Digital pathology with artificial intelligence analyses provides greater insights into treatment-induced fibrosis regression in NASH

Tropifexor plus cenicriviroc combination versus monotherapy in nonalcoholic steatohepatitis: Results from the phase 2b TANDEM study

BACKGROUND AND AIMS

With distinct mechanisms of action, the combination of tropifexor (TXR) and cenicriviroc (CVC) may provide an effective treatment for NASH. This randomized, multicenter, double-blind, phase 2b study assessed the safety and efficacy of TXR and CVC combination, compared with respective monotherapies.

APPROACH AND RESULTS

Patients (N = 193) were randomized 1:1:1:1 to once-daily TXR 140 μg (TXR 140 ), CVC 150 mg (CVC), TXR 140 μg + CVC 150 mg (TXR 140 + CVC), or TXR 90 μg + CVC 150 mg (TXR 90 + CVC) for 48 weeks. The primary and secondary end points were safety and histological improvement, respectively. Rates of adverse events (AEs) were similar across treatment groups. Pruritus was the most frequently experienced AE, with highest incidence in the TXR 140 group (40.0%). In TXR and combination groups, alanine aminotransferase (ALT) decreased from baseline to 48 weeks (geometric mean change: -21%, TXR 140 ; -16%, TXR 140 + CVC; -13%, TXR 90 + CVC; and +17%, CVC). Reductions in body weight observed at week 24 (mean changes from baseline: TXR 140 , -2.5 kg; TXR 140 + CVC, -1.7 kg; TXR 90 + CVC, -1.0 kg; and CVC, -0.1 kg) were sustained to week 48. At least 1-point improvement in fibrosis stage/steatohepatitis resolution without worsening of fibrosis was observed in 32.3%/25.8%, 31.6%/15.8%, 29.7%/13.5%, and 32.5%/22.5% of patients in the TXR 140 , CVC, TXR 140 + CVC, and TXR 90 + CVC groups, respectively.

CONCLUSIONS

The safety profile of TXR + CVC combination was similar to respective monotherapies, with no new signals. TXR monotherapy showed sustained ALT and body weight decreases. No substantial incremental efficacy was observed with TXR + CVC combination on ALT, body weight, or in histological end points compared with monotherapy.

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD

BACKGROUND

Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment.

AIM

To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD.

METHODS

AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts.

RESULTS

AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts.

CONCLUSION

AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.

Practical Guide, Challenges, and Pitfalls in Liver Fibrosis Staging

Liver fibrosis staging has many challenges, including the large number of proposed staging systems, the heterogeneity of the histopathologic changes of many primary liver diseases, and the potential for slight differences in histologic interpretation to significantly affect clinical management. This review focuses first on fibrosis regression. Following this, each of the major categories of liver disease is discussed in regard to (1) appropriate fibrosis staging systems, (2) emerging concepts, (3) current clinical indications for liver biopsy, (4) clinical decisions determined by fibrosis stage, and (5) histologic challenges and pitfalls related to staging.

Clinical trials reimagined

Clinical trials have been a central driver of change and have provided the evidence base necessary to advance new therapies for liver diseases. This review provides a perspective on the status of trials in hepatology and a vantage point into the emerging capabilities and external forces that will shape the conduct of clinical trials in the future. The adaptations to clinical trial operations in response to the disruptions by the COVID-19 pandemic and opportunities for innovation in hepatology trials are emphasized. Future trials in hepatology will be driven by unmet therapeutic needs and fueled by technological advances incorporating digital capabilities with expanded participant-derived data collection, computing, and analytics. Their design will embrace innovative trial designs adapted to these advances and that emphasize broader and more inclusive participant engagement. Their conduct will be further shaped by evolving regulatory needs and the emergence of new stakeholders in the clinical trials ecosystem. The evolution of clinical trials will offer unique opportunities to advance new therapeutics that will ultimately improve the lives of patients with liver diseases.

