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.

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.

Spatial molecular and cellular determinants of STAT3 activation in liver fibrosis progression in non-alcoholic fatty liver disease.

Background & Aims: The prevalence of non-alcoholic fatty liver disease (NAFLD) and its severe form, non-alcoholic steatohepatitis (NASH), is increasing. Individuals with NASH often develop liver fibrosis and advanced liver fibrosis is the main determinant of mortality in individuals with NASH. We and others have reported that STAT3 contributes to liver fibrosis and hepatocellular carcinoma in mice. Methods: Here, we explored whether STAT3 activation in hepatocyte and non-hepatocyte areas, measured by phospho-STAT3 (pSTAT3), is associated with liver fibrosis progression in 133 patients with NAFLD. We further characterized the molecular and cellular determinants of STAT3 activation by integrating spatial distribution and transcriptomic changes in fibrotic NAFLD livers.Results: pSTAT3 scores in non-hepatocyte areas progressively increased with fibrosis severity (r = 0.53, p <0.001). Correlation analyses between pSTAT3 scores and expression of 1,540 immune- and cancer-associated genes revealed a large effect of STAT3 activation on gene expression changes in non-hepatocyte areas and confirmed a major role for STAT3 activation in fibrogenesis. Digital spatial transcriptomic profiling was also performed on 13 regions selected in hepatocyte and non-hepatocyte areas from four NAFLD liver biopsies with advanced fibrosis, using a customized panel of markers including pSTAT3, PanCK+CK8/18, and CD45. The regions were further segmented based on positive or negative pSTAT3 staining. Cell deconvolution analysis revealed that activated STAT3 was enriched in hepatic progenitor cells (HPCs) and sinusoidal endothelial cells. Regression of liver fibrosis upon STAT3 inhibition in mice with NASH resulted in a reduction of HPCs, demonstrating a direct role for STAT3 in HPC expansion. Conclusion: Increased understanding of the spatial dependence of STAT3 signaling in NASH and liver fibrosis progression could lead to novel targeted treatment approaches. Impact and implications: Advanced liver fibrosis is the main determinant of mortality in patients with NASH. This study showed using liver biopsies from 133 patients with NAFLD, that STAT3 activation in non-hepatocyte areas is strongly associated with fibrosis severity, inflammation, and progression to NASH. STAT3 activation was enriched in hepatic progenitor cells (HPCs) and sinusoidal endothelial cells (SECs), as determined by innovative technologies interrogating the spatial distribution of pSTAT3. Finally, STAT3 inhibition in mice resulted in reduced liver fibrosis and depletion of HPCs, suggesting that STAT3 activation in HPCs contributes to their expansion and fibrogenesis in NAFLD.

Cellular and Molecular Mechanisms of Liver Fibrosis in Patients with NAFLD.

The expression of immune- and cancer-related genes was measured in liver biopsies from 107 NAFLD patients. The strongest difference in overall gene expression was between liver fibrosis stages F3 and F4, with 162 cirrhosis-associated genes identified. Strong correlations with fibrosis progression from F1 to F4 were observed for 91 genes, including CCL21, CCL2, CXCL6, and CCL19. In addition, the expression of 21 genes was associated with fast progression to F3/F4 in an independent group of eight NAFLD patients. These included the four chemokines, SPP1, HAMP, CXCL2, and IL-8. A six-gene signature including SOX9, THY-1, and CD3D had the highest performance detecting the progressors among F1/F2 NAFLD patients. We also characterized immune cell changes using multiplex immunofluorescence platforms. Fibrotic areas were strongly enriched in CD3+ T cells compared to CD68+ macrophages. While the number of CD68+ macrophages increased with fibrosis severity, the increase in CD3+ T-cell density was more substantial and progressive from F1 to F4. The strongest correlation with fibrosis progression was observed for CD3+CD45R0+ memory T cells, while the most significant increase in density between F1/F2 and F3/F4 was for CD3+CD45RO+FOXP3+CD8- and CD3+CD45RO-FOXP3+CD8- regulatory T cells. A specific increase in the density of CD68+CD11b+ Kupffer cells with liver fibrosis progression was also observed.

