Abstract 5704: IDH2 mutation reduce radiotherapy induced immune response in glioblastoma by affecting micronucleus formation
Bibliographic record
Abstract
Abstract DNA methylation is the most abundant epigenetic modification, it plays a critical role in tissue homeostasis, genomic stability, and mitotic fidelity. Isocitrate dehydrogenase genes (IDH1/2) are non-redundantly mutated in several types of cancers including Glioblastoma (GBM), and their mutation induces a DNA hypermethylation phenotype. Radiotherapy (RT), either alone or in combination with other treatments, forms a primary intervention for GBM but the full scope of how IDH1/2 mutations influence this response are not known. In this work, we demonstrate that IDH2 mutation reduces the formation of post-RT micronuclei (MN), small DNA bodies in the cytoplasm distinct from the primary nucleus. Previously, MN has been found to recruit the pattern recognition receptor cGAS to activate an interferon-mediated signalling cascade via STING. We demonstrate that hypermethylation induced by IDH2 mutation does not impact cGAS localization to MN but instead reduces the overall burden of MN which correlates with decreased cGAS-STING mediated transcriptional activation. Mechanistically, IDH2 mutation drives centromeric hypermethylation which stabilizes kinetochore assembly and the fidelity of mitotic chromosome segregation post radiation. We also demonstrate that a reduction of MN formation in IDH2 mutant tumors reduces synergy between RT and immune checkpoint blockade in murine glioma models. Together our data suggest that metabolic alterations in cancers directly influence mitotic fidelity and response to RT with important implications for combination treatments that capitalize on synergy with the innate cellular signalling toward the adaptive immune system. Citation Format: Sara Mahmoud Elkashef, Shirony Nicholson, Shane Harding. IDH2 mutation reduce radiotherapy induced immune response in glioblastoma by affecting micronucleus formation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5704.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".