Abstract IA17: Non-canonical aspects of ATM and p53 signaling pathways
Bibliographic record
Abstract
Abstract The ATM protein kinase and p53 protein are both central mediators of many aspects of DNA damage and cellular stress signaling. While there is a clear, direct relationship between ATM and p53, ATM has numerous substrates in addition to p53 and, conversely, p53 can be activated by selected stresses without ATM. We have identified novel aspects of stress response signaling independently involving either ATM or p53. Though ATM plays a central role in mediating cellular responses to DNA breakage, some of the clinical abnormalities in the cancer-prone disorder, Ataxia-telangiectasia (A-T), are difficult to attribute directly to alterations in DNA damage signaling, such as neurodegeneration (primarily cerebellar), immunodeficiency, insulin resistance, progressive lung disease, and telangiectasia development. Our recent data demonstrate that, in addition to its DNA damage signaling functions, the ATM protein kinase has critical, p53-independent, non-canonical roles in modulating mitochondrial function and affecting metabolic stress signaling. It is intriguing that one gene product seems to be at a nexus of DNA damage signaling and metabolic signaling, but perhaps it should not be surprising that these pathways would be linked and that a protein with a PI-3K domain and a protein in the mTOR kinase family would provide such a link. These insights suggest that Ataxia-telangiectasia should be considered, at least in part, as a mitochondrial dysfunction disease and provide links between cancer-related DNA damage signaling, general metabolic signaling pathways, and cancer development. We have also identified novel aspects of p53 regulation by DNA damage involving ATM-independent regulation of RNA splicing, a process which affects splicing of p53 and other gene products and modulates cellular outcome after DNA damage. This DNA damage-induced alternative splicing pathway expands the repertoire of gene products that modulate cellular stress responses. Citation Format: Michael B. Kastan, Peter Scarbrough, Jing Chen, Adam Brown, John Crutchley, Donald Fleenor. Non-canonical aspects of ATM and p53 signaling pathways [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr IA17.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".