The essentiality landscape of cell cycle related genes in human pluripotent and cancer cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Cell cycle regulation is a complex system consisting of growth-promoting and growth-restricting mechanisms, whose coordinated activity is vital for proper division and propagation. Alterations in this regulation may lead to uncontrolled proliferation and genomic instability, triggering carcinogenesis. Here, we conducted a comprehensive bioinformatic analysis of cell cycle-related genes using data from CRISPR/Cas9 loss-of-function screens performed in four cancer cell lines and in human embryonic stem cells (hESCs). Results Cell cycle genes, and in particular S phase and checkpoint genes, are highly essential for the growth of cancer and pluripotent cells. However, checkpoint genes are also found to underlie the differences between the cell cycle features of these cell types. Interestingly, while growth-promoting cell cycle genes overlap considerably between cancer and stem cells, growth-restricting cell cycle genes are completely distinct. Moreover, growth-restricting genes are consistently less frequent in cancer cells than in hESCs. Here we show that most of these genes are regulated by the tumor suppressor gene TP53 , which is mutated in most cancer cells. Therefore, the growth-restriction system in cancer cells lacks important factors and does not function properly. Intriguingly, M phase genes are specifically essential for the growth of hESCs and are highly abundant among hESC-enriched genes. Conclusions Our results highlight the differences in cell cycle regulation between cell types and emphasize the importance of conducting cell cycle studies in cells with intact genomes, in order to obtain an authentic representation of the genetic features of the cell cycle.
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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 | 0.000 | 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) | 0.000 | 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 it