Genome-wide association study identifies high-impact susceptibility loci for HCC in North America.

BACKGROUND AND AIMS: Despite the substantial impact of environmental factors, individuals with a family history of liver cancer have an increased risk for HCC. However, genetic factors have not been studied systematically by genome-wide approaches in large numbers of individuals from European descent populations (EDP). APPROACH AND RESULTS: We conducted a 2-stage genome-wide association study (GWAS) on HCC not affected by HBV infections. A total of 1872 HCC cases and 2907 controls were included in the discovery stage, and 1200 HCC cases and 1832 controls in the validation. We analyzed the discovery and validation samples separately and then conducted a meta-analysis. All analyses were conducted in the presence and absence of HCV. The liability-scale heritability was 24.4% for overall HCC. Five regions with significant ORs (95% CI) were identified for nonviral HCC: 3p22.1, MOBP , rs9842969, (0.51, [0.40-0.65]); 5p15.33, TERT , rs2242652, (0.70, (0.62-0.79]); 19q13.11, TM6SF2 , rs58542926, (1.49, [1.29-1.72]); 19p13.11 MAU2 , rs58489806, (1.53, (1.33-1.75]); and 22q13.31, PNPLA3 , rs738409, (1.66, [1.51-1.83]). One region was identified for HCV-induced HCC: 6p21.31, human leukocyte antigen DQ beta 1, rs9275224, (0.79, [0.74-0.84]). A combination of homozygous variants of PNPLA3 and TERT showing a 6.5-fold higher risk for nonviral-related HCC compared to individuals lacking these genotypes. This observation suggests that gene-gene interactions may identify individuals at elevated risk for developing HCC. CONCLUSIONS: Our GWAS highlights novel genetic susceptibility of nonviral HCC among European descent populations from North America with substantial heritability. Selected genetic influences were observed for HCV-positive HCC. Our findings indicate the importance of genetic susceptibility to HCC development.

Evidence for an alternative fatty acid desaturation pathway increasing cancer plasticity.

Most tumours have an aberrantly activated lipid metabolism1,2 that enables them to synthesize, elongate and desaturate fatty acids to support proliferation. However, only particular subsets of cancer cells are sensitive to approaches that target fatty acid metabolism and, in particular, fatty acid desaturation3. This suggests that many cancer cells contain an unexplored plasticity in their fatty acid metabolism. Here we show that some cancer cells can exploit an alternative fatty acid desaturation pathway. We identify various cancer cell lines, mouse hepatocellular carcinomas, and primary human liver and lung carcinomas that desaturate palmitate to the unusual fatty acid sapienate to support membrane biosynthesis during proliferation. Accordingly, we found that sapienate biosynthesis enables cancer cells to bypass the known fatty acid desaturation pathway that is dependent on stearoyl-CoA desaturase. Thus, only by targeting both desaturation pathways is the in vitro and in vivo proliferation of cancer cells that synthesize sapienate impaired. Our discovery explains metabolic plasticity in fatty acid desaturation and constitutes an unexplored metabolic rewiring in cancers.

Gut microbiome features associated with liver fibrosis in Hispanics, a population at high risk for fatty liver disease.

BACKGROUND AND AIMS: Hispanics are disproportionately affected by NAFLD, liver fibrosis, cirrhosis, and HCC. Preventive strategies and noninvasive means to identify those in this population at high risk for liver fibrosis, are urgently needed. We aimed to characterize the gut microbiome signatures and related biological functions associated with liver fibrosis in Hispanics and identify environmental and genetic factors affecting them. APPROACH AND RESULTS: Subjects of the population-based Cameron County Hispanic Cohort (CCHC; n = 217) were screened by vibration-controlled transient elastography (FibroScan). Among them, 144 (66.7%) had steatosis and 28 (13.0%) had liver fibrosis. The gut microbiome of subjects with liver fibrosis was enriched with immunogenic commensals (e.g., Prevotella copri, Holdemanella, Clostridiaceae 1) and depleted of Bacteroides caccae, Parabacteroides distasonis, Enterobacter, and Marinifilaceae. The liver fibrosis-associated metagenome was characterized by changes in the urea cycle, L-citrulline biosynthesis and creatinine degradation pathways, and altered synthesis of B vitamins and lipoic acid. These metagenomic changes strongly correlated with the depletion of Parabacteroides distasonis and enrichment of Prevotella and Holdemanella. Liver fibrosis was also associated with depletion of bacterial pathways related to L-fucose biosynthesis. Alcohol consumption, even moderate, was associated with high Prevotella abundance. The single-nucleotide polymorphisms rs3769502 and rs7573751 in the NCK adaptor protein 2 (NCK2) gene positively associated with high Prevotella abundance. CONCLUSION: Hispanics with liver fibrosis display microbiome profiles and associated functional changes that may promote oxidative stress and a proinflammatory environment. These microbiome signatures, together with NCK2 polymorphisms, may have utility in risk modeling and disease prevention in this high-risk population.

