Abstract IA020: Micronuclei are a nexus of DNA damage signaling and genomic instability
Bibliographic record
Abstract
Abstract Micronuclei have classically been considered inert biomarkers of genomic instability arising from failed DNA damage repair and chromosome segregation errors in mitosis. Work from several groups including our own have now demonstrated that micronuclei are active contributors to the cellular response to DNA damage by driving chromothripsis and through induction of anti-viral gene expression programs mediated by the cGAS-STING pathway. We now show that the specific DNA damage type leading to micronuclei formation influences the capacity for cGAS localization and activation. This arises in part due to discrete chromatin features, present prior to DNA damage induction, that are retained in micronuclei several days after their formation. Together these data demonstrate that micronuclei connect the pre-damage chromatin status and the chromatin context of micronuclei-inciting lesions to the long-term signaling outcomes important for anti-tumor immunity. This finding implies that micronuclei represent archives for the nature of DNA repair failure and downstream signaling consequences. Based on this premise we will present our efforts in micronuclear proteomics where we uncover common features of micronuclei including splicing deficiencies. Such deficiencies presage exacerbated MN-associated DNA damage that is upstream of chromothripsis. These studies have direct implications for how cells sense the aftermath of DNA damage and how micronuclei contribute to ongoing genomic instability. Citation Format: Shane M. Harding. Micronuclei are a nexus of DNA damage signaling and genomic instability [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr IA020.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".