Current Therapeutical Approaches Targeting Lipid Metabolism in NAFLD

Nonalcoholic fatty liver disease (NAFLD, including nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH)) is a high-prevalence disorder, affecting about 1 billion people, which can evolve to more severe conditions like cirrhosis or hepatocellular carcinoma. NAFLD is often concomitant with conditions of the metabolic syndrome, such as central obesity and insulin-resistance, but a specific drug able to revert NAFL and prevent its evolution towards NASH is still lacking. With the liver being a key organ in metabolic processes, the potential therapeutic strategies are many, and range from directly targeting the lipid metabolism to the prevention of tissue inflammation. However, side effects have been reported for the drugs tested up to now. In this review, different approaches to the treatment of NAFLD are presented, including newer therapies and ongoing clinical trials. Particular focus is placed on the reverse cholesterol transport system and on the agonists for nuclear factors like PPAR and FXR, but also drugs initially developed for other conditions such as incretins and thyromimetics along with validated natural compounds that have anti-inflammatory potential. This work provides an overview of the different therapeutic strategies currently being tested for NAFLD, other than, or along with, the recommendation of weight loss.

Risk stratification and early detection biomarkers for precision HCC screening

Hepatocellular carcinoma (HCC) mortality remains high primarily due to late diagnosis as a consequence of failed early detection. Professional societies recommend semi-annual HCC screening in at-risk patients with chronic liver disease to increase the likelihood of curative treatment receipt and improve survival. However, recent dynamic shift of HCC etiologies from viral to metabolic liver diseases has significantly increased the potential target population for the screening, whereas annual incidence rate has become substantially lower. Thus, with the contemporary HCC etiologies, the traditional screening approach might not be practical and cost-effective. HCC screening consists of (i) definition of rational at-risk population, and subsequent (ii) repeated application of early detection tests to the population at regular intervals. The suboptimal performance of the currently available HCC screening tests highlights an urgent need for new modalities and strategies to improve early HCC detection. In this review, we overview recent developments of clinical, molecular, and imaging-based tools to address the current challenge, and discuss conceptual framework and approaches of their clinical translation and implementation. These encouraging progresses are expected to transform the current "one-size-fits-all" HCC screening into individualized precision approaches to early HCC detection and ultimately improve the poor HCC prognosis in the foreseeable future.

Sample size calculation for a NanoString GeoMx spatial transcriptomics experiment to study predictors of fibrosis progression in non-alcoholic fatty liver disease

Sample size calculation for spatial transcriptomics is a novel and understudied research topic. Prior publications focused on powering spatial transcriptomics studies to detect specific cell populations or spatially variable expression patterns on tissue slides. However, power calculations for translational or clinical studies often relate to the difference between patient groups, and this is poorly described in the literature. Here, we present a stepwise process for sample size calculation to identify predictors of fibrosis progression in non-alcoholic fatty liver disease as a case study. We illustrate how to infer study hypothesis from prior bulk RNA-sequencing data, gather input requirements and perform a simulation study to estimate required sample size to evaluate gene expression differences between patients with stable fibrosis and fibrosis progressors with NanoString GeoMx Whole Transcriptome Atlas assay.

Targeting protein modifications in metabolic diseases: molecular mechanisms and targeted therapies

