Network analyses identify liver-specific targets for treating liver diseases

The multifaceted role of PCSK9 in cancer pathogenesis, tumor immunity, and immunotherapy

Proprotein convertase subtilisin/kexin type 9 (PCSK9), a well-known regulator of cholesterol metabolism and cardiovascular diseases, has recently garnered attention for its emerging involvement in cancer biology. The multifunctional nature of PCSK9 extends beyond lipid regulation and encompasses a wide range of cellular processes that can influence cancer progression. Studies have revealed that PCSK9 can modulate signaling pathways, such as PI3K/Akt, MAPK, and Wnt/β-catenin, thereby influencing cellular proliferation, survival, and angiogenesis. Additionally, the interplay between PCSK9 and cholesterol homeostasis may impact membrane dynamics and cellular migration, further influencing tumor aggressiveness. The central role of the immune system in monitoring and controlling cancer is increasingly recognized. Recent research has demonstrated the ability of PCSK9 to modulate immune responses through interactions with immune cells and components of the tumor microenvironment. This includes effects on dendritic cell maturation, T cell activation, and cytokine production, suggesting a role in shaping antitumor immune responses. Moreover, the potential influence of PCSK9 on immune checkpoints such as PD1/PD-L1 lends an additional layer of complexity to its immunomodulatory functions. The growing interest in cancer immunotherapy has prompted exploration into the potential of targeting PCSK9 for therapeutic benefits. Preclinical studies have demonstrated synergistic effects between PCSK9 inhibitors and established immunotherapies, offering a novel avenue for combination treatments. The strategic manipulation of PCSK9 to enhance tumor immunity and improve therapeutic outcomes presents an exciting area for further investigations. Understanding the mechanisms by which PCSK9 influences cancer biology and immunity holds promise for the development of novel immunotherapeutic approaches. This review aims to provide a comprehensive analysis of the intricate connections between PCSK9, cancer pathogenesis, tumor immunity, and the potential implications for immunotherapeutic interventions.

A promising therapy for fatty liver disease: PCSK9 inhibitors

BACKGROUND

Fatty liver disease (FLD) poses a significant global health concern worldwide, with its classification into nonalcoholic fatty liver disease (NAFLD) and alcoholic fatty liver disease (AFLD) contingent upon the presence or absence of chronic and excessive alcohol consumption. The absence of specific therapeutic interventions tailored to FLD at various stages of the disease renders its treatment exceptionally arduous. Despite the fact that FLD and hyperlipidemia are intimately associated, there is still debate over how lipid-lowering medications affect FLD. Proprotein Convertase Subtilisin/ Kexin type 9 (PCSK9) is a serine protease predominantly synthesized in the liver, which has a crucial impact on cholesterol homeostasis. Research has confirmed that PCSK9 inhibitors have prominent lipid-lowering properties and substantial clinical effectiveness, thereby justifying the need for additional exploration of their potential role in FLD.

PURPOSE

Through a comprehensive literature search, this review is to identify the relationship and related mechanisms between PCSK9, lipid metabolism and FLD. Additionally, it will assess the pharmacological mechanism and applicability of PCSK9 inhibitors (including naturally occurring PCSK9 inhibitors, such as conventional herbal medicines) for the treatment of FLD and serve as a guide for updating the treatment protocol for such conditions.

METHODS

A comprehensive literature search was conducted using several electronic databases, including Pubmed, Medline, Embase, CNKI, Wanfang database and ClinicalTrials.gov, from the inception of the database to 30 Jan 2024. Key words used in the literature search were "fatty liver", "hepatic steatosis", "PCSK9", "traditional Chinese medicine", "herb medicine", "botanical medicine", "clinical trial", "vivo", "vitro", linked with AND/OR. Most of the included studies were within five years.

RESULTS

PCSK9 participates in the regulation of circulating lipids via both LDLR dependent and independent pathways, and there is a potential association with de novo lipogenesis. Major clinical studies have demonstrated a positive correlation between circulating PCSK9 levels and the severity of NAFLD, with elevated levels of circulating PCSK9 observed in individuals exposed to chronic alcohol. Numerous studies have demonstrated the potential of PCSK9 inhibitors to ameliorate non-alcoholic steatohepatitis (NASH), potentially completely alleviate liver steatosis, and diminish liver impairment. In animal experiments, PCSK9 inhibitors have exhibited efficacy in alleviating alcoholic induced liver lipid accumulation and hepatitis. Traditional Chinese medicine such as berberine, curcumin, resveratrol, piceatannol, sauchinone, lupin, quercetin, salidroside, ginkgolide, tanshinone, lunasin, Capsella bursa-pastoris, gypenosides, and Morus alba leaves are the main natural PCS9 inhibitors. Excitingly, by inhibiting transcription, reducing secretion, direct targeting and other pathways, traditional Chinese medicine exert inhibitory effects on PCSK9, thereby exerting potential FLD therapeutic effects.

CONCLUSION

PCSK9 plays an important role in the development of FLD, and PCSK9 inhibitors have demonstrated beneficial effects on lipid regulation and FLD in both preclinical and clinical studies. In addition, some traditional Chinese medicines have improved the disease progression of FLD by inhibiting PCSK9 and anti-inflammatory and antioxidant effects. Consequently, the inhibition of PCSK9 appears to be a promising therapeutic strategy for FLD.

Design and synthesis of novel JNK inhibitors targeting liver pyruvate kinase for the treatment of non-alcoholic fatty liver disease and hepatocellular carcinoma

Non-alcoholic fatty liver disease (NAFLD) comprises a broad range of liver disease including hepatocellular carcinoma (HCC) with is no FDA-approved drug. Liver pyruvate kinase (PKL) is a major regulator of metabolic flux and ATP generation in liver presenting a potential target for the treatment of NAFLD. Based on our recent finding of JNK-5A's effectiveness in inhibiting PKLR expression through a drug repositioning pipeline, this study aims to improve its efficacy further. We synthesized a series of JNK-5A analogues with targeted modifications, guided by molecular docking studies. These compounds were evaluated for their activities on PKL expression, cell viability, triacylglyceride (TAG) levels, and the expressions of steatosis-related proteins in the human HepG2 cell line. Subsequently, the efficacy of these compounds was assessed in reducing TAG level and toxicity. Compounds 40 (SET-151) and 41 (SET-152) proved to be the most efficient in reducing TAG levels (11.51 ± 0.90 % and 10.77 ± 0.67 %) and demonstrated lower toxicity (61.60 ± 5.00 % and 43.87 ± 1.42 %) in HepG2 cells. Additionally, all synthesized compounds were evaluated for their anti-cancer properties revealing that compound 74 (SET-171) exhibited the highest toxicity in cell viability with IC50 values of 8.82 µM and 2.97 µM in HepG2 and Huh7 cell lines, respectively. To summarize, compounds 40 (SET-151) and 41 (SET-152) show potential for treating NAFLD, while compound 74 (SET-171) holds potential for HCC therapy.

System biology approaches for drug repurposing

Drug repurposing, or drug repositioning, refers to the identification of alternative therapeutic applications for established medications that go beyond their initial indications. This strategy has becoming increasingly popular since it has the potential to significantly reduce the overall costs of drug development by around $300 million. System biology methodologies have been employed to facilitate medication repurposing, encompassing computational techniques such as signature matching and network-based strategies. These techniques utilize pre-existing drug-related data types and databases to find prospective repurposed medications that have minimal or acceptable harmful effects on patients. The primary benefit of medication repurposing in comparison to drug development lies in the fact that approved pharmaceuticals have already undergone multiple phases of clinical studies, thereby possessing well-established safety and pharmacokinetic properties. Utilizing system biology methodologies in medication repurposing offers the capacity to expedite the discovery of viable candidates for drug repurposing and offer novel perspectives for structure-based drug design.

Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.

