Abstract PR14: Ewing sarcoma cells exploit the IL1RAP-CTH axis to drive oxidative stress adaptation and lung metastasis
Bibliographic record
Abstract
Abstract Metastasis is a highly inefficient process due to the high oxidative stress that cancer cells experience, such as in the circulation and at distant organs prior to colonization. How cancer cells adapt to those stressful conditions and develop anti-anoikis properties remains elusive. Here our global translatome and proteome analyses have uncovered novel signatures exploited by oncogene-transformed cells to adapt and survive anoikis-inducing stress. We reveal that EWS-ETS chimeric oncoproteins trigger the expression of the IL1RAP surface protein to alleviate oxidative stress and facilitate stress adaptation, thereby promoting lung metastasis in Ewing sarcoma. Proteomic profiling identifies CTH, a key enzyme for de novo cysteine synthesis and redox regulation, as an important functional downstream mediator of IL1RAP. Blockade of either IL1RAP or CTH, using genetic or pharmacologic approaches, renders EWS cells susceptible to oxidative stress in vitro, and dramatically mitigates primary tumor growth, local invasion and lung metastasis in mice. Importantly, high expression of this IL1RAP-CTH axis correlates with markedly decreased overall and event-free survival in EWS patients. Thus, our study has defined a novel mechanism exploited by EWS cells for metastasis, which can be a potential therapeutic target for high-risk metastatic EWS. This abstract is also being presented as Poster B58. Citation Format: Haifeng Zhang, Amal M. El-Naggar, Hongwei Cheng, Alberto Delaidelli, Gian Luca Negri, Wei Li, Dimiter S. Dimitrov, Poul H.B. Sorensen. Ewing sarcoma cells exploit the IL1RAP-CTH axis to drive oxidative stress adaptation and lung metastasis [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr PR14.
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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".