The ever-increasing prevalence of noncommunicable diseases (NCDs) represents a major public health burden worldwide. The most common form of NCD is metabolic diseases, which affect people of all ages and usually manifest their pathobiology through life-threatening cardiovascular complications. A comprehensive understanding of the pathobiology of metabolic diseases will generate novel targets for improved therapies across the common metabolic spectrum. Protein posttranslational modification (PTM) is an important term that refers to biochemical modification of specific amino acid residues in target proteins, which immensely increases the functional diversity of the proteome. The range of PTMs includes phosphorylation, acetylation, methylation, ubiquitination, SUMOylation, neddylation, glycosylation, palmitoylation, myristoylation, prenylation, cholesterylation, glutathionylation, S-nitrosylation, sulfhydration, citrullination, ADP ribosylation, and several novel PTMs. Here, we offer a comprehensive review of PTMs and their roles in common metabolic diseases and pathological consequences, including diabetes, obesity, fatty liver diseases, hyperlipidemia, and atherosclerosis. Building upon this framework, we afford a through description of proteins and pathways involved in metabolic diseases by focusing on PTM-based protein modifications, showcase the pharmaceutical intervention of PTMs in preclinical studies and clinical trials, and offer future perspectives. Fundamental research defining the mechanisms whereby PTMs of proteins regulate metabolic diseases will open new avenues for therapeutic intervention.

Future Treatment Options and Regimens for Nonalcoholic Fatty Liver Disease

Recent progress in our understanding of the pathogenic mechanisms that drive progression of nonalcoholic steatohepatitis as well as lessons learned from several clinical trials that have been conducted over the past 15 years guide our current regulatory framework and trial design. Targeting the metabolic drivers should probably be the backbone of therapy in most of the patients, with some requiring more specific intrahepatic antiinflammatory and antifibrotic actions to achieve success. New and innovative targets and approaches as well as combination therapies are currently explored, while awaiting a better understanding of disease heterogeneity that should allow for future individualized medicine.

AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trials

Clinical trials in nonalcoholic steatohepatitis (NASH) require histologic scoring for assessment of inclusion criteria and endpoints. However, guidelines for scoring key features have led to variability in interpretation, impacting clinical trial outcomes. We developed an artificial intelligence (AI)-based measurement (AIM) tool for scoring NASH histology (AIM-NASH). AIM-NASH predictions for NASH Clinical Research Network (CRN) grades of necroinflammation and stages of fibrosis aligned with expert consensus scores and were reproducible. Continuous scores produced by AIM-NASH for key histological features of NASH correlated with mean pathologist scores and with noninvasive biomarkers and strongly predicted patient outcomes. In a retrospective analysis of the ATLAS trial, previously unmet pathological endpoints were met when scored by the AIM-NASH algorithm alone. Overall, these results suggest that AIM-NASH may assist pathologists in histologic review of NASH clinical trials, reducing inter-rater variability on trial outcomes and offering a more sensitive and reproducible measure of patient therapeutic response.

An integrated view of anti-inflammatory and antifibrotic targets for the treatment of NASH

Successful development of treatments for non-alcoholic fatty liver disease (NAFLD) and its progressive form, non-alcoholic steatohepatitis (NASH) has been challenging. Because NASH and fibrosis lead to NAFLD progression towards cirrhosis and to clinical outcomes, approaches have either sought to attenuate metabolic dysregulation and cell injury, or directly target the inflammation and fibrosis that ensue. Targets for reducing the activation of inflammatory cascades include nuclear receptor agonists (thyroid hormone receptor-beta, e.g. resmetirom, peroxisome proliferator-activated receptor [PPAR], e.g. lanifibranor, farnesoid X receptor [FXR], e.g. obeticholic acid), modulators of lipotoxicity (e.g. aramchol, acetyl-CoA carboxylase inhibitors) or modification of genetic variants (e.g. PNPLA3 gene silencing). Extrahepatic inflammatory signals from circulation, adipose tissue or gut are targets of hormonal agonists (e.g. glucagon-like peptide-1 [GLP-1] like semaglutide, fibroblast growth factor [FGF]-19 or FGF21), microbiota or lifestyle (weight loss, diet, exercise) interventions. Stress signals and hepatocyte death activate immune responses engaging innate (macrophages, lymphocytes) and adaptive (auto-aggressive T-cells) mechanisms. Therapies seek to blunt immune cell activation, recruitment (chemokine receptor inhibitors) and responses (e.g. galectin 3 inhibition, anti-platelet drugs). The disease-driving pathways of NASH converge to elicit fibrosis, which is reversible. The activation of hepatic stellate cells (HSC) into matrix-producing myofibroblasts can be inhibited by antagonizing soluble factors (e.g. integrins, cytokines), cellular crosstalk (e.g. with macrophages), and agonizing nuclear receptor signaling (e.g. FXR or PPAR agonists). In advanced fibrosis, cell therapy with restorative macrophages or reprogrammed T-cells (e.g., CAR T) may accelerate repair through HSC deactivation or killing, or by enhancing matrix degradation. Heterogeneity of disease - either due to genetics or divergent disease drivers - is an obstacle to defining effective drugs for all patients with NASH that will be incrementally overcome.

