Urology, University of Wisconsin - Madison

Bayesian Adaptive methods with Pharmacogenomics to Treat Bladder Cancer

Funding:

Veteran's Administration Hospital Merit Review

Principal Investigator:

Jason Gee, MD

Project Summary:

Bladder cancer is the second most-common malignancy of the genitourinary tract. Muscle-invasive bladder cancer, which accounts for virtually all mortality from this disease, is initially diagnosed in about 25–30% of patients. Such patients generally undergo radical cystectomy with possible neoadjuvant or adjuvant chemotherapy. Remaining patients are initially diagnosed with superficial bladder tumors. These include patients diagnosed with carcinoma in situ (CIS/Tis); it is this group of patients who are at high risk for tumor recurrence and progression to muscle-invasive disease. They are typically treated with up totwo 6-week courses of intravesical bacillus calmette guerin (BCG) as a bladder-sparing approach. While response to the first BCG treatment course is ~70%, response to the second is lower. Salvage regimens are of limited efficacy, thus patients failing BCG therapy proceed to radical cystectomy given their high risk of progression. These difficult-to-treat patients are thus an ideal cohort for evaluation of new molecular-based treatment strategies.

Epidermal growth factor receptor (EGFR) has been identified as a potential target in bladder cancer, and the expression of EGFR, whose quantity and distribution are associated with a pan-urothelial abnormality, increases with increasing tumor stage and aggressiveness. Agents that inhibit EGFR function are currently being evaluated in prevention and treatment of advanced disease. However, recent studies suggest response to EGFR inhibitors may depend on individual genetic variation. For instance, EGFR polymorphisms have been identified that affect level of EGFR transcription and thereby may modulate response to erlotnib, a tyrosine kinase inhibitor targeting EGFR. Indeed, mutations in the EGFR have predicted response to Iressa, another EGFR inhibitor, in patients with lung cancer. EGFR mutations have also been identified in bladder cancer, although their functional significance remains unclear.

These studies provide a novel way of documenting (and maybe predicting) genetic susceptibility to effects of erlotnib. To use these observations in patient care, we need to develop reliable, effective clinical-translational statistical methods to enable prospective assignment of therapy based on molecular profiling. Adaptive design methods can be tailored to clinical outcome during a clinical study; such continual evaluation and adjustment of statistical methods will provide the most effective analysis of pharmacogenomic data. We therefore hypothesize that a pharmacogenomic approach based on genotyping for EGFR mutations, using Bayesian adaptive design methodology, is effective in assigning bladder cancer patients with BCG-refractory carcinoma in situ to erlotnib/intravesical BCG vs. intravesical BCG alone and may reliably predict pathologic and biologic response to erlotnib/BCG.

To test this hypothesis, we propose a 2-stage study design:
Stage I: Primary Objective: Develop a new class of flexible clinical trial designs with pharmacogenomic biomarkers. Stage II: Primary Objective:Test the design developed in Stage I in optimizing selection of bladder cancer patients with BCG-refractory carcinoma in situto receive intravesical BCG +/- erlotnib to enhance pathologic response to therapy.

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