R-Loops and R-Loop-Binding Proteins in Cancer Progression and Drug Resistance
Bibliographic record
Abstract
R-loops are three-stranded DNA/RNA hybrids that form by the annealing of the mRNA transcript to its coding template while displacing the non-coding strand. While R-loop formation regulates physiological genomic and mitochondrial transcription and DNA damage response, imbalanced R-loop formation can be a threat to the genomic integrity of the cell. As such, R-loop formation is a double-edged sword in cancer progression, and perturbed R-loop homeostasis is observed across various malignancies. Here, we discuss the interplay between R-loops and tumor suppressors and oncogenes, with a focus on BRCA1/2 and ATR. R-loop imbalances contribute to cancer propagation and the development of chemotherapy drug resistance. We explore how R-loop formation can cause cancer cell death in response to chemotherapeutics and be used to circumvent drug resistance. As R-loop formation is tightly linked to mRNA transcription, their formation is unavoidable in cancer cells and can thus be explored in novel cancer therapeutics.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".