Remodeling of the human skeletal muscle proteome found after long-term endurance training but not after strength training

Exercise training has tremendous systemic tissue-specific health benefits, but the molecular adaptations to long-term exercise training are not completely understood. We investigated the skeletal muscle proteome of highly endurance-trained, strength-trained, and untrained individuals and performed exercise- and sex-specific analyses. Of the 6,000+ proteins identified, >650 were differentially expressed in endurance-trained individuals compared with controls. Strikingly, 92% of the shared proteins with higher expression in both the male and female endurance groups were known mitochondrial. In contrast to the findings in endurance-trained individuals, minimal differences were found in strength-trained individuals and between females and males. Lastly, a co-expression network and comparative literature analysis revealed key proteins and pathways related to the health benefits of exercise, which were primarily related to differences in mitochondrial proteins. This network is available as an interactive database resource where investigators can correlate clinical data with global gene and protein expression data for hypothesis generation.

Multi-omics network analysis on samples from sequential biopsies reveals vital role of proliferation arrest for Macrosteatosis related graft failure in rats after liver transplantation

To investigate the molecular impact of graft MaS on post-transplant prognosis, based on multi-omics integrative analysis. Rats were fed by methionine-choline deficient diet (MCD) for MaS grafts. Samples were collected from grafts by sequential biopsies. Transcriptomic and metabolomic profilings were assayed. Post-transplant MaS status showed a close association with graft failure. Differentially expressed genes (DEGs) for in-vivo MaS were mainly enriched on pathways of cell cycle and DNA replication. Post-transplant MaS caused arrests of graft regeneration via inhibiting the E2F1 centered network, which was confirmed by an in vitro experiment. Data from metabolomics assays found insufficient serine/creatine which is located on one‑carbon metabolism was responsible for MaS-related GF. Pre-transplant MaS caused severe fibrosis in long-term survivors. DEGs for grafts from long-term survivors with pre-transplant MaS were mainly enriched in pathways of ECM-receptor interaction and focal adhesion. Transcriptional regulatory network analysis confirmed SOX9 as a key transcription factor (TF) for MaS-related fibrosis. Metabolomic assays found elevation of aromatic amino acid (AAA) was a major feature of fibrosis in long-term survivors. Graft MaS in vivo increased post-transplant GF via negative regulations on graft regeneration. Pre-transplant MaS induced severe fibrosis in long-term survivors via activations on ECM-receptor interaction and AAA metabolism.

Characterization of an in vitro steatosis model simulating activated de novo lipogenesis in MAFLD patients

Activated de novo lipogenesis (DNL) is the critical pathway involved in the progression of metabolic-associated fatty liver disease (MAFLD). We present an in vitro steatosis model for MAFLD that induces steatosis through activated DNL. This model utilizes insulin and LXR receptor ligand T0901317, eliminating the need for fatty acid treatment. Significant increases in triglycerides (TAGs) and expression of DNL-related transcription factors were observed. Transcriptomic analysis revealed distinct gene expression profiles between the DNL and conventional oleic acid (OA)-induced steatosis model. DNL steatosis model exhibited elevated pathways related to glycolysis, cholesterol homeostasis, and bile acid metabolism, reflecting its clinical relevance to MAFLD. Moreover, C75 and JNK-IN-5A compounds effectively reduced TAG accumulation and steatosis-related protein expression in the DNL model, whereas they had no significant impact on TAG accumulation in the OA model. In conclusion, we introduce an ideal model for steatosis study, which could help in understanding the MAFLD mechanisms.

Identification and validation of PCSK9 as a prognostic and immune-related influencing factor in tumorigenesis: a pan-cancer analysis

Introduction

Proprotein convertase subtilisin/kexin-9 (PCSK9) has been primarily studied in the cardiovascular field however, its role in cancer pathophysiology remains incompletely defined. Recently, a pivotal role for PCSK9 in cancer immunotherapy was proposed based on the finding that PCSK9 inhibition was associated with enhancing the antigen presentation efficacy of target programmed cell death-1 (PD-1). Herein, we provide results of a comprehensive pan-cancer analysis of PCSK9 that assessed its prognostic and immunological functions in cancer.

Methods

Using a variety of available online cancer-related databases including TIMER, cBioPortal, and GEPIA, we identified the abnormal expression of PCSK9 and its potential clinical associations in diverse cancer types including liver, brain and lung. We also validated its role in progression-free survival (PFS) and immune infiltration in neuroblastoma.

Results

Overall, the pan-cancer survival analysis revealed an association between dysregulated PCSK9 and poor clinical outcomes in various cancer types. Specifically, PCSK9 was extensively genetically altered across most cancer types and was consistently found in different tumor types and substages when compared with adjacent normal tissues. Thus, aberrant DNA methylation may be responsible for PCSK9 expression in many cancer types. Focusing on liver hepatocellular carcinoma (LIHC), we found that PCSK9 expression correlated with clinicopathological characteristics following stratified prognostic analyses. PCSK9 expression was significantly associated with immune infiltrate since specific markers of CD8+ T cells, macrophage polarization, and exhausted T cells exhibited different PCSK9-related immune infiltration patterns in LIHC and lung squamous cell carcinoma. In addition, PCSK9 was connected with resistance of drugs such as erlotinib and docetaxel. Finally, we validated PCSK9 expression in clinical neuroblastoma samples and concluded that PCSK9 appeared to correlate with a poor PFS and natural killer cell infiltration in neuroblastoma patients.

Conclusion

PCSK9 could serve as a robust prognostic pan-cancer biomarker given its correlation with immune infiltrates in different cancer types, thus potentially highlighting a new direction for targeted clinical therapy of cancers.

Data-driven transcriptomics analysis identifies PCSK9 as a novel key regulator in liver aging

The liver, as a crucial metabolic organ, undergoes significant pathological changes during the aging process, which can have a profound impact on overall health. To gain a comprehensive understanding of these alterations, we employed data-driven approaches, along with biochemical methods, histology, and immunohistochemistry techniques, to systematically investigate the effects of aging on the liver. Our study utilized a well-established rat aging model provided by the National Institute of Aging. Systems biology approaches were used to analyze genome-wide transcriptomics data from liver samples obtained from young (4-5 months old) and aging (20-21 months old) Fischer 344 rats. Our findings revealed pathological changes occurring in various essential biological processes in aging livers. These included mitochondrial dysfunction, increased oxidative/nitrative stress, decreased NAD + content, impaired amino acid and protein synthesis, heightened inflammation, disrupted lipid metabolism, enhanced apoptosis, senescence, and fibrosis. These results were validated using independent datasets from both human and rat aging studies. Furthermore, by employing co-expression network analysis, we identified novel driver genes responsible for liver aging, confirmed our findings in human aging subjects, and pointed out the cellular localization of the driver genes using single-cell RNA-sequencing human data. Our study led to the discovery and validation of a liver-specific gene, proprotein convertase subtilisin/kexin type 9 (PCSK9), as a potential therapeutic target for mitigating the pathological processes associated with aging in the liver. This finding envisions new possibilities for developing interventions aimed to improve liver health during the aging process.

Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine

Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.

An Integrative Multiomics Framework for Identification of Therapeutic Targets in Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a heterogeneous disease with a poor prognosis. Therefore, identifying additional therapeutic modalities is required to improve outcome. However, the lack of biomarkers of disease progression hampers the preclinical to clinical translational process. Here, this work assesses and identifies progressive alterations in pulmonary function, transcriptomics, and metabolomics in the mouse lung at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, this work identifies two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. This work presents a multi-omics-based framework to establish a translational link between the bleomycin-induced PF model in mice and human idiopathic pulmonary fibrosis to identify druggable targets and test therapeutic candidates. This work also indicates peripheral cannabinoid receptor 1 (CB1 R) antagonism as a rational therapeutic target for clinical translation in PF. Mouse Lung Fibrosis Atlas can be accessed freely at https://niaaa.nih.gov/mouselungfibrosisatlas.

