Deep learning and digital pathology powers prediction of HCC development in steatotic liver disease.

BACKGROUND AND AIMS: Identifying patients with steatotic liver disease who are at a high risk of developing HCC remains challenging. We present a deep learning (DL) model to predict HCC development using hematoxylin and eosin-stained whole-slide images of biopsy-proven steatotic liver disease. APPROACH AND RESULTS: We included 639 patients who did not develop HCC for ≥7 years after biopsy (non-HCC class) and 46 patients who developed HCC <7 years after biopsy (HCC class). Paired cases of the HCC and non-HCC classes matched by biopsy date and institution were used for training, and the remaining nonpaired cases were used for validation. The DL model was trained using deep convolutional neural networks with 28,000 image tiles cropped from whole-slide images of the paired cases, with an accuracy of 81.0% and an AUC of 0.80 for predicting HCC development. Validation using the nonpaired cases also demonstrated a good accuracy of 82.3% and an AUC of 0.84. These results were comparable to the predictive ability of logistic regression model using fibrosis stage. Notably, the DL model also detected the cases of HCC development in patients with mild fibrosis. The saliency maps generated by the DL model highlighted various pathological features associated with HCC development, including nuclear atypia, hepatocytes with a high nuclear-cytoplasmic ratio, immune cell infiltration, fibrosis, and a lack of large fat droplets. CONCLUSIONS: The ability of the DL model to capture subtle pathological features beyond fibrosis suggests its potential for identifying early signs of hepatocarcinogenesis in patients with steatotic liver disease.

The Spatial Extracellular Proteomic Tumor Microenvironment Distinguishes Molecular Subtypes of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) mortality rates continue to increase faster than those of other cancer types due to high heterogeneity, which limits diagnosis and treatment. Pathological and molecular subtyping have identified that HCC tumors with poor outcomes are characterized by intratumoral collagenous accumulation. However, the translational and post-translational regulation of tumor collagen, which is critical to the outcome, remains largely unknown. Here, we investigate the spatial extracellular proteome to understand the differences associated with HCC tumors defined by Hoshida transcriptomic subtypes of poor outcome (Subtype 1; S1; n = 12) and better outcome (Subtype 3; S3; n = 24) that show differential stroma-regulated pathways. Collagen-targeted mass spectrometry imaging (MSI) with the same-tissue reference libraries, built from untargeted and targeted LC-MS/MS was used to spatially define the extracellular microenvironment from clinically-characterized, formalin-fixed, paraffin-embedded tissue sections. Collagen α-1(I) chain domains for discoidin-domain receptor and integrin binding showed distinctive spatial distribution within the tumor microenvironment. Hydroxylated proline (HYP)-containing peptides from the triple helical regions of fibrillar collagens distinguished S1 from S3 tumors. Exploratory machine learning on multiple peptides extracted from the tumor regions could distinguish S1 and S3 tumors (with an area under the receiver operating curve of ≥0.98; 95% confidence intervals between 0.976 and 1.00; and accuracies above 94%). An overall finding was that the extracellular microenvironment has a high potential to predict clinically relevant outcomes in HCC.

Serum MYCN as a predictive biomarker of prognosis and therapeutic response in the prevention of hepatocellular carcinoma recurrence.

