Posttranslational Modifications of the Retinoblastoma Tumor Suppressor Protein as Determinants of Function
Bibliographic record
Abstract
The retinoblastoma tumor suppressor protein (pRB) plays an integral role in G1-S checkpoint control and consequently is a frequent target for inactivation in cancer. The RB protein can function as an adaptor, nucleating components such as E2Fs and chromatin regulating enzymes into the same complex. For this reason, pRB's regulation by posttranslational modifications is thought to be critical. pRB is phosphorylated by a number of different kinases such as cyclin dependent kinases (Cdks), p38 MAP kinase, Chk1/2, Abl, and Aurora b. Although phosphorylation of pRB by Cdks has been extensively studied, activities regulated through phosphorylation by other kinases are just starting to be understood. As well as being phosphorylated, pRB is acetylated, methylated, ubiquitylated, and SUMOylated. Acetylation, methylation, and SUMOylation play roles in pRB mediated gene silencing. Ubiquitinylation of pRB promotes its degradation and may be used to regulate apoptosis. Recent proteomic data have revealed that pRB is posttranslationally modified to a much greater extent than previously thought. This new information suggests that many unknown pathways affect pRB regulation. This review focuses on posttranslational modifications of pRB and how they influence its function. The final part of the review summarizes new phosphorylation sites from accumulated proteomic data and discusses the possibilities that might arise from this data.
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 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".