<i>EIF1AX</i> mutation in thyroid tumors: A retrospective analysis of cytology, histopathology and co-mutation profiles
Bibliographic record
Abstract
BACKGROUND: The EIF1AX mutation has been identified in various benign and malignant thyroid lesions, with a higher prevalence in poorly differentiated thyroid carcinoma (PDTC) and anaplastic thyroid carcinoma, especially when combined with RAS or TP53 mutation. However, data and clinical significance of EIF1AX mutations in thyroid nodules is still limited. We investigated the prevalence of EIF1AX mutations and co-mutations in cytologically indeterminate thyroid nodules at our institution. METHODS: . Mutation type and presence of co-mutations were correlated with histopathologic diagnosis and clinical characteristics. Histopathology diagnoses were subsequently categorized as benign, borderline, malignant or aggressive malignant (≥ 10% PDTC component). Chi-square test was used to compare the malignancy associations of the: 1) A113_splice mutation compared to non-A113_splice mutations 2) singular A113_splice mutations compared to singular non-A113_splice mutations. Fisher's Exact Test was used to determine the association of A113_splice mutation with aggressive malignancies compared to non-A113_splice mutations. A p value of 0.05 or less was considered statistically significant. RESULTS: Out of 1583 patients who underwent FNA, 621 had further molecular testing. 31 cases (5%) harbored EIF1AX mutations. Of these cases, 12 (38.7%) were malignant, 2 (6.5%) were borderline, and 17 (55%) were benign. 4/31 cases (13%) were aggressive malignant (≥ 10% PDTC component). The most prevalent mutation was the A113_splice mutation at the junction of intron 5 and exon 6 (48%). All other mutations, except one, were located at the N-terminal in exon 2. 7/31 cases (22.6%) harbored ≥ 1 co-mutation(s), including 4 RAS, 3 TP53, 1 TERT and 1 PIK3CA, with 86% of them being malignant. All 4 nodules with RAS co-mutations were malignant including one PDTC. CONCLUSION: Our study reports the largest cohort of EIF1AX mutations in Bethesda III/IV FNA samples with surgical follow-up to our knowledge. The presence of the EIF1AX mutation confers a 45.2% risk of malignancy (ROM) or borderline after surgery. However, the coexistence of EIF1AX mutations with other driver mutations such as RAS, TERT or TP53 conferred an 86% ROM. While 55% of thyroid nodules were benign at the time of surgery, the possible malignant transformation of these nodules, had they not been resected, is unknown. Finally, 13% of the nodules with EIF1AX mutations were aggressive with a significant PDTC component. These findings can further aid in clinical decisions for patients with thyroid nodules.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".