Reprogramming of Lipid Metabolism Mediates Crosstalk, Remodeling, and Intervention of Microenvironment Components in Breast Cancer

Abstract

Due to the unique characteristics of breast cancer initiation sites and significant alterations in tumor metabolism, breast cancer cells rely on lipid metabolic reprogramming to effectively regulate metabolic programs during the disease progression cascade. This adaptation enables them to meet the energy demands required for proliferation, invasion, metastasis, and responses to signaling molecules in the breast cancer microenvironment. In this review, we comprehensively examined the distinctive features of lipid metabolic reprogramming in breast cancer and elucidated the underlying mechanisms driving aberrant behavior of tumor cells. Additionally, we emphasize the potential role and adaptive changes in lipid metabolism within the breast cancer microenvironment, while summarizing recent preclinical studies. Overall, precise control over lipid metabolism rewiring and understanding of plasticity within the breast cancer microenvironment hold promising implications for developing targeted treatment strategies against this disease. Therefore, interventions targeting the lipid metabolism in breast cancer may facilitate innovative advancements in clinical applications.

A novel amino acid metabolism-related gene signature to predict the overall survival of esophageal squamous cell carcinoma patients

“…Despite advancements in diagnostic techniques and treatment modalities, the prognosis of ESCC patients remains poor, and patients have a 5-year survival rate ranging from 15% to 25% ( 1 ). Metabolic reprogramming, which is a crucial hallmark of malignancy, undergoes changes in metabolic patterns to meet energy demands during tumor progression, and heterogeneous metabolic subtypes can be observed in local invasive lesions ( 7 , 23 ). Several recent studies have shed light on the intricate connection between amino acid metabolism and EC, particularly the pivotal role of amino acid metabolism in tumor growth and progression ( 24 - 26 ).…”

Comprehensive untargeted serum metabolomics identifies biomarkers and metabolic pathways in breast cancer

“…The surge in breast cancer incidence worldwide over recent decades underscores the urgency for improved diagnostic methods to assess disease progression accurately. Advancements in analytical techniques have enabled a deeper exploration of tumor metabolism across various cancer types [22][23].…”

“…Hierarchical clustering was performed using the R platform to explore patterns within the data Statistical analysis to determine signi cant differences (using a nonparametric test) was conducted with IBM SPSS Statistics 22, considering metabolites with a p-value less than 0.05 as signi cant. OPLS-DA were conducted using SIMCA-P + 12.0 software [23]. Z-score analysis was employed to evaluate the dispersion of different metabolites.…”