Role of AMPK in Atrial Metabolic Homeostasis and Substrate Preference.

Atrial fibrillation is the most common clinical arrhythmia and may be due in part to metabolic stress. Atrial specific deletion of the master metabolic sensor, AMP-activated protein kinase (AMPK), induces atrial remodeling culminating in atrial fibrillation in mice, implicating AMPK signaling in the maintenance of atrial electrical and structural homeostasis. However, atrial substrate preference for mitochondrial oxidation and the role of AMPK in regulating atrial metabolism are unknown. Here, using LC-MS/MS methodology combined with infusions of [ 13 C 6 ]glucose and [ 13 C 4 ]ß-hydroxybutyrate in conscious mice, we demonstrate that conditional deletion of atrial AMPK catalytic subunits shifts mitochondrial atrial metabolism away from fatty acid oxidation and towards pyruvate oxidation. LC-MS/MS-based quantification of acyl-CoAs demonstrated decreased atrial tissue content of long-chain fatty acyl-CoAs. Proteomic analysis revealed a broad downregulation of proteins responsible for fatty acid uptake (LPL, CD36, FABP3), acylation and oxidation. Atrial AMPK deletion reduced expression of atrial PGC1-α and downstream PGC1-α/PPARα/RXR regulated gene transcripts. In contrast, atrial [ 14 C]2-deoxyglucose uptake and GLUT1 expression increased with fasting in mice with AMPK deletion, while the expression of glycolytic enzymes exhibited heterogenous changes. Thus, these results highlight the crucial homeostatic role of AMPK in the atrium, with loss of atrial AMPK leading to downregulation of the PGC1-α/PPARα pathway and broad metabolic reprogramming with a loss of fatty acid oxidation, which may contribute to atrial remodeling and arrhythmia.

Mitochondrial network remodeling of the diabetic heart: implications to ischemia related cardiac dysfunction.

Mitochondria play a central role in cellular energy metabolism, and their dysfunction is increasingly recognized as a critical factor in the pathogenesis of diabetes-related cardiac pathophysiology, including vulnerability to ischemic events that culminate in myocardial infarction on the one hand and ventricular arrhythmias on the other. In diabetes, hyperglycemia and altered metabolic substrates lead to excessive production of reactive oxygen species (ROS) by mitochondria, initiating a cascade of oxidative stress that damages mitochondrial DNA, proteins, and lipids. This mitochondrial injury compromises the efficiency of oxidative phosphorylation, leading to impaired ATP production. The resulting energy deficit and oxidative damage contribute to functional abnormalities in cardiac cells, placing the heart at an increased risk of electromechanical dysfunction and irreversible cell death in response to ischemic insults. While cardiac mitochondria are often considered to be relatively autonomous entities in their capacity to produce energy and ROS, their highly dynamic nature within an elaborate network of closely-coupled organelles that occupies 30-40% of the cardiomyocyte volume is fundamental to their ability to exert intricate regulation over global cardiac function. In this article, we review evidence linking the dynamic properties of the mitochondrial network to overall cardiac function and its response to injury. We then highlight select studies linking mitochondrial ultrastructural alterations driven by changes in mitochondrial fission, fusion and mitophagy in promoting cardiac ischemic injury to the diabetic heart.

Downregulation of adipose LPL by PAR2 contributes to the development of hypertriglyceridemia.

Lipoprotein lipase (LPL) hydrolyzes circulating triglycerides (TGs), releasing fatty acids (FA) and promoting lipid storage in white adipose tissue (WAT). However, the mechanisms regulating adipose LPL and its relationship with the development of hypertriglyceridemia are largely unknown. WAT from obese humans exhibited high PAR2 expression, which was inversely correlated with the LPL gene. Decreased LPL expression was also inversely correlated with elevated plasma TG levels, suggesting that adipose PAR2 might regulate hypertriglyceridemia by downregulating LPL. In mice, aging and high palmitic acid diet (PD) increased PAR2 expression in WAT, which was associated with a high level of macrophage migration inhibitory factor (MIF). MIF downregulated LPL expression and activity in adipocytes by binding with CXCR2/4 receptors and inhibiting Akt phosphorylation. In a MIF overexpression model, high-circulating MIF levels suppressed adipose LPL, and this suppression was associated with increased plasma TGs but not FA. Following PD feeding, adipose LPL expression and activity were significantly reduced, and this reduction was reversed in Par2-/- mice. Recombinant MIF infusion restored high plasma MIF levels in Par2-/- mice, and the levels decreased LPL and attenuated adipocyte lipid storage, leading to hypertriglyceridemia. These data collectively suggest that downregulation of adipose LPL by PAR2/MIF may contribute to the development of hypertriglyceridemia.

Targeting white adipose tissue to combat insulin resistance.

Metabolic and endocrine dysfunction of white adipose tissue (WAT) is linked to inflammation, which has been considered a key mechanism of insulin resistance (IR). However, recent studies revealed non-inflammatory mechanisms of IR in WAT, which may trigger inflammation and could be developed as a novel strategy to counteract IR.

LDL receptor-related protein 5 selectively transports unesterified polyunsaturated fatty acids to intracellular compartments.