The proto-oncogene MYCN expression marked a cancer stem-like cell population in hepatocellular carcinoma (HCC) and served as a therapeutic target of acyclic retinoid (ACR), an orally administered vitamin A derivative that has demonstrated promising efficacy and safety in reducing HCC recurrence. This study investigated the role of MYCN as a predictive biomarker for therapeutic response to ACR and prognosis of HCC. MYCN gene expression in HCC was analyzed in the Cancer Genome Atlas and a Taiwanese cohort (N = 118). Serum MYCN protein levels were assessed in healthy controls (N = 15), patients with HCC (N = 116), pre- and post-surgical patients with HCC (N = 20), and a subset of patients from a phase 3 clinical trial of ACR (N = 68, NCT01640808). The results showed increased MYCN gene expression in HCC tumors, which positively correlated with HCC recurrence in non-cirrhotic or single-tumor patients. Serum MYCN protein levels were higher in patients with HCC, decreased after surgical resection of HCC, and were associated with liver functional reserve and fibrosis markers, as well as long-term HCC prognosis (>4 years). Subgroup analysis of a phase 3 clinical trial of ACR identified serum MYCN as the risk factor most strongly associated with HCC recurrence. Patients with HCC with higher serum MYCN levels after a 4-week treatment of ACR exhibited a significantly higher risk of recurrence (hazard ratio 3.27; p = .022). In conclusion, serum MYCN holds promise for biomarker-based precision medicine for the prevention of HCC, long-term prognosis of early-stage HCC, and identification of high-response subgroups for ACR-based treatment.

Targeting the liver clock improves fibrosis by restoring TGF-ß signaling.

BACKGROUND & AIMS: Liver fibrosis is the major driver for hepatocellular carcinoma and liver disease related death. Approved anti-fibrotic therapies are absent and compounds in development have limited efficacy. Increased TGF-ß signaling drives collagen deposition by hepatic stellate cells (HSC)/myofibroblasts. Here, we aimed to dissect the role of the circadian clock (CC) in controlling TGF-ß signaling and liver fibrosis. METHODS: Using CC-mutant mice, enriched HSCs and myofibroblasts obtained from healthy and fibrotic mice in different CC-phases and loss-of-function studies in human hepatocytes and myofibroblasts, we investigated the relationship between CC and TGF-ß signaling. We explored hepatocyte-myofibroblast communication through bioinformatic analyses of single-nuclei transcriptomes and validation in cell-based models. Using mouse models for MASH fibrosis and spheroids from patients with liver disease, we performed proof-of-concept studies to validate pharmacological targetability and clinical translatability. RESULTS: We discovered that the CC-oscillator temporally gates TGF-ß signaling and this regulation is broken in fibrosis. We demonstrate that HSCs and myofibroblasts contain a functional CC with rhythmic expression of numerous genes, including fibrogenic genes. Perturbation studies in hepatocytes and myofibroblasts revealed a reciprocal relationship between TGF-ß-activation and CC perturbation, which was confirmed in patient-derived ex vivo and in vivo models. Pharmacological modulation of CC-TGF-ß signaling inhibited fibrosis in mouse models in vivo as well as patient-derived liver spheroids. CONCLUSION: The CC regulates TGF-ß signaling, and the breakdown of this control is associated with liver fibrosis in patients. Pharmacological proof-of-concept studies across different models uncover the CC as a therapeutic candidate target for liver fibrosis - a rising global unmet medical need. IMPACT AND IMPLICATIONS: Liver fibrosis due to metabolic diseases is a global health challenge. Many liver functions are rhythmic throughout the day being controlled by the circadian clock (CC). Here we demonstrate that the regulation of the CC is perturbed upon chronic liver injury and this perturbation contributes to fibrotic disease. By showing that a compound targeting the CC improves liver fibrosis in patient-derived models, this study provides a novel therapeutic candidate strategy to treat fibrosis in patients. Additional studies will be needed for clinical translation. Since the findings uncovers a previously undiscovered profibrotic mechanism and therapeutic target, the study is of interest for scientists investigating liver disease, clinical hepatologists and drug developers.

Effect of previous infection with hepatitis B virus on the incidence of hepatocellular carcinoma after sustained virologic response in patients with chronic hepatitis C virus infection.

