Comprehensive Molecular Characterization of Urachal Adenocarcinoma Reveals Commonalities With Colorectal Cancer, Including a Hypermutable Phenotype
Bibliographic record
Abstract
Purpose Urachal adenocarcinoma is a rare type of primary bladder adenocarcinoma that comprises less than 1% of all bladder cancers. The low incidence of urachal adenocarcinomas does not allow for an evidence-based approach to therapy. Transcriptome profiling of urachal adenocarcinomas has not been previously reported. We hypothesized that an in-depth molecular understanding of urachal adenocarcinoma would uncover rational therapeutic strategies. Patients and Methods We performed targeted exon sequencing and global transcriptome profiling of 12 urachal tumors to generate a comprehensive molecular portrait of urachal adenocarcinoma. A single patient with an MSH6 mutation was treated with the anti–programmed death-ligand 1 antibody, atezolizumab. Results Urachal adenocarcinoma closely resembles colorectal cancer at the level of RNA expression, which extends previous observations that urachal tumors harbor genomic alterations that are found in colorectal adenocarcinoma. A subset of tumors was found to have alterations in genes that are associated with microsatellite instability ( MSH2 and MSH6) and hypermutation ( POLE). A patient with an MSH6 mutation was treated with immune checkpoint blockade, which resulted in stable disease. Conclusion Because clinical trials are next to impossible for patients with rare tumors, precision oncology may be an important adjunct for treatment decisions. Our findings demonstrate that urachal adenocarcinomas molecularly resemble colorectal adenocarcinomas at the level of RNA expression, are the first report, to our knowledge, of MSH2 and MSH6 mutations in this disease, and support the consideration of immune checkpoint blockade as a rational therapeutic treatment of this exceedingly rare tumor.
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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 | 0.001 | 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) | 0.001 | 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".