A study published in Cancer Biology & Medicine has introduced a new classification system for breast cancer based on the cancer-immunity cycle (CIC), offering insights into why some patients respond to immunotherapy while others do not and identifying potential new treatment targets. The research, conducted by scientists from Fudan University Shanghai Cancer Center and Shanghai Medical College, analyzed the activity of six key steps in the anti-tumor immune response to categorize breast cancer into three distinct subtypes with different immune profiles and therapeutic vulnerabilities.
Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, but many breast cancer patients do not benefit from them. The CIC framework maps the sequential steps required for an effective immune response, from antigen release to tumor cell killing. Defects in any step can halt the cycle and cause treatment resistance. Previous research focused on individual steps, lacking a holistic view. To address this, the team developed a 'CIC score' to measure the activity of each step across tumors.
Analyzing the scores, they identified three clusters. Cluster 1 (C1) was 'immune-cold,' with low immune infiltration, poor prognosis, and abundance of immunosuppressive M2 macrophages. Cluster 3 (C3) was 'immune-hot,' with high immune cell infiltration, active T cells, and the best response to ICI therapy. Cluster 2 (C2) was an intermediate subtype with a unique defect in antigen presentation. Despite high tumor mutational burden (TMB), C2 tumors showed frequent HLA loss of heterozygosity and an immunosuppressive microenvironment enriched with dysfunctional dendritic cells and regulatory T cells.
Multi-omic analyses revealed distinct metabolic dependencies: C1 tumors were enriched in sphingolipid metabolism, while C2 tumors depended on serine metabolism. The enzyme PSAT1 emerged as a key metabolic regulator in C2; its knockdown in cancer cells reduced expression of immunosuppressive molecules like PD-L1 and TGFB1. 'The CIC provides a powerful framework for understanding how tumors evade the immune system,' the authors said. 'By building a comprehensive score that captures the efficiency of this entire cycle, we've moved beyond the simple hot and cold tumor paradigm to identify distinct, actionable defects.'
This classification has immediate clinical implications. The CIC score could serve as a biomarker to stratify patients, identifying those likely to respond to ICIs and sparing others from side effects. The discovery of distinct immune-evasion mechanisms suggests novel combination therapies: for C1, converting the cold microenvironment to hot; for C2, enhancing antigen presentation by targeting PSAT1 or overcoming HLA loss. The study, published with DOI 10.20892/j.issn.2095-3941.2025.0611, was supported by the National Key Research and Development Project of China and the National Natural Science Foundation of China. The findings offer a roadmap for more personalized immunotherapy in breast cancer.
