Immunotherapy landscape analyses of necroptosis characteristics for breast cancer patients

Abstract Necroptosis plays a major role in breast cancer (BC) progression and metastasis. Besides, necroptosis also regulates inflammatory response and tumor microenvironment. Here, we aim to explore the predictive signature based on necroptosis-related genes (NRGs) for predicting the prognosis and response to therapies. Using Lasso multivariate cox analysis, we firstly established the NRG signature based on TCGA database. A total of 6 NRGs (FASLG, IPMK, FLT3, SLC39A7, HSP90AA1, and LEF1), which were associated with the prognosis of BC patients, were selected to establish our signature. Next, CIBERSORT algorithm was utilized to evaluate immune cell infiltration levels. We compare the response to immunotherapy using IMvigor 210 database, and also compared immune indicators in two risk groups via multiple methods. The biological function of IPMK was explored via in vitro verification. Finally, our results indicated that the signature was an independent prognostic indicator for BC patients with better efficiency than other reported signatures. The immune cell infiltration levels were higher, and the response to immunotherapy and chemotherapy was better in the low-risk groups. Besides, other immunotherapy-related factors, including TMB, TIDE, and expression of immune checkpoints were also increased in the low-risk group. Clinical sample validation showed that CD206 and IPMK in clinical samples were both up-regulated in the high-risk group. In vitro assay showed that IPMK promoted BC cell proliferation and migration, and also enhanced macrophage infiltration and M2 polarization. In summary, we successfully established the NRG signature, which could be used to evaluate BC prognosis and identify patients who will benefit from immunotherapy.