Changes of liver metabolites following hepatectomy with ischemia reperfusion towards liver regeneration

Transcriptome sequencing and metabolome analysis reveal the metabolic reprogramming of partial hepatectomy and extended hepatectomy

Surgical resection remains a critical treatment option for many patients with primary and secondary hepatic neoplasms. Extended hepatectomy (eHx) may be required for some patients with large tumors, which may cause liver failure and death. Partial hepatectomy (pHx) and eHx mouse models were constructed, liver tissues were sampled at 18, 36, and 72 h posthepatectomy. Transcriptome and metabolome analyses were employed to explore the different potential mechanisms in regeneration and injury between pHx and eHx. The results showed that eHx was associated with more severe liver injury and lower survival rates than pHx. Transcriptomics data showed there were 1842, 2129, and 1277 differentially expressed genes (DEGs) in eHx and 962, 1305, and 732 DEGs in pHx at 18, 36, and 72 h posthepatectomy, respectively, compared with the those in the sham groups. Compared with pHx, the number of DEGs in the eHx group reached a maximum of 230 at 18 h after surgery and decreased sequentially to 87 and 43 at 36 and 72 h. Metabolomics analysis identified a total of 1399 metabolites, and 48 significant differentially produced metabolites (DPMs) were screened between eHx and pHx. Combined analysis of DEGs and DPMs indicated that cholesterol metabolism and insulin resistance may be two important pathways for liver regeneration and mouse survival postextended hepatectomy. Our results showed the global influence of pHx and eHx on the transcriptome and metabolome in mouse liver, and revealed cholesterol metabolism and insulin resistance pathways might be involved in regeneration post-pHx and -eHx.

Normalization of lipid oxidation defects arising from hypoxia early posthepatectomy prevents liver failure in mouse

Surgical liver failure (SLF) develops when a marginal amount of hepatic mass is left after surgery, such as following excessive resection. SLF is the commonest cause of death due to liver surgery; however, its etiology remains obscure. Using mouse models of standard hepatectomy (sHx) (68%, resulting in full regeneration) or extended hepatectomy (eHx) (86%/91%, causing SLF), we explored the causes of early SLF related to portal hyperafflux. Assessing the levels of HIF2A with or without oxygenating agent inositol trispyrophosphate (ITPP) indicated hypoxia early after eHx. Subsequently, lipid oxidation (PPARA/PGC1α) was downregulated and associated with persisting steatosis. Mild oxidation with low-dose ITPP reduced the levels of HIF2A, restored downstream PPARA/PGC1α expression along with lipid oxidation activities (LOAs), and normalized steatosis and other metabolic or regenerative SLF deficiencies. Promotion of LOA with L-carnitine likewise normalized the SLF phenotype, and both ITPP and L-carnitine markedly raised survival in lethal SLF. In patients who underwent hepatectomy, pronounced increases in serum carnitine levels (reflecting LOA) were associated with better recovery. Lipid oxidation thus provides a link between the hyperafflux of O₂-poor portal blood, the metabolic/regenerative deficits, and the increased mortality typifying SLF. Stimulation of lipid oxidation-the prime regenerative energy source-particularly through L-carnitine may offer a safe and feasible way to reduce SLF risks in the clinic.

Essential amino acids as diagnostic biomarkers of hepatocellular carcinoma based on metabolic analysis

Metabolomics, defined as the comprehensive identification of all small metabolites in a biological sample, has the power to shed light on phenotypic changes associated with various diseases, including cancer. To discover potential metabolomic biomarkers of hepatocellular carcinoma (HCC), we investigated the metabolomes of tumor and non-tumor tissue in 20 patients with primary HCC using capillary electrophoresis-time-of-flight mass spectrometry. We also analyzed blood samples taken immediately before and 14 days after hepatectomy to identify associated changes in the serum metabolome. Marked changes were detected in the different quantity of 61 metabolites that could discriminate between HCC tumor and paired non-tumor tissue and additionally between HCC primary tumors and colorectal liver metastases. Among the 30 metabolites significantly upregulated in HCC tumors compared with non-tumor tissues, 10 were amino acids, and 7 were essential amino acids (leucine, valine, tryptophan, isoleucine, methionine, lysine, and phenylalanine). Similarly, the serum metabolomes of HCC patients before hepatectomy revealed a significant increase in 16 metabolites, including leucine, valine, and tryptophan. Our results reveal striking differences in the metabolomes of HCC tumor tissue compared with non-tumor tissue, and identify the essential amino acids leucine, valine, and tryptophan as potential metabolic biomarkers for HCC.

Angelica sinensis Polysaccharide and Astragalus membranaceus Polysaccharide Accelerate Liver Regeneration by Enhanced Glycolysis via Activation of JAK2/STAT3/HK2 Pathway

