Serum detection of MUC1 and renin identifies circulating biomarkers for breast cancer prognosis

Background: Cytogenetic abnormalities involving multiple loci on the long arm of chromosome 1 are among the most frequent alterations in human breast carcinoma. To define their biological and clinical significance, we conducted a large-scale integrative genomic analysis across diverse breast cancer datasets. Methods: Data from over 13,000 breast tumors (n = 13,146 samples; 12,229 patients across 30 studies) were analyzed using cBioPortal, including The Cancer Genome Atlas (TCGA). Copy number alterations, mRNA/protein expression, and clinical outcomes were evaluated. Comparative analyses with >100,000 samples across 35 other cancers (n = 105,424) determined specificity. Mutual exclusivity and co-occurrence analyses identified genetic interaction patterns relevant to tumor progression. Serum detectability of top candidates was evaluated. Results: Eight genes particularly TRIM67, DISC1, REN, DNM3, ATP1B1, VSIG8, SPTA1, and MUC1 from different loci of 1q chromosome showed recurrent amplifications (12-15%) in breast tumors, significantly exceeding frequencies in pan-cancer datasets (~3%). These genes displayed low baseline expression in normal breast tissue but were highly expressed in tumors. Co-occurrence analyses revealed significant genetic interplay, including TP53 with MUC1/SPTA1/VSIG8 and PIK3CA with TRIM67/DISC1/REN, suggesting cooperative gain-of-function driving aggressive phenotypes. Among the eight amplified 1q genes, MUC1 and REN showed the strongest clinical relevance, as both encode secreted or shed proteins that were readily detectable in serum and have established associations with aggressive breast cancer biology. In contrast, DNM3 and ATP1B1 were detectable at lower abundance in serum-derived extracellular vesicles, supporting their potential as emerging but less established circulating markers. Conclusions: Multi-locus amplifications contribute collectively to breast cancer progression through distinct gene interaction networks. This study identifies a core set of functionally relevant, serum-detectable gene products that may serve as biomarkers for prognosis, recurrence monitoring, and therapeutic targeting in aggressive breast cancer.