Abstract PS3-06-19: Phylogenetic and Transcriptomic Analyses Reveal Specific Adaptations for Progression of Breast Cancer

Abstract Introduction: Metastatic spread and cancer evolution in response to treatment represent major obstacles to positive patient outcomes. Preliminary evidence on cancer metastatic progression supports evolutionary selection from primary tumors as a proposed mechanism for metastasis. PanCancer and focused studies have demonstrated an overall pattern of increased genomic alterations concurrent with increased clonality in metastasis compared to primary tumors. This circumstance is likely to arise due to ongoing mutational processes during cancer progression that result in selection for a specific subclone seeding. This selection process will manifest in genomic adaptations such as small mutations, copy number alterations, or epigenetic modifications regulating gene expression and directed towards enhancing tumor survival and proliferation. The genomic composition of seeding clones across tumors may give us unique insight into metastatic progression. Methods: Our study aims at defining networks of progression in metastasis of breast cancer with a total of 2077 patients participating from the ORIEN consortium. The current analysis focused on 112 paired cases of primary and metastasis (regional lymph node or distal). Subclonal deconvolution was used to define seeding clone clusters and reconstruct tumor phylogenies based on PyClone and CONIPHER modeling. Transcriptomics analysis of a subset of cases with successful RNASeq (N=62) was performed to identify differential expression between primary and metastasis using limma. Copy number alterations were identified with ASCAT or Sequenza and analyzed using GISTIC2. dNdS mutation rates were used to model positive selection. Gene Set Enrichment Analysis was used to identify differentially expressed pathways. Results: Our analysis of 112 cases of paired breast tumors has identified specific oncogenes and tumor suppressors, including transcription factors, kinases, and chromatin remodelers, under positive selection for mutation at different stages of progression. These genes include GATA3, TP53, and 4 potentially novel breast cancer driver genes. Copy number analysis identified a unique profile for amplifications and deletions in selection for metastatic progression, including the early acquisition of broad chromosome arm events and focal enrichment. Transcriptomics analysis revealed 5 specific pathways enriched in progression programs such as EMT and immune regulation. Tumor microenvironment and mutation signatures are being analyzed to elucidate the progression networks of breast cancer. Hierarchical clustering and machine learning approaches will be used to model clinical, molecular, and seeding clone features for additional insights into the evolutionary networks that drive metastasis. Conclusion: Our study uses innovations in cancer genomics to determine the subclonal progression into metastasis with a comprehensive genomic and transcriptomic profile. This approach can yield valuable insights into cancer evolution and therapeutic markers. Disclaimer: The contents of this publication are the sole responsibility of the author(s) and do not necessarily reflect the views, opinions, or policies of Uniformed Services University of the Health Sciences (USUHS), the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., the Department of Defense (DoD) or the Departments of the Army, Navy, or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. government. Citation Format: M. Russo, P. Raj-Kumar, J. Liu, A. Praveen-Kumar, A. Kovatich, A. Tan, H. Hu, C. Shriver, X. Lin. Phylogenetic and Transcriptomic Analyses Reveal Specific Adaptations for Progression of Breast Cancer abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-06-19.