Analysis of TSC Cortical Tubers by Deep Sequencing of TSC1, TSC2 and KRAS Demonstrates that Small Second‐Hit Mutations in these Genes are Rare Events
Bibliographic record
Abstract
Tuberous sclerosis complex (TSC) is an often severe neurocutaneous syndrome. Cortical tubers are the predominant neuropathological finding in TSC, and their number and location has been shown to correlate roughly with the severity of neurologic features in TSC. Past studies have shown that genomic deletion events in TSC1 or TSC2 are very rare in tubers, and suggested the potential involvement of the MAPK pathway in their pathogenesis. We used deep sequencing to assess all coding exons of TSC1 and TSC2, and the activating mutation hot spots within KRAS in 46 tubers from TSC patients. Germline heterozygous mutations were identified in 81% of tubers. The same secondary mutation in TSC2 was identified in six tuber samples from one individual. Further study showed that this second hit mutation was widely distributed in the cortex from one cerebral hemisphere of this individual at frequencies up to 10%. No other secondary mutations were found in the other 40 tubers analyzed. These data indicate that small second hit mutations in any of these three genes are very rare in TSC tubers. However, in one TSC individual, a second hit TSC2 point mutation occurred early during brain development, and likely contributed to tuber formation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".