Tumor Suppressor and Aging Biomarker p16INK4a Induces Cellular Senescence without the Associated Inflammatory Secretory Phenotype
Bibliographic record
Abstract
Cellular senescence suppresses cancer by preventing the proliferation of cells that experience potentially oncogenic stimuli. Senescent cells often express p16(INK4a), a cyclin-dependent kinase inhibitor, tumor suppressor, and biomarker of aging, which renders the senescence growth arrest irreversible. Senescent cells also acquire a complex phenotype that includes the secretion of many cytokines, growth factors, and proteases, termed a senescence-associated secretory phenotype (SASP). The SASP is proposed to underlie age-related pathologies, including, ironically, late life cancer. Here, we show that ectopic expression of p16(INK4a) and another cyclin-dependent kinase inhibitor, p21(CIP1/WAF1), induces senescence without a SASP, even though they induced other features of senescence, including a stable growth arrest. Additionally, human fibroblasts induced to senesce by ionizing radiation or oncogenic RAS developed a SASP regardless of whether they expressed p16(INK4a). Cells induced to senesce by ectopic p16(INK4a) expression lacked paracrine activity on epithelial cells, consistent with the absence of a functional SASP. Nonetheless, expression of p16(INK4a) by cells undergoing replicative senescence limited the accumulation of DNA damage and premature cytokine secretion, suggesting an indirect role for p16(INK4a) in suppressing the SASP. These findings suggest that p16(INK4a)-positive cells may not always harbor a SASP in vivo and, furthermore, that the SASP is not a consequence of p16(INK4a) activation or senescence per se, but rather is a damage response that is separable from the growth arrest.
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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) | 0.002 | 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".