Cancers Exhibit a Mutator Phenotype: Clinical Implications
Bibliographic record
Abstract
Malignancies are characterized by mutations. We have hypothesized that the thousands of mutations in most human cancers do not result from the low mutation rates exhibited by normal human cells. Instead, cancer cells express a mutator phenotype (i.e., the mutation rate in the cancer cells is much greater than that in normal cells). We consider the following points: (a) Mutations in genes that govern genetic stability could be the cause of a mutator phenotype exhibited by human cancers. (b) A mutator phenotype increases the efficiency of acquiring mutations including those associated with cancer. (c) Recent experimental evidence indicates that human tumors contain a vast array of both clonal mutations and nonexpanded (random) mutations. (d) The presence of nonexpanded mutations in tumors has fundamental clinical implications for cancer risk assessment, grading, and prognosis including the rapid emergence of resistance to chemotherapeutic agents. Lastly, (e) if a mutator phenotype drives carcinogenesis, drugs that target mutator pathways might prevent cancer by delay.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".