The genomic landscape of metastasis in treatment-naïve breast cancer models

Metastasis remains the principle cause of mortality for breast cancer and presents a critical challenge because secondary lesions are often refractory to conventional treatments. While specific genetic alterations are tightly linked to primary tumor development and progression, the role of genetic a...

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Veröffentlicht in:PLoS genetics 2020-05, Vol.16 (5), p.e1008743
Hauptverfasser: Ross, Christina, Szczepanek, Karol, Lee, Maxwell, Yang, Howard, Qiu, Tinghu, Sanford, Jack D, Hunter, Kent
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creator Ross, Christina
Szczepanek, Karol
Lee, Maxwell
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Qiu, Tinghu
Sanford, Jack D
Hunter, Kent
description Metastasis remains the principle cause of mortality for breast cancer and presents a critical challenge because secondary lesions are often refractory to conventional treatments. While specific genetic alterations are tightly linked to primary tumor development and progression, the role of genetic alteration in the metastatic process is not well-understood. The theory of tumor evolution postulated by Peter Nowell in 1976 has yet to be proven in the context of metastasis. Therefore, in order to investigate how somatic evolution contributes to breast cancer metastasis, we performed exome, whole genome, and RNA sequencing of matched metastatic and primary tumors from pre-clinical mouse models of breast cancer. Here we show that in a treatment-naïve setting, recurrent single nucleotide variants and copy number variation, but not gene fusion events, play key metastasis-driving roles in breast cancer. For instance, we identified recurrent mutations in Kras, a known driver of colorectal and lung tumorigenesis that has not been previously implicated in breast cancer metastasis. However, in a set of in vivo proof-of-concept experiments we show that the Kras G12D mutation is sufficient to significantly promote metastasis using three syngeneic allograft models. The work herein confirms the existence of metastasis-driving mutations and presents a novel framework to identify actionable metastasis-targeted therapies.
doi_str_mv 10.1371/journal.pgen.1008743
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subjects Algorithms
Amino acids
Animal models
Animals
Biology and Life Sciences
Breast cancer
Breast Neoplasms - genetics
Breast Neoplasms - pathology
Cancer therapies
Cells, Cultured
Clonal Evolution - genetics
Copy number
Disease Models, Animal
Disease Progression
DNA Mutational Analysis - methods
Exome Sequencing
Extravasation
Female
Gene expression
Gene fusion
Genetic engineering
Genomics - methods
HEK293 Cells
Heterografts
High-Throughput Nucleotide Sequencing
Humans
Hypotheses
Medicine and Health Sciences
Metastases
Metastasis
Mice
Mice, Inbred BALB C
Mice, Inbred C57BL
Mice, Nude
Mice, Transgenic
Models, Biological
Mutation
Neoplasm Metastasis
Patients
Research and Analysis Methods
Ribonucleic acid
RNA
Tumors
title The genomic landscape of metastasis in treatment-naïve breast cancer models
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