Genomic Divergence Between Matched Primary and Metastatic Tumors Across Cancer Types: A Pan-Cancer Analysis of 5,692 Samples

Introduction: Metastasis represents the leading cause of cancer-related mortality and is characterized by complex biological processes such as genomic instability, immune evasion, and therapy resistance. While metastatic tumors often retain the truncal drivers of their primary counterparts, the extent and nature of additional somatic alterations acquired during progression remain incompletely defined across cancer types. Methods: A comprehensive pan-cancer analysis was conducted using targeted sequencing data from 2,846 patients with matched primary and metastatic tumors (totaling 5,692 samples) obtained from the AACR Project GENIE v18.0 cohort. Harmonized variant calls were used to compare mutation burden, fraction of genome altered (FGA), gene-level mutation frequencies, copy number alterations (CNA), and structural variants (SV) between compartments. Statistical comparisons were adjusted for multiple testing using the Benjamini-Hochberg method. Results: Metastatic tumors exhibited a significantly higher median mutation count (6 vs. 5; p < 0.001) and FGA (0.186 vs. 0.140; p < 0.001) compared to matched primary tumors. This increase was most prominent in non-small cell lung, breast, colorectal, pancreatic, and prostate cancers. Eleven genes, including KDM5A, CDKN2A, MYC, ESR1, and AR, were significantly enriched in metastases, suggesting mechanisms such as cell cycle deregulation, therapy-induced selection, and chromatin remodeling. Notably, ESR1 alterations were enriched in breast cancer metastases, consistent with endocrine therapy resistance, while AR alterations were markedly more frequent in metastatic prostate cancer. CNA analysis revealed recurrent amplifications (MYC, ERBB2, CCND1) and deletions (CDKN2A, PTEN, RB1) in metastatic tumors. Structural variants involving genes linked to DNA damage response and epigenetic regulation were also more prevalent in the metastatic setting. Conclusions: In this large-scale matched cohort of 2,846 patients and 5,692 tumor samples, metastatic tumors exhibited increased mutation burden and widespread genomic instability. Although treatment data were not available to directly associate resistance-related alterations with specific therapies, the observed patterns suggest that these acquired changes reflect context-dependent selection for survival and proliferative advantage in advanced disease, rather than the emergence of novel metastasis-specific driver events. Conclusions: In this large-scale matched cohort of 2,846 patients and 5,692 tumor samples, metastatic tumors exhibited increased mutation burden and widespread genomic instability. Although treatment data were not available to directly associate resistance-related alterations with specific therapies, the observed patterns suggest that these acquired changes reflect context-dependent selection for survival and proliferative advantage in advanced disease, rather than the emergence of novel metastasis-specific driver events.