Fig. 3

Genomic alterations of known significance and applicability to large cohorts. a, b The alteration status of significantly mutated genes predicted by MutSig2CV^{23, 24} (a), focal SCNAs (b), and known cancer-associated genes²² are shown for cfDNA and tumor biopsies from 27 metastatic breast cancer (MBC) patients. Mutated genes with MutSig2CV q-value < 0.1 are statistically significant. Mutations that were exclusively detected in one sample may be present at low CCF in the other matched sample but were excluded from the frequency calculation. SCNA frequencies were computed for oncogenes (MYC to ERBB2) and tumor suppressors (BRCA1 to ATM) using only amplification and deletion status, respectively. Mutations were predicted using MuTect and SCNAs were predicted using ReCapSeg and ABSOLUTE. Red dot indicates distinct mutations in tumor and cfDNA. c Mutational signatures in whole-exome sequencing of cfDNA and tumor biopsies were predicted using a Bayesian non-negative matrix factorization (NMF) approach²⁹ (“Methods”). Samples with predicted biallelic inactivation of BRCA1/2 are indicated in red and blue. Black line denotes y = x; blue line denotes model fit using linear least squares regression. d Neoantigen burden, defined as the number of predicted neoantigen SSNVs, was calculated using NetMHCpan³³ (“Methods”). Black line denotes y = x; blue line denotes model fit using linear least squares regression. e Applicability to many patients with metastatic cancer. Tumor fractions estimated from ULP-WGS of cfDNA from 903 blood samples from 391 patients with metastatic breast cancer and 536 blood samples from 129 patients with metastatic prostate cancers. The earliest blood drawn for each patient is shown. Samples with coverage <0.05× were excluded