TY - JOUR T1 - Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support an Evolutionary Model of Breast Cancer JF - bioRxiv DO - 10.1101/667303 SP - 667303 AU - Runpu Chen AU - Steve Goodison AU - Yijun Sun Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/06/12/667303.abstract N2 - The interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We have developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a linear, branching evolutionary model with two distinct trajectories for malignant progression. Here, we use the progression model as a foundation to investigate the relationships between matched primary and metastasis breast tumor samples. Mapping paired data onto the model confirmed that molecular breast cancer subtypes can shift during progression, and supported directional tumor evolution through luminal breast cancer subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a breast cancer progression roadmap will provide a foundation for the development of improved cancer diagnostics, prognostics and targeted therapeutics. ER -