Polyunsaturated fatty acids (PUFAs), which cannot be synthesized by animals and must be supplied from the diet, have been strongly associated with human health. However, the mechanisms for their accretion remain poorly understood. Here, we show that LDL receptor-related protein 5 (LRP5), but not its homolog LRP6, selectively transports unesterified PUFAs into a number of cell types. The LDLa ligand-binding repeats of LRP5 directly bind to PUFAs and are required and sufficient for PUFA transport. In contrast to the known PUFA transporters Mfsd2a, CD36 and FATP2, LRP5 transports unesterified PUFAs via internalization to intracellular compartments including lysosomes, and n-3 PUFAs depend on this transport mechanism to inhibit mTORC1. This LRP5-mediated PUFA transport mechanism suppresses extracellular trap formation in neutrophils and protects mice from myocardial injury during ischemia-reperfusion. Thus, this study reveals a biologically important mechanism for unesterified PUFA transport to intracellular compartments.

Cancer drug sensitivity prediction from routine histology images.

Drug sensitivity prediction models can aid in personalising cancer therapy, biomarker discovery, and drug design. Such models require survival data from randomised controlled trials which can be time consuming and expensive. In this proof-of-concept study, we demonstrate for the first time that deep learning can link histological patterns in whole slide images (WSIs) of Haematoxylin & Eosin (H&E) stained breast cancer sections with drug sensitivities inferred from cell lines. We employ patient-wise drug sensitivities imputed from gene expression-based mapping of drug effects on cancer cell lines to train a deep learning model that predicts patients' sensitivity to multiple drugs from WSIs. We show that it is possible to use routine WSIs to predict the drug sensitivity profile of a cancer patient for a number of approved and experimental drugs. We also show that the proposed approach can identify cellular and histological patterns associated with drug sensitivity profiles of cancer patients.

Extracellular macrophage migration inhibitory factor (MIF) downregulates adipose hormone-sensitive lipase (HSL) and contributes to obesity.

Attenuation of adipose hormone sensitive lipase (HSL) may impair lipolysis and exacerbate obesity. We investigate the role of cytokine, macrophage migration inhibitory factor (MIF) in regulating adipose HSL and adipocyte hypertrophy. Extracellular MIF downregulates HSL in an autocrine fashion, by activating the AMPK/JNK signaling pathway upon binding to its membrane receptor, CD74. WT mice fed high fat diet (HFD), as well as mice overexpressing MIF, both had high circulating MIF levels and showed suppression of HSL during the development of obesity. Blocking the extracellular action of MIF by a neutralizing MIF antibody significantly reduced obesity in HFD mice. Interestingly, intracellular MIF binds with COP9 signalosome subunit 5 (Csn5) and JNK, which leads to an opposing effect to inhibit JNK phosphorylation. With global MIF deletion, adipocyte JNK phosphorylation increased, resulting in decreased HSL expression, suggesting that the loss of MIF's intracellular inhibitory action on JNK was dominant in Mif-/- mice. Adipose tissue from Mif-/- mice also exhibited higher Akt and lower PKA phosphorylation following HFD feeding compared with WT, which may contribute to the downregulation of HSL activation during more severe obesity. Both intracellular and extracellular MIF have opposing effects to regulate HSL, but extracellular actions predominate to downregulate HSL and exacerbate the development of obesity during HFD.

AI-Based Risk Score from Tumour-Infiltrating Lymphocyte Predicts Locoregional-Free Survival in Nasopharyngeal Carcinoma.

BACKGROUND: Locoregional recurrence of nasopharyngeal carcinoma (NPC) occurs in 10% to 50% of cases following primary treatment. However, the current main prognostic markers for NPC, both stage and plasma Epstein-Barr virus DNA, are not sensitive to locoregional recurrence. METHODS: We gathered 385 whole-slide images (WSIs) from haematoxylin and eosin (H&E)-stained NPC sections (n = 367 cases), which were collected from Sun Yat-sen University Cancer Centre. We developed a deep learning algorithm to detect tumour nuclei and lymphocyte nuclei in WSIs, followed by density-based clustering to quantify the tumour-infiltrating lymphocytes (TILs) into 12 scores. The Random Survival Forest model was then trained on the TILs to generate risk score. RESULTS: Based on Kaplan-Meier analysis, the proposed methods were able to stratify low- and high-risk NPC cases in a validation set of locoregional recurrence with a statically significant result (p < 0.001). This finding was also found in distant metastasis-free survival (p < 0.001), progression-free survival (p < 0.001), and regional recurrence-free survival (p < 0.05). Furthermore, in both univariate analysis (HR: 1.58, CI: 1.13-2.19, p < 0.05) and multivariate analysis (HR:1.59, CI: 1.11-2.28, p < 0.05), we also found that our methods demonstrated a strong prognostic value for locoregional recurrence. CONCLUSION: The proposed novel digital markers could potentially be utilised to assist treatment decisions in cases of NPC.

Cross-linking breast tumor transcriptomic states and tissue histology.

Identification of the gene expression state of a cancer patient from routine pathology imaging and characterization of its phenotypic effects have significant clinical and therapeutic implications. However, prediction of expression of individual genes from whole slide images (WSIs) is challenging due to co-dependent or correlated expression of multiple genes. Here, we use a purely data-driven approach to first identify groups of genes with co-dependent expression and then predict their status from WSIs using a bespoke graph neural network. These gene groups allow us to capture the gene expression state of a patient with a small number of binary variables that are biologically meaningful and carry histopathological insights for clinical and therapeutic use cases. Prediction of gene expression state based on these gene groups allows associating histological phenotypes (cellular composition, mitotic counts, grading, etc.) with underlying gene expression patterns and opens avenues for gaining biological insights from routine pathology imaging directly.