The PCNA inhibitor AOH1996 suppresses cancer stemness and enhances anti-PD1 immunotherapy in squamous cell carcinoma
Bibliographic record
Abstract
Abstract Background Proliferating cell nuclear antigen (PCNA), a well-documented anticancer target, is critical for DNA synthesis, replication, and repair. AOH1996, a small-molecule PCNA inhibitor, is currently undergoing clinical trials for the treatment of advanced solid tumors. However, the therapeutic effect of AOH1996 on head and neck squamous cell carcinoma (HNSCC) remains unclear. Methods The effects of AOH1996 on HNSCC biological behaviors and cancer stemness were tested in HNSCC cells and nude mice. The combination treatment of AOH1996 and anti-PD1 was performed in a 4-nitroquinoline N-oxide (4NQO)-induced HNSCC mouse model. RNA sequencing, Western Blotting, immunofluorescence staining, comet assays, and qRT‒PCR were conducted for mechanistic studies. Results Our results showed that AOH1996 effectively inhibited HNSCC proliferation and invasion both in vitro and in vivo. AOH1996 suppressed HNSCC stemness, development, and metastasis. Moreover, AOH1996 altered the tumor immune microenvironment into an inflamed state with increased CD8+ T-cell infiltration, rendering it a favorable partner for combination therapy with immune checkpoint inhibitors. Mechanistically, AOH1996 induced cellular DNA damage, suppressed cancer stemness through the upregulation of p-TBK1, and promoted the secretion of CD8+ T-cell-recruiting chemokines by stimulating IRF3-mediated transcription. Conclusions Taken together, our results demonstrated that AOH1996 suppressed tumor growth, eliminated cancer stem cells (CSCs), and synergistically enhanced the efficacy of anti-PD1 immunotherapy in HNSCC.
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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) | 0.001 | 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".