Fatty acid transport proteins (FATPs) in cancer

Polysaccharide of sunflower (Helianthus annuus L.) stalk pith inhibits cancer proliferation and metastases via TNF-α pathway

The decoctions of sunflower (Helianthus annuus L. HAL) stalk pith have been used to treat advanced cancer, and polysaccharide of sunflower stalk pith (HSPP) was key ingredient of the decoctions. To forage specially structured HSPP with anti-tumor effects and to uncover its mechanisms of anticancer activity, syngeneic mouse model of lung carcinoma metastasis was established and the HSPP was found to contain long-chain fatty acid. Encouragingly, the mean survival of the polysaccharide group (47.3 ± 12.8 d) and its sub-fractions group HSPP-4 (50.7 ± 13.0 d) was significantly increased compared with control group (38.7 ± 12.7 d) or positive control group (41.8 ± 13.4 d), (n = 20, P < 0.01 vs. the control group or positive control group). Furthermore, the HSPP exerted inhibitory effects on the tumor cells' metastasis. Eventually, it is postulated that the polysaccharide could inhibit tumor proliferation and metastasis by reduction of TNF-α from the macrophage.

Fetal Hypoglycemia Induced by Placental SLC2A3-RNA Interference Alters Fetal Pancreas Development and Transcriptome at Mid-Gestation

Glucose, the primary energy substrate for fetal oxidative processes and growth, is transferred from maternal to fetal circulation down a concentration gradient by placental facilitative glucose transporters. In sheep, SLC2A1 and SLC2A3 are the primary transporters available in the placental epithelium, with SLC2A3 located on the maternal-facing apical trophoblast membrane and SLC2A1 located on the fetal-facing basolateral trophoblast membrane. We have previously reported that impaired placental SLC2A3 glucose transport resulted in smaller, hypoglycemic fetuses with reduced umbilical artery insulin and glucagon concentrations, in addition to diminished pancreas weights. These findings led us to subject RNA derived from SLC2A3-RNAi (RNA interference) and NTS-RNAi (non-targeting sequence) fetal pancreases to qPCR followed by transcriptomic analysis. We identified a total of 771 differentially expressed genes (DEGs). Upregulated pathways were associated with fat digestion and absorption, particularly fatty acid transport, lipid metabolism, and cholesterol biosynthesis, suggesting a potential switch in energetic substrates due to hypoglycemia. Pathways related to molecular transport and cell signaling in addition to pathways influencing growth and metabolism of the developing pancreas were also impacted. A few genes directly related to gluconeogenesis were also differentially expressed. Our results suggest that fetal hypoglycemia during the first half of gestation impacts fetal pancreas development and function that is not limited to β cell activity.

A metabolomics study on carcinogenesis of ground-glass nodules

Objective

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer.

Material and Methods

Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure.

Results

Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples.

Conclusion

Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.

Lipids as mediators of cancer progression and metastasis

Metastasis formation is a complex process, involving multiple crucial steps, which are controlled by different regulatory mechanisms. In this context, the contribution of cancer metabolism to the metastatic cascade is being increasingly recognized. This Review focuses on changes in lipid metabolism that contribute to metastasis formation in solid tumors. We discuss the molecular mechanisms by which lipids induce a pro-metastatic phenotype and explore the role of lipids in response to oxidative stress and as signaling molecules. Finally, we reflect on potential avenues to target lipid metabolism to improve the treatment of metastatic cancers.

AI-Based Homology Modelling of Fatty Acid Transport Protein 1 Using AlphaFold: Structural Elucidation and Molecular Dynamics Exploration

Fatty acid transport protein 1 (FATP1) is an integral transmembrane protein that is involved in facilitating the translocation of long-chain fatty acids (LCFA) across the plasma membrane, thereby orchestrating the importation of LCFA into the cell. FATP1 also functions as an acyl-CoA ligase, catalyzing the ATP-dependent formation of fatty acyl-CoA using LCFA and VLCFA (very-long-chain fatty acids) as substrates. It is expressed in various types of tissues and is involved in the regulation of crucial signalling pathways, thus playing a vital role in numerous physiological and pathological conditions. Structural insight about FATP1 is, thus, extremely important for understanding the mechanism of action of this protein and developing efficient treatments against its anomalous expression and dysregulation, which are often associated with pathological conditions such as breast cancer. As of now, there has been no prior prediction or evaluation of the 3D configuration of the human FATP1 protein, hindering a comprehensive understanding of the distinct functional roles of its individual domains. In our pursuit to unravel the structure of the most commonly expressed isoforms of FATP1, we employed the cutting-edge ALPHAFOLD 2 model for an initial prediction of the entire protein's structure. This prediction was complemented by molecular dynamics simulations, focusing on the most promising model. We predicted the structure of FATP1 in silico and thoroughly refined and validated it using coarse and molecular dynamics in the absence of the complete crystal structure. Their relative dynamics revealed the different properties of the characteristic FATP1.