Previous infection with hepatitis B virus (HBV), which is assessed by HBV core antibody (HBcAb) or surface antibody (HBsAb) titres, has reportedly been associated with an increased risk of developing hepatocellular carcinoma (HCC). We investigated the influence of previous HBV infection on the incidence of HCC in patients with hepatitis C virus (HCV) infection who achieved eradication of HCV, that is sustained virologic response (SVR). Both HBcAb and HBsAb were measured in a total of 1214 patients with HCV infection who had not been coinfected with HBV, as determined by both negative HBs antigen and HBV DNA, and in whom SVR was confirmed. Patients were followed up for a median of 5.7 years, and the incidence of post-SVR HCC was compared based on HBcAb and/or HBsAb. In both univariate and multivariate analyses, the incidence of post-SVR HCC did not differ based on the presence of HBcAb or HBsAb. In conclusion, previous HBV infection has no impact on the incidence of HCC in patients with HCV after SVR.

Comparison of six hepatocellular carcinoma prediction models in Japanese patients after sustained virologic response undergoing rigorous surveillance for hepatocellular carcinoma.

BACKGROUND AND AIM: While several predictive models for the development of hepatocellular carcinoma (HCC) have been proposed, including those for patients with chronic hepatitis C virus (HCV) infection who have achieved sustained virologic response (SVR), the best model may differ between regions. We compared the ability of six reported models to stratify the risk of post-SVR HCC in Japan, where rigorous surveillance and early detection of HCC is common. METHODS: A total of 6048 patients with no history of HCC who achieved SVR by oral direct-acting antiviral drugs were enrolled in this nationwide study. Patients continued HCC surveillance every 6 months after SVR. The incidence of post-SVR HCC was compared between risk groups using the aMAP score, FIB-4 index, Tahata model, GAF4 criteria, GES score, and ADRES score. RESULTS: During the observation period with a median duration of 4.0 years after SVR, post-SVR HCC developed in 332 patients (5.5%). All six models performed significantly at stratifying the incidence of HCC. However, Harrell's C-index was below 0.8 for all models (range, 0.660-0.748), indicating insufficient stratification ability. CONCLUSION: Although all six proposed models demonstrated a good ability to predict the development of post-SVR HCC, their ability to stratify the risk of post-SVRHCC was unsatisfactory. Further studies are necessary to identify the best model for assessing the risk of post-SVR HCC in regions where early detection of HCC is common.

Hepatitis B virus-specific human stem cell memory T cells differentiate into cytotoxic T cells and eradicate HBV-infected hepatocytes in mice.

Chronic infection with the hepatitis B virus (HBV) induces progressive hepatic impairment. Achieving complete eradication of the virus remains a formidable challenge. Cytotoxic T lymphocytes, specific to viral antigens, either exhibit a numerical deficiency or succumb to an exhausted state in individuals chronically afflicted with HBV. The comprehension of the genesis and dissemination of stem cell memory T cells (TSCMs) targeting HBV remains inadequately elucidated. We identified TSCMs in subjects with chronic HBV infection and scrutinized their efficacy in a murine model with human hepatocyte transplants, specifically the TK-NOG mice. TSCMs were discerned in all subjects under examination. Introduction of TSCMs into the HBV mouse model precipitated a severe necro-inflammatory response, resulting in the elimination of human hepatocytes. TSCMs may constitute a valuable tool in the pursuit of a remedial therapy for HBV infection.

Multi-omics analysis of a fatty liver model using human hepatocyte chimeric mice.

We developed a fatty liver mouse model using human hepatocyte chimeric mice. As transplanted human hepatocytes do not respond to mouse growth hormone (GH) and tend to accumulate fat, we hypothesized that addition of human GH would alter lipid metabolism and reduce accumulation of fat in the liver even when fed a high-fat diet. Six uPA/SCID chimeric mice were fed a high-fat GAN diet to induce fatty liver while six were fed a normal CRF1 diet, and GH was administered to three mice in each group. The mice were euthanized at 8 weeks, and human hepatocytes were extracted for RNA-Seq, DIA proteomics, and metabolomics analysis. Abdominal echocardiography revealed that the degree of fatty liver increased significantly in mice fed GAN diet (p < 0.001) and decreased significantly in mice treated with GH (p = 0.026). Weighted gene correlation network analysis identified IGF1 and SEMA7A as eigengenes. Administration of GH significantly reduced triglyceride levels and was strongly associated with metabolism of amino acids. MiBiOmics analysis identified perilipin-2 as a co-inertia driver. Results from multi-omics analysis revealed distinct gene expression and protein/metabolite profiles in each treatment group when mice were fed a high-fat or normal diet with or without administration of GH.

