MultiStage Clonal Expansion model for Esophageal AdenoCarcinoma

Basic Model Attributes
Cancer siteEsophageal
Host institution Fred Hutch Cancer Research Center
Purpose To provide a mathematical and computational framework for multiscale modeling of the natural history of progression from normal esophageal squamous epithelium to esophageal adenocarcinoma (EAC). Fundamental scales in the MSCE-EAC (MSEAC) model include the cell, crypt, clonal patch, tissue [normal, Barrett's esophagus (BE), high grade dysplasia (HGD), and EAC], individual, and population levels. The development of BE is recognized as an early step in progression to EAC, with an enhanced risk for BE among individuals with gastroesophageal reflux disease (GERD) symptoms. The model represents age-dependent development of weekly or more frequent GERD symptoms, with transitions from both GERD and non-GERD pathways to develop BE, two additional mutations or epigenetic changes for the initiation of HGD, with clonal expansion of cells comprising HGD, malignant transformation, and a more rapid clonal expansion process for EAC. GERD incidence data were utilized to calibrate the model for age-dependent GERD prevalence, and Surveillance Epidemiology and End Results (SEER) incidence data were used for likelihood-based calibration of the remaining parameters of the multiscale EAC progression model. EAC incidence has increased approximately seven-fold in the US since 1975, as reflected in SEER data. These temporal trends were modeled by systematically applying flexible period and cohort trends to the biological parameters of the MSEAC model, and using likelihood methods for model comparison and selection of the best model fit to SEER incidence. To identify which biological parameters may be influenced by temporal trends, we compared alternative models with period and/or cohort effects influencing GERD development, the transition rate to BE, early mutation steps, growth of premalignant lesions, malignant transformation, and clonal growth of the tumor. The best model fit includes a sigmoidal (birth) cohort trend on both premalignant and malignant clonal expansion. Spatial simulations of the growth of premalignant clones (identified with HGD) and malignant tumors are mapped to represent two-dimensional localization and growth on the BE segment of the esophageal surface(represented as a torus). This spatial modeling component of the MSEAC model allows analysis of the probability for biopsy sampling of HGD and preclinical EAC during screening, along with symptomatic cancer detection. This framework is inherently 'multiscale' in that it bridges the cellular scale with the population scale, allowing us to model physically the process of endoscopic screening of BE patients for the presence of premalignant and preclinical malignant lesions prior to the appearance of cancer symptoms and/or a cancer diagnosis.
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