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Metabolic role of fatty acid binding protein 7 in mediating triple-negative breast cancer cell death via PPAR-? signaling.

ABSTRACT: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, partly due to the lack of targeted therapy available. Cancer cells heavily reprogram their metabolism and acquire metabolic plasticity to satisfy the high-energy demand due to uncontrolled proliferation. Accumulating evidence shows that deregulated lipid metabolism affects cancer cell survival, and therefore we sought to understand the function of fatty acid binding protein 7 (FABP7), which is expressed predominantly in TNBC tissues. As FABP7 was not detected in the TNBC cell lines tested, Hs578T and MDA-MB-231 cells were transduced with lentiviral particles containing either FABP7 open reading frame or red fluorescent protein. During serum starvation, when lipids were significantly reduced, FABP7 decreased the viability of Hs578T, but not of MDA-MB-231, cells. FABP7-overexpressing Hs578T (Hs-FABP7) cells failed to efficiently utilize other available bioenergetic substrates such as glucose to sustain ATP production, which led to S/G2 phase arrest and cell death. We further showed that this metabolic phenotype was mediated by PPAR-? signaling, despite the lack of fatty acids in culture media, as Hs-FABP7 cells attempted to survive. This study provides imperative evidence of metabolic vulnerabilities driven by FABP7 via PPAR-? signaling.

SUBMITTER: Kwong SC

PROVIDER: S-EPMC6824484 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Metabolic role of fatty acid binding protein 7 in mediating triple-negative breast cancer cell death via PPAR-α signaling.

Kwong Soke Chee SC Jamil Amira Hajirah Abd AHA Rhodes Anthony A Taib Nur Aishah NA Chung Ivy I

Journal of lipid research 20190904 11

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, partly due to the lack of targeted therapy available. Cancer cells heavily reprogram their metabolism and acquire metabolic plasticity to satisfy the high-energy demand due to uncontrolled proliferation. Accumulating evidence shows that deregulated lipid metabolism affects cancer cell survival, and therefore we sought to understand the function of fatty acid binding protein 7 (FABP7), which is expressed predomi ...[more]

PMID: 31484694

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Project description:Targeting a tumor's metabolic dependencies is a clinically actionable therapeutic approach; however, identifying subtypes of tumors likely to respond remains difficult. The use of lipids as a nutrient source is of particular importance, especially in breast cancer. Imaging techniques offer the opportunity to quantify nutrient use in preclinical tumor models to guide development of new drugs that restrict uptake or utilization of these nutrients. We describe a fast and dynamic approach to image fatty acid uptake in vivo and demonstrate its relevance to study both tumor metabolic reprogramming directly, as well as the effectiveness of drugs targeting lipid metabolism. Specifically, we developed a quantitative optical approach to spatially and longitudinally map the kinetics of long-chain fatty acid uptake in in vivo murine models of breast cancer using a fluorescently labeled palmitate molecule, Bodipy FL c16. We chose intra-vital microscopy of mammary tumor windows to validate our approach in two orthotopic breast cancer models: a MYC-overexpressing, transgenic, triple-negative breast cancer (TNBC) model and a murine model of the 4T1 family. Following injection, Bodipy FL c16 fluorescence increased and reached its maximum after approximately 30 min, with the signal remaining stable during the 30-80 min post-injection period. We used the fluorescence at 60 min (Bodipy60), the mid-point in the plateau region, as a summary parameter to quantify Bodipy FL c16 fluorescence in subsequent experiments. Using our imaging platform, we observed a two- to four-fold decrease in fatty acid uptake in response to the downregulation of the MYC oncogene, consistent with findings from in vitro metabolic assays. In contrast, our imaging studies report an increase in fatty acid uptake with tumor aggressiveness (6NR, 4T07, and 4T1), and uptake was significantly decreased after treatment with a fatty acid transport inhibitor, perphenazine, in both normal mammary pads and in the most aggressive 4T1 tumor model. Our approach fills an important gap between in vitro assays providing rich metabolic information at static time points and imaging approaches visualizing metabolism in whole organs at a reduced resolution.

Project description:BackgroundThe high heterogeneity of triple negative breast cancer (TNBC) is the main clinical challenge for individualized therapy. Considering that fatty acid metabolism (FAM) plays an indispensable role in tumorigenesis and development of TNBC, we proposed a novel FAM-based classification to characterize the tumor microenvironment immune profiles and heterogeneous for TNBC.MethodsWeighted gene correlation network analysis (WGCNA) was performed to identify FAM-related genes from 221 TNBC samples in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. Then, non-negative matrix factorization (NMF) clustering analysis was applied to determine FAM clusters based on the prognostic FAM-related genes, which chosen from the univariate/multivariate Cox regression model and the least absolute shrinkage and selection operator (LASSO) regression algorithm. Then, a FAM scoring scheme was constructed to further quantify FAM features of individual TNBC patient based on the prognostic differentially expressed genes (DEGs) between different FAM clusters. Systematically analyses were performed to evaluate the correlation between the FAM scoring system (FS) with survival outcomes, genomic characteristics, tumor microenvironment (TME) features and immunotherapeutic response for TNBC, which were further validated in the Cancer Genome Atlas (TCGA) and GSE58812 datasets. Moreover, the expression level and clinical significancy of the selected FS gene signatures were further validated in our cohort.Results1860 FAM-genes were screened out using WGCNA. Three distinct FAM clusters were determined by NMF clustering analysis, which allowed to distinguish different groups of patients with distinct clinical outcomes and tumor microenvironment (TME) features. Then, prognostic gene signatures based on the DEGs between different FAM clusters were identified using univariate Cox regression analysis and Lasso regression algorithm. A FAM scoring scheme was constructed, which could divide TNBC patients into high and low-FS subgroups. Low FS subgroup, characterized by better prognosis and abundance with effective immune infiltration. While patients with higher FS were featured with poorer survival and lack of effective immune infiltration. In addition, two independent immunotherapy cohorts (Imvigor210 and GSE78220) confirmed that patients with lower FS demonstrated significant therapeutic advantages from anti-PD-1/PD-L1 immunotherapy and durable clinical benefits. Further analyses in our cohort found that the differential expression of CXCL13, FBP1 and PLCL2 were significantly associated with clinical outcomes of TNBC samples.ConclusionsThis study revealed FAM plays an indispensable role in formation of TNBC heterogeneity and TME diversity. The novel FAM-based classification could provide a promising prognostic predictor and guide more effective immunotherapy strategies for TNBC.

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Dataset Information

Metabolic role of fatty acid binding protein 7 in mediating triple-negative breast cancer cell death via PPAR-? signaling.

Publications

Metabolic role of fatty acid binding protein 7 in mediating triple-negative breast cancer cell death via PPAR-α signaling.

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