Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Reveals a Tissue-Resident Macrophage-Related Signature for Predicting Immunotherapy Response in Breast Cancer Patients

Cancers (Basel). 2022 Nov 9;14(22):5506. doi: 10.3390/cancers14225506.

Abstract

Immune checkpoint therapy (ICT) is among the widely used treatments for breast cancer (BC), but most patients do not respond to ICT and the availability of the predictive biomarkers is limited. Emerging evidence indicates that tissue-resident macrophages (RTMs) inhibit BC progression, suggesting that their presence may predict immunotherapy response. A single-cell RNA-sequencing analysis of BC samples was performed to identify five RTM clusters with a mixed phenotype of M1-M2 macrophages. The comprehensive results showed that a high score of each RTM cluster was associated with a high infiltration of CD8+ T cells, M1 macrophages, and dendritic cells, and improved overall survival. In addition, a low score of each RTM cluster was associated with a high infiltration of M0 macrophages, naïve B cells and Tregs, and poor overall survival. Gene signatures from each RTM cluster were significantly enriched in responders compared with nonresponders. Each RTM cluster expression was significantly higher in responders than in nonresponders. The analyses of bulk RNA-seq datasets of BC samples led to identification and validation of a gene expression signature, named RTM.Sig, which contained the related genes of RTM clusters for predicting response to immunotherapy. This study highlights RTM.Sig could provide a valuable tool for clinical decisions in administering ICT.

Keywords: breast cancer; immune checkpoint therapy; single-cell RNA-sequencing; tissue-resident macrophages.