A Body Shape Index as a Simple Anthropometric Marker of Abdominal Obesity and Risk of Cardiovascular Events.

BACKGROUND: A Body Shape Index (ABSI) has been reported to have associations with cardiovascular risk factors. However, there is no information on the association between ABSI and incidence of cardiovascular events. METHODS: We investigated the associations between ABSI and first major cardiovascular events (death from cardiovascular disease, nonfatal acute coronary syndrome, and nonfatal stroke) in 1857 subjects from the database of Flow-Mediated Dilation Japan registry and from Hiroshima University Vascular Function registry. RESULTS: The areas under the curves of ABSI to predict the first major cardiovascular events were superior to BMI (men: P=0.032, women: P=0.015) and waist circumference in women (men: P=0.078, women: P=0.002). The subjects were divided into two groups based on the cutoff value of ABSI for predicting first major cardiovascular events: a low ABSI group (<0.0822 in men and <0.0814 in women) and a high ABSI group (≥0.0822 in men and ≥0.0814 in women). During a median follow-up period of 41.6 months, 56 subjects died (23 from cardiovascular causes), 16 had nonfatal acute coronary syndrome, and 14 had nonfatal stroke. The Kaplan-Meier curves for first major cardiovascular events were significantly different between the two groups (men, P<0.001; women, P<0.001). Multivariate analysis revealed that high ABSI remained an independent predictor of first major cardiovascular events (men: hazard ratio, 2.33; 95% CI, 1.07 to 5.06; P=0.033; women: hazard ratio, 8.33; 95% CI, 1.06 to 65.49; P=0.044). CONCLUSIONS: High ABSI is independently associated with incidence of cardiovascular events. ABSI calculation should be performed for evaluation of risk of cardiovascular events.

Upstroke time is a more useful marker of atherosclerosis than percentage of mean arterial pressure for detecting coronary artery disease in subjects with a normal ankle-brachial index.

Upstroke time (UT) and percentage of mean arterial pressure (%MAP) at the ankle have been shown to serve as atherosclerotic markers. The purpose of this study was to directly compare the diagnostic accuracy of UT with that of %MAP for clinical coronary artery disease (CAD) in subjects with a normal ankle-brachial index (ABI) in both legs. We measured UT and %MAP in 1953 subjects with a normal ABI. The optimal cutoff values of UT and %MAP derived from a receiver operating characteristic (ROC) curve to diagnose CAD were 148 ms and 40.4%, respectively. Multivariable analyses revealed that both UT ≥ 148 ms (odds ratio [OR], 2.72; p < 0.001) and %MAP ≥ 40.4% (OR, 1.28; p = 0.003) were significantly associated with CAD. When the subjects were divided into four groups according to the cutoff values of UT and %MAP, there was no significant difference in the risk of CAD between subjects with UT ≥ 148 ms and %MAP < 40.4% and those with UT ≥ 148 ms and %MAP ≥ 40.4% (OR, 1.45; p = 0.09). ROC curve analyses revealed that the area under the curve value of UT was significantly higher than that of %MAP (0.69 vs. 0.53, p < 0.001). The addition of UT to traditional risk factors significantly improved the diagnostic accuracy for CAD (0.82 to 0.84, p = 0.004), whereas the addition of %MAP to traditional risk factors did not improve the diagnostic accuracy for CAD (0.82 to 0.82, p = 0.84). UT is more useful than %MAP for identifying individuals with CAD among those with a normal ABI.