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Minimal functional driver gene heterogeneity among untreated metastases
Minimal functional driver gene heterogeneity among untreated metastases
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Minimal functional driver gene heterogeneity among untreated metastases
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Minimal functional driver gene heterogeneity among untreated metastases
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Minimal functional driver gene heterogeneity among untreated metastases
Minimal functional driver gene heterogeneity among untreated metastases
Journal Article

Minimal functional driver gene heterogeneity among untreated metastases

2018
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Overview
Treatment decisions for cancer patients are increasingly guided by analysis of the gene mutations that drive primary tumor growth. Relatively little is known about driver gene mutations in metastases, which cause most cancer-related deaths. Reiter et al. explored whether the growth of different metastatic lesions within an individual patient is fueled by the same or distinct gene mutations. In a study of 76 untreated metastases from 20 patients with different types of cancer, all metastases within a patient shared the same functional driver gene mutations. Thus, analysis of a single biopsy could help oncologists select the optimal therapy for patients with widespread metastatic disease. Science , this issue p. 1033 The growth of different metastatic lesions within an individual cancer patient is fueled by the same genetic mutations. Metastases are responsible for the majority of cancer-related deaths. Although genomic heterogeneity within primary tumors is associated with relapse, heterogeneity among treatment-naïve metastases has not been comprehensively assessed. We analyzed sequencing data for 76 untreated metastases from 20 patients and inferred cancer phylogenies for breast, colorectal, endometrial, gastric, lung, melanoma, pancreatic, and prostate cancers. We found that within individual patients, a large majority of driver gene mutations are common to all metastases. Further analysis revealed that the driver gene mutations that were not shared by all metastases are unlikely to have functional consequences. A mathematical model of tumor evolution and metastasis formation provides an explanation for the observed driver gene homogeneity. Thus, single biopsies capture most of the functionally important mutations in metastases and therefore provide essential information for therapeutic decision-making.