The promotion of liver regeneration is crucial to avoid liver failure after hepatectomy. Angelica sinensis polysaccharide (ASP) and Astragalus membranaceus polysaccharide (AMP) have been identified as being associated with hepatoprotective effects. However, their roles and specific mechanisms in liver regeneration remain to be elucidated. In the present study, it suggested that the respective use of ASP or AMP strikingly promoted hepatocyte proliferation in vitro with a wide range of concentrations (from 12.5 μg/mL to 3200 μg/mL), and a stronger promoting effect was observed in combined interventions. A significantly enhanced liver/body weight ratio (4.20%) on day 7 and reduced serum transaminase (ALT 243.53 IU/L and AST 423.74 IU/L) and total bilirubin (52.61 IU/L) levels on day 3 were achieved by means of ASP-AMP administration after partial hepatectomy in mice. Metabonomics showed that differential metabolites were enriched in glycolysis with high expression of beta-d-fructose 6-phosphate and lactate, followed by significantly strengthened lactate secretion in the supernatant (0.54) and serum (0.43) normalized to control. Upon ASP-AMP treatment, the knockdown of hexokinase 2 (HK2) or inhibited glycolysis caused by 2-deoxy-d-glucose decreased hepatocyte proliferation in vitro and in vivo. Furthermore, pathway analysis predicted the role of JAK2/STAT3 pathway in ASP-AMP-regulated liver regeneration, and phosphorylation of JAK2 and STAT3 was proven to be elevated in this promoting process. Finally, downregulated expression of HK2, an attenuated level of lactate secretion, and reduced hepatocyte proliferation were displayed when STAT3 was knocked out in vitro. Therefore, it can be concluded that ASP-AMP accelerated liver regeneration and exerted a hepatoprotective effect after hepatectomy, in which the JAK2/STAT3/HK2 pathway was actively involved in activating glycolysis.

Secretome of Stressed Peripheral Blood Mononuclear Cells Alters Transcriptome Signature in Heart, Liver, and Spleen after an Experimental Acute Myocardial Infarction: An In Silico Analysis

Simple Summary

Acute myocardial infarction is characterized by impaired coronary blood flow, which leads to cardiac ischemia and, ultimately, compromised heart function. Damage and cellular responses are not limited to the non-perfused area, but rather affect the entire heart, as well as distal organs, such as the liver and spleen. We found that the therapeutic secretome of stressed white blood cells improved short-term and long-term cardiac performance in a porcine infarction model. In order to unravel the molecular events governing secretome-mediated tissue regeneration, we performed transcriptional analyses of the non-perfused, transition, and perfused heart, as well as the liver and spleen 24 h after myocardial infarction. We observed a highly tissue-specific effect of the secretome and, except for the transition zone, a uniform downregulation of pro-inflammatory factors and pathways. Simultaneously, the secretome strongly promoted the expression of genes that are essential for heart function in the non-perfused area. In the liver and spleen, different metabolic processes were induced. Together, our data suggest several plausible mechanisms by which the secretome improves heart function after cardiac ischemia. Deepening our understanding of the molecular processes identified here might uncover further pharmacologic strategies aiming at delimiting adverse cardiac remodeling and sequelae after myocardial infarction.

Abstract

Acute myocardial infarction (AMI) is a result of cardiac non-perfusion and leads to cardiomyocyte necrosis, inflammation, and compromised cardiac performance. Here, we showed that the secretome of γ-irradiated peripheral blood mononuclear cells (PBMCsec) improved heart function in a porcine AMI model and displayed beneficial long- and short-term effects. As an AMI is known to strongly affect gene regulation of the ischemia non-affected heart muscle and distal organs, we employed a transcriptomics approach to further study the immediate molecular events orchestrated using the PBMCsec in myocardium, liver, and spleen 24 h post ischemia. In the infarcted area, the PBMCsec mainly induced genes that were essential for cardiomyocyte function and simultaneously downregulated pro-inflammatory genes. Interestingly, genes associated with pro-inflammatory processes were activated in the transition zone, while being downregulated in the remote zone. In the liver, we observed a pronounced inhibition of immune responses using the PBMCsec, while genes involved in urea and tricarboxylic cycles were induced. The spleen displayed elevated lipid metabolism and reduced immunological processes. Together, our study suggested several types of pharmacodynamics by which the PBMCsec conferred immediate cardioprotection. Furthermore, our data supported the assumption that an AMI significantly affects distal organs, suggesting that a holistic treatment of an AMI, as achieved by PBMCsec, might be highly beneficial.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

Metabolic hallmarks of liver regeneration

Despite the crucial role of cell metabolism in biological processes, particularly cell division, metabolic aspects of liver regeneration are not well defined. Better understanding of the metabolic activity governing division of liver cells will provide powerful insights into mechanisms of physiological and pathological liver regeneration. Recent studies have provided evidence that metabolic response to liver failure might be a proximal signal to initiate cell proliferation in liver regeneration. In this review, we highlight how lipids, carbohydrates, and proteins dynamically change and orchestrate liver regeneration. In addition, we discuss translational studies in which metabolic intervention has been used to treat chronic liver diseases (CLDs).

Explorative study of serum biomarkers of liver failure after liver resection

Conventional biochemical markers have limited usefulness in the prediction of early liver dysfunction. We, therefore, tried to find more useful liver failure biomarkers after liver resection that are highly sensitive to internal and external challenges in the biological system with a focus on liver metabolites. Twenty pigs were divided into the following 3 groups: sham operation group (n = 6), 70% hepatectomy group (n = 7) as a safety margin of resection model, and 90% hepatectomy group (n = 7) as a liver failure model. Blood sampling was performed preoperatively and at 1, 6, 14, 30, 38, and 48 hours after surgery, and 129 primary metabolites were profiled. Orthogonal projection to latent structures-discriminant analysis revealed that, unlike in the 70% hepatectomy and sham operation groups, central carbon metabolism was the most significant factor in the 90% hepatectomy group. Binary logistic regression analysis was used to develop a predictive model for mortality risk following hepatectomy. The recommended variables were malic acid, methionine, tryptophan, glucose, and γ-aminobutyric acid. Area under the curve of the linear combination of five metabolites was 0.993 (95% confidence interval: 0.927–1.000, sensitivity: 100.0, specificity: 94.87). We proposed robust biomarker panels that can accurately predict mortality risk associated with hepatectomy.