Abstract A038: Large-scale single-cell and spatial multi-omics elucidate the mechanism by which mitochondrial copper metabolism biomarkers promote immune evasion in breast cancer

Abstract Aberrant copper metabolism is increasingly implicated in tumor progression, yet how it spatially orchestrates the immune microenvironment (TME) remains poorly understood. Here, we integrated large-scale single-cell RNA sequencing and spatial transcriptomics to dissect the immunomodulatory roles of three identified copper metabolism-related prognostic biomarkers—SLC31A1, DLAT, and PDHA1—in breast cancer. We novelly identified SLC31A1 as a specific marker for SPP1+ macrophages(SLC31A1highSPP1+Macro), a subset that spatially excludes cytotoxic T cells and expands the regulatory T cell (Treg) pool. Concurrently, DLAT was enriched in CXCL13+ Tfh cells, which were found to suppress CD8+GZMK+ T cells. Expanding on this, our spatial analysis revealed a critical metabolic-immune axis involving PDHA1, which is specifically upregulated in CD4+CTLA4+ Tregs. By reconstructing cellular communication networks and ecological niches, we demonstrated that PDHA1highCD4+ Tregs actively impede the infiltration and cytotoxic function of CD8+GZMK+ T cells. Crucially, this study is the first to systematically link the two dominant immunosuppressive populations—SPP1+ macrophages and CD4+CTLA4+ Tregs—by defining SLC31A1 and PDHA1 as their respective metabolic checkpoints. These two axes synergistically construct a metabolic driver that reshapes the TME into a "cold" phenotype. Leveraging these high-resolution spatial insights, we developed a novel multi-modal, multi-task Reinforcement Learning (RL) framework. By incorporating the distinct spatial biological behaviors of SLC31A1highSPP1+ macrophages and PDHA1highCD4+CTLA4+ Tregs rather than simple expression levels, this model robustly predicts patient prognosis and immunotherapy sensitivity, outperforming traditional metrics. Finally, the clinical relevance of SLC31A1 and PDHA1as a therapeutic target and biomarker was validated via qPCR and multiplex immunohistochemistry (mIHC) in an independent cohort from Yijishan Hospital. Collectively, our findings provide a holistic view of how mitochondrial copper metabolism fuels the synergy between key immunosuppressive cells and offer an advanced AI-driven tool for precision oncology. Citation Format: Bowen Chu, Xin Tong, Xinhao Tang, Xiaoya Wang, Xinyu Tian, Rui Zhang, Yijun Jiang, Shuai Yan, Shuai Hao. Large-scale single-cell and spatial multi-omics elucidate the mechanism by which mitochondrial copper metabolism biomarkers promote immune evasion in breast cancer abstract. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr A038.