Materials and Methods: We studied 26 patients with biopsy-proven cTanyN1-3M0 bladder cancer (2005-2016) who underwent induction chemotherapy and radical cystectomy with pelvic lymphadenectomy. Metastasis and overall survival (OS) outcomes were examined using Kaplan-Meier method and compared using log-rank test. Paired pretherapy primary bladder and nodal tissues were available for 10 patients. In these patients, whole-transcriptome RNA-seq analysis was performed on bladder tumor (for pT0 and pN0 prediction) and lymph-nodal metastasis (for pN0 prediction) tissues to identify differentially expressed genes (DEGs) with a false discovery rate < 0.1.
Results: pN0 pathologic responders, but not pT0 responders, had significantly improved freedom from metastasis (5-year: pN0 88.9% vs pN+ 27.4%, log-rank P = .018) and OS (5-year: pN0 76.2% vs pN+ 12.2%, log-rank P = .024). Using RNA-seq data, we identified a significant discordance rate of 87.5% between DEG-based predictive signatures for pT0 and pN0 response to cisplatin-based chemotherapy. This datum, combined with the knowledge that ∼40% of patients who achieve pT0 status at radical surgery, achieve it simply through the therapeutic effect of TURBT (SWOG S8710), underscores a substantial bias in the current biomarker discovery initiatives that use pT0 as an endpoint.
Conclusions: Our findings suggest a need for devising novel study designs to aid in the discovery of reliable biomarkers for preoperative chemo/immunotherapy response in bladder cancer. Clinical node-positive patients may be ideally situated but remain understudied.
Sood, Akshay,1,2 Lim, Amy H.,2 Yao, Hui,3 Wei, Peng,3 Narayan, Vikram M.,2 Lee, I-Ling,2 Seif, Mohammed A.,2 Bree, Kelly K.,2 Matulay, Justin T.,2 Campbell, Matthew T.,4 Kamat, Ashish M.,2 Dinney, Colin P.N.,2 Navai, Neema2
- Department of Urology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio
- Department of Urology, The U.T. MD Anderson Cancer Center, Houston, Texas
- Department of Bioinformatics and Computational Biology, The U.T. MD Anderson Cancer Center, Houston, Texas
- Department of Medical Oncology, The U.T. MD Anderson Cancer Center, Houston, Texas