Exploration of Novel Urolithin C Derivatives as Non-Competitive Inhibitors of Liver Pyruvate Kinase

The inhibition of liver pyruvate kinase could be beneficial to halt or reverse non-alcoholic fatty liver disease (NAFLD), a progressive accumulation of fat in the liver that can lead eventually to cirrhosis. Recently, urolithin C has been reported as a new scaffold for the development of allosteric inhibitors of liver pyruvate kinase (PKL). In this work, a comprehensive structure-activity analysis of urolithin C was carried out. More than 50 analogues were synthesized and tested regarding the chemical features responsible for the desired activity. These data could pave the way to the development of more potent and selective PKL allosteric inhibitors.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

The endocannabinoid system promotes hepatocyte progenitor cell proliferation and maturation by modulating cellular energetics

The proliferation and differentiation of hepatic progenitor cells (HPCs) drive the homeostatic renewal of the liver under diverse conditions. Liver regeneration is associated with an increase in Axin2⁺Cnr1⁺ HPCs, along with a marked increase in the levels of the endocannabinoid anandamide (AEA). But the molecular mechanism linking AEA signaling to HPC proliferation and/or differentiation has not been explored. Here, we show that in vitro exposure of HPCs to AEA triggers both cell cycling and differentiation along with increased expression of Cnr1, Krt19, and Axin2. Mechanistically, we found that AEA promotes the nuclear localization of the transcription factor β-catenin, with subsequent induction of its downstream targets. Systemic analyses of cells after CRISPR-mediated knockout of the β-catenin-regulated transcriptome revealed that AEA modulates β-catenin-dependent cell cycling and differentiation, as well as interleukin pathways. Further, we found that AEA promotes OXPHOS in HPCs when amino acids and glucose are readily available as substrates, but AEA inhibits it when the cells rely primarily on fatty acid oxidation. Thus, the endocannabinoid system promotes hepatocyte renewal and maturation by stimulating the proliferation of Axin2⁺Cnr1⁺ HPCs via the β-catenin pathways while modulating the metabolic activity of their precursor cells.

Tuning liver pyruvate kinase activity up or down with a new class of allosteric modulators

The liver isoform of pyruvate kinase (PKL) has gained interest due to its potential capacity to regulate fatty acid synthesis involved in the progression of non-alcoholic fatty liver disease (NAFLD). Here we describe a novel series of PKL modulators that can either activate or inhibit the enzyme allosterically, from a cryptic site at the interface of two protomers in the tetrameric enzyme. Starting from urolithin D, we designed and synthesised 42 new compounds. The effect of these compounds on PKL enzymatic activity was assessed after incubation with cell lysates obtained from a liver cell line. Pronounced activation of PKL activity, up to 3.8-fold, was observed for several compounds at 10 μM, while other compounds were prominent PKL inhibitors reducing its activity to 81% at best. A structure-activity relationship identified linear-shaped sulfone-sulfonamides as activators and non-linear compounds as inhibitors. Crystal structures revealed the conformations of these modulators, which were used as a reference for designing new modulators.

Identification and Characterization of Metabolic Subtypes of Endometrial Cancer Using a Systems-Level Approach

Endometrial cancer (EC) is the most common gynecological cancer worldwide. Understanding metabolic adaptation and its heterogeneity in tumor tissues may provide new insights and help in cancer diagnosis, prognosis, and treatment. In this study, we investigated metabolic alterations of EC to understand the variations in metabolism within tumor samples. Integration of transcriptomics data of EC (RNA-Seq) and the human genome-scale metabolic network was performed to identify the metabolic subtypes of EC and uncover the underlying dysregulated metabolic pathways and reporter metabolites in each subtype. The relationship between metabolic subtypes and clinical variables was explored. Further, we correlated the metabolic changes occurring at the transcriptome level with the genomic alterations. Based on metabolic profile, EC patients were stratified into two subtypes (metabolic subtype-1 and subtype-2) that significantly correlated to patient survival, tumor stages, mutation, and copy number variations. We observed the co-activation of the pentose phosphate pathway, one-carbon metabolism, and genes involved in controlling estrogen levels in metabolic subtype-2, which is linked to poor survival. PNMT and ERBB2 are also upregulated in metabolic subtype-2 samples and present on the same chromosome locus 17q12, which is amplified. PTEN and TP53 mutations show mutually exclusive behavior between subtypes and display a difference in survival. This work identifies metabolic subtypes with distinct characteristics at the transcriptome and genome levels, highlighting the metabolic heterogeneity within EC.

Ellagic Acid and Its Metabolites as Potent and Selective Allosteric Inhibitors of Liver Pyruvate Kinase

Liver pyruvate kinase (PKL) has recently emerged as a new target for non-alcoholic fatty liver disease (NAFLD), and inhibitors of this enzyme could represent a new therapeutic option. However, this breakthrough is complicated by selectivity issues since pyruvate kinase exists in four different isoforms. In this work, we report that ellagic acid (EA) and its derivatives, present in numerous fruits and vegetables, can inhibit PKL potently and selectively. Several polyphenolic analogues of EA were synthesized and tested to identify the chemical features responsible for the desired activity. Molecular modelling studies suggested that this inhibition is related to the stabilization of the PKL inactive state. This unique inhibition mechanism could potentially herald the development of new therapeutics for NAFLD.

NAFLD: genetics and its clinical implications

Worldwide non-alcoholic fatty liver disease (NAFLD) is recognized as the most common type of liver disease and its burden increasing at an alarming rate. NAFLD entails steatosis, fibrosis, cirrhosis, and, finally, hepatocellular carcinoma (HCC). The substantial inter-patient variation during disease progression is the hallmark of individuals with NAFLD. The variability of NAFLD development and related complications among individuals is determined by genetic and environmental factors. Genome-wide association studies (GWAS) have discovered reproducible and robust associations between gene variants such as PNPLA3, TM6SF2, HSD17B13, MBOAT7, GCKR and NAFLD. Evidences have provided the new insights into the NAFLD biology and underlined potential pharmaceutical targets. Ideally, the candidate genes associated with the hereditability of NAFLD are mainly involved in assembly of lipid droplets, lipid remodeling, lipoprotein packing and secretion, redox status mitochondria, and de novo lipogenesis. In recent years, the ability to translate genetics into a clinical context has emerged substantially by combining genetic variants primarily associated with NAFLD into polygenic risk scores (PRS). These score in combination with metabolic factors could be utilized to identify the severe liver diseases in patients with the gene regulatory networks (GRNs). Hereby, we even have highlighted the current understanding related to the schedule therapeutic approach of an individual based on microbial colonization and dysbiosis reversal as a therapy for NAFLD. The premise of this review is to concentrate on the potential of genetic factors and their translation into the design of novel therapeutics, as well as their implications for future research into personalized medications using microbiota.

The role of PCSK9 in NAFLD/NASH and therapeutic implications of PCSK9 inhibition

INTRODUCTION

There are inconsistent findings regarding the effect of lipid-lowering agents on nonalcoholic fatty liver disease (NAFLD). Proprotein Convertase Subtilisin/Kexin type 9 (PCSK9) is an important player in cholesterol homeostasis and intracellular lipogenesis, and PCSK9 inhibitors (PCSK9-i) have been found to be efficient for pharmacological management of hyperlipidemia.

AREAS COVERED

Whether PCSK9 (itself) or PCSK9-i affects NAFLD is still disputed. To address this question, we review published preclinical and clinical studies providing evidence for the role of PCSK9 in and the effect of PCSK9-I on the development and pathogenesis of NAFLD.

EXPERT OPINION

The current evidence from a landscape of preclinical and clinical studies examining the role of PCSK9 in NAFLD shows controversial results. Preclinical studies indicate that PCSK9 associates with NAFLD and nonalcoholic steatohepatitis (NASH) progression in opposite directions. In humans, it has been concluded that the severity of hepatic steatosis affects the correlation between circulating PCSK9 and liver fat content in humans, with a possible impact of circulating PCSK9 in the early stages of NAFLD, but not in the late stages. However, data from clinical trials with PCSK9-i reassure to the safety of these agents, although real-life long-term evidence is needed.

Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains

Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger this asymmetry, an understanding of the comprehensive and synergistic effect of the antistress spatially related pathways is still lacking. Recent progress in the bioinformatics area has the potential to fill these gaps through the use of in silico studies, able to investigate biological functions and pathway overlaps, and to identify promising targets in plant responses. Presently, for the first time, a comprehensive network-based analysis of proteomic signatures was used to identify functions and pivotal genes involved in the coordinated signalling pathways and molecular activities that asymmetrically modulate the response of different bent poplar root sectors and sides. To accomplish this aim, 66 candidate proteins, differentially represented across the poplar bent root sides and sectors, were grouped according to their abundance profile patterns and mapped, together with their first neighbours, on a high-confidence set of interactions from STRING to compose specific cluster-related subnetworks (I-VI). Successively, all subnetworks were explored by a functional gene set enrichment analysis to identify enriched gene ontology terms. Subnetworks were then analysed to identify the genes that are strongly interconnected with other genes (hub gene) and, thus, those that have a pivotal role in the bent root asymmetric response. The analysis revealed novel information regarding the response coordination, communication, and potential signalling pathways asymmetrically activated along the main root axis, delegated mainly to Ca2+ (for new lateral root formation) and ROS (for gravitropic response and lignin accumulation) signatures. Furthermore, some of the data indicate that the concave side of the bent sector, where the mechanical forces are most intense, communicates to the other (neighbour and distant) sectors, inducing spatially related strategies to ensure water uptake and accompanying cell modification. This information could be critical for understanding how plants maintain and improve their structural integrity-whenever and wherever it is necessary-in natural mechanical stress conditions.

