Abstract 4261: Pathways of metastatic bladder cancer from a longitudinal patient data set

Bladder cancer (BCa), the 6th commonest cancer in the U.S., is highly lethal when metastatic. Sites and patterns of patient-specific metastatic spread are deemed random and unpredictable. Whether BCa metastatic patterns can be quantified and predicted more accurately is unknown. We used a prospective, longitudinal dataset of 3,505 BCa patients who underwent definitive treatment following diagnosis and were continuously enrolled (1971-2016; mean follow-up 6.13 years). Metastases developed in 30% (n=1,040) of patients, with 5-year survival rate of 18%, compared to 72% in those without metastases (n=2,465). The three commonest metastatic sites at time-of-first progression were pelvis (n=283; 27.2%), bone (n=274; 26.3%), and lung (n=247; 23.8%). We illustrate metastatic pathway progression as color-coded, circular, tree-ring diagrams (primary in the center; metastatic sites outwards). Markov chain modeling, denoting nodes as potential anatomic metastatic sites, indicated higher probability of spread from the bladder to pelvis (15.6%), bone (15.6%), and lung (13.9%), categorizing 4 of 10 anatomical sites as ‘spreaders' and 2 as ‘sponges'. We created a dynamical, data-visualization, web-platform that displays temporal, spatial and Markov modeling figures with predictive capability. For contrasting subgroups, this platform indicated differences in transition probabilities, rank-ordering of metastatic sites, and spreader/sponge node classification. Spatiotemporal patterns of BCa metastasis and sites of spread indicate underlying organotropic mechanisms in the prediction of response. This recognition opens the possibility of organ site-specific therapeutic targeting in the oligo-metastatic disease setting. In the precision medicine era, visualization of complex, time-resolved clinical data will enhance management of post-operative, metastatic BCa patients. Citation Format: Jeremy M. Mason, Zaki Hasnain, Gus Miranda, Karanvir Gill, Paul K. Newton, Inderbir S. Gill, Peter Kuhn. Pathways of metastatic bladder cancer from a longitudinal patient data set [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4261.