Somatic DICER1 pathogenic variants detected in a well-differentiated fetal lung adenocarcinoma diagnosed in a man with familial adenomatous polyposis
Bibliographic record
Abstract
Well-differentiated fetal lung adenocarcinoma (WDFLAC) is a rare pulmonary carcinoma characterized by its resemblance to fetal lung. It is thought to be caused by somatic pathogenic variants (PVs) in the genes CTNNB1 or APC, which lead to the nuclear accumulation of beta(β)-catenin and down-stream activation of key oncogenes. Recent studies, however, have shown that germline and/or somatic PVs in DICER1 are also implicated in the etiology of lung tumors with fetal-type morphologies. Here, we report the second case of WDFLAC in a male non-smoker with familial adenomatous polyposis (FAP), and the first case with confirmed inactivating PVs in both APC and DICER1. A review of the literature also showed that out of the 17 WDFLAC cases for which sequencing of DICER1, CTNNB1 and/or APC was performed, 13 had PVs in DICER1 and either CTNNB1 or APC, with one patient having all three genes mutated. Taken together, this suggests that the development of WDFLAC may be the summative effect of WNT and DICER1 dysfunction. It may thus be beneficial to test for DICER1 variants in diagnostically challenging cases and, if a germline DICER1 PV is found, additional screening for DICER1-associated tumors could be pursued.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".