Patients with fibrosis from non-alcoholic steatohepatitis have heterogeneous intrahepatic macrophages and therapeutic targets.

Background and Aims: In clinical trials for reducing fibrosis in NASH patients, therapeutics that target macrophages have had variable results. We evaluated intrahepatic macrophages in patients with non-alcoholic steatohepatitis to determine if fibrosis influenced phenotypes and expression of CCR2 and Galectin-3. Approach & Results: We used nCounter to analyze liver biopsies from well-matched patients with minimal (n=12) or advanced (n=12) fibrosis to determine which macrophage-related genes would be significantly different. Known therapy targets (e.g., CCR2 and Galectin-3) were significantly increased in patients with cirrhosis.However, several genes (e.g., CD68, CD16, and CD14) did not show significant differences, and CD163, a marker of pro-fibrotic macrophages was significantly decreased with cirrhosis. Next, we analyzed patients with minimal (n=6) or advanced fibrosis (n=5) using approaches that preserved hepatic architecture by multiplex-staining with anti-CD68, Mac387, CD163, CD14, and CD16. Spectral data were analyzed using deep learning/artificial intelligence to determine percentages and spatial relationships. This approach showed patients with advanced fibrosis had increased CD68+, CD16+, Mac387+, CD163+, and CD16+CD163+ populations. Interaction of CD68+ and Mac387+ populations was significantly increased in patients with cirrhosis and enrichment of these same phenotypes in individuals with minimal fibrosis correlated with poor outcomes. Evaluation of a final set of patients (n=4) also showed heterogenous expression of CD163, CCR2, Galectin-3, and Mac387, and significant differences were not dependent on fibrosis stage or NAFLD activity. Conclusions: Approaches that leave hepatic architecture intact, like multispectral imaging, may be paramount to developing effective treatments for NASH. In addition, understanding individual differences in patients may be required for optimal responses to macrophage-targeting therapies.

Lipidomic Profiles of Plasma Exosomes Identify Candidate Biomarkers for Early Detection of Hepatocellular Carcinoma in Patients with Cirrhosis.

Novel biomarkers for HCC surveillance in cirrhotic patients are urgently needed. Exosomes and their lipid content in particular represent potentially valuable noninvasive diagnostic biomarkers. We isolated exosomes from plasma of 72 cirrhotic patients, including 31 with HCC. Exosomes and unfractionated plasma were processed for untargeted lipidomics using ultra-high-resolution mass spectrometry. A total of 2,864 lipid species, belonging to 52 classes, were identified. Both exosome fractionation and HCC diagnosis had significant impact on the lipid profiles. Ten lipid classes were enriched in HCC exosomes compared with non-HCC exosomes. Dilysocardiolipins were detected in 35% of the HCC exosomes but in none of the non-HCC exosomes (P < 0.001). Cardiolipins and sphingosines had the highest differential effects (fold change of 133.08, q = 0.001 and 38.57, q < 0.001, respectively). In logistic regression analysis, high abundances of exosomal sphingosines, dilysocardiolipins, lysophosphatidylserines, and (O-acyl)-1-hydroxy fatty acids were strongly associated with HCC [OR (95% confidence interval (CI)), 271.1 (14.0-5,251.9), P < 0.001; 46.5 (2.3-939.9), P = 0.012; 14.9 (4.3-51.2), P < 0.001; 10.3 (3.2-33.1), P < 0.001]. Four lipid classes were depleted in HCC exosomes compared with non-HCC exosomes. In logistic regression analysis, lack of detection of sulfatides and acylGlcSitosterol esters was strongly associated with HCC [OR (95% CI): 215.5 (11.5-4,035.9), P < 0.001; 26.7 (1.4-528.4), P = 0.031]. These HCC-associated changes in lipid composition of exosomes reflected alterations in glycerophospholipid metabolism, retrograde endocannabinoid signaling, and ferroptosis. In conclusion, this study identified candidate biomarkers for early detection of HCC as well as altered pathways in exosomes that may contribute to tumor development and progression. PREVENTION RELEVANCE: This study identifies lipids in circulating exosomes, that could serve as biomarkers for the early detection of hepatocellular carcinoma as well as altered pathways in exosomes that may contribute to tumor development and progression.