Abstract
Background: Metastatic breast cancer is a deadly disease with a low 5-year survival rate. Tracking metastatic spread in living patients is difficult and thus poorly understood. Methods: Via rapid autopsy, we have collected 30 tumor samples over 3 timepoints and across 8 organs from a triple-negative metastatic breast cancer patient. The large number of sites sampled, together with deep whole-genome sequencing and advanced computational analysis, allowed us to comprehensively reconstruct the tumor’s evolution at subclonal resolution. Results: The most unique, previously unreported aspect of the tumor’s evolution that we observed in this patient was the presence of “subclone incubators,” defined as metastatic sites where substantial tumor evolution occurs before colonization of additional sites and organs by subclones that initially evolved at the incubator site. Overall, we identified four discrete waves of metastatic expansions, each of which resulted in a number of new, genetically similar metastasis sites that also enriched for particular organs (e.g., abdominal vs bone and brain). The lung played a critical role in facilitating metastatic spread in this patient: the lung was the first site of metastatic escape from the primary breast lesion, subclones at this site were likely the source of all four subsequent metastatic waves, and multiple sites in the lung acted as subclone incubators. Finally, functional annotation revealed that many known drivers or metastasis-promoting tumor mutations in this patient were shared by some, but not all metastatic sites, highlighting the need for more comprehensive surveys of a patient’s metastases for effective clinical intervention. Conclusions: Our analysis revealed the presence of substantial tumor evolution at metastatic incubator sites in a patient, with potentially important clinical implications. Our study demonstrated that sampling of a large number of metastatic sites affords unprecedented detail for studying metastatic evolution.
| Original language | English |
|---|---|
| Article number | 170 |
| Journal | Genome Medicine |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2021 |
| Externally published | Yes |
Funding
We thank the patient and her family for generously participating in and supporting this research. We thank Kathy Raven from Raven Forensic Pathology & Autopsy Services for conducting a rapid autopsy. X.H., Y.Q., and G.T.M. were supported by U24CA209999 to G.T.M. S.W.B., A.H.B., A.L.C., G.S., and J.A.M. were supported by U54CA209978. A.L.C. was supported by P30CA042014 from the NCI. S.W.B. was supported by the NLM training grant 5T15LM007124. We thank the University of Utah and the College of Pharmacy for supporting the sequencing of the samples. Research reported in this publication utilized the High-Throughput Genomics and Bioinformatic Analysis Shared Resource at Huntsman Cancer Institute at the University of Utah and was supported by the NCI of the NIH under Award Number P30CA042014. The support and resources from the Center for High-Performance Computing at the University of Utah are gratefully acknowledged. The computational resources used were partially funded by the NIH Shared Instrumentation Grant 1S10OD021644-01A1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.
| Funders | Funder number |
|---|---|
| National Institutes of Health | 1S10OD021644-01A1 |
| National Cancer Institute | U24CA209999, P30CA042014 |
| U.S. National Library of Medicine | 5T15LM007124 |
| University of Utah |
Keywords
- Metastatic breast cancer
- Subclone
- Tumor evolution
