Ionizing radiation induces ataxia telangiectasia mutated kinase (ATM)-mediated phosphorylation of LKB1/STK11 at Thr-366
Bibliographic record
Abstract
The serine/threonine protein kinase LKB1 functions as a tumour suppressor, and mutations in this enzyme lead to the inherited Peutz-Jeghers cancer syndrome. We previously found that LKB1 was phosphorylated at Thr-366 in vivo, a residue conserved in mammalian, Xenopus and Drosophila LKB1, located on a C-terminal non-catalytic moiety of the enzyme. Mutation of Thr-366 to Ala or Asp partially inhibited the ability of LKB1 to suppress growth of G361 melanoma cells, but did not affect LKB1 activity in vitro or LKB1 localization in vivo. As a first step in exploring the role of this phosphorylation further, we have generated a phosphospecific antibody specifically recognizing LKB1 phosphorylated at Thr-366 and demonstrate that exposure of cells to ionizing radiation (IR) induced a marked phosphorylation of LKB1 at Thr-366 in the nucleus. Thr-366 lies in an optimal phosphorylation motif for the phosphoinositide 3-kinase-like kinases DNA-dependent protein kinase (DNA-PK), ataxia telangiectasia mutated kinase (ATM) and ataxia telangiectasia-related kinase (ATR), which function as sensors for DNA damage in cells and mediate cellular responses to DNA damage. We demonstrate that both DNA-PK and ATM efficiently phosphorylate LKB1 at Thr-366 in vitro and provide evidence that ATM mediates this phosphorylation in vivo. This is based on the finding that LKB1 is not phosphorylated in a cell line lacking ATM in response to IR, and that agents which induce cellular responses via ATR in preference to ATM poorly induce phosphorylation of LKB1 at Thr-366. These observations provide the first link between ATM and LKB1 and suggest that ATM could regulate LKB1.
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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) | 0.002 | 0.001 |
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".