SDHA Loss-of-Function Mutations in KIT-PDGFRA Wild-Type Gastrointestinal Stromal Tumors Identified by Massively Parallel Sequencing
Bibliographic record
Abstract
Approximately 10%-15% of gastrointestinal stromal tumors (GISTs) in adults do not harbor any mutation in the KIT or PDGFRA genes (ie, KIT/PDGFRA wild-type GISTs). Recently, mutations in SDHB and SDHC (which encode succinate dehydrogenase subunits B and C, respectively) but not in SDHA and SDHD (which encode subunits A and D, respectively) were identified in KIT/PDGFRA wild-type GISTs. To search for novel pathogenic mutations, we sequenced the tumor transcriptome of two young adult patients who developed sporadic KIT/PDGFRA wild-type GISTs by using a massively parallel sequencing approach. The only variants identified as disease related by computational analysis were in SDHA. One patient carried the homozygous nonsense mutation p.Ser384X, the other patient was a compound heterozygote harboring a p.Arg31X nonsense mutation and a p.Arg589Trp missense mutation. The heterozygous nonsense mutations in both patients were present in germline DNA isolated from peripheral blood. Protein structure analysis indicates that all three mutations lead to functional inactivation of the protein. This is the first report, to our knowle dge, that identifies SDHA inactivation as a common oncogenic event in GISTs that lack a mutation in KIT and PDGFRA.
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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 | 0.000 |
| 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 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".