Genetic polymorphisms of PKLR gene and their associations with milk production traits in Chinese Holstein cows

Our previous work had confirmed that pyruvate kinase L/R (PKLR) gene was expressed differently in different lactation periods of dairy cattle, and participated in lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, suggesting that PKLR is a candidate gene to affect milk production traits in dairy cattle. Here, we verified whether this gene has significant genetic association with milk yield and composition traits in a Chinese Holstein cow population. In total, we identified 21 single nucleotide polymorphisms (SNPs) by resequencing the entire coding region and partial flanking region of PKLR gene, in which, two SNPs were located in 5′ promoter region, two in 5′ untranslated region (UTR), three in introns, five in exons, six in 3′ UTR and three in 3′ flanking region. The single marker association analysis displayed that all SNPs were significantly associated with milk yield, fat and protein yields or protein percentage (p ≤ 0.0497). The haplotype block containing all the SNPs, predicted by Haploview, had a significant association with fat yield and protein percentage (p ≤ 0.0145). Further, four SNPs in 5′ regulatory region and eight SNPs in UTR and exon regions were predicted to change the transcription factor binding sites (TFBSs) and mRNA secondary structure, respectively, thus affecting the expression of PKLR, leading to changes in milk production phenotypes, suggesting that these SNPs might be the potential functional mutations for milk production traits in dairy cattle. In conclusion, we demonstrated that PKLR had significant genetic effects on milk production traits, and the SNPs with significant genetic effects could be used as candidate genetic markers for genomic selection (GS) in dairy cattle.

Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver pathologies. However, no medical treatment has been approved for the treatment of NAFLD. In our previous study, we found that PKLR could be a potential target for treatment of NALFD. Here, we investigated the effect of PKLR in in vivo model and performed drug repositioning to identify a drug candidate for treatment of NAFLD.

METHODS

Tissue samples from liver, muscle, white adipose and heart were obtained from control and PKLR knockout mice fed with chow and high sucrose diets. Lipidomics as well as transcriptomics analyses were conducted using these tissue samples. In addition, a computational drug repositioning analysis was performed and drug candidates were identified. The drug candidates were both tested in in vitro and in vivo models to evaluate their toxicity and efficacy.

FINDINGS

The Pklr KO reversed the increased hepatic triglyceride level in mice fed with high sucrose diet and partly recovered the transcriptomic changes in the liver as well as in other three tissues. Both liver and white adipose tissues exhibited dysregulated circadian transcriptomic profiles, and these dysregulations were reversed by hepatic knockout of Pklr. In addition, 10 small molecule drug candidates were identified as potential inhibitor of PKLR using our drug repositioning pipeline, and two of them significantly inhibited both the PKLR expression and triglyceride level in in vitro model. Finally, the two selected small molecule drugs were evaluated in in vivo rat models and we found that these drugs attenuate the hepatic steatosis without side effect on other tissues.

INTERPRETATION

In conclusion, our study provided biological insights about the critical role of PKLR in NAFLD progression and proposed a treatment strategy for NAFLD patients, which has been validated in preclinical studies.

FUNDING

ScandiEdge Therapeutics and Knut and Alice Wallenberg Foundation.

A pipeline for the reconstruction and evaluation of context-specific human metabolic models at a large-scale

Constraint-based (CB) metabolic models provide a mathematical framework and scaffold for in silico cell metabolism analysis and manipulation. In the past decade, significant efforts have been done to model human metabolism, enabled by the increased availability of multi-omics datasets and curated genome-scale reconstructions, as well as the development of several algorithms for context-specific model (CSM) reconstruction. Although CSM reconstruction has revealed insights on the deregulated metabolism of several pathologies, the process of reconstructing representative models of human tissues still lacks benchmarks and appropriate integrated software frameworks, since many tools required for this process are still disperse across various software platforms, some of which are proprietary. In this work, we address this challenge by assembling a scalable CSM reconstruction pipeline capable of integrating transcriptomics data in CB models. We combined omics preprocessing methods inspired by previous efforts with in-house implementations of existing CSM algorithms and new model refinement and validation routines, all implemented in the Troppo Python-based open-source framework. The pipeline was validated with multi-omics datasets from the Cancer Cell Line Encyclopedia (CCLE), also including reference fluxomics measurements for the MCF7 cell line. We reconstructed over 6000 models based on the Human-GEM template model for 733 cell lines featured in the CCLE, using MCF7 models as reference to find the best parameter combinations. These reference models outperform earlier studies using the same template by comparing gene essentiality and fluxomics experiments. We also analysed the heterogeneity of breast cancer cell lines, identifying key changes in metabolism related to cancer aggressiveness. Despite the many challenges in CB modelling, we demonstrate using our pipeline that combining transcriptomics data in metabolic models can be used to investigate key metabolic shifts. Significant limitations were found on these models ability for reliable quantitative flux prediction, thus motivating further work in genome-wide phenotype prediction.

Genome-scale models of human metabolism are promising tools capable of contextualising large omics datasets within a framework that enables analysis and manipulation of metabolic phenotypes. Despite various successes in applying these methods to provide mechanistic hypotheses for deregulated metabolism in disease, there is no standardized workflow to extract these models using existing methods and the tools required to do so are mostly implemented using proprietary software. We have assembled a generic pipeline to extract and validate context-specific metabolic models using multi-omics datasets and implemented it using the troppo framework. We first validate our pipeline using MCF7 cell line models and assess their ability to predict lethal gene knockouts as well as flux activity using multi-omics data. We also demonstrate how this approach can be generalized for large-scale transcriptomics datasets and used to generate insights on the metabolic heterogeneity of cancer and relevant features for other data mining approaches. The pipeline is available as part of an open-source framework that is generic for a variety of applications.

Genome-scale metabolic modelling of the human gut microbiome reveals changes of the glyoxylate and dicarboxylate metabolism in metabolic disorders

The human gut microbiome has been associated with metabolic disorders including obesity, type 2 diabetes, and atherosclerosis. Understanding the contribution of microbiome metabolic changes is important for elucidating the role of gut bacteria in regulating metabolism. We used available metagenomics data from these metabolic disorders, together with genome-scale metabolic modeling of key bacteria in the individual and community-level to investigate the mechanistic role of the gut microbiome in metabolic diseases. Modeling predicted increased levels of glutamate consumption along with the production of ammonia, arginine, and proline in gut bacteria common across the disorders. Abundance profiles and network-dependent analysis identified the enrichment of tartrate dehydrogenase in the disorders. Moreover, independent plasma metabolite levels showed associations between metabolites including proline and tyrosine and an increased tartrate metabolism in healthy obese individuals. We, therefore, propose that an increased tartrate metabolism could be a significant mediator of the microbiome metabolic changes in metabolic disorders.

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Metagenomic analysis highlights key common bacterial species across metabolic diseases

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Metabolic models showed higher levels of acetate produced by disease enriched bacteria

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Reaction analysis revealed increases in the glyoxylate and dicarboxylate pathway

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Metabolomics and modeling analysis showed the potential role of tartrate metabolism

PharmOmics: A species- and tissue-specific drug signature database and gene-network-based drug repositioning tool

Drug development has been hampered by a high failure rate in clinical trials due to our incomplete understanding of drug functions across organs and species. Therefore, elucidating species- and tissue-specific drug functions can provide insights into therapeutic efficacy, potential adverse effects, and interspecies differences necessary for effective translational medicine. Here, we present PharmOmics, a drug knowledgebase and analytical tool that is hosted on an interactive web server. Using tissue- and species-specific transcriptome data from human, mouse, and rat curated from different databases, we implemented a gene-network-based approach for drug repositioning. We demonstrate the potential of PharmOmics to retrieve known therapeutic drugs and identify drugs with tissue toxicity using in silico performance assessment. We further validated predicted drugs for nonalcoholic fatty liver disease in mice. By combining tissue- and species-specific in vivo drug signatures with gene networks, PharmOmics serves as a complementary tool to support drug characterization and network-based medicine.

