Bibliographic record
Abstract
Genetic, or genomic, instability refers to a series of observed spontaneous genetic changes occurring at an accelerated rate in cell populations derived from the same ancestral precursor. This is far from a new finding, but is one that has increasingly gained more attention in the last decade due to its plausible role(s) in tumorigenesis. The majority of genetic alterations contributing to the malignant transformation are seen in growth regulatory genes, and in genes involved in cell cycle progression and arrest. Genomic instability may present itself through alterations in the length of short repeat stretches of coding and non-coding DNA, resulting in microsatellite instability. Tumors with such profiles are referred to as exhibiting a mutator phenotype, which is largely a consequence of inactivating mutations in DNA damage repair genes. Genomic instability may also, and most commonly, results from gross chromosomal changes, such as translocations or amplifications, which lead to chromosomal instability. Telomere length and telomerase activity, important in maintaining chromosomal structure and in regulating a normal cell's lifespan, have been shown to have a function in both suppressing and facilitating malignant transformation. In addition to such direct sequence and structural changes, gene silencing through the hypermethylation of promoter regions, or increased gene expression through the hypomethylation of such regions, together, form an alternative, epigenetic mechanism leading to instability. Emerging evidence also suggests that dietary and environmental agents can further modulate the contribution of genetic instability to tumorigenesis. Currently, there is still much debate over the distinct classes of genomic instability and their specific roles in the initiation of tumor formation, as well as in the progressive transition to a cancerous state. This review examines the various molecular mechanisms that result in this genomic instability and the potential contribution of the latter to human carcinogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".