Person:

Mata, Douglas

Introduction: Level I evidence supports the use of cisplatin-based neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer prior to radical cystectomy (RC). On average, 30–40% of patients achieve a complete pathologic response (i.e., stage pT0) after receiving NAC. Some centers risk-stratify patients, suggesting that there may be a higher-risk population that would derive the most benefit from NAC. Recently, a risk-stratification model developed at M.D. Anderson Cancer Center (MDACC) specified criteria for clinical staging and patient selection for NAC. We applied this model to our own RC patient cohort and evaluated our own experience with clinical risk stratification and the effect of NAC on post treatment risk categories. Methods: We retrospectively reviewed the charts of consecutive patients who underwent RC at two institutions between 2004 and 2014 and noted whether or not they received NAC. We determined the clinical stage by reviewing the exam under anesthesia, transurethral resection biopsy (TURBT) pathology, and preoperative imaging. Patients with cT2-T4a node-negative disease were included. Those with sarcomatoid features or adenocarcinoma were excluded. Patients were classified as high risk if they had tumor-associated hydronephrosis, clinical stage≥T3b-T4a disease, variant histology (i.e., micropapillary or small cell), or lymphovascular invasion (LVI), as specified by the MDACC model. Variables were examined for associations with cancer-specific survival (CSS), overall survival (OS), and risk-category reclassification. Results: We identified 166 patients with a median follow-up time of 22.2 months. In all, 117 patients (70.5%) did not receive NAC, 68 (58.1%) of whom we classified as high risk. Among patients not receiving NAC, CSS and OS were significantly decreased in high-risk patients (log-rank test p = 0.01 for both comparisons). The estimated age-adjusted hazard ratios of high-risk classification for cancer-specific and overall death were 3.2 (95% CI: 1.2 to 8.6) and 2.2 (95% CI: 1.1 to 4.4), respectively. On post-RC final pathology, 23 (46.9%) low-risk patients were up-classified to high risk and 17 (25.0%) high-risk patients were down-classified. Complete pathologic responses (pT0) were achieved in 7 (6.0%) patients and partial responses (pT1, pTa, pTis) were achieved in 28 (23.9%) patients. Of the 49 patients who did receive NAC, 43 (87.8%) received cisplatin-based and six (12.2%) received carboplatin-based regimens. Applying the MDACC model, we categorized 41 (83.7%) patients as high risk prior to NAC treatment. On final pathology, 3 (37.5%) low-risk patients were up-classified and 17 (41.5%) high-risk patients were down-classified. Complete pathologic responses (pT0) were seen in 13 (26.5%) patients and partial responses were seen in 10 (20.4%) patients. Although the utilization of NAC was not statistically significantly associated with CSS or OS (log-rank test p > 0.05 for both comparisons), it was associated with a 1.2 times increased odds (95% CI: 0.4 to 2.1) of post-RC reclassification from high to low risk on age-adjusted logistic regression. Conclusions: We found similar results using the clinical risk-stratification model in our cohort and showed that the high-risk category was associated with lower CSS and OS. NAC was associated with a higher probability of risk reclassification from high to low risk.

Precision medicine has a goal of customizing disease prevention and treatment strategies. Under the precision medicine paradigm, each patient has unique pathologic processes resulting from cellular genomic, epigenomic, proteomic, and metabolomic alterations, which are influenced by pharmacological, environmental, microbial, dietary, and lifestyle factors. Hence, to realize the promise of precision medicine, multi-level research methods that can comprehensively analyze many of these variables are needed. In order to address this gap, the integrative field of molecular pathology and population data science (i.e., molecular pathological epidemiology) has been developed to enable such multi-level analyses, especially in gastrointestinal cancer research. Further integration of pharmacology can improve our understanding of drug effects, and inform decision-making of drug use at both the individual and population levels. Such integrative research demonstrated potential benefits of aspirin in colorectal carcinoma with PIK3CA mutations, providing the basis for new clinical trials. Evidence also suggests that HPGD (15-PDGH) expression levels in normal colon and the germline rs6983267 polymorphism that relates to tumor CTNNB1 (β-catenin)/WNT signaling status may predict the efficacy of aspirin for cancer chemoprevention. As immune checkpoint blockade targeting the CD274 (PD-L1)/PDCD1 (PD-1) pathway for microsatellite instability-high (or mismatch repair-deficient) metastatic gastrointestinal or other tumors has become standard of care, potential modifying effects of dietary, lifestyle, microbial, and environmental factors on immunotherapy need to be studied to further optimize treatment strategies. With its broad applicability, our integrative approach can provide insights into the interactive role of medications, exposures, and molecular pathology, and guide the development of precision medicine.