Abstract 3955: 53BP1 facilitates the ATM-dependent phosphorylation of APLF in the DNA damage response
Bibliographic record
Abstract
Abstract Aprataxin and polynucleotide kinase-like factor (APLF) is a DNA repair factor which facilitates DNA repair in part through interactions with its forkhead-associated (FHA) domain. The APLF FHA domain mediates interactions with specific threonine phosphorylated epitopes via a functionally conserved and essential arginine residue (Arg-27). In the context of DNA double-strand break (DSB) repair, substitution of APLF amino acid residue Arg-27 to alanine abolishes interactions with the DSB repair scaffold protein XRCC4, and impairs DSB repair. APLF is also a component of the ATM-dependent DNA damage response (DDR), which also includes 53BP1, and undergoes ionizing-radiation induced phosphorylation at Ser-116 facilitating its role in DSB repair. Here we demonstrate that the APLF FHA domain is essential for Ser-116 phosphorylation and for the association with 53BP1, which collectively enhance the accumulation of APLF at sites of DNA damage. The level of 53BP1 expression, but not XRCC4, was found to correlate with the phosphorylation of APLF by ATM, and disruption of the APLF-53BP1 interaction was associated with impaired cell survival following DNA damage. These results suggest that the APLF FHA domain directs interactions with multiple partners in the DNA damage response, and that 53BP1 facilitates the ATM-dependent phosphorylation of APLF. Citation Format: Amanda L. Fenton, Diana Tran, Christine Anne Koch. 53BP1 facilitates the ATM-dependent phosphorylation of APLF in the DNA damage response. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3955. doi:10.1158/1538-7445.AM2014-3955
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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) | 0.019 | 0.005 |
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".