Somatic Mutations in Circulating Cell-Free DNA and Risk for Hepatocellular Carcinoma in Hispanics.

Hispanics are disproportionally affected by liver fibrosis and hepatocellular carcinoma (HCC). Advanced liver fibrosis is a major risk factor for HCC development. We aimed at identifying somatic mutations in plasma cell-free DNA (cfDNA) of Hispanics with HCC and Hispanics with advanced liver fibrosis but no HCC. Targeted sequencing of over 262 cancer-associated genes identified nonsynonymous mutations in 22 of the 27 HCC patients. Mutations were detected in known HCC-associated genes (e.g., CTNNB1, TP53, NFE2L2, and ARID1A). No difference in cfDNA concentrations was observed between patients with mutations and those without detectable mutations. HCC patients with higher cfDNA concentrations or higher number of mutations had a shorter overall survival (p < 0.001 and p = 0.045). Nonsynonymous mutations were also identified in 17 of the 51 subjects with advanced liver fibrosis. KMT2C was the most commonly mutated gene. Nine genes were mutated in both subjects with advanced fibrosis and HCC patients. Again, no significant difference in cfDNA concentrations was observed between subjects with mutations and those without detectable mutations. Furthermore, higher cfDNA concentrations and higher number of mutations correlated with a death outcome in subjects with advanced fibrosis. In conclusion, cfDNA features are promising non-invasive markers for HCC risk prediction and overall survival.

High Prevalence of Hepatic Fibrosis, Measured by Elastography, in a Population-Based Study of Mexican Americans.

BACKGROUND & AIMS: Hepatic fibrosis is a primary risk factor for cirrhosis and hepatocellular carcinoma, which affect a disproportionate number of Hispanics in the United States. We aimed to determine the prevalence of significant fibrosis, measured by point shear-wave elastography (pSWE), and determine characteristics of hepatic fibrosis and simple steatosis in a population-based study of Mexican American Hispanics in south Texas. METHODS: Liver stiffness was measured by pSWE, performed by 2 separate operators, for 406 participants in the Cameron County Hispanic Cohort from 2015 through 2017. Significant fibrosis (F2-F4) was defined as median stiffness > 1.34 m/s. Steatosis was determined by ultrasound. All participants underwent a clinical examination that included a comprehensive laboratory analysis and standardized interview about their medical and social history. We calculated weighted prevalence of fibrosis and determined clinical and demographic associations with significant fibrosis (with or without steatosis) and simple steatosis with no/minimal fibrosis using multinomial logistic regression. RESULTS: Fifty-nine participants were excluded due to unreliable pSWE findings or inconclusive ultrasound results, for a final analysis of 347 participants. The prevalence of significant fibrosis was 13.8%; most of these participants (37/42, 88.1%) had no evidence of viral hepatitis or heavy drinking. Levels of liver enzymes were associated with fibrosis and simple steatosis. Indicators of metabolic health (insulin resistance, triglycerides, and cholesterol) were significantly associated with simple steatosis. Fibrosis, but not simple steatosis, was significantly associated with of antibodies against HCV in plasma (odds ratio, 18.9; P = .0138) and non-significantly associated with reduced platelet count (odds ratio, 0.8 per 50x103/µL; 95% CI, 0.5-1.1). Multivariable analyses, as well as sensitivity analyses removing F4 fibrosis and viral or alcoholic etiologies, confirmed our results. CONCLUSION: We estimated the prevalence of fibrosis in a large population of Mexican American Hispanics using pSWE measurements. We found Mexican American Hispanics to have a higher prevalence of fibrosis compared to European and Asian populations, primarily attributable to metabolic disease.

Design of the Texas Hepatocellular Carcinoma Consortium Cohort Study.

