Hepatoma-intrinsic CCRK inhibition diminishes myeloid-derived suppressor cell immunosuppression and enhances immune-checkpoint blockade efficacy
Bibliographic record
Abstract
Objective Myeloid-derived suppressor cells (MDSCs) contribute to tumour immunosuppressive microenvironment and immune-checkpoint blockade resistance. Emerging evidence highlights the pivotal functions of cyclin-dependent kinases (CDKs) in tumour immunity. Here we elucidated the role of tumour-intrinsic CDK20, or cell cycle-related kinase (CCRK) on immunosuppression in hepatocellular carcinoma (HCC). Design Immunosuppression of MDSCs derived from patients with HCC and relationship with CCRK were determined by flow cytometry, expression analyses and co-culture systems. Mechanistic studies were also conducted in liver-specific CCRK -inducible transgenic (TG) mice and Hepa1–6 orthotopic HCC models using CRISPR/Cas9-mediated Ccrk depletion and liver-targeted nanoparticles for interleukin (IL) 6 trapping. Tumorigenicity and immunophenotype were assessed on single or combined antiprogrammed death-1-ligand 1 (PD-L1) therapy. Results Tumour-infiltrating CD11b + CD33 + HLA-DR − MDSCs from patients with HCC potently inhibited autologous CD8 + T cell proliferation. Concordant overexpression of CCRK and MDSC markers (CD11b/CD33) positively correlated with poorer survival rates. Hepatocellular CCRK stimulated immunosuppressive CD11b + CD33 + HLA-DR − MDSC expansion from human peripheral blood mononuclear cells through upregulating IL-6. Mechanistically, CCRK activated nuclear factor-κB (NF-κB) via enhancer of zeste homolog 2 (EZH2) and facilitated NF-κB-EZH2 co-binding to IL-6 promoter. Hepatic CCRK induction in TG mice activated the EZH2/NF-κB/IL-6 cascade, leading to accumulation of polymorphonuclear (PMN) MDSCs with potent T cell suppressive activity. In contrast, inhibiting tumorous Ccrk or hepatic IL-6 increased interferon γ + tumour necrosis factor-α + CD8 + T cell infiltration and impaired tumorigenicity, which was rescued by restoring PMN-MDSCs. Notably, tumorous Ccrk depletion upregulated PD-L1 expression and increased intratumorous CD8 + T cells, thus enhancing PD-L1 blockade efficacy to eradicate HCC. Conclusion Our results delineate an immunosuppressive mechanism of the hepatoma-intrinsic CCRK signalling and highlight an overexpressed kinase target whose inhibition might empower HCC immunotherapy.
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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) | 0.002 | 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".