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Record W3196316775 · doi:10.1016/j.celrep.2021.109621

GAGE mediates radio resistance in cervical cancers via the regulation of chromatin accessibility

2021· article· en· W3196316775 on OpenAlexfundno aff
Dawn Sijin Nin, Caryn Wujanto, Tuan Zea Tan, Diana Lim, J Damen, Kuan-Yi Wu, Ziyu Dai, Zheng‐Wei Lee, Shabana Binte Idres, Yiat Horng Leong, Sudhakar Jha, Joseph Ng, Jeffrey Low, Shih‐Chung Chang, David S.P. Tan, Wei Wu, Bok Ai Choo, Lih‐Wen Deng

Bibliographic record

VenueCell Reports · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
FundersNational Cancer Institute, Cairo UniversityKementerian Pendidikan MalaysiaNational University Health SystemTerry Fox FoundationNational Cancer Institute - SingaporeNational University of SingaporeMinistry of Education
KeywordsChromatinHistoneAcetylationBiomarkerCancer researchChromatin remodelingHistone deacetylaseBiologyHistone deacetylase inhibitorEpigeneticsCancerMedicineBioinformaticsInternal medicineDNAGeneticsGene

Abstract

fetched live from OpenAlex

Radiotherapy (RT) resistance is a major cause of treatment failure in cancers that use definitive RT as their primary treatment modality. This study identifies the cancer/testis (CT) antigen G antigen (GAGE) as a mediator of radio resistance in cervical cancers. Elevated GAGE expression positively associates with de novo RT resistance in clinical samples. GAGE, specifically the GAGE12 protein variant, confers RT resistance through synemin-dependent chromatin localization, promoting the association of histone deacetylase 1/2 (HDAC1/2) to its inhibitor actin. This cumulates to elevated histone 3 lysine 56 acetylation (H3K56Ac) levels, increased chromatin accessibility, and improved DNA repair efficiency. Molecular or pharmacological disruption of the GAGE-associated complex restores radiosensitivity. Molecularly, this study demonstrates the role of GAGE in the regulation of chromatin dynamics. Clinically, this study puts forward the utility of GAGE as a pre-screening biomarker to identify poor responders at initial diagnosis and the therapeutic potential of agents that target GAGE and its associated complex in combination with radiotherapy to improve outcomes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.240
Teacher spread0.231 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations23
Published2021
Admission routes1
Has abstractyes

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