Prevalence of APC and PTEN Alterations in Urachal Cancer
Bibliographic record
Abstract
Urachal carcinoma (UrC) is a rare tumor with remarkable histological and molecular similarities to colorectal cancer (CRC). Adenomatous polyposis coli (APC) is the most frequently affected gene in CRC, but the prevalence and significance of its alterations in UrC is poorly understood. In addition, loss of phosphatase and tensin homologue (PTEN) was shown to be associated with therapy resistance in CRC. Our primary aim was to assess specific genetic alterations including APC and PTEN in a large series of UrC samples in order to identify clinically significant genomic alterations. We analyzed a total of 40 UrC cases. Targeted 5-gene (APC, PTEN, DICER1, PRKAR1A, TSHR, WRN) panel sequencing was performed on the Illumina MiSeq platform (n = 34). In addition, ß-catenin (n = 38) and PTEN (n = 30) expressions were assessed by immunohistochemistry. APC and PTEN genes were affected in 15% (5/34) and 6% (2/34) of cases. Two of five APC alterations (p.Y1075*, p.K1199*) were truncating pathogenic mutations. One of the two PTEN variants was a pathogenic frameshift insertion (p.C211fs). In 29% (11/38) of samples, at least some weak nuclear ß-catenin immunostaining was detected and PTEN loss was observed in 20% (6/30) of samples. The low prevalence of APC mutations in UrC represents a characteristic difference to CRC. Based on APC and ß-catenin results, the Wnt pathway seems to be rarely affected in UrC. Considering the formerly described involvement of PTEN protein loss in anti-EGFR therapy-resistance its immunohistochemical testing may have therapeutic relevance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".