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Abstract IA22: Tumor cells highjack diverse cellular processes to maintain redox balance

2020· article· en· W3046047132 on OpenAlexaboutno aff
Haifeng Zhang, Amal M. El Naggar, Hongwei Cheng, Wěi Li, Dimiter S. Dimitrov, Poul H. Sorensen

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsOxidative stressMetastasisAnoikisCancer researchCancerBiologyMedicineSarcomaBioinformaticsPathologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract In aggressive sarcomas such as Ewing sarcoma (EwS) and osteosarcoma (OS), the single most powerful predictor of poor outcome is metastatic disease, highlighting the critical need to identify new factors driving metastasis in these diseases. Metastasis is widely regarded as a very inefficient process, likely due to diverse stress forms that can potentially cull premetastatic cancer cells during the metastatic cascade, including hypoxia in primary tumors, anoikis stress in the circulation, and increased oxidative stress at distant organs prior to colonization. Adaptation to such conditions requires rapid stress-alleviating plasticity to confer fitness for metastatic progression, but mechanisms remain elusive. Studies in our laboratory indicate that mitigation of oxidative stress, not only during local invasion at the primary tumor site but also in the circulation during dissemination, and potentially as part of colonization at distant sites, is critical for childhood sarcoma metastatic capacity. Indeed, EwS and OS cells appear to utilize many different strategies to maintain redox balance, such as the induction of antioxidant pathways involving NRF2 or through other mechanisms such as alterations in amino acid transporter systems to facilitate production of glutathione and other antioxidants via amino acid metabolism. Some of these pathways are transcriptionally regulated, such as by direct activation of EWS-ETS fusion targets, while others are regulated through rapid translational activation by pioneer translation factors such as YB-1. Examples of each of these processes will be discussed. Citation Format: Hai-Feng Zhang, Amal M. El Naggar, Hongwei Cheng, Wei Li, Dimiter S. Dimitrov, Poul H. Sorensen. Tumor cells highjack diverse cellular processes to maintain redox balance [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 IA22.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.050
GPT teacher head0.367
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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