Liver fibrosis phenotyping and severity scoring by quantitative image analysis of biopsy slides

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

Cancer-associated Fibroblast-specific Expression of the Matricellular Protein CCN1 Coordinates Neovascularization and Stroma Deposition in Melanoma Metastasis

Melanoma is the leading cause of skin cancer-related death. As prognosis of patients with melanoma remains problematic, identification of new therapeutic targets remains essential. Matricellular proteins are nonstructural extracellular matrix proteins. They are secreted into the tumor microenvironment to coordinate behavior among different cell types, yet their contribution to melanoma is underinvestigated. Examples of matricellular proteins include those comprising the CCN family. The CCN family member, CCN1, is highly proangiogenic. Herein, we show that, in human patients with melanoma, although found in several tumor cell types, CCN1 is highly expressed by a subset of cancer-associated fibroblasts (CAF) in patients with melanoma and this expression correlates positively with expression of proangiogenic genes and progressive disease/resistance to anti-PD1 checkpoint inhibitors. Consistent with these observations, in a syngeneic C57BL6 mouse model of melanoma, loss of CCN1 expression from Col1A2-Cre-, herein identified as "universal," fibroblasts, impaired metastasis of subcutaneously injected B16F10 tumor cells to lung, concomitant with disrupted neovascularization and collagen organization. Disruption of the extracellular matrix in the loss of CCN1 was validated using a novel artificial intelligence-based image analysis platform that revealed significantly decreased phenotypic fibrosis and composite morphometric collagen scores. As drug resistance is linked to matrix deposition and neoangiogenesis, these data suggest that CCN1, due to its multifaceted role, may represent a novel therapeutic target for drug-resistant melanoma. Our data further emphasize the essential role that cancer-associated, (universal) Col1A2-Cre-fibroblasts and extracellular matrix remodeling play in coordinating behavior among different cell types within the tumor microenvironment.

SIGNIFICANCE

In human patients, the expression of proangiogenic matricellular protein CCN1 in CAFs correlates positively with expression of stroma and angiogenic markers and progressive disease/resistance to checkpoint inhibitor therapy. In an animal model, loss of CCN1 from CAFs impaired metastasis of melanoma cells, neovascularization, and collagen deposition, emphasizing that CAFs coordinate cellular behavior in a tumor microenvironment and that CCN1 may be a novel target.

Human Precision-Cut Liver Slices: A Potential Platform to Study Alcohol-Related Liver Disease

Alcohol-related liver disease (ALD) encompasses a range of pathological conditions that are complex to study at the clinical and preclinical levels. Despite the global burden of ALD, there is a lack of effective treatments, and mortality is high. One of the reasons for the unsuccessful development of novel therapies is that experimental studies are hindered by the challenge of recapitulating this multifactorial disorder in vitro, including the contributions of hepatotoxicity, impaired lipid metabolism, fibrosis and inflammatory cytokine storm, which are critical drivers in the pathogenesis of ALD in patients and primary targets for drug development. Here, we present the unique characteristics of the culture of human precision-cut liver slices (PCLS) to replicate key disease processes in ALD. PCLS were prepared from human liver specimens and treated with ethanol alone or in combination with fatty acids and lipopolysaccharide (FA + LPS) for up to 5 days to induce hepatotoxic, inflammatory and fibrotic events associated with ALD. Alcohol insult induced hepatocyte death which was more pronounced with the addition of FA + LPS. This mixture showed a significant increase in the cytokines conventionally associated with the prototypical inflammatory response observed in severe ALD, and interestingly, alcohol alone exhibited a different effect. Profibrogenic activation was also observed in the slices and investigated in the context of slice preparation. These results support the versatility of this organotypic model to study different pathways involved in alcohol-induced liver damage and ALD progression and highlight the applicability of the PCLS for drug discovery, confirming their relevance as a bridge between preclinical and clinical studies.