FRA1 (FOSL1) suppresses neoplastic transformation and modulates radiation responses via transcriptional control of mitogenic and stress-responsive networks
Bibliographic record
Abstract
Purpose: , is an inducible subunit of the AP-1 transcription factor complex and regulates gene expression in response to proliferative and environmental cues. Although FRA1 has been linked to cancer progression, its role in early transformation and radiation responses remains unclear. Methods: CRISPR-engineered human CGL1 cells-a hybrid of HeLa and normal fibroblasts-were used to evaluate the impact of FRA1 overexpression and knockout on neoplastic transformation. Transformation frequency, clonogenic survival, DNA damage recognition and repair, and cell cycle distribution were assessed following irradiation. Transcriptomic profiling was performed under baseline and serum-stimulated conditions. Results: FRA1 loss markedly increased both spontaneous and radiation-induced transformation frequency, while overexpression suppressed transformation under both conditions. FRA1-deficient cells were sensitized to radiation-induced cell killing, despite intact DNA damage recognition and repair. In contrast, FRA1 overexpression promoted G2/M accumulation post-irradiation, suggesting enhanced checkpoint activation. Transcriptomic profiling revealed that FRA1 remodels AP-1 complex composition and functions as a transcriptional repressor of mitogen- and stress-responsive genes. FRA1-mediated repression was observed across gene networks involved in extracellular matrix remodeling, hypoxia signaling, inflammation, and proliferation, under both baseline and serum-stimulated conditions. Conclusion: These findings establish FRA1 as a key modulator of neoplastic transformation and radiation response, acting primarily through transcriptional repression of pro-tumorigenic signaling pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".