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Development of PharmOmics, a platform for drug repositioning and toxicity prediction

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Contains >18000 species/tissue-specific gene signatures for 941 drugs and chemicals

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Benchmarked and validated network-based drug repositioning and toxicity prediction

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PharmOmics is freely accessible via an online web server to facilitate user access

A Gene Co-Expression Network-Based Drug Repositioning Approach Identifies Candidates for Treatment of Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC) is the most common malignancy of liver cancer. However, treatment of HCC is still severely limited due to limitation of drug therapy. We aimed to screen more possible target genes and candidate drugs for HCC, exploring the possibility of drug treatments from systems biological perspective. We identified ten candidate target genes, which are hub genes in HCC co-expression networks, which also possess significant prognostic value in two independent HCC cohorts. The rationality of these target genes was well demonstrated through variety analyses of patient expression profiles. We then screened candidate drugs for target genes and finally identified withaferin-a and mitoxantrone as the candidate drug for HCC treatment. The drug effectiveness was validated in in vitro model and computational analysis, providing more evidence for our drug repositioning method and results.

Abstract

Hepatocellular carcinoma (HCC) is a malignant liver cancer that continues to increase deaths worldwide owing to limited therapies and treatments. Computational drug repurposing is a promising strategy to discover potential indications of existing drugs. In this study, we present a systematic drug repositioning method based on comprehensive integration of molecular signatures in liver cancer tissue and cell lines. First, we identify robust prognostic genes and two gene co-expression modules enriched in unfavorable prognostic genes based on two independent HCC cohorts, which showed great consistency in functional and network topology. Then, we screen 10 genes as potential target genes for HCC on the bias of network topology analysis in these two modules. Further, we perform a drug repositioning method by integrating the shRNA and drug perturbation of liver cancer cell lines and identifying potential drugs for every target gene. Finally, we evaluate the effects of the candidate drugs through an in vitro model and observe that two identified drugs inhibited the protein levels of their corresponding target genes and cell migration, also showing great binding affinity in protein docking analysis. Our study demonstrates the usefulness and efficiency of network-based drug repositioning approach to discover potential drugs for cancer treatment and precision medicine approach.

Transcriptomic analysis reveals a novel regulatory factor of ECHDC1 involved in lipid metabolism of non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is the highest incidence of chronic liver disease worldwide characterized by lipid accumulation in the liver. The full understanding of the lipogenesis of NAFLD is extreme importance. Here, whole-genome transcriptome analysis was performed on liver tissues of NAFLD patients and healthy controls to identify the differentially expressed genes and find new pathways and target genes related to the lipogenesis of NAFLD. Combined with the Gene Expression Omnibus (GEO) database, we found 86 overlapping genes, many of which are related to lipid metabolism of NAFLD. ECHDC1 is one of 86 overlapping genes, and its role in NAFLD has not been reported. The expression of ECHDC1 was significantly increased in liver tissue of patients with NAFLD than that of healthy controls, and oil Red O intensity was positively correlated with the expression levels of ECHDC1. Inhibition of ECHDC1 expression in HepG2 cells by RNAi significantly reduced intracellular lipid droplet number in vitro. In summary, this study analyzed pathogenic factors related to NAFLD at the whole-genome level and demonstrated that ECHDC1 may be involved in the occurrence and development of NAFLD by regulating hepatic lipid metabolism.

System and network biology-based computational approaches for drug repositioning

Recent advances in computational biology have not only fastened the drug discovery process but have also proven to be a powerful tool for the search of existing molecules of therapeutic value for drug repurposing. The system biology-based drug repurposing approaches shorten the time and reduced the cost of the whole process when compared to de novo drug discovery. In the present pandemic situation, these computational approaches have emerged as a boon to tackle the COVID-19 associated morbidities and mortalities. In this chapter, we present the overview of system biology-based network system approaches which can be exploited for the drug repurposing of disease. Besides, we have included information on relevant repurposed drugs which are currently used for the treatment of COVID-19.

Combined Analysis of Expression Profiles in a Mouse Model and Patients Identified BHMT2 as a New Regulator of Lipid Metabolism in Metabolic-Associated Fatty Liver Disease

Metabolic associated fatty liver disease (MAFLD) is associated with obesity, type 2 diabetes mellitus, and other metabolic syndromes. Farnesoid X receptor (FXR, NR1H4) plays a prominent role in hepatic lipid metabolism. This study combined the expression of liver genes in FXR knockout (KO) mice and MAFLD patients to identify new pathogenic pathways for MAFLD based on genome-wide transcriptional profiling. In addition, the roles of new target genes in the MAFLD pathogenic pathway were also explored. Two groups of differentially expressed genes were obtained from FXR-KO mice and MAFLD patients by transcriptional analysis of liver tissue samples. The similarities and differences between the two groups of differentially expressed genes were analyzed to identify novel pathogenic pathways and target genes. After the integration analysis of differentially expressed genes, we identified 134 overlapping genes, many of which have been reported to play an important role in lipid metabolism. Our unique analysis method of comparing differential gene expression between FXR-KO mice and patients with MAFLD is useful to identify target genes and pathways that may be strongly implicated in the pathogenesis of MAFLD. The overlapping genes with high specificity were screened using the Gene Expression Omnibus (GEO) database. Through comparison and analysis with the GEO database, we determined that BHMT2 and PKLR could be highly correlated with MAFLD. Clinical data analysis and RNA interference testing in vitro confirmed that BHMT2 may a new regulator of lipid metabolism in MAFLD pathogenesis. These results may provide new ideas for understanding the pathogenesis of MAFLD and thus provide new targets for the treatment of MAFLD.

Defining NASH from a Multi-Omics Systems Biology Perspective

Non-alcoholic steatohepatitis (NASH) is a chronic liver disease affecting up to 6.5% of the general population. There is no simple definition of NASH, and the molecular mechanism underlying disease pathogenesis remains elusive. Studies applying single omics technologies have enabled a better understanding of the molecular profiles associated with steatosis and hepatic inflammation—the commonly accepted histologic features for diagnosing NASH, as well as the discovery of novel candidate biomarkers. Multi-omics analysis holds great potential to uncover new insights into disease mechanism through integrating multiple layers of molecular information. Despite the technical and computational challenges associated with such efforts, a few pioneering studies have successfully applied multi-omics technologies to investigate NASH. Here, we review the most recent technological developments in mass spectrometry (MS)-based proteomics, metabolomics, and lipidomics. We summarize multi-omics studies and emerging omics biomarkers in NASH and highlight the biological insights gained through these integrated analyses.

Integrative Network Analysis Revealed Genetic Impact of Pyruvate Kinase L/R on Hepatocyte Proliferation and Graft Survival after Liver Transplantation

Background

Pyruvate kinase L/R (PKLR) has been suggested to affect the proliferation of hepatocytes via regulation of the cell cycle and lipid metabolism. However, its impact on the global metabolome and its clinical implications remain unclear.

Aims

We aimed to clarify the genetic impact of PKLR on the metabolomic profiles of hepatoma cells and its potential effects on grafts for liver transplantation (LT).

Methods

Nontargeted and targeted metabolomic assays were performed in human hepatoma cells transfected with lentiviral vectors causing PKLR overexpression and silencing, respectively. We then constructed a molecular network based on integrative analysis of transcriptomic and metabolomic data. We also assessed the biological functions of PKLR in the global metabolome in LT grafts in patients via a weighted correlation network model.

Results

Multiomic analysis revealed that PKLR perturbations significantly affected the pyruvate, citrate, and glycerophospholipid metabolism pathways, as crucial steps in de novo lipogenesis (DNL). We also confirmed the importance of phosphatidylcholines (PC) and its derivative lyso-PC supply on improved survival of LT grafts in patients. Coexpression analysis revealed beneficial effects of PKLR overexpression on posttransplant prognosis by alleviating arachidonic acid metabolism of the grafts, independent of operational risk factors.

