Human hepatic stellate cells orchestrate the accumulation and function of CD103 <sup>+</sup> tissue-resident CD8 <sup>+</sup> T-cells in liver fibrosis
Bibliographic record
Abstract
Abstract Tissue-resident memory cells (T RM ) contribute to protective and pathogenic responses in the liver, yet precisely how hepatic T RM adapt and integrate cues from the underlying stroma and extracellular matrix (ECM) in chronic liver disease (CLD) has yet to be fully defined. Here we describe a role for activated myofibroblast-like hepatic stellate cells (HSCs) in the accumulation and in situ localisation of CD8 + T RM in the CLD liver. Activated HSCs drive a program of tissue residence in activated, tissue-infiltrating CD8 + T-cells in a TGFβ-dependent manner. We show upregulation of CD103, ECM-binding integrins and adhesion molecules driven by TGFβ which together contribute to the sequestration of T RM within the ECM-rich fibrotic niche. Ex vivo , hepatic CD103 + T RM correlate with the extent of ECM deposited, express an altered repertoire of co-stimulatory and co-inhibitory receptors, transcriptional regulators of cellular exhaustion and produce less proinflammatory mediators upon TCR engagement in CLD than in health. Through expression of several co-inhibitory ligands, we further demonstrate the potential for activated HSCs to acquire an immunomodulatory phenotype and limit the capacity of CD103 + T RM to produce anti-viral and anti-tumour mediators upon antigen encounter. Finally, we demonstrate that strategies to block such regulatory pathways, including the PD1:PD-L1/PD-L2 axis, have the potential to restore the antigen-specific effector function of tissue-compartmentalised CD103 + T RM and thus contribute to improving the effectiveness of local immunosurveillance in CLD. One Sentence Summary: Activated hepatic stellate cells characteristic of liver fibrosis orchestrate an accumulation of a CD103 + T RM population with a reduced capacity for antigen-specific effector function in human CLD.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".