Background: Systemic factors can strongly affect how tumor cells behave, grow, and communicate with other cells as increasingly in breast cancer. Lipid metabolic reprogramming is one systemic way tumor cells undergo, however, the formation and dynamics of lipid associated with tumor immune microenvironment (TIME) still remain elusive. The sophisticated bidirectional crosstalk of tumor cells with cancer metabolism, gene expression, and TIME could have the potential to identify novel biomarkers for diagnosing, prognostic, and immunotherapy. This study aimed to construct a prognostic signature to detect the bi-crosstalk between lipid metabolic system and the TIME of breast cancer.
Methods: R software was selected to detect the expression of LRGs and perform the GO/KEGG analysis. Considering the clinical information and pathological features, a predictive nomogram was constructed to predict the survival probability and LASSO Cox regression analysis was performed to construct a prognostic gene signature. The TMB, MSI as well as immune infiltration analysis were performed, in addition, consensus cluster analysis of LRGs were also performed.
Results: These 16 lipid metabolic-related genes (LRGs) were mainly involved in the process of lipid metabolism and fatty acid binding in breast cancer by functional enrichment analysis. Prognosis analysis identified the prognostic value of FABP7 and NDUFAB1 in breast cancer patients. The prognostic gene signature constructed with FABP7 and NDUFAB1 was significantly related to immune infiltration and could predict the overall survival (OS) rate with above average correctness of breast cancer patients. The analysis of immune infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI) were significantly correlated with FABP7 and NDUFAB1. Consensus clusters analysis identified the up mRNAs were mostly related to the oncogenesis process while the down were associated with immune-related signaling pathways.
Conclusion: We performed a comprehensive analysis to evaluate the lipid metabolic system and identified a signature constructed by two prognostic genes for immunotherapies in breast cancer. Our results also revealed evidence of the vulnerabilities in the bidirectional interplay between the lipid metabolic system and the TIME which may contribute to deciphering the heterogeneity of the TIME in breast cancer.