OBJECTIVES: The Texas Hepatocellular Carcinoma Consortium cohort study investigates risk factors of hepatocellular carcinoma (HCC) and biomarkers for early HCC detection in patients with liver cirrhosis. METHODS: Adult patients with liver cirrhosis are enrolled at 5 clinical centers from 3 cities in Texas, with a target of 5,000 patients. Clinical history, risk factor questionnaires, liver imaging, laboratory data, and blood samples were collected at enrollment and at each 6-month follow-up visit. RESULTS: The primary outcome was the development of HCC. Biomarkers were tested in banked blood samples using prospective specimen collection, retrospective blinded evaluation design. CONCLUSIONS: We describe study design, eligibility criteria, recruitment, study cores, and sample size and analysis considerations.

Differentiation therapy for hepatocellular carcinoma: Multifaceted effects of miR-148a on tumor growth and phenotype and liver fibrosis.

UNLABELLED: The death rate from hepatocellular carcinoma (HCC) is increasing, and liver cancer is the second leading cause of cancer-related mortality worldwide. Most patients with HCC have underlying liver cirrhosis and compromised liver function, limiting treatment options. Cirrhosis is associated with cell dedifferentiation and expansion of hepatocholangiolar progenitor cells. We identified a microRNA signature associated with HCC and hepatocytic differentiation of progenitor cells. We further identified miR-148a as an inducer of hepatocytic differentiation that is down-regulated in HCC. MiR-148a-mimetic treatment in vivo suppressed tumor growth, reduced tumor malignancy and liver fibrosis, and prevented tumor development. These effects were associated with an increased differentiated phenotype and mediated by IκB kinase alpha/NUMB/NOTCH signaling. CONCLUSION: miR-148a is an inhibitor of the IκB kinase alpha/NUMB/NOTCH pathway and an inducer of hepatocytic differentiation that when deregulated promotes HCC initiation and progression. Differentiation-targeted therapy may be a promising strategy to treat and prevent HCC.

MicroRNA Regulates Hepatocytic Differentiation of Progenitor Cells by Targeting YAP1.

MicroRNA expression profiling in human liver progenitor cells following hepatocytic differentiation identified miR-122 and miR-194 as the microRNAs most strongly upregulated during hepatocytic differentiation of progenitor cells. MiR-194 was also highly upregulated following hepatocytic differentiation of human embryonic stem cells (hESCs). Overexpression of miR-194 in progenitor cells accelerated their differentiation into hepatocytes, as measured by morphological features such as canaliculi and expression of hepatocytic markers. Overexpression of miR-194 in hESCs induced their spontaneous differentiation, a phenotype accompanied with accelerated loss of the pluripotent factors OCT4 and NANOG and decrease in mesoderm marker HAND1 expression. We then identified YAP1 as a direct target of miR-194. Inhibition of YAP1 strongly induced hepatocytic differentiation of progenitor cells and YAP1 overexpression reversed the miR-194-induced hepatocytic differentiation of progenitor cells. In conclusion, we identified miR-194 as a potent inducer of hepatocytic differentiation of progenitor cells and further identified YAP1 as a mediator of miR-194's effects on hepatocytic differentiation and liver progenitor cell fate. Stem Cells 2016;34:1284-1296.

The Precarious Health of Young Mexican American Men in South Texas, Cameron County Hispanic Cohort, 2004-2015.

INTRODUCTION: Hispanic men have higher rates of illness and death from various chronic conditions than do non-Hispanic men. We aimed to characterize the health of Mexican American men living on the US-Mexico border in South Texas and elucidate indications of chronic disease in young men. METHODS: We sampled all male participants from the Cameron County Hispanic Cohort, an ongoing population-based cohort of Mexican Americans in Brownsville, Texas. We calculated descriptive statistics and stratified the sample into 3 age groups to estimate the prevalence of sociodemographic, behavioral, and clinical factors by age group and evaluated differences between age groups. RESULTS: Obesity prevalence was approximately 50% across all age groups (P = .83). Diabetes prevalence was high overall (26.8%), and 16.9% (95% confidence interval [CI], 10.1%-23.8%) of men younger than 35 had diabetes. More than 70% of these young men had elevated liver enzymes, and mean values of aspartate aminotransferase were significantly higher in younger men (45.0 u/L; 95% CI, 39.5-50.6 u/L) than in both older age groups. Less than 20% of young men had any form of health insurance. Current smoking was higher in young men than in men in the other groups, and the rate was higher than the national prevalence of current smoking among Hispanic men. CONCLUSIONS: We suggest a need for obesity and diabetes prevention programs and smoking cessation programs for men in this region. Opportunities exist to expand current intervention programs and tailor them to better reach this vulnerable population of young Hispanic men. Elevated liver enzymes in men younger than 35 suggest a substantial burden of liver abnormalities, a finding that warrants further study.

