Multiomics profiling of urothelial carcinoma in situ reveals CIS-specific gene signature and immune characteristics
Bibliographic record
Abstract
Urothelial carcinoma in situ (CIS) is an aggressive phenotype of non-muscle-invasive bladder cancer. Molecular features unique to CIS compared to high-grade papillary tumors are underexplored. RNA sequencing of CIS, papillary tumors, and normal urothelium showed lower immune marker expression in CIS compared to papillary tumors. We identified a 46-gene expression signature in CIS samples including selectively upregulated known druggable targets MTOR , TYK2 , AXIN1 , CPT1B , GAK , and PIEZO1 and selectively downregulated BRD2 and NDUFB2 . High expression of selected genes was significantly associated with CIS in an independent dataset. Mutation analysis of matched CIS and papillary tumors revealed shared mutations between samples across time points and mutational heterogeneity. CCDC138 was the most frequently mutated gene in CIS. The immunological landscape showed higher levels of PD-1-positive cells in CIS lesions compared to papillary tumors. We identified CIS lesions to have distinct characteristics compared to papillary tumors potentially contributing to the aggressive phenotype.
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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 | 0.001 |
| 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".