New Classification System Decodes Breast Cancer Immunity, Paving Way for Personalized Immunotherapy

A new study published in Cancer Biology & Medicine has introduced a classification system for breast cancer based on the cancer-immunity cycle (CIC), offering a more comprehensive approach to predicting patient response to immunotherapy and identifying 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 CIC to categorize breast cancer into three distinct subtypes, each with unique immune evasion mechanisms.

The cancer-immunity cycle describes the step-by-step process of the anti-tumor immune response, from antigen release to T-cell killing of cancer cells. A defect at any step can halt the entire cycle, rendering immunotherapies like immune checkpoint inhibitors (ICIs) ineffective. While previous studies focused on individual steps, the new research introduces a "CIC score" that captures the efficiency of the entire cycle, providing a holistic assessment of a patient's immune status.

Using this score, the team identified three clusters: C1, an "immune-cold" tumor with low immune infiltration and poor prognosis; C3, an "immune-hot" tumor with high immune activity and best response to ICIs; and C2, an intermediate subtype with a unique defect in antigen presentation. Despite a 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 metabolic dependencies for each cluster. C1 showed enrichment in sphingolipid metabolism, while C2 exhibited a strong reliance on serine metabolism. Notably, the enzyme PSAT1 was identified as a key metabolic regulator in C2, and its knockdown reduced expression of immunosuppressive molecules like PD-L1 and TGFB1. This finding suggests that targeting PSAT1 could restore antigen presentation and improve immunotherapy outcomes.

"The CIC provides a powerful framework for understanding how tumors evade the immune system," the authors stated. "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 system not only predicts which patients will benefit from current immunotherapies but also points to specific combination strategies to overcome resistance.

The classification has immediate clinical implications, serving as a biomarker to stratify patients and guide treatment decisions. For C1 tumors, therapies might focus on converting the "cold" microenvironment into a "hot" one, while for C2 patients, enhancing antigen presentation through PSAT1 targeting or overcoming HLA loss could be key. The study was supported by the National Key Research and Development Project of China and the National Natural Science Foundation of China, with full details available at DOI 10.20892/j.issn.2095-3941.2025.0611.