Abstract SY28-01: Management of MAP kinase and apoptosis signaling thresholds by microRNAs
Bibliographic record
Abstract
Abstract An important problem in cancer biology is concerned with how apoptotic thresholds are established. Defective regulation of apoptosis can cause resistance to chemotherapeutic agents and radiation therapy, which highlights the need to resensitize these tumors to therapy. The apoptosis pathway was first elucidated in the roundworm Caenorhabditis elegans, and studies in this organism continue to uncover regulatory mechanisms that are also conserved in humans. By taking advantage of the powerful genetics, cell biology, and proteomics tools of C. elegans, we seek to understand how apoptotic signaling is fine-tuned in response to ionizing radiation (IR). Our work has uncovered a network of regulatory mechanisms, such as ubiquitin proteolysis and microRNAs, that control the levels of apoptotic proteins. I will discuss our recent efforts to understand how microRNA 35 (mir-35) antagonizes translation of the BH3-only protein EGL-1 and the Ras/MAPK effector NDK-1 in response to IR. EGL-1 is homologous to human PUMA and NDK-1 is the worm orthologue of human NME1 (NME/NM23 nucleoside diphosphate kinase 1), which has been shown to regulate MAPK signaling in both worms and human cells. mir-35 normally functions to buffer IR-induced apoptosis through its combinatorial effects on EGL-1 and NDK-1 translation. Ablation of mir-35, or mutations in the mir-35 binding sites in the 3'-untranslated region (3'UTR) of egl-1 and ndk-1, increase the levels of these proteins and cause hypersensitivity to IR-induced apoptosis. By targeting both the core apoptosis pathway and the MAPK cascade, we propose that mir-35 plays a key role in fine-tuning apoptotic signaling in order to protect healthy cells and ensure a rapid response to DNA-damaging agents. Given the high conservation in the organization of these pathways from C. elegans to human, manipulating microRNAs might help resensitize tumors that have developed resistance to radiation and/or chemotherapy. Citation Format: W. Brent Derry. Management of MAP kinase and apoptosis signaling thresholds by microRNAs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr SY28-01.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 0.000 |
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 teacher head, 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".