Tropifexor for nonalcoholic steatohepatitis: an adaptive, randomized, placebo-controlled phase 2a/b trial

The multimodal activities of farnesoid X receptor (FXR) agonists make this class an attractive option to treat nonalcoholic steatohepatitis. The safety and efficacy of tropifexor, an FXR agonist, in a randomized, multicenter, double-blind, three-part adaptive design, phase 2 study, in patients with nonalcoholic steatohepatitis were therefore assessed. In Parts A + B, 198 patients were randomized to receive tropifexor (10-90 μg) or placebo for 12 weeks. In Part C, 152 patients were randomized to receive tropifexor 140 µg, tropifexor 200 µg or placebo (1:1:1) for 48 weeks. The primary endpoints were safety and tolerability to end-of-study, and dose response on alanine aminotransferase (ALT), aspartate aminotransferase (AST) and hepatic fat fraction (HFF) at week 12. Pruritus was the most common adverse event in all groups, with a higher frequency in the 140- and 200-µg tropifexor groups. Decreases from baseline in ALT and HFF were greater with tropifexor versus placebo at week 12, with a relative decrease in least squares mean from baseline observed with all tropifexor doses for ALT (tropifexor 10-90-μg dose groups ranged from -10.7 to -16.5 U l-1 versus placebo (-7.8 U l-1) and tropifexor 140- and 200-μg groups were -18.0 U l-1 and -23.0 U l-1, respectively, versus placebo (-8.3 U l-1)) and % HFF (tropifexor 10-90-μg dose groups ranged from -7.48% to -15.04% versus placebo (-6.19%) and tropifexor 140- and 200-μg groups were -19.07% and -39.41%, respectively, versus placebo (-10.77%)). Decreases in ALT and HFF were sustained up to week 48; however, similar trends in AST with tropifexor at week 12 were not observed. As with other FXR agonists, dose-related pruritus was frequently observed. Clinicaltrials.gov registration: NCT02855164.

Surveillance of the progression and assessment of treatment endpoints for nonalcoholic steatohepatitis

Nonalcoholic steatohepatitis (NASH) is an aggressive form of nonalcoholic fatty liver disease (NAFLD) characterized by steatosis-associated inflammation and liver injury. Without effective treatment or management, NASH can have life-threatening outcomes. Evaluation and identification of NASH patients at risk for adverse outcomes are therefore important. Key issues in screening NASH patients are the assessment of advanced fibrosis, differentiation of NASH from simple steatosis, and monitoring of dynamic changes during follow-up and treatment. Currently, NASH staging and evaluation of the effectiveness for drugs still rely on pathological diagnosis, despite sample error issues and the subjectivity associated with liver biopsy. Optimizing the pathological assessment of liver biopsy samples and developing noninvasive surrogate methods for accessible, accurate, and safe evaluation are therefore critical. Although noninvasive methods including elastography, serum soluble biomarkers, and combined models have been implemented in the last decade, noninvasive diagnostic measurements are not widely applied in clinical practice. More work remains to be done in establishing cost-effective strategies both for screening for at-risk NASH patients and identifying changes in disease severity. In this review, we summarize the current state of noninvasive methods for detecting steatosis, steatohepatitis, and fibrosis in patients with NASH, and discuss noninvasive assessments for screening at-risk patients with a focus on the characteristics that should be monitored at follow-up.

