Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast Cancer

The interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a...

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Bibliographic Details
Published inCancer research (Chicago, Ill.) Vol. 80; no. 2; pp. 170 - 174
Main Authors Chen, Runpu, Goodison, Steve, Sun, Yijun
Format Journal Article
LanguageEnglish
Published United States 15.01.2020
Subjects
Adult
Aged
Aged, 80 and over
Breast - pathology
Breast Neoplasms - genetics
Breast Neoplasms - mortality
Breast Neoplasms - pathology
Cohort Studies
Computational Biology
Datasets as Topic
Disease Progression
Evolution, Molecular
Female
Gene Expression Profiling
Humans
Linear Models
Middle Aged
Models, Biological
Prognosis
Survival Analysis
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ISSN0008-5472
1538-7445
1538-7445
DOI10.1158/0008-5472.CAN-19-2296

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Summary:The interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We 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 used 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 subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a roadmap of breast cancer progression will facilitate the development of improved cancer diagnostics, prognostics, and targeted therapeutics. SIGNIFICANCE: Analysis of matched primary and metastatic tumor samples supports a unidirectional, linear cancer evolution process and sheds light on longstanding issues regarding the origins of molecular subtypes and their progression relationships.
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ISSN:0008-5472
1538-7445
1538-7445
DOI:10.1158/0008-5472.CAN-19-2296