Somatic microindels in human cancer: the insertions are highly error-prone and derive from nearby but not adjacent sense and antisense templates
Bibliographic record
Abstract
Somatic microindels (microdeletions with microinsertions) have been studied in normal mouse tissues using the Big Blue lacI transgenic mutation detection system. Here we analyze microindels in human cancers using an endogenous and transcribed gene, the TP53 gene. Microindel frequency, the enhancement of 1-2 microindels and other features are generally similar to that observed in the non-transcribed lacI gene in normal mouse tissues. The current larger sample of somatic microindels reveals recurroids: mutations in which deletions are identical and the co-localized insertion is similar. The data reveal that the inserted sequences derive from nearby but not adjacent sequences in contrast to the slippage that characterizes the great majority of pure microinsertions. The microindel inserted sequences derive from a template on the sense or antisense strand with similar frequency. The estimated error rate of the insertion process of 13% per bp is by far the largest reported in vivo, with the possible exception of somatic hypermutation in the immunoglobulin gene. The data constrain possible mechanisms of microindels and raise the question of whether microindels are 'scars' from the bypass of large DNA adducts by a translesional polymerase, e.g. the 'Tarzan model' presented herein.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".