Palbociclib Renders Human Papilloma Virus–Negative Head and Neck Squamous Cell Carcinoma Vulnerable to the Senolytic Agent Navitoclax
Bibliographic record
Abstract
Abstract We demonstrate that inhibition of cyclin-dependent kinases 4/6 (CDK4/6) leads to senescence in human papillomavirus (HPV)–negative (−) head and neck squamous cell carcinoma (HNSCC), but not in HPV-positive (+) HNSCC. The BCL-2 family inhibitor, navitoclax, has been shown to eliminate senescent cells effectively. We evaluated the efficacy of combining palbociclib and navitoclax in HPV− HNSCC. Three HPV− HNSCC cell lines (CAL27, HN31, and PCI15B) and three HPV+ HNSCC cell lines (UPCI-SCC-090, UPCI-SCC-154, and UM-SCC-47) were treated with palbociclib. Treatment drove reduced expression of phosphorylated Rb (p-Rb) and phenotypic evidence of senescence in all HPV− cell lines, whereas HPV+ cell lines did not display a consistent response by Rb or p-Rb and did not exhibit morphologic changes of senescence in response to palbociclib. In addition, treatment of HPV− cells with palbociclib increased both β-galactosidase protein expression and BCL-xL protein expression compared with untreated controls in HPV− cells. Co-expression of β-galactosidase and BCL-xL occurred consistently, indicating elevated BCL-xL expression in senescent cells. Combining palbociclib with navitoclax led to decreased HPV− HNSCC cell survival and led to increased apoptosis levels in HPV− cell lines compared with each agent given alone. Implications: This work exploits a key genomic hallmark of HPV− HNSCC (CDKN2A disruption) using palbociclib to induce BCL-xL–dependent senescence, which subsequently causes the cancer cells to be vulnerable to the senolytic agent, navitoclax.
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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".