Abstract
Objective: As a dominant component within the tumor microenvironment, macrophages exert essential roles in nearly all aspects of triple-negative breast cancer (TNBC). This work explored macrophage-associated signature genes for prognostication and treatment for TNBC. Methods: Single-cell (GSE180286) and bulk transcriptome profiles (TCGA-TNBC, GSE96058 and GSE45255) were analyzed by multiple computational approaches. The expression of signature genes was verified in tumor tissues and paracancerous normal tissues from patients with TNBC (n=5), HER2(+) breast cancer (n=5), and HR(+) breast cancer (n=5) through immunofluorescence and Western blot. Additionally, gene expression was examined in breast cancer cells (MDA-MB-231, and MCF-7) and mammary epithelial cells (MCF10A) using RT-qPCR and Western blot. Following RNA interference or overexpression, CCK-8, wound scratch and Transwell assays were performed. To assess model robustness, 1000 iterations of Bootstrap resampling were performed to calculate optimism-corrected performance metrics; calibration curves were generated via the rms package. Decision Curve Analysis (DCA) was conducted to evaluate the clinical decision-making value. Results: A single-cell map of the microenvironment in non-TNBC and TNBC was depicted. At both the single-cell and bulk levels, macrophages exhibited a higher abundance in TNBC versus non-TNBC. A macrophage-based gene signature (CTSD, CTSL, ELK4, HSPA8, XRCC4) was developed, with a high-risk score predicting poorer outcomes. This signature demonstrated reliable performance in external validation, particularly for one-year survival (AUC > 0.9). Bootstrap analysis corrected the original AUC from 0.706 to 0.739 (optimism=-0.033, difference <5%), and AUC values from 1000 resamplings concentrated in 0.70-0.75 (standard deviation=0.018). External validation confirmed the signature's ability to reliably predict patient prognosis, especially one-year survival. High-risk patients showed greater responsiveness to immunotherapy. The aberrant expression of CTSD, CTSL, ELK4, HSPA8, and XRCC4 in TNBC and non-TNBC was validated both in vivo and in vitro. Knockdown of XRCC4 attenuated malignant behaviors of MDA-MB-231, MCF-7, and MCF10A cells, whereas overexpression of CTSD, CTSL, and HSPA8 produced the opposite effect. Conclusion: Altogether, a novel macrophage-based gene signature was proposed for estimating survival outcomes and treatment responses in TNBC. The aberrant expression of these signature genes contributes to tumor malignant progression. Our findings offer valuable insights for future clinical research involving macrophages in TNBC.