TRLS-08 Decoding the Gene Expression Signature of Early and Late Breast Cancer Brain Metastases in Pair-Matched Patient Samples: An Individual Patient Data Meta-Analysis

Breast cancer (BC) is the second most common cause of brain metastases (BM), with a poor median overall survival (OS) of 4.4–18.9 months. Brain metastasis-free survival (BMFS) is an independent prognostic factor for OS. Despite advancements in bioinformatic technologies, the molecular drivers of breast cancer brain metastases (BCBM) remain poorly understood due to low statistical power in the pair-matched BCBM studies (n = 11–39) and limited BM data in the landmark metastatic BC studies (AURORA, CMI-MBC; n = 3–8). In this study, we aim to better characterise the change in transcriptomic signature of BMs—particularly early BMs—compared to their matched primary BCs, by leveraging the growing body of existing literature. This individual patient data (IPD) meta-analysis identified 18 eligible studies from MEDLINE, Embase, and Web of Science up to October 2024, making it the largest discovery cohort of its kind (n = 233, PROSPERO ID: CRD42025633118). Differentially expressed genes (DEGs) between pair-matched BC and BM will be identified and stratified by receptor subtype and BMFS. Gene set enrichment analysis (GSEA) will identify key pathways and regulators, while sample-wise enrichment scores and survival outcomes (BMFS, OS) will be used to calculate hazard ratios (HRs). Principal component analysis (PCA) and Cochrane’s Q-test will assess dataset heterogeneity. Identified markers will undergo internal and external validation using the TCGA BRCA dataset (n = 1,393) and an unpublished BCBM cohort (n = 18) from St. Michael’s Hospital, Toronto. This study will address a critical gap in high-power gene expression research on BCBM, synthesising existing evidence to identify novel targetable pathways and prognostic biomarkers that advance early detection, risk stratification, and therapeutic development of BCBM.