Evolutionary history of metastatic breast cancer reveals minimal seeding from axillary lymph nodes

Ikram Ullah(Karolinska Institutet), Govindasamy-Muralidharan Karthik(Karolinska Institutet), Amjad Alkodsi(University of Helsinki), Una Kjällquist(Karolinska Institutet), Gustav Stålhammar(Karolinska Institutet), John Lövrot(Karolinska Institutet), Nelson-Fuentes Martinez(Karolinska University Hospital), Jens Lagergren(KTH Royal Institute of Technology), Sampsa Hautaniemi(University of Helsinki), Johan Hartman(Karolinska University Hospital), Jonas Bergh(Karolinska University Hospital)
Journal of Clinical Investigation
February 25, 2018
Cited by 151Open Access
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Abstract

Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.


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