Abstract 4479: Protein arginine methyltransferase PRMT6 regulates cancer stemness through CRAF methylation in hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Arginine methylation is a post-translational modification that plays pivotal roles in signal transduction and gene transcription during cell fate determination. We found protein methyltransferase 6 (PRMT6) to be frequently down-regulated in hepatocellular carcinoma (HCC) cells and its expression to negatively correlate with aggressive cancer features in HCC patients. Silencing of PRMT6 promoted the tumor-initiating, metastasis and therapy resistance potential of HCC cells. Consistently, loss of PRMT6 expression aggravated liver tumorigenesis in a DEN+CCL4 HCC induced PRMT6-/- mouse model. Integrated transcriptome and protein-protein interaction studies revealed an enrichment of genes implicated in RAS signaling and that PRMT6 interacted with CRAF, and likely other RAF family members, and their methylation at conserved arginine 100, negatively regulating its activity, and as a consequence resulting in enhanced MEK/ERK signaling. Our work uncovered a critical repressive function for PRMT6 in maintenance of HCC cells by regulating the MEK/ERK pathway via arginine methylation of RAF, providing a new avenue of molecular mechanism by which ERK mediated stemness in HCC cells are developed. Citation Format: LH Chan, L Zhou, Kai Yu Ng, TL Wong, TK Lee, YP Ching, YF Yuan, D Xie, S Richard, MS Huen, XY Guan, S Ma. Protein arginine methyltransferase PRMT6 regulates cancer stemness through CRAF methylation in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4479.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".