NRF3 involves HSPA5, a key regulator of the unfolded protein response, which we identified as a potential NRF3 interactor. HSPA5 levels increased in the absence of NRF3, thereby promoting cancer cell survival and migration. Pharmacological inhibition or knock-down of HSPA5 rescued the malignant features of NRF3-deficient SCC cells in vitro and in preclinical mouse models. Together with the strong expression of HSPA5 in NRF3-deficient cancer cells of SCC patients, these results suggest HSPA5 inhibition as a treatment strategy for these malignancies in stratified cancer patients.
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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".