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.

Application of digital pathology and machine learning in the liver, kidney and lung diseases

The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology.

Rational combination therapy for NASH: Insights from clinical trials and error

So far without an approved therapy, non-alcoholic steatohepatitis (NASH) remains at the beginning of its therapeutic cycle, whereby many pharmacological agents are initially developed as monotherapies. Given the complex pathogenesis of NASH, the prevailing opinion is that combination therapy will be key to its treatment and that therapeutic efforts should be aimed at developing combinations rather than monotherapies. However, the development of combination therapies is associated with multiple challenges, which we attempt to describe here, and which extend beyond the perceived biological rationale of combining two different mechanisms of action. Important hurdles include predicting the added benefit of a specific combination regimen over monotherapies, given the limited data provided by early phase trials. Regulatory requirements for approving a combination span from preclinical models, through initial demonstration of the efficacy of the combination, to complex late-stage therapeutic trials. Development pathways for combination therapies are, in this paradigm, highly demanding in terms of patient and sponsor resources. In light of recent, negative, late-stage trials of monotherapies, well-designed combination development programmes could be essential to avoid additional failures that may hold back therapeutic research and access to treatment for patients. Enthusiasm for combination therapies should be maintained but realistically balanced against the complexity of demonstrating their therapeutic value.

Second-Harmonic Generated Quantifiable Fibrosis Parameters Provide Signatures for Disease Progression and Regression in Nonalcoholic Fatty Liver Disease

Introduction:

The current ordinal fibrosis staging system for nonalcoholic steatohepatitis (NASH) has a limited dynamic range. The goal of this study was to determine if second-harmonic generated (SHG) quantifiable collagen fibrillar properties (qFP) and their derived qFibrosis score capture changes in disease progression and regression in a murine model of NASH, in which disease progression can be induced by a high fat sugar water (HFSW) diet and regression by reversal to chow diet (CD).

Methods:

DIAMOND mice were fed a CD or HFSW diet for 40 to 52 weeks. Regression related changes were studied in mice with diet reversal for 4 weeks after 48 to 60 weeks of a HFSW diet.

Results:

As expected, mice on HFSW developed steatohepatitis with stage 2 to 3 fibrosis between weeks 40 and 44. Both the collagen proportionate area and the qFibrosis score based on 15 SHG-quantified collagen fibrillar properties in humans were significantly higher in mice on HFSW for 40 to 44 weeks compared to CD fed mice. These changes were greatest in the sinusoids (Zone 2) with further increase in septal and portal fibrosis related scores between weeks 44 and 48. Diet reversal led to decrease in qFibrosis, septal thickness, and cellularity with greatest changes in Zone 2. Specific qFPs associated with progression only, regression only, or both processes were identified and categorized based on direction of fibrosis change.

Conclusion:

Complementing recent human studies, these findings support the concept that changes of disease progression and regression can be assessed using SHG-based image quantification of fibrosis related parameters.

Emerging pharmacological treatment options for MAFLD

Metabolic dysfunction-associated fatty liver disease (MAFLD) prevalence and incidence is rising globally. It is associated with metabolic comorbidities, obesity, overweight, type 2 diabetes mellitus, and at least two metabolic risk factors, such as hypertension, hypertriglyceridemia, hypercholesterolemia, insulin resistance, and cardiovascular risk, increasing the risk of mortality. The excessive accumulation of fat comprises apoptosis, necrosis, inflammation and ballooning degeneration progressing to fibrosis, cirrhosis, and liver decompensations including hepatocellular carcinoma development. The limitation of approved drugs to prevent MAFLD progression is a paradigm. This review focuses on recent pathways and targets with evidence results in phase II/III clinical trials.