Conclusion

This systems-level analysis indicated that PKLR affected hepatoma cell viability via impacts on the whole process of DNL, from glycolysis to final PC synthesis. PKLR also improved prognosis after LT, possibly via its impact on the increased genesis of beneficial glycerophospholipids.

Next-Generation Genome-Scale Metabolic Modeling through Integration of Regulatory Mechanisms

Genome-scale metabolic models (GEMs) are powerful tools for understanding metabolism from a systems-level perspective. However, GEMs in their most basic form fail to account for cellular regulation. A diverse set of mechanisms regulate cellular metabolism, enabling organisms to respond to a wide range of conditions. This limitation of GEMs has prompted the development of new methods to integrate regulatory mechanisms, thereby enhancing the predictive capabilities and broadening the scope of GEMs. Here, we cover integrative models encompassing six types of regulatory mechanisms: transcriptional regulatory networks (TRNs), post-translational modifications (PTMs), epigenetics, protein-protein interactions and protein stability (PPIs/PS), allostery, and signaling networks. We discuss 22 integrative GEM modeling methods and how these have been used to simulate metabolic regulation during normal and pathological conditions. While these advances have been remarkable, there remains a need for comprehensive and widespread integration of regulatory constraints into GEMs. We conclude by discussing challenges in constructing GEMs with regulation and highlight areas that need to be addressed for the successful modeling of metabolic regulation. Next-generation integrative GEMs that incorporate multiple regulatory mechanisms and their crosstalk will be invaluable for discovering cell-type and disease-specific metabolic control mechanisms.

DNA and RNA Sequencing Recapitulated Aberrant Tumor Metabolism in Liver Cancer Cell Lines

AIM

Metabolic reprogramming has recently attracted extensive attention for understanding cancer development. We aimed to demonstrate a genomic and transcriptomic landscape of metabolic reprogramming underlying liver cancer cell lines.

METHODS

We investigated metabolic aberrant at both the transcriptome and genome levels using transcriptome and whole-exome sequencing data from 12 human liver cancer cell lines (hLCCLs) and one normal liver cell line.

RESULTS

Three subgroups of hLCCLs characterized from transcriptome sequencing data exhibit significantly different aberrations in various metabolic processes, including amino acid, lipid, energy, and carbohydrate metabolism. Furthermore, whole-exome sequencing revealed distinct mutational signatures among different subgroups of hLCCLs and identified a total of 19 known driver genes implicated in metabolism.

CONCLUSION

Our findings highlighted differential metabolic mechanisms in the development of liver cancer and provided a resource for further investigating its metabolic mechanisms.

Integrative proteomic network analyses support depot-specific roles for leucine rich repeat LGI family member 3 in adipose tissues

LGI family member 3 (LGI3) is a member of the LGI protein family. In our previous studies, LGI3 was determined to be expressed in adipose tissues, skin and the brain, where it served as a pleiotropic cytokine. The results indicated that LGI3 levels are increased in adipose tissues of obese individuals in comparison with control individuals and that LGI3 suppressed adipogenesis via its receptor, disintegrin and metalloproteinase domain-containing protein 23. Additionally, it was reported that LGI3 upregulates tumor necrosis factor-α and downregulated adiponectin and hypothesized that LGI3 may act as a proinflammatory adipokine involved in adipose tissue inflammation. In the present study, cytokine arrays were used to analyze cytokine levels in adipose tissues and plasma of LGI3-knockout mice and signaling protein arrays used to analyze the expression and phosphorylation of these proteins in LGI3-treated preadipocytes. The results suggested that expression levels of 129 gene products (24 cytokines and 105 signaling proteins) were altered in response to LGI3 deficiency or LGI3 treatment, respectively. Protein-protein interaction network analysis of LGI3-regulated gene products revealed that 94% of the gene products (21 cytokines and 100 signaling proteins) formed an interaction network cluster. Functional enrichment analysis for the LGI3-regulated gene products, including those from our previous studies, revealed an association with numerous biological processes, including inflammatory responses, cellular differentiation and development and metabolic regulation. Gene co-expression network analysis revealed that these LGI3-regulated gene products were involved in various biological processes in an overlapping and differential manner between subcutaneous and visceral adipose tissues. Notably, inflammatory responses were more strongly associated with the LGI3-regulated gene co-expression network in visceral adipose tissues than in subcutaneous adipose tissues. Analysis of expression quantitative trait loci identified four single nucleotide variants that affect expression of LGI3 in an adipose depot-specific manner. Taken together, the results suggested that LGI3 may serve depot-specific roles as an adipokine in adipose tissues.

Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction

Myocardial infarction (MI) promotes a range of systemic effects, many of which are unknown. Here, we investigated the alterations associated with MI progression in heart and other metabolically active tissues (liver, skeletal muscle, and adipose) in a mouse model of MI (induced by ligating the left ascending coronary artery) and sham-operated mice. We performed a genome-wide transcriptomic analysis on tissue samples obtained 6- and 24 hr post MI or sham operation. By generating tissue-specific biological networks, we observed: (1) dysregulation in multiple biological processes (including immune system, mitochondrial dysfunction, fatty-acid beta-oxidation, and RNA and protein processing) across multiple tissues post MI and (2) tissue-specific dysregulation in biological processes in liver and heart post MI. Finally, we validated our findings in two independent MI cohorts. Overall, our integrative analysis highlighted both common and specific biological responses to MI across a range of metabolically active tissues.

The human body is like a state-of-the-art car, where each part must work together with all the others. When a car breaks down, most of the time the problem is not isolated to only one part, as it is an interconnected system. Diseases in the human body can also have systemic effects, so it is important to study their implications throughout the body. Most studies of heart attacks focus on the direct impact on the heart and the cardiovascular system. Learning more about how heart attacks affect rest of the body may help scientists identify heart attacks early or create improved treatments.

Arif and Klevstig et al. show that heart attacks affect the metabolism throughout the body. In the experiments, mice underwent a procedure that mimics either a heart attack or a fake procedure. Then, Arif and Klevstig et al. compared the activity of genes in the heart, muscle, liver and fat tissue of the two groups of mice 6- and 24-hours after the operations. This revealed disruptions in the immune system, metabolism and the production of proteins. The experiments also showed that changes in the activity of four important genes are key to these changes. This suggests that this pattern of changes could be used as a way to identify heart attacks.

The experiments show that heart attacks have important effects throughout the body, especially on metabolism. These discoveries may help scientists learn more about the underlying biological processes and develop new treatments that prevent the harmful systemic effects of heart attacks and boost recovery.

Using genetic variants to evaluate the causal effect of cholesterol lowering on head and neck cancer risk: A Mendelian randomization study

Head and neck squamous cell carcinoma (HNSCC), which includes cancers of the oral cavity and oropharynx, is a cause of substantial global morbidity and mortality. Strategies to reduce disease burden include discovery of novel therapies and repurposing of existing drugs. Statins are commonly prescribed for lowering circulating cholesterol by inhibiting HMG-CoA reductase (HMGCR). Results from some observational studies suggest that statin use may reduce HNSCC risk. We appraised the relationship of genetically-proxied cholesterol-lowering drug targets and other circulating lipid traits with oral (OC) and oropharyngeal (OPC) cancer risk using two-sample Mendelian randomization (MR). For the primary analysis, germline genetic variants in HMGCR, NPC1L1, CETP, PCSK9 and LDLR were used to proxy the effect of low-density lipoprotein cholesterol (LDL-C) lowering therapies. In secondary analyses, variants were used to proxy circulating levels of other lipid traits in a genome-wide association study (GWAS) meta-analysis of 188,578 individuals. Both primary and secondary analyses aimed to estimate the downstream causal effect of cholesterol lowering therapies on OC and OPC risk. The second sample for MR was taken from a GWAS of 6,034 OC and OPC cases and 6,585 controls (GAME-ON). Analyses were replicated in UK Biobank, using 839 OC and OPC cases and 372,016 controls and the results of the GAME-ON and UK Biobank analyses combined in a fixed-effects meta-analysis. We found limited evidence of a causal effect of genetically-proxied LDL-C lowering using HMGCR, NPC1L1, CETP or other circulating lipid traits on either OC or OPC risk. Genetically-proxied PCSK9 inhibition equivalent to a 1 mmol/L (38.7 mg/dL) reduction in LDL-C was associated with an increased risk of OC and OPC combined (OR 1.8 95%CI 1.2, 2.8, p = 9.31 x10-05), with good concordance between GAME-ON and UK Biobank (I2 = 22%). Effects for PCSK9 appeared stronger in relation to OPC (OR 2.6 95%CI 1.4, 4.9) than OC (OR 1.4 95%CI 0.8, 2.4). LDLR variants, resulting in genetically-proxied reduction in LDL-C equivalent to a 1 mmol/L (38.7 mg/dL), reduced the risk of OC and OPC combined (OR 0.7, 95%CI 0.5, 1.0, p = 0.006). A series of pleiotropy-robust and outlier detection methods showed that pleiotropy did not bias our findings. We found limited evidence for a role of cholesterol-lowering in OC and OPC risk, suggesting previous observational results may have been confounded. There was some evidence that genetically-proxied inhibition of PCSK9 increased risk, while lipid-lowering variants in LDLR, reduced risk of combined OC and OPC. This result suggests that the mechanisms of action of PCSK9 on OC and OPC risk may be independent of its cholesterol lowering effects; however, this was not supported uniformly across all sensitivity analyses and further replication of this finding is required.

