Editorial: Hallmark of cancer: Resisting cell death
Bibliographic record
Abstract
In 2000, Douglas Hanahan and Robert Weinberg proposed 6 physiological features as the hallmarks of cancer (1), which evolved into 14 hallmarks with the rapid advances in cancer research over the past two decades (2). Among the long list of hallmarks, conceivably being further updated in the future, evading programmed cell death constitutes one of the founder mechanisms whereby tumors can establish successfully (1, 2). Whereas apoptosis was regarded as the primary form of programmed cell death two decades ago, it is currently well acknowledged that cell death can be executed through a plethora of programmed mechanisms. The latest recommendations by the Nomenclature Committee on Cell Death in 2018 proposed 13 distinct forms of programmed cell death, including classical forms of autonomous cell death, such as apoptosis, necroptosis, autosis, ferroptosis and netosis, and the emerging concept of noncell-autonomous death, such as entosis, which is mediated by the formation of cell-in-cell structures (CICs) (3). Novel mechanisms of cell death, such as cuproptosis (4), are continually being identified. Given the pivotal role of resisting cell death in the development and progression of tumors, almost every form of cell death has been, more or less, implicated in human cancers. This Research Topic collected a set of research articles and comprehensive reviews related to the representative forms of cell death that are currently undergoing extensive investigation in multiple human cancers to promote the diagnostic and therapeutic applications of targeting cell death in the clinic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".