A new study published in Cancer Biology & Medicine has introduced a novel classification system for breast cancer based on the cancer-immunity cycle (CIC), offering a more holistic approach to predicting patient response to immune checkpoint inhibitors (ICIs) and uncovering new therapeutic targets. The research, conducted by scientists from Fudan University Shanghai Cancer Center and Shanghai Medical College, Fudan University, analyzed the activity of six key steps in the CIC to generate a 'CIC score' that categorizes breast cancer into three distinct subtypes with different immune profiles and clinical outcomes.
The cancer-immunity cycle describes the stepwise process of an anti-tumor immune response, from antigen release to T-cell killing of cancer cells. Defects at any step can render immunotherapies like ICIs ineffective. While previous research has focused on individual steps, this study provides a comprehensive assessment. The team analyzed data from multiple breast cancer cohorts and identified three clusters: C1, C2, and C3. C1 tumors were 'immune-cold,' with low immune infiltration, poor prognosis, and abundant immunosuppressive M2 macrophages. C3 tumors were 'immune-hot,' with high immune cell infiltration, active T cells, and the best response to ICI therapy. The most intriguing finding was the C2 subtype, which had high tumor mutational burden (TMB) but a unique defect in antigen presentation, including 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 for each cluster: C1 showed enrichment in sphingolipid metabolism, while C2 exhibited a strong reliance on serine metabolism. The enzyme PSAT1 emerged as a key metabolic regulator in C2, and 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 stated. 'By building a comprehensive score, we've moved beyond the simple hot and cold tumor paradigm to identify distinct, actionable defects.' This classification could serve as a robust biomarker to stratify patients, identifying those likely to respond to ICIs and sparing others from unnecessary side effects. Moreover, it points to new combination strategies, such as targeting PSAT1 in C2 tumors to enhance antigen presentation or converting cold tumors to hot in C1. The study was supported by grants from the National Key Research and Development Project of China and the National Natural Science Foundation of China. The full study can be accessed at https://doi.org/10.20892/j.issn.2095-3941.2025.0611.
