Expression of Nucleoside Transporters and Deoxycytidine Kinase Proteins in Muscle Invasive Urothelial Carcinoma of the Bladder: Correlation with Pathological Response to Neoadjuvant Platinum/Gemcitabine Combination Chemotherapy
Bibliographic record
Abstract
PURPOSE: In pancreatic cancer, deoxycytidine kinase and the human equilibrative nucleoside transporter 1 have been validated as predictive markers for benefit from gemcitabine therapy. Gemcitabine is used with cisplatin or carboplatin as neoadjuvant chemotherapy for muscle invasive urothelial cancer of the bladder before radical cystectomy and patients rendered disease-free at surgery tend to have better outcomes. In this trial we examined if nucleoside transporter or deoxycytidine kinase protein abundance in biopsy specimens before chemotherapy is related to the response to neoadjuvant chemotherapy. MATERIALS AND METHODS: A total of 62 consecutive patients undergoing neoadjuvant chemotherapy with platinum/gemcitabine at a single institution were accrued. Initial transurethral resection of bladder tumor specimens and cystectomy specimens were collected, and scored for nucleoside transporter and deoxycytidine kinase expression. Pathological response rates and survival data were collected. RESULTS: Of the 62 patients 17 (27%) achieved a complete pathological response (pT0) to neoadjuvant chemotherapy. Nucleoside transporter and deoxycytidine kinase protein expression in the transurethral resection of bladder tumor specimens did not predict for pT0 status to neoadjuvant chemotherapy. Median overall survival was not reached for the group achieving pT0 status and was 46 months for those with persistent cancer at definitive surgery (p = 0.07). Median followup for the cohort was 30 months. CONCLUSIONS: Nucleoside transporter and deoxycytidine kinase expression in transurethral resection of bladder tumor samples do not predict for response to gemcitabine and platinum neoadjuvant chemotherapy. Patients should continue to be offered neoadjuvant chemotherapy before radical cystectomy based on clinical and pathological staging.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".