Osteopontin and latent-TGF ß binding-protein 2 as potential diagnostic markers for HBV-related hepatocellular carcinoma.

Chronic Hepatitis B (HB) is the main risk factor for chronic liver disease (CLD) and hepatocellular carcinoma (HCC) in many low-resource countries, where diagnosis is constrained by lack of clinical, histopathological and biomarker resources. We have used proteomics to detect plasma biomarkers that outperform α-Fetoprotein (AFP), the most widely used biomarker for HCC diagnosis in low-resource contexts. Deep-plasma proteome analysis was performed in HCC patients, patients with CLD and in HB-carrier controls from Thailand (South-East Asia) and The Gambia (West-Africa). Mass spectrometry profiling identified latent-transforming growth factor ß binding-protein 2 (LTBP2) and Osteopontin (OPN) as being significantly elevated in HCC versus CLD and controls. These two proteins were further analyzed by ELISA in a total of 684 plasma samples, including 183 HCC, 274 CLD and 227 asymptomatic controls. When combined, LTBP2 and OPN showed an area under the receiver operating curve of 0.85 in distinguishing HCC from CLD in subjects with AFP <20 ng/mL. In a prospective cohort of 115 CLD patients from Korea, increased plasma levels of LTBP2 and/or OPN were detected in plasma collected over 2 years prior to diagnosis in 21 subjects who developed HCC. Thus, the combination of LTBP2 and OPN outperformed AFP for diagnosis and prediction of HCC and may therefore improve biomarker-based detection of HBV-related HCC.

Extracellular matrix dynamics in hepatocarcinogenesis: a comparative proteomics study of PDGFC transgenic and Pten null mouse models.

We are reporting qualitative and quantitative changes of the extracellular matrix (ECM) and associated receptor proteomes, occurring during the transition from liver fibrosis and steatohepatitis to hepatocellular carcinoma (HCC). We compared two mouse models relevant to human HCC: PDGFC transgenic (Tg) and Pten null mice, models of disease progression from fibrosis and steatohepatitis to HCC. Using mass spectrometry, we identified in the liver of both models proteins for 26 collagen-encoding genes, providing the first evidence of expression at the protein level for 16 collagens. We also identified post-transcriptional protein variants for six collagens and lysine hydroxylation modifications for 14 collagens. Tumor-associated collagen proteomes were similar in both models with increased expression of collagens type IV, VI, VII, X, XIV, XV, XVI, and XVIII. Splice variants for Col4a2, Col6a2, Col6a3 were co-upregulated while only the short form of Col18a1 increased in the tumors. We also identified tumor specific increases of nidogen 1, decorin, perlecan, and of six laminin subunits. The changes in these non-collagenous ECM proteins were similar in both models with the exception of laminin ß3, detected specifically in the Pten null tumors. Pdgfa and Pdgfc mRNA expression was increased in the Pten null liver, a possible mechanism for the similarity in ECM composition observed in the tumors of both models. In contrast and besides the strong up-regulation of integrin α5 protein observed in the liver tumors of both models, the expression of the six other integrins identified was specific to each model, with integrins α2b, α3, α6, and ß1 up-regulated in Pten null tumors and integrins α8 and ß5 up-regulated in the PDGFC Tg tumors. In conclusion, HCC-associated ECM proteins and ECM-integrin networks, common or specific to HCC subtypes, were identified, providing a unique foundation to using ECM composition for HCC classification, diagnosis, prevention, or treatment.

Gut Microbiome and Hepatic Transcriptomic Determinants of HCC Development in Mice with Metabolic Dysfunction-Associated Steatohepatitis.

