Immunohistochemistry for ATRX Can Miss ATRX Mutations
Bibliographic record
Abstract
Neuroblastoma is the most common extracranial solid tumor of childhood with a median age of presentation of 17 months. A common theme in high-risk neuroblastoma is maintenance of telomeres, one mechanism for which involves alternate lengthening of telomeres (ALT) associated with ATRX gene mutations. Mutations are believed to result in loss of ATRX protein, and therefore immunohistochemistry is used to detect mutations. We screened 133 cases of neuroblastoma by ATRX immunohistochemistry, and found 9 cases with partial to total absence of ATRX. Sequencing for ATRX mutations detected a mutation in 1 of 9 cases, suggesting immunostaining was not reliable for detecting mutations. To correlate immunostaining with ALT, fluorescence in situ hybridization (FISH) for ALT was performed in 6 of these cases and 5 (from 4 patients) showed ALT, implying impaired ATRX protein function, despite the failure to identify a mutation. Two other cases with large deletions in the ATRX gene showed diffusely positive staining for ATRX protein but showed ALT by FISH. Four of the 6 patients with ALT-positive tumors were over 5 years old. Therefore, 29 additional patients 5 years old and above with ATRX-positive tumors were screened for ALT by FISH and 6 additional cases with ALT were detected, bringing the total to 29% (10/34) of children 5 years old and above, 70% of which showed positive ATRX immunohistochemistry. Patients with ATRX mutations in neuroblastoma tend to have a more chronic and progressive course of disease. Screening neuroblastoma tumors at diagnosis for ATRX mutations may help identify patients who might benefit from personalized therapy directed against ALT. However, relaying on negative immunohistochemistry for ATRX protein to identify ALT in neuroblastoma may miss a significant proportion of patients. The addition of FISH for ALT as part of the diagnostic workup, especially for older children (5 y old and above), would help ensure that patients are correctly identified for anti-ALT therapy.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".