IL27 Signaling Serves as an Immunologic Checkpoint for Innate Cytotoxic Cells to Promote Hepatocellular Carcinoma
Bibliographic record
Abstract
Although inflammatory mechanisms driving hepatocellular carcinoma (HCC) have been proposed, the regulators of anticancer immunity in HCC remain poorly understood. We found that IL27 receptor (IL27R) signaling promotes HCC development in vivo. High IL27EBI3 cytokine or IL27RA expression correlated with poor prognosis for patients with HCC. Loss of IL27R suppressed HCC in vivo in two different models of hepatocarcinogenesis. Mechanistically, IL27R sig-naling within the tumor microenvironment restrains the cytotoxicity of innate cytotoxic lymphocytes. IL27R ablation enhanced their accumulation and activation, whereas depletion or functional impairment of innate cytotoxic cells abrogated the effect of IL27R disruption. Pharmacologic neutralization of IL27 signaling increased infiltration of innate cytotoxic lymphocytes with upregulated cytotoxic molecules and reduced HCC development. Our data reveal an unexpected role of IL27R signaling as an immunologic checkpoint regulating innate cytotoxic lymphocytes and promoting HCC of different etiologies, thus indicating a therapeutic potential for IL27 pathway blockade in HCC. SIGNIFICANCE: HCC, the most common form of liver cancer, is characterized by a poor survival rate and limited treatment options. The discovery of a novel IL27-dependent mechanism controlling anticancer cytotoxic immune response will pave the road for new treatment options for this devastating disease. This article is highlighted in the In This Issue feature, p. 1825.
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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 | 0.001 |
| 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".