Pathogenesis of hereditary tumors: beyond the “two‐hit” hypothesis
Bibliographic record
Abstract
Knudson's 'two-hit' hypothesis has provided extremely important insights into the pathogenesis of tumors in autosomal dominant tumor predisposition syndromes, but recent evidence suggests that some such tumors may occur without a 'second hit' or require more than two mutations. Inactivation of both RB1 alleles appears to be insufficient by itself to cause malignancy in the tumors that develop in patients with hereditary retinoblastoma. On the other hand, certain tumors in patients with tuberous sclerosis complex appear to develop in haploinsufficient tissues that do not have 'second hit' mutations of a tuberous sclerosis gene. The molecular pathogenesis of certain other tumors in patients with tuberous sclerosis complex or neurofibromatosis 1 may not be fully explained by the 'two-hit' hypothesis either. Hereditary tumors, like non-hereditary tumors, may arise by a variety of molecular mechanisms, with loss of both alleles of a particular tumor suppressor gene being a frequent, but not invariably necessary or sufficient, event. Four models are presented to explain how various tumors may arise in patients with inherited tumor predisposition syndromes such as hereditary retinoblastoma, tuberous sclerosis complex or neurofibromatosis 1. Even tumors of one particular type may develop by more than one mechanism.
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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 | 0.002 | 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) | 0.002 | 0.001 |
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".