Background: Liquid biopsy analysis detecting circulating tumor cells (CTC) or circulating tumor DNA (ctDNA) is a non-invasive approach that may provide clinically actionable information for patients’ (pts) treatment decisions when conventional biopsy is otherwise inaccessible or infeasible. Here we report a liquid biopsy method including CTC characterization & ctDNA alterations in pts symptomatic of first metastatic recurrence with a history of primary breast cancer (BC). Methods: Blood samples from 34 symptomatic BC pts were collected for cell & cell-free DNA analysis before undergoing contemporaneous tissue biopsy & initiating treatment for metastatic BC (MBC). Blood was also collected from 25 blood donors (HD) with no known cancer history. After plasma isolation, nucleated cells were plated, & slides were bio-banked. Immunofluorescent staining & subsequent imaging were performed on replicate slides. CTCs were identified using Epic Sciences digital imaging & machine learning algorithms trained to identify breast cancer cells. Single-cell (sc) isolation for genomic quantification of large-scale transitions (scLST) was used to further characterize individual CTCs. cfDNA from bio-banked plasma was analyzed to detect Class IA alterations in ctDNA. Results: Within this cohort of 34 patients, CTCs & ctDNA alterations were detected in 80% & 58%, respectively while no CTCs & ctDNA were detected in the HD cohort suggesting high specificity (100% & 100%). In this study, 26 pts were confirmed MBC (M1-BC) by tissue biopsy, 3 pts were non-MBC by tissue biopsy but still diagnosed as metastatic (Mx-BC), & 5 pts were confirmed non-MBC (M0-BC). To benchmark the cellular (CTCs & scLST+CTCs) & genomic (ctDNA) individual platforms, we designed thresholds of CTCs > 4, scLST+CTC+, & ctDNA+ that optimally identified M1-BC pts with high specificity (100%, 100%, & 100%) but low sensitivity (46%, 46%, & 50%). CTCs > 4 & scLST+CTC+ cutoffs had low concordance with the presence of ctDNA alterations, suggesting these platforms provide independent & complementary value when identifying MBC. To test this hypothesis, we designed combination models [CTC > 4][ctDNA+] & [scLST+CTC+][ctDNA+] that significantly improved sensitivity (75% & 67%) over individual platforms while maintaining high specificity (100% & 100%) when identifying the first recurrence of metastasis in BC pts. Conclusions: To our knowledge, this is the first report showing the additive & complementary value of models combining cellular & genomic liquid biopsy platforms for the detection of the first MBC recurrence. Our data suggest the clinical utility of combined CTC & ctDNA platforms for the identification of MBC when tissue biopsy is inaccessible or infeasible.