New Breast Cancer Classification Predicts Immunotherapy Response

A groundbreaking study from Fudan University Shanghai Cancer Center and Shanghai Medical College introduces a novel classification system for breast cancer based on the cancer-immunity cycle (CIC). Published in Cancer Biology & Medicine, the research analyzed six key steps of the anti-tumor immune response to categorize patients into three distinct subtypes: immune-cold (C1), an intermediate subtype (C2) with a unique antigen presentation defect, and immune-hot (C3). This framework moves beyond the simple 'hot' vs 'cold' tumor paradigm, identifying specific immune evasion mechanisms and metabolic dependencies. For instance, C2 tumors, despite high mutational burden, show HLA loss and reliance on serine metabolism via the enzyme PSAT1. The CIC score offers a robust biomarker to predict immunotherapy response, potentially sparing non-responders from side effects while guiding targeted combination therapies.

Researchers developed a "CIC score" to measure activity across six CIC steps. The C1 cluster is immune-cold with poor prognosis and M2 macrophages, while C3 is immune-hot with active T cells and best ICI response. The unexpected C2 cluster, though immune-intermediate, has a defect in antigen presentation despite high tumor mutational burden, featuring HLA loss and an immunosuppressive microenvironment. Multi-omic analyses revealed metabolic vulnerabilities: C1 relies on sphingolipid metabolism, and C2 depends on serine metabolism, with PSAT1 identified as a key regulator. Knockdown of PSAT1 reduced expression of immunosuppressive molecules like PD-L1 and TGFB1, suggesting a new therapeutic target.

The findings have immediate clinical implications. The CIC score can stratify patients for immunotherapy, identifying those likely to benefit. For C1, strategies to convert cold tumors to hot are needed; for C2, enhancing antigen presentation via PSAT1 inhibition or overcoming HLA loss is key. This research, supported by national grants, paves the way for personalized breast cancer treatment, addressing why some patients fail to respond to current immunotherapies and offering new avenues to overcome resistance.