Purpose: Hepatocellular carcinoma (HCC) related to metabolic dysfunction-associated steatotic liver disease (MASLD) is often diagnosed at a late stage, and its incidence is increasing. Predictive biomarkers are therefore needed to identify individuals at high risk of HCC. We aimed to characterize the gut microbiome and hepatic transcriptome associated with HCC development in female mice with hepatocyte-deletion of Pten (HepPten -). These mice present with large variations in HCC development, making them a powerful model for biomarker discovery. Methods & Results: Sequencing of stool 16S and hepatic RNA was performed on a first set of mice. Among all liver histology parameters measured, the strongest association with microbiome composition changes was with the number of tumors detected at necropsy, followed by inflammation. The gut microbiome of mice with more than 2 tumors was enriched with Lachnospiraceae UCG and depleted of Palleniella intestinalis and Odoribacter. In contrast, hepatic transcriptomic changes were most strongly associated with tumor burden, followed by liver fibrosis. The 840 differentially expressed genes correlating with tumor burden were enriched in leukocyte extravasation and interleukin 10 receptor A (IL10RA) pathways. In addition, the abundance of Spp1-high epithelial cells is correlated with tumor burden. Association between tumor number and depletion of Palleniella intestinalis, and between tumor burden and circulating levels of C-X-C motif chemokine ligand 13 (CXCL13) and stem cell factor (SCF), was further validated in an independent set of mice. Conclusion: We identified microbiome components contributing to liver carcinogenesis by inducing inflammation, and changes in hepatic gene expression and hepatic cells distribution that contribute to tumor growth. Such information can be highly valuable for the development of new prevention strategies as well as of new biomarkers for risk modeling in HCC.

Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes.

Mexican Americans are disproportionally affected by metabolic dysfunction-associated steatotic liver disease (MASLD), which often co-occurs with diabetes. Despite extensive evidence on the causative role of the gut microbiome in MASLD, studies determining the involvement of the gut phageome are scarce. In this cross-sectional study, we characterized the gut phageome in Mexican Americans of South Texas by stool shotgun metagenomic sequencing of 340 subjects, concurrently screened for liver steatosis by transient elastography. Inter-individual variations in the phageome were associated with gender, country of birth, diabetes, and liver steatosis. The phage signatures for diabetes and liver steatosis were subsequently determined. Enrichment of Inoviridae was associated with both diabetes and liver steatosis. Diabetes was further associated with the enrichment of predominantly temperate Escherichia phages, some of which possessed virulence factors. Liver steatosis was associated with the depletion of Lactococcus phages r1t and BK5-T, and enrichment of the globally prevalent Crassvirales phages, including members of genus cluster IX (Burzaovirus coli, Burzaovirus faecalis) and VI (Kahnovirus oralis). The Lactococcus phages showed strong correlations and co-occurrence with Lactococcus lactis, while the Crassvirales phages, B. coli, B. faecalis, and UAG-readthrough crAss clade correlated and co-occurred with Prevotella copri. In conclusion, we identified the gut phageome signatures for two closely linked metabolic diseases with significant global burden. These phage signatures may have utility in risk modeling and disease prevention in this high-risk population, and identification of potential bacterial targets for phage therapy.IMPORTANCEPhages influence human health and disease by shaping the gut bacterial community. Using stool samples from a high-risk Mexican American population, we provide insights into the gut phageome changes associated with diabetes and liver steatosis, two closely linked metabolic diseases with significant global burden. Common to both diseases was an enrichment of Inoviridae, a group of phages that infect bacterial hosts chronically without lysis, allowing them to significantly influence bacterial growth, virulence, motility, biofilm formation, and horizontal gene transfer. Diabetes was additionally associated with the enrichment of Escherichia coli-infecting phages, some of which contained virulence factors. Liver steatosis was additionally associated with the depletion of Lactococcus lactis-infecting phages, and enrichment of Crassvirales phages, a group of virulent phages with high global prevalence and persistence across generations. These phageome signatures may have utility in risk modeling, as well as identify potential bacterial targets for phage therapy.

Training Robust T1-Weighted Magnetic Resonance Imaging Liver Segmentation Models Using Ensembles of Datasets with Different Contrast Protocols and Liver Disease Etiologies.

Image segmentation of the liver is an important step in several treatments for liver cancer. However, manual segmentation at a large scale is not practical, leading to increasing reliance on deep learning models to automatically segment the liver. This manuscript develops a deep learning model to segment the liver on T1w MR images. We sought to determine the best architecture by training, validating, and testing three different deep learning architectures using a total of 819 T1w MR images gathered from six different datasets, both publicly and internally available. Our experiments compared each architecture's testing performance when trained on data from the same dataset via 5-fold cross validation to its testing performance when trained on all other datasets. Models trained using nnUNet achieved mean Dice-Sorensen similarity coefficients > 90% when tested on each of the six datasets individually. The performance of these models suggests that an nnUNet liver segmentation model trained on a large and diverse collection of T1w MR images would be robust to potential changes in contrast protocol and disease etiology.

