Characterizing and exploiting the many roles of aberrant H2B monoubiquitination in cancer pathogenesis
Bibliographic record
Abstract
Monoubiquitination of histone H2B on lysine 120 (H2Bub1) is implicated in the control of multiple essential processes, including transcription, DNA damage repair and mitotic chromosome segregation. Accordingly, aberrant regulation of H2Bub1 can induce transcriptional reprogramming and genome instability that may promote oncogenesis. Remarkably, alterations of the ubiquitin ligases and deubiquitinating enzymes regulating H2Bub1 are emerging as ubiquitous features in cancer, further supporting the possibility that the misregulation of H2Bub1 is an underlying mechanism contributing to cancer pathogenesis. To date, aberrant H2Bub1 dynamics have been reported in multiple cancer types and are associated with transcriptional changes that promote oncogenesis in a cancer type-specific manner. Owing to the multi-functional nature of H2Bub1, misregulation of its writers and erasers may drive disease initiation and progression through additional synergistic processes. Accordingly, understanding the molecular determinants and pathogenic impacts associated with aberrant H2Bub1 regulation may reveal novel drug targets and therapeutic vulnerabilities that can be exploited to develop innovative precision medicine strategies that better combat cancer. In this review, we present the normal functions of H2Bub1 in the control of DNA-associated processes and describe the pathogenic implications associated with its misregulation in cancer. We further discuss the challenges coupled with the development of therapeutic strategies targeting H2Bub1 misregulation and expose the potential benefits of designing treatments that synergistically exploit the multiple functionalities of H2Bub1 to improve treatment selectivity and efficacy.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".