The EGFR ligand amphiregulin regulates genomic integrity by facilitating heterochromatin formation in response to replication stress
Bibliographic record
Abstract
Abstract The EGFR ligand, amphiregulin (AREG) is a key mammary ductal cell differentiation and growth factor. AREG has also been detected in the nucleus of some epithelial cancers although the physiological stimulus and nuclear role are not known. Using immortalized mammary epithelial cells (MECs), we have discovered that AREG undergoes retrograde trafficking to the nuclear membrane (nAREG) in close proximity with lamin A where it is required to both maintain constitutive heterochromatin and transiently increases H3K9me3 in response to replication stress (RS). RS resulted in an increase in AREG protein, enhanced nuclear membrane prelamin A and increased heterochromatin protein, HP1α. In contrast, siRNA-mediated depletion of endogenous AREG reduced HP1α and SUV39h1 proteins accompanied by decompaction and reduction in H3K9me3 heterochromatin despite the presence of soluble AREG. The nuclear membrane (NM) was also impacted resulting in dissipation of the Ran-GTPase gradient, reduced matrix lamin A with increased invaginations. Moreover, AREG knockdown slowed replication fork speed, increased new replication origins and enhanced global transcription while promoting and exacerbating DNA damage in response to RS. DNA damage was most pronounced in AREG-depleted BRCA2 mut/+ MECs which entered senescence following RS, indicating an important nAREG-dependent role in genomic stabilization in these cells. Overall, this study reveals a novel and fundamental role for nAREG in heterochromatin maintenance and the response to RS, that is most critical in BRCA2 mut/+ MECs deficient in replication fork protection.
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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".