Enhancement Pattern Mapping for Early Detection of Hepatocellular Carcinoma in Patients with Cirrhosis.

Background and Aims: Limited methods exist to accurately characterize the risk of malignant progression of liver lesions. Enhancement pattern mapping (EPM) measures voxel-based root mean square deviation (RMSD) of parenchyma and the contrast-to-noise (CNR) ratio enhances in malignant lesions. This study investigates the utilization of EPM to differentiate between HCC versus cirrhotic parenchyma with and without benign lesions. Methods: Patients with cirrhosis undergoing MRI surveillance were studied prospectively. Cases (n=48) were defined as patients with LI-RADS 3 and 4 lesions who developed HCC during surveillance. Controls (n=99) were patients with and without LI-RADS 3 and 4 lesions who did not develop HCC. Manual and automated EPM signals of liver parenchyma between cases and controls were quantitatively validated on an independent patient set using cross validation with manual methods avoiding parenchyma with artifacts or blood vessels. Results: With manual EPM, RMSD of 0.37 was identified as a cutoff for distinguishing lesions that progress to HCC from background parenchyma with and without lesions on pre-diagnostic scans (median time interval 6.8 months) with an area under the curve (AUC) of 0.83 (CI: 0.73-0.94) and a sensitivity, specificity, and accuracy of 0.65, 0.97, and 0.89, respectively. At the time of diagnostic scans, a sensitivity, specificity, and accuracy of 0.79, 0.93, and 0.88 were achieved with manual EPM with an AUC of 0.89 (CI: 0.82-0.96). EPM RMSD signals of background parenchyma that did not progress to HCC in cases and controls were similar (case EPM: 0.22 ± 0.08, control EPM: 0.22 ± 0.09, p=0.8). Automated EPM produced similar quantitative results and performance. Conclusion: With manual EPM, a cutoff of 0.37 identifies quantifiable differences between HCC cases and controls approximately six months prior to diagnosis of HCC with an accuracy of 89%.

Current surveillance and diagnostic methods in hepatocellular carcinoma are suboptimal. Enhancement pattern mapping is an imaging technique that quantifies lesion signals and may be useful in diagnostic and surveillance methods. Enhancement pattern mapping describes quantifiable differences between malignant and benign liver tissue on contrast-enhanced MRI. It amplifies lesion signal and distinguishes malignancy in a surveillance population. The novel imaging technique was investigated at single institution and analyzed lesions compared to cirrhotic parenchyma. Future efforts will include further risk stratification across LI-RADS group categories. The results provide evidence that enhancement pattern mapping uses available imaging data to distinguish hepatocellular carcinoma from non-cancerous parenchyma with and without benign lesions on scans six months prior to diagnosis with standard MRI. The technique introduces a prospective modality to improve diagnostic accuracy and early detection with the goal of improving clinical outcomes.

Protection against fibrosis by a bacterial consortium in metabolic dysfunction-associated steatohepatitis and the role of amino acid metabolism.

The gut microbiota drives progression to liver fibrosis, the main determinant of mortality in metabolic dysfunction-associated steatohepatitis (MASH). In this study, we aimed to identify bacterial species associated with protection against liver fibrosis in a high-risk population, and test their potential to protect against liver fibrosis in vivo. Based on stool shotgun metagenomic sequencing of 340 subjects from a population cohort disproportionally affected by MASH, we identified bacterial species from the Bacteroidales and Clostridiales orders associated with reduced risk of liver fibrosis. A bacterial consortium was subsequently tested in a mouse model of MASH, which demonstrated protective effects against liver fibrosis. Six of the eight inoculated bacteria were detected in mouse stool and liver. Intrahepatic presence of bacteria was further confirmed by bacterial culture of mouse liver tissue. Changes in liver histological parameters, gut functional profiles, and amino acid profiles were additionally assessed. Comparison between fibrosis-associated human metagenome and bacteria-induced metagenome changes in mice identified microbial functions likely to mediate the protective effect against liver fibrosis. Amino acid profiling confirmed an increase in cysteine synthase activity, associated with reduced fibrosis. Other microbiota-induced changes in amino acids associated with reduced fibrosis included increased gut asparaginase activity and decreased hepatic tryptophan-to-kynurenine conversion. This human-to-mouse study identified bacterial species and their effects on amino acid metabolism as innovative strategies to protect against liver fibrosis in MASH.

Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis.

Background & Aims: The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of current screening modalities. Methods: We developed a multicenter prospective cohort of patients with cirrhosis undergoing surveillance with MRI and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up. Results: We identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who did not develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, and PNPLA3 and TMS6SF2 single nucleotide polymorphisms, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top six variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC 0.88, 95% CI 0.83-0.93). Finally, 23 metabolites distinguished Cases with LI-RADS-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases. Conclusions: This study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as biomarkers of HCC risk, and microbiota-derived metabolites as contributors to HCC development. Impact and implications: The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, particularly blood biomarkers. Longitudinal collection of paired blood samples and MRI images from patients with cirrhosis is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early-stage HCC detection for patients with cirrhosis undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.

Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies.

Image segmentation of the liver is an important step in treatment planning for liver cancer. However, manual segmentation at a large scale is not practical, leading to increasing reliance on deep learning models to automatically segment the liver. This manuscript develops a generalizable deep learning model to segment the liver on T1-weighted MR images. In particular, three distinct deep learning architectures (nnUNet, PocketNet, Swin UNETR) were considered using data gathered from six geographically different institutions. A total of 819 T1-weighted MR images were gathered from both public and internal sources. Our experiments compared each architecture's testing performance when trained both intra-institutionally and inter-institutionally. Models trained using nnUNet and its PocketNet variant achieved mean Dice-Sorensen similarity coefficients>0.9 on both intra- and inter-institutional test set data. The performance of these models suggests that nnUNet and PocketNet liver segmentation models trained on a large and diverse collection of T1-weighted MR images would on average achieve good intra-institutional segmentation performance.

Heterogeneity in intrahepatic macrophage populations and druggable target expression in patients with steatotic liver disease-related fibrosis.

Background & Aims: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. Methods: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). Results: Several genes known to be pro-fibrotic (e.g. CD206, TREM2, CD163, and ARG1) showed either no significant differences or significantly decreased with advanced fibrosis. Although marked variability in gene expression was observed in individual patients with cirrhosis, several druggable targets and their ligands (e.g. CCR2, CCR5, CCL2, CCL5, and LGALS3) were significantly increased when compared to patients with minimal fibrosis. Antibody panels identified populations that were significantly increased (e.g. Mac387+), decreased (e.g. CD14+), or enriched (e.g. interactions of Mac387) in patients that had progression of disease or advanced fibrosis. Despite heterogeneity in patients with SLD, several macrophage phenotypes and druggable targets showed a positive correlation with increasing NAFLD activity scores and fibrosis stages. Conclusions: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. Impact and implications: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases.

Identification of osteopontin as a novel marker for early hepatocellular carcinoma.

UNLABELLED: The aim of this study was to identify a biomarker that could improve alpha-fetoprotein (AFP) performance in hepatocellular carcinoma (HCC) surveillance among patients with cirrhosis. We performed proteomic profiling of plasma from patients with cirrhosis or HCC and validated selected candidate HCC biomarkers in two geographically distinct cohorts to include HCC of different etiologies. Mass spectrometry profiling of highly fractionated plasma from 18 cirrhosis and 17 HCC patients identified osteopontin (OPN) as significantly up-regulated in HCC cases, compared to cirrhosis controls. OPN levels were subsequently measured in 312 plasma samples collected from 131 HCC patients, 76 cirrhosis patients, 52 chronic hepatitis C (CHC) and B (CHB) patients, and 53 healthy controls in two independent cohorts. OPN plasma levels were significantly elevated in HCC patients, compared to cirrhosis, CHC, CHB, or healthy controls, in both cohorts. OPN alone or in combination with AFP had significantly better area under the receiver operating characteristic curve, compared to AFP, in comparing cirrhosis and HCC in both cohorts. OPN overall performance remained higher than AFP in comparing cirrhosis and the following HCC groups: HCV-related HCC, HBV-associated HCC, and early HCC. OPN also had a good sensitivity in AFP-negative HCC. In a pilot prospective study including 22 patients who developed HCC during follow-up, OPN was already elevated 1 year before diagnosis. CONCLUSION: OPN was more sensitive than AFP for the diagnosis of HCC in all studied HCC groups. In addition, OPN performance remained intact in samples collected 1 year before diagnosis.