Immune checkpoints expression patterns predict prognosis and immune microenvironment remodeling in triple-negative breast cancer

Abstract

Targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown. Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. Molecular typings based on the ICGs expression profiled were identified and the associations between ICGs molecular typing and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs) were further explored. We identified two ICGs clusters and two ICGs-related gene clusters, which were were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We also established and ICGs Riskscore quantification system to assess the ICGs expression patterns for individuals. TNBC patients with lower ICGs Riskscore were characterized by increased immune cell infiltration, favorable clinical outcome and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict OS in TNBC and the proposed nomogram presents good performance. Genomic features analysis revealed that high ICGs-related riskscore group presented an increased tumor mutation burden compared with the low ICGs-related riskscore group. Collectively, dissecting the ICGs expression patterns not only provides a new insight of subtype of TNBC but also deepens the understanding of ICGs in tumor immune microenvironment.