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Abstract LB-139: PRMT6-dependent CRAF/ERK signaling regulates cancer stem cell plasticity in liver cancer

2017· article· en· W2943908605 on OpenAlexaff
Lok-Hei Chan, Lei Zhou, Kai Yu Ng, Tin Lok Wong, Stella Chai, Terence K. Lee, Xin‐Yuan Guan, Chung Mau Lo, Kwan Man, Benedetta Artegiani, Hans Clevers, Helen Hoi Ning Yan, Suet Yi Leung, Stéphane Richard, Michael S.Y. Huen, Stephanie Ma

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsConcordia UniversityMcGill University
Fundersnot available
KeywordsCancer stem cellCancer researchBiologyLiver cancerStem cellMetastasisCancer cellChromatinCancerStem cell markerProtein arginine methyltransferase 5MethyltransferaseMethylationMolecular biologyCell biologyHepatocellular carcinomaBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Hepatocellular carcinoma (HCC), the major type of liver cancer, remains one of the most prevalent and deadliest cancer types in the world. Contemporary challenge in treating HCC has been the common therapy resistance and recurrence after therapy, all of which have been reported to be associated with stem-like behavior of cancer cells. Our group has previously identified a functional liver cancer stem cell (CSC) subset marked by the CD133 cell surface phenotype. Utilizing a PCR array encompassing diverse human chromatin modifiers, protein arginine methyltransferase 6 (PRMT6) was found to be differentially down-regulated in CD133+ liver CSCs of human HCC cells as well as CD133 enriched chemoresistant hepatospheres as compared to their counterparts. Clinically, reduced PRMT6 expression was detected in HCC specimens and correlated with a higher risk of metastasis. PRMT6 negatively regulated diverse in vitro cancer stem cell properties of HCC cells including self-renewal, therapy resistance, metastasis and expression of CSC and pluripotency markers. In addition, PRMT6 also suppressed in vivo tumor initiation and serial transplantation. Surprising, contrary to its usual localization in the nucleus as a chromatin modification enzyme mediating histone H3R2 methylation, we found PRMT6 to be predominantly expressed in the cytoplasm in normal liver and HCC cells. Through tandem affinity purification and subsequent mass spectrometry profiling, we identified CRAF, a serine/threonine-protein kinase, as a novel cytoplasmic protein partner of PRMT6. Binding of PRMT6 to CRAF inhibited its kinase activity through site-specific arginine methylation, resulting in inhibition of ERK-mediated CSC plasticity in HCC, demonstrated through in vivo / in vitro methylation assays, kinase assay and functional rescue experiments with the ERK inhibitor U0126. The link between PRMT6, ERK and cancer stemness was further substantiated in primary human normal liver and HCC organoids with or without PRMT6 modulated. Taken together, we found PRMT6 to be down-regulated in the liver CSC subset and to be functionally involved in regulating liver CSC plasticity via an unprecedented role in the cytoplasm through suppression of CRAF/ERK cascade. Citation Format: Lok Hei Chan, Lei Zhou, Kai Yu Ng, Tin Lok Wong, Stella Chai, Terence K Lee, Xin Yuan Guan, Yick Pang Ching, Chung Mau Lo, Kwan Man, Benedetta Artegiani, Hans Clevers, Helen H Yan, Suet Yi Leung, Stèphane Richard, Michael SY Huen, Stephanie Ma. PRMT6-dependent CRAF/ERK signaling regulates cancer stem cell plasticity in liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-139. doi:10.1158/1538-7445.AM2017-LB-139

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.059
GPT teacher head0.372
Teacher spread0.312 · 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 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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