Study

Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

Study ID Alternative Stable ID Type
EGAS00001002777 Other

Study Description

Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

Study Datasets 1 dataset.

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Dataset ID Description Technology Samples
EGAD00001004212 Files from whole exome sequencing of 14 tumors from two cancer patients (endometrial and lung cancer) along with a matched normal tissue per patient. Illumina HiSeq 2000 16

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Publications

Publications Citations
Minimal functional driver gene heterogeneity among untreated metastases.
Science 361:2018 1033-1037
51