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Record W4409540194 · doi:10.1016/j.ccell.2025.03.027

Circular RMST cooperates with lineage-driving transcription factors to govern neuroendocrine transdifferentiation

2025· article· en· W4409540194 on OpenAlexafffund
Mona Teng, Jiacheng Guo, Xin Xu, Xinpei Ci, Yulin Mo, Yakup Kohen, Zuyao Ni, Sujun Chen, Martin Bakht, Sheng‐Yu Ku, Michael Sigouros, Wenqin Luo, Colette Maya Macarios, Ziting Xia, Moliang Chen, Sami Ul Haq, Wen‐Bin Yang, Alejandro Berlín, Theodorus van der Kwast, Leigh Ellis, Amina Zoubeidi, Gang Zheng, Jie Ming, Yuzhuo Wang, Haissi Cui, Benjamin H. Lok, Brian Raught, Himisha Beltran, Jun Qin, Housheng Hansen He

Bibliographic record

VenueCancer Cell · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMechanisms of cancer metastasis
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoUniversity of British ColumbiaUniversity Health NetworkPrincess Margaret Cancer Centre
FundersTerry Fox Research InstituteNational Natural Science Foundation of ChinaCanada Foundation for InnovationCanadian Institutes of Health ResearchCancer Research SocietyMemorial Sloan-Kettering Cancer CenterAstraZenecaNational Cancer InstituteNational Institutes of HealthProstate Cancer FoundationU.S. Department of Defense
KeywordsTransdifferentiationTranscription factorBiologyLineage (genetic)Cell biologyGeneticsComputational biologyBioinformaticsGeneStem cell

Abstract

fetched live from OpenAlex

Circular RNA (circRNA) is a class of noncoding RNA with regulatory potentials. Its role in the transdifferentiation of prostate and lung adenocarcinoma into neuroendocrine prostate cancer (NEPC) and small cell lung cancer (SCLC) remains unexplored. Here, we identified circRMST as an exceptionally abundant circRNA predominantly expressed in NEPC and SCLC, with strong conservation between humans and mice. Functional studies using shRNA, siRNA, CRISPR-Cas13, and Cas9 consistently demonstrate that circRMST is essential for tumor growth and the expression of ASCL1, a master regulator of neuroendocrine fate. Genetic knockout of Rmst in NEPC genetic engineered mouse models prevents neuroendocrine transdifferentiation, maintaining tumors in an adenocarcinoma state. Mechanistically, circRMST physically interacts with lineage transcription factors NKX2-1 and SOX2. Loss of circRMST induces NKX2-1 protein degradation through autophagy-lysosomal pathway and alters the genomic binding of SOX2, collectively leading to the loss of ASCL1 transcription.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.064
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.240
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2025
Admission routes2
Has abstractyes

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