The fork remodeler helicase-like transcription factor in cancer development: all at once
Bibliographic record
Abstract
The Helicase-like Transcription Factor (HLTF) is a member of the SNF2-family of fork remodelers, primarily studied for its capacity to provide DNA Damage Tolerance (DDT) and to induce replication fork reversal (RFR). HLTF is recruited at stalled forks where both its ATPase motor and HIP116 Rad5p N-terminal (HIRAN) domains are necessary for regulating its interaction with DNA. HIRAN bestows specificity to ssDNA 3'-end and imparts branch migration as well as DNA remodeling capabilities facilitating damage repair. Both expression regulation and mutation rate affect HLTF activity. Gene hypermethylation induces loss of HLTF function, in particular in colorectal cancer (CRC), implying a tumour suppressor role. Surprisingly, a correlation between hypermethylation and HLTF mRNA upregulation has also been observed, even within the same cancer type. In many cancers, both complex mutation patterns and the presence of gene Copy Number Variations (CNVs) have been reported. These conditions affect the amount of functional HLTF and question the physiological role of this fork remodeler. This review offers a systematic collection of the presently strewed information regarding HLTF, its structural and functional characteristics, the multiple roles in DDT and the regulation in cancer progression highlighting new research perspectives.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".