TP53/mTORC1-mediated bidirectional regulation of PD-L1 modulates immune evasion in hepatocellular carcinoma
Bibliographic record
Abstract
Background Immunotherapy has facilitated great breakthroughs in the treatment of hepatocellular carcinoma (HCC). However, the efficacy and response rate of immunotherapy are limited and vary among different patients with HCC. TP53 mutation substantially affects the expression of immune checkpoint molecules in multiple cancers. However, the regulatory relationship between programmed death ligand 1 (PD-L1) and TP53 is poorly studied in HCC. We aimed to elucidate the regulatory mechanism of PD-L1 in HCC with different TP53 statuses and to assess its role in modulating immune evasion in HCC. Methods HCC mouse models and cell lines with different TP53 statuses were constructed. PD-L1 levels were detected by PCR, western blotting and flow cytometry. RNA-seqencing, immunoprecipitation, chromatin immunoprecipitation and transmission electron microscopy were used to elucidate the regulatory mechanism in HCC with different TP53 status. HCC mouse models and patient with HCC samples were analyzed to demonstrate the preclinical and clinical significance of the findings. Results We report that loss of p53 promoted PD-L1 expression and reduced CD8 + T-cell infiltration in patient with HCC samples and mouse models. Mammalian target of rapamycin (mTOR) pathway was activated in p53-loss-of-function HCC or after knocking down TP53. The transcription factor E2F1 was found to bind to the p53 protein in TP53 wild-type HCC cells, and inhibiting mammalian target of rapamycin complex 1 (mTORC1) disrupted this binding and enhanced E2F1 translocation to the nucleus, where it bound to the PD-L1 promoter and transcriptionally upregulated PD-L1. In p53-loss-of-function HCC cells, autophagosomes were activated after mTORC1 suppression, promoting the degradation of PD-L1 protein. The combination of mTOR inhibitor and anti-PD-L1 antibody enhanced CD8 + T-cell infiltration and tumor suppression in TP53 wild-type HCC mouse models, but no benefit was observed in p53-loss-of-function HCC mouse models. In patients with TP53 wild-type HCC, PD-L1 levels were significantly higher in the high E2F1 group than in the low E2F1 group, and the low E2F1 level group had significantly superior survival. Conclusion We revealed the bidirectional regulatory mechanism of PD-L1 mediated by TP53/mTORC1 in HCC. The combination of mTOR inhibitor and anti-PD-L1 antibody could be a novel precise immunotherapy scheme for TP53 wild-type HCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 0.000 |
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.
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 teacher head, 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".