TY - JOUR
T1 - Reconstructing metastatic seeding patterns of human cancers
AU - Reiter, Johannes G.
AU - Makohon-Moore, Alvin P.
AU - Gerold, Jeffrey M.
AU - Bozic, Ivana
AU - Chatterjee, Krishnendu
AU - Iacobuzio-Donahue, Christine A.
AU - Vogelstein, Bert
AU - Nowak, Martin A.
N1 - Funding Information:
This work was supported by the European Research Council (ERC) start grant 279307: Graph Games (J.G.R., C.K.), Austrian Science Fund (FWF) grant no. P23499-N23 (J.G.R., K.C.), FWF NFN grant no. S11407-N23 RiSE/SHiNE (J.G.R., K.C.), a Landry Cancer Biology Fellowship (J.M.G.), National Institutes of Health grants CA179991 (C.A.I.-D., I.B.), F31CA180682 (A.P.M.-M.), CA43460 (B.V.), the Lustgarten Foundation for Pancreatic Cancer Research, The Sol Goldman Center for Pancreatic Cancer Research, The Virginia and D.K. Ludwig Fund for Cancer Research, Office of Naval Research grant N00014-16-1-2914, the Bill and Melinda Gates Foundation OPP1148627
Publisher Copyright:
©The Author(s) 2017.
PY - 2017/1/31
Y1 - 2017/1/31
N2 - Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumour samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumour heterogeneity among distinct samples. In silico benchmarking on simulated tumour phylogenies across a wide range of sample purities (15-95%) and sequencing depths (25-800 ×) demonstrates the accuracy of Treeomics compared with existing methods.
AB - Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumour samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumour heterogeneity among distinct samples. In silico benchmarking on simulated tumour phylogenies across a wide range of sample purities (15-95%) and sequencing depths (25-800 ×) demonstrates the accuracy of Treeomics compared with existing methods.
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U2 - 10.1038/ncomms14114
DO - 10.1038/ncomms14114
M3 - Article
C2 - 28139641
AN - SCOPUS:85011690566
SN - 2041-1723
VL - 8
JO - Nature communications
JF - Nature communications
M1 - 14114
ER -