Exploration of prognosis and immunometabolism landscapes in ER+ breast cancer based on a novel lipid metabolism-related signature - Shen, Lesang; Huang, Huanhuan; Li, Jiaxin; Chen, Wuzhen; Yao, Yao; Hu, Jianming; Zhou, Jun; Huang, Fengbo; Ni, Chao (Frontiers in Immunology, 2023)
Lipid metabolic reprogramming is gaining attention as a hallmark of cancer and is closely associated with oxidative stress. Recently, mounting evidence has indicated that the malignant behavior of breast cancer (BC) is closely related to lipid metabolism. Here, we focus on the estrogen receptor-positive (ER+) subtype, the most common subgroup of BC, and explore immunometabolic landscapes and the prognostic significance of lipid metabolism-related genes (LMRGs). First, two LMRG molecular patterns were identified through consensus clustering, and they were found to be associated with distinct prognoses and immune cell infiltration patterns. Next, a prognostic signature based on nine survival-related LMRGs was established by least absolute shrinkage and selection operator (LASSO) analysis using samples from The Cancer Genome Atlas (TCGA) database and validated using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database and two external cohorts. The signature was confirmed to be an independent prognostic factor, and a nomogram incorporating the signature, age and T stage was established (area under the curve (AUC) of 5-year overall survival: 0.778). Pathway enrichment analysis revealed differences in immune activities, lipid biosynthesis and drug metabolism between groups with low- and high-risk scores. Further exploration identified differences in immune microenvironment profiles, immune checkpoint expression patterns, and immunotherapy and chemotherapy sensitivities between the two groups. Finally, arachidonate 15-lipoxygenase (ALOX15) was selected as the most prominent differentially expressed gene between the two groups. Its expression was positively related to tumor size, tumor stage and degree of vascular invasion in our cohort (n = 149). In conclusion, we developed a lipid metabolism-based signature with value for prognosis prediction and immunotherapy or chemotherapy guidance for ER+ BC.