Increase in lamin B1 promotes telomere instability by disrupting the shelterin complex in human cells
Bibliographic record
Abstract
Telomere maintenance is essential to preserve genomic stability and involves telomere-specific proteins, DNA replication and repair proteins. Lamins are key components of the nuclear envelope and play numerous roles, including maintenance of the nuclear integrity, regulation of transcription, and DNA replication. Elevated levels of lamin B1, one of the major lamins, have been observed in some human pathologies and several cancers. Yet, the effect of lamin B1 dysregulation on telomere maintenance remains unknown. Here, we unveil that lamin B1 overexpression drives telomere instability through the disruption of the shelterin complex. Indeed, lamin B1 dysregulation leads to an increase in telomere dysfunction-induced foci, telomeric fusions and telomere losses in human cells. Telomere aberrations were preceded by mislocalizations of TRF2 and its binding partner RAP1. Interestingly, we identified new interactions between lamin B1 and these shelterin proteins, which are strongly enhanced at the nuclear periphery upon lamin B1 overexpression. Importantly, chromosomal fusions induced by lamin B1 in excess were rescued by TRF2 overexpression. These data indicated that lamin B1 overexpression triggers telomere instability through a mislocalization of TRF2. Altogether our results point to lamin B1 as a new interacting partner of TRF2, that is involved in telomere stability.
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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".