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Abstract

<title>Abstract</title> <p> Metastasis remains the major cause of mortality in triple-negative breast cancer (TNBC) <sup>1,2</sup> , yet the metastatic potential of primary tumors is difficult to predict at diagnosis <sup>3,4</sup> . Here, we leveraged patient-derived xenograft (PDX) models as a functional readout of primary tumor metastatic propensity. We first performed integrated genomic and transcriptomic profiling of 57 primary breast tumors and their matched PDX models and found that key driver mutations, recurrent copy number alterations, and molecular subtype features were largely conserved between patient tumors and xenografts. These findings support the utility of matched PDX models as clinically relevant platforms for studying tumor-intrinsic features associated with breast cancer progression. We classified the 38 TNBC PDX models based on their reproducible in vivo metastasis capacity and the clinical outcomes of the corresponding patients. Non-metastatic PDX models were characterized by the lack of distant metastasis development in either mouse experiments or clinical follow-up data (n = 4). PDX models were defined as metastatic models when they developed distant metastasis in both mice and humans (n = 4). Single-cell transcriptomic profiling of these tumors revealed that metastatic samples were characterized by hypoxia-associated metabolic reprogramming, with coordinated activation of hypoxia and glycolysis pathways. Network-based prioritization identified adenylate kinase 1 (AK1) as a candidate regulator of this metastatic program. Functionally, AK1 promoted metastatic potential in primary tumor by supporting glycolytic ATP production, resistance to hypoxic and oxidative stress, and promoting trans-endothelial migration. Together, our findings establish primary tumor–matched PDX models as a clinically relevant discovery platform for metastatic potential. Using reproducible PDX metastasis as a functional readout, we identify AK1 as a key regulator underlying metastatic potential in primary TNBC. </p>

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Keywords

metastatic models primary metastasis potential

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