PCSK9 promotes tumor growth by inhibiting tumor cell apoptosis in hepatocellular carcinoma

Background

Proprotein convertase subtilisin/kexin type 9 (PCSK9), one of the key enzymes in the process of lipid transport, is involved in the disease progression of various types of tumors. This article is to study the role of PCSK9 in the progression of hepatocellular carcinoma (HCC).

Methods

Immunohistochemistry was used to assess the expression of PCSK9 in tumor specimens from 105 HCC patients who underwent curative resection. Western blotting and quantitative real-time PCR were used to test the protein and mRNA expression levels in HCC cell lines. Cell Counting Kit-8 (CCK-8) and clone formation assays were performed to evaluate the proliferation ability of different kinds of cells in vitro. Flow cytometry was used to analyze cell cycle distribution and apoptosis rate. A xenograft model was established to study the effect of PCSK9 on HCC growth in vivo. TUNEL and immunofluorescence assays were used to detect cell apoptosis.

Results

High expression of PCSK9 in tumor tissues was related to microvascular invasion (p = 0.036) and large tumor size (p = 0.001) in HCC patients. Overall survival and disease-free survival after surgery were poor in patients with high expression of PCSK9 (p = 0.035 and p = 0.007, respectively). In vivo and in vitro experiments showed that PCSK9 promoted the growth of HCC by inhibiting cell apoptosis. A mechanistic study revealed that PCSK9 increases FASN expression, thereby inhibiting apoptosis of HCC cells via the Bax/Bcl-2/Caspase9/Caspase3 pathway.

Conclusions

PCSK9 expression level in HCC is an indicator of poor prognosis for patients with HCC. FASN-mediated anti-apoptosis plays an important role in PCSK9-induced HCC progression.

An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease

Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights.

Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

As expenditure on drug development increases exponentially, the overall drug discovery process requires a sustainable revolution. Since artificial intelligence (AI) is leading the fourth industrial revolution, AI can be considered as a viable solution for unstable drug research and development. Generally, AI is applied to fields with sufficient data such as computer vision and natural language processing, but there are many efforts to revolutionize the existing drug discovery process by applying AI. This review provides a comprehensive, organized summary of the recent research trends in AI-guided drug discovery process including target identification, hit identification, ADMET prediction, lead optimization, and drug repositioning. The main data sources in each field are also summarized in this review. In addition, an in-depth analysis of the remaining challenges and limitations will be provided, and proposals for promising future directions in each of the aforementioned areas.

Proprotein Convertase Subtilisin/Kexin Type 9 Promotes Gastric Cancer Metastasis and Suppresses Apoptosis by Facilitating MAPK Signaling Pathway Through HSP70 Up-Regulation

Objective

To examine the effect of proprotein convertase subtilisin/kexin type 9 (PCSK9) on gastric cancer (GC) progression and prognosis, and to explore the underlying mechanism.

Methods

PCSK9 expression levels in human GC tissues were determined by quantitative real-time PCR, western blotting, and immunohistochemical assay. PCSK9 serum levels were detected by enzyme-linked immunosorbent assay. The relationships of PCSK9 and GC progression and survival were analyzed using the Chi-square test, Kaplan-Meier analysis, and Cox proportional hazards model. The effect of PCSK9 on cell invasion, migration, and apoptosis were determined in human GC cell lines and mouse xenograft model separately using PCSK9 knockdown and overexpression strategies. The PCSK9 interacting molecules, screened by co-immunoprecipitation combined with LC-MS/MS, were identified by immunofluorescence localization and western blotting. Additionally, the mitogen-activated protein kinase (MAPK) pathway was assessed by western blotting.

Results

PCSK9 mRNA and protein levels were significantly elevated in GC tissues compared with the paired normal tissues at our medical center (P < 0.001). Notably, the up-regulation of PCSK9 expression in GC tissues was related to tumor progression and poor survival. GC patients had higher serum levels of PCSK9 than the age-matched healthy controls (P < 0.001); PCSK9 promoted invasive and migratory ability and inhibited apoptosis in GC cells with no apparent affection in cell proliferation. The silencing of PCSK9 reversed these effects, suppressing tumor metastasis in vitro and in vivo. Furthermore, PCSK9 maintained these functions through up-regulating heat shock protein 70 (HSP70), ultimately facilitating the mitogen-activated protein kinase (MAPK) pathway.

Conclusion

Collectively, our data revealed that high PCSK9 expression levels in GC tissue were correlated with GC progression and poor prognosis and that PCSK9 could promote GC metastasis and suppress apoptosis by facilitating MAPK signaling pathway through HSP70 up-regulation. PCSK9 may represent a novel potential therapeutic target in GC.

Clear mortality gap caused by graft macrosteatosis in Chinese patients after cadaveric liver transplantation

BACKGROUND

Liver transplantation (LT) is one of the most effective surgical treatment for patients with end-stage liver disease. Steatosis is a contributor for inferior graft quality. But its impact and safety on transplantation was less assessed in Chinese patients.

METHODS

Graft steatosis and related information involved in recipients, donors and surgical procedures were retrospectively collected from 239 patients.

RESULTS

Donor macrosteatosis (MaS) caused about 2.14 and 2.80 folds of increment on patient and graft mortality. Dose-response analysis revealed prominent risk of grafts on overall patient/organ mortality when MaS content exceeded 10% (P<0.05). Noteworthy, deaths were only observed in MaS group when concurrent with extremely higher post-transplant alanine aminotransferase (ALT, 64%). However, microsteatosis (MiS) grafts didn't affect outcomes after LT. In a cohort of Chinese patients, MaS had comprehensive effects on post-transplant outcomes with relatively lower safety threshold at 10%. Mortality gap caused by MaS grafts was observed in patients with severer ischemia reperfusion injury.

CONCLUSIONS

Our study revealled the graft MaS affected the post-transplant outcomes in lower risk cutoff in Chinese patients. Further study is worthy to validate these results and investigate inner mechanism under the phenomenon.

Fat mass and obesity-associated protein regulates lipogenesis via m6 A modification in fatty acid synthase mRNA

As the first identified N⁶ -methyladenosine (m⁶ A) demethylase, fat mass and obesity-associated (FTO) protein is associated with fatty acid synthase (FASN) and lipid accumulation. However, little is known about the regulatory role of FTO in the expression of FASN and de novo lipogenesis through m⁶ A modification. In this study, we used FTO small interfering RNA to explore the effects of FTO knockdown on hepatic lipogenesis and its underlying epigenetic mechanism in HepG2 cells. We found that knockdown of FTO increased m⁶ A levels in total RNA and enhanced the expression of YTH domain family member 2 which serves as the m⁶ A-binding protein. The de novo lipogenic enzymes and intracellular lipid content were significantly decreased under FTO knockdown. Mechanistically, knockdown of FTO dramatically enhanced m⁶ A levels in FASN messenger RNA (mRNA), leading to the reduced expression of FASN mRNA through m⁶ A-mediated mRNA decay. The protein expressions of FASN along with acetyl CoA carboxylase and ATP-citrate lyase were further decreased, which inhibited de novo lipogenesis, thereby resulting in the deficiency of lipid accumulation in HepG2 cells and the induction of cellular apoptosis. The results reveal that FTO regulates hepatic lipogenesis via FTO-dependent m⁶ A demethylation in FASN mRNA and indicate the critical role of FTO-mediated lipid metabolism in the survival of HepG2 cells. This study provides novel insights into a unique RNA epigenetic mechanism by which FTO mediates hepatic lipid accumulation through m⁶ A modification and indicates that FTO could be a potential target for obesity-related diseases and cancer.

