Hepatic stellate cell stearoyl co-A desaturase activates leukotriene B4 receptor 2 - β-catenin cascade to promote liver tumorigenesis
Bibliographic record
Abstract
most deadly malignancy. Activated hepatic stellate cells (aHSC) give rise to cancer-associated fibroblasts in HCC and are considered a potential therapeutic target. Here we report that selective ablation of stearoyl CoA desaturase-2 (Scd2) in aHSC globally suppresses nuclear CTNNB1 and YAP1 in tumors and tumor microenvironment and prevents liver tumorigenesis in male mice. Tumor suppression is associated with reduced leukotriene B4 receptor 2 (LTB4R2) and its high affinity oxylipin ligand, 12-hydroxyheptadecatrienoic acid (12-HHTrE). Genetic or pharmacological inhibition of LTB4R2 recapitulates CTNNB1 and YAP1 inactivation and tumor suppression in culture and in vivo. Single cell RNA sequencing identifies a subset of tumor-associated aHSC expressing Cyp1b1 but no other 12-HHTrE biosynthetic genes. aHSC release 12-HHTrE in a manner dependent on SCD and CYP1B1 and their conditioned medium reproduces the LTB4R2-mediated tumor-promoting effects of 12-HHTrE in HCC cells. CYP1B1-expressing aHSC are detected in proximity of LTB4R2-positive HCC cells and the growth of patient HCC organoids is blunted by LTB4R2 antagonism or knockdown. Collectively, our findings suggest aHSC-initiated 12-HHTrE-LTB4R2-CTNNB1-YAP1 pathway as a potential HCC therapeutic target.
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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".