A study published in Cancer Biology & Medicine has introduced a novel framework to classify breast cancer based on the cancer-immunity cycle (CIC), offering a systematic approach to predict patient response to immune checkpoint inhibitors (ICIs) and identify new therapeutic targets. The research, conducted by scientists at Fudan University Shanghai Cancer Center and Shanghai Medical College, analyzed the activity of six key steps in the CIC to generate a "CIC score" for each patient, leading to the identification of three distinct subtypes.
The first subtype, C1, represents an "immune-cold" tumor with low immune infiltration, poor prognosis, and an abundance of immunosuppressive M2 macrophages. In contrast, the C3 subtype is "immune-hot," characterized by high immune cell infiltration, active T cells, and the best response to ICI therapy. The most surprising finding was the C2 subtype, an intermediate group with a unique defect in antigen presentation. Despite having a high tumor mutational burden (TMB), which typically indicates potential responsiveness to immunotherapy, C2 tumors exhibited frequent human leukocyte antigen (HLA) loss of heterozygosity and an immunosuppressive tumor microenvironment enriched with dysfunctional dendritic cells and regulatory T cells.
"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." The study also identified specific metabolic dependencies for each subtype. C1 tumors showed enrichment in sphingolipid metabolism, while C2 tumors demonstrated a strong reliance on serine metabolism. Notably, the enzyme PSAT1 was identified as a key metabolic regulator in C2, and its knockdown reduced the expression of immunosuppressive molecules like PD-L1 and TGFB1.
This classification system has immediate clinical implications. The CIC score could serve as a robust biomarker to stratify patients, identifying those likely to benefit from ICI therapy and sparing others from unnecessary side effects. Moreover, the discovery of distinct immune-evasion mechanisms provides a roadmap for developing novel combination therapies. For C1 tumors, strategies may focus on converting the "cold" microenvironment into a "hot" one, while for C2 tumors, enhancing antigen presentation by targeting PSAT1 or overcoming HLA loss could be key. The study, published with DOI 10.20892/j.issn.2095-3941.2025.0611, was supported by grants from the National Key Research and Development Project of China and the National Natural Science Foundation of China.