Effects of active farnesoid X receptor on GLUTag enteroendocrine L cells

Activated transcription factor (TF) farnesoid X receptor (FXR) represses glucagon-like peptide-1 (GLP-1) secretion in enteroendocrine L cells. This, in turn, reduces insulin secretion, which is triggered when β cells bind GLP-1. Preventing FXR activation could boost GLP-1 production and insulin secretion. Yet, FXR's broader role in L cell biology still lacks understanding. Here, we show that FXR is a multifaceted TF in L cells using proteomics and gene expression data generated on GLUTag L cells. Most striking, 252 proteins regulated upon glucose stimulation have their abundances neutralized upon FXR activation. Mitochondrial repression or glucose import block are likely mechanisms of this. Further, FXR physically targets bile acid metabolism proteins, growth factors and other TFs, regulates ChREBP, while extensive text-mining found 30 FXR-regulated proteins to be well-known in L cell biology. Taken together, this outlines FXR as a powerful TF, where GLP-1 secretion block is just one of many downstream effects.

Liver Pyruvate Kinase Promotes NAFLD/NASH in Both Mice and Humans in a Sex-Specific Manner

BACKGROUND & AIMS

The etiology of nonalcoholic fatty liver disease (NAFLD) is poorly understood, with males and certain populations exhibiting markedly increased susceptibility. Using a systems genetics approach involving multi-omic analysis of ∼100 diverse inbred strains of mice, we recently identified several candidate genes driving NAFLD. We investigated the role of one of these, liver pyruvate kinase (L-PK or Pklr), in NAFLD by using patient samples and mouse models.

METHODS

We examined L-PK expression in mice of both sexes and in a cohort of bariatric surgery patients. We used liver-specific loss- and gain-of-function strategies in independent animal models of diet-induced steatosis and fibrosis. After treatment, we measured several metabolic phenotypes including obesity, insulin resistance, dyslipidemia, liver steatosis, and fibrosis. Liver tissues were used for gene expression and immunoblotting, and liver mitochondria bioenergetics was characterized.

RESULTS

In both mice and humans, L-PK expression is up-regulated in males via testosterone and is strongly associated with NAFLD severity. In a steatosis model, L-PK silencing in male mice improved glucose tolerance, insulin sensitivity, and lactate/pyruvate tolerance compared with controls. Furthermore, these animals had reduced plasma cholesterol levels and intrahepatic triglyceride accumulation. Conversely, L-PK overexpression in male mice resulted in augmented disease phenotypes. In contrast, female mice overexpressing L-PK were unaffected. Mechanistically, L-PK altered mitochondrial pyruvate flux and its incorporation into citrate, and this, in turn, increased liver triglycerides via up-regulated de novo lipogenesis and increased PNPLA3 levels accompanied by mitochondrial dysfunction. Also, L-PK increased plasma cholesterol levels via increased PCSK9 levels. On the other hand, L-PK silencing reduced de novo lipogenesis and PNPLA3 and PCSK9 levels and improved mitochondrial function. Finally, in fibrosis model, we demonstrate that L-PK silencing in male mice reduced both liver steatosis and fibrosis, accompanied by reduced de novo lipogenesis and improved mitochondrial function.

CONCLUSIONS

L-PK acts in a male-specific manner in the development of liver steatosis and fibrosis. Because NAFLD/nonalcoholic steatohepatitis exhibit sexual dimorphism, our results have important implications for the development of personalized therapeutics.

Multitissue Multiomics Systems Biology to Dissect Complex Diseases

Most complex diseases involve genetic and environmental risk factors, engage multiple cells and tissues, and follow a polygenic or omnigenic model depicting numerous genes contributing to pathophysiology. These multidimensional complexities pose challenges to traditional approaches that examine individual factors. In turn, multitissue multiomics systems biology has emerged to comprehensively elucidate within- and cross-tissue molecular networks underlying gene-by-environment interactions and contributing to complex diseases. The power of systems biology in retrieving novel insights and formulating new hypotheses has been well documented. However, the field faces various challenges that call for debate and action. In this opinion article, I discuss the concepts, benefits, current state, and challenges of the field and point to the next steps toward network-based systems medicine.

Systems Biology Approaches to Understand the Host-Microbiome Interactions in Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) comprise a broad range of progressive neurological disorders with multifactorial etiology contributing to disease pathophysiology. Evidence of the microbiome involvement in the gut-brain axis urges the interest in understanding metabolic interactions between the microbiota and host physiology in NDDs. Systems Biology offers a holistic integrative approach to study the interplay between the different biologic systems as part of a whole, and may elucidate the host–microbiome interactions in NDDs. We reviewed direct and indirect pathways through which the microbiota can modulate the bidirectional communication of the gut-brain axis, and explored the evidence of microbial dysbiosis in Alzheimer’s and Parkinson’s diseases. As the gut microbiota being strongly affected by diet, the potential approaches to targeting the human microbiota through diet for the stimulation of neuroprotective microbial-metabolites secretion were described. We explored the potential of Genome-scale metabolic models (GEMs) to infer microbe-microbe and host-microbe interactions and to identify the microbiome contribution to disease development or prevention. Finally, a systemic approach based on GEMs and ‘omics integration, that would allow the design of sustainable personalized anti-inflammatory diets in NDDs prevention, through the modulation of gut microbiota was described.

Fatty Acid Synthase Inhibitor TVB-2640 Reduces Hepatic de Novo Lipogenesis in Males With Metabolic Abnormalities

BACKGROUND AND AIMS

Elevated hepatic de novo lipogenesis (DNL) is a key distinguishing characteristic of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis. In rodent models of NAFLD, treatment with a surrogate of TVB-2640, a pharmacological fatty acid synthase inhibitor, has been shown to reduce hepatic fat and other biomarkers of DNL. The purpose of this phase I clinical study was to test the effect of the TVB-2640 in obese men with certain metabolic abnormalities that put them at risk for NAFLD.

APPROACH AND RESULTS

Twelve subjects (mean ± SEM, 42 ± 2 years, body mass index 37.4 ± 1.2 kg/m² , glucose 103 ± 2 mg/dL, triacylglycerols 196 ± 27 mg/dL, and elevated liver enzymes) underwent 10 days of treatment with TVB-2640 at doses ranging from 50-150 mg/day. Food intake was controlled throughout the study. Hepatic DNL was measured before and after an oral fructose/glucose bolus using isotopic labeling with 1-¹³ C₁ -acetate intravenous infusion, followed by measurement of labeled very low-density lipoprotein palmitate via gas chromatography mass spectometry. Substrate oxidation was measured by indirect calorimetry. Across the range of doses, fasting DNL was reduced by up to 90% (P = 0.003). Increasing plasma concentrations of TVB-2640 were associated with progressive reductions in the percent of fructose-stimulated peak fractional DNL (R²  = -0.749, P = 0.0003) and absolute DNL area under the curve 6 hours following fructose/glucose bolus (R²  = -0.554, P = 0.005). For all subjects combined, alanine aminotransferase was reduced by 15.8 ± 8.4% (P = 0.05). Substrate oxidation was unchanged, and safety monitoring revealed that the drug was well tolerated, without an increase in plasma triglycerides. Alopecia occurred in 2 subjects (reversed after stopping the drug), but otherwise no changes were observed in fasting glucose, insulin, ketones, and renal function.

CONCLUSION

These data support the therapeutic potential of a fatty acid synthase inhibitor, TVB-2640 in particular, in patients with NAFLD and nonalcoholic steatohepatitis.

From genome sequencing to the discovery of potential biomarkers in liver disease

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.