CFI-402257, a TTK inhibitor, effectively suppresses hepatocellular carcinoma
Bibliographic record
Abstract
Deregulation of cell cycle is a typical feature of cancer cells. Normal cells rely on the strictly coordinated spindle assembly checkpoint (SAC) to maintain the genome integrity and survive. However, cancer cells could bypass this checkpoint mechanism. In this study, we showed the clinical relevance of threonine tyrosine kinase (TTK) protein kinase, a central regulator of the SAC, in hepatocellular carcinoma (HCC) and its potential as therapeutic target. Here, we reported that a newly developed, orally active small molecule inhibitor targeting TTK (CFI-402257) effectively suppressed HCC growth and induced highly aneuploid HCC cells, DNA damage, and micronuclei formation. We identified that CFI-402257 also induced cytosolic DNA, senescence-like response, and activated DDX41-STING cytosolic DNA sensing pathway to produce senescence-associated secretory phenotypes (SASPs) in HCC cells. These SASPs subsequently led to recruitment of different subsets of immune cells (natural killer cells, CD4 + T cells, and CD8 + T cells) for tumor clearance. Our mass cytometry data illustrated the dynamic changes in the tumor-infiltrating immune populations after treatment with CFI-402257. Further, CFI-402257 improved survival in HCC-bearing mice treated with anti-PD-1, suggesting the possibility of combination treatment with immune checkpoint inhibitors in HCC patients. In summary, our study characterized CFI-402257 as a potential therapeutic for HCC, both used as a single agent and in combination therapy.
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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) | 0.001 | 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".