CD8 T cell hyperfunction and reduced tumour control in models of advanced liver fibrosis
Bibliographic record
Abstract
Abstract Immune dysfunction, both depression and hyperactivation, in liver disease contributes to significant morbidities and mortalities, depending on liver damage severity and etiology. The underlying causes of immune dysfunction in advanced liver disease, whether pathogen or host-mediated, remain unclear. We reported lasting generalized CD8 + T cell hyperfunction in individuals with advanced liver fibrosis in chronic HCV infection. The separation of viral and fibrosis-driven effects or the association of this phenomenon with clinical outcomes of advanced liver fibrosis remains to be determined. Here, a hepatotoxic murine model of liver fibrosis was used to decouple liver fibrosis from viral infection. Carbon tetrachloride (CCl 4 )-treated mice presented progressive liver fibrosis within ≈12 weeks, resulting in severe diffuse fibrosis, focal necrosis and surrounding mixed inflammation; pathology similar to that of chronic HCV infection. Taking advantage of this model, we investigated if liver fibrosis caused systemic CD8 + T cell hyperfunction and evaluated its impact on host immune response. At peak liver fibrosis, circulating CD8 + T cells presented increased expression of IFN-γ and granzyme B (GrzB) in comparison to control animals. CD8 + T cell hyperfunction arose by 8 weeks of CCl 4 treatment and was sustained with continued liver insult. As a result, fibrotic mice were unable to resist an ectopic tumour challenge and were less responsive to immunotherapy. Furthermore, CD8 + T cell dysfunction was observed in other contexts of chronic liver insult such as high fat diet-induced liver steatosis, even in the absence of significant fibrosis. Collectively, this study shows the impact of chronic liver insult on systemic CD8 + T cell function and its association with impaired immune response, such as tumour surveillance.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".