Quantification of intratumoral collagen and elastin fibers within hepatocellular carcinoma tissues finds correlations with clinico-patho-radiological features

Liver fibrosis analysis using digital pathology

Digital pathology has enabled the noninvasive quantification of pathological parameters. In addition, the combination of digital pathology and artificial intelligence has enabled the analysis of a vast amount of information, leading to the sharing of much information and the elimination of knowledge gaps. Fibrosis, which reflects chronic inflammation, is the most important pathological parameter in chronic liver diseases, such as viral hepatitis and metabolic dysfunction-associated steatotic liver disease. It has been reported that the quantitative evaluation of various fibrotic parameters by digital pathology can predict the prognosis of liver disease and hepatocarcinogenesis. Liver fibrosis evaluation methods include 1 fiber quantification, 2 elastin and collagen quantification, 3 s harmonic generation/two photon excitation fluorescence (SHG/TPE) microscopy, and 4 Fibronest™..　In this review, we provide an overview of role of digital pathology on the evaluation of fibrosis in liver disease and the characteristics of recent methods to assess liver fibrosis.

The extracellular matrix in hepatocellular carcinoma: Mechanisms and therapeutic vulnerability

The tumor microenvironment (TME) is influenced by a "disorganized" extracellular matrix (ECM) that sensitizes cancer cells toward mechanical stress, signaling, and structural alterations. In hepatocellular carcinoma (HCC), lack of knowledge about key ECM proteins driving the TME refractory to targeted therapies poses a barrier to the identification of new therapeutic targets. Herein, we discuss the contributions of various ECM components that impact hepatocytes and their surrounding support network during tumorigenesis. In addition, the underpinnings by which ECM proteins transduce mechanical signals to the liver TME are detailed. Finally, in view of the bidirectional feedback between the ECM, transformed hepatocytes, and immune cells, we highlight the potential role of the ECM disorganization process in shaping responses to immune checkpoint inhibitors and targeted therapies. Our comprehensive characterization of these ECM components may provide a roadmap for innovative therapeutic approaches to restrain HCC.

3D printed tissue models: From hydrogels to biomedical applications

The development of new advanced constructs resembling structural and functional properties of human organs and tissues requires a deep knowledge of the morphological and biochemical properties of the extracellular matrices (ECM), and the capacity to reproduce them. Manufacturing technologies like 3D printing and bioprinting represent valuable tools for this purpose. This review will describe how morphological and biochemical properties of ECM change in different tissues, organs, healthy and pathological states, and how ECM mimics with the required properties can be generated by 3D printing and bioprinting. The review describes and classifies the polymeric materials of natural and synthetic origin exploited to generate the hydrogels acting as "inks" in the 3D printing process, with particular emphasis on their functionalization allowing crosslinking and conjugation with signaling molecules to develop bio-responsive and bio-instructive ECM mimics.

What is the "washout" of hepatocellular carcinoma as observed on the equilibrium phase CT?: consideration based on the concept of extracellular volume fraction

PURPOSE

To verify the hypothesis that extracellular volume fraction (ECV) and precontrast CT density are the main determinants of washout of hepatocellular carcinoma (HCC) at the equilibrium phase CT.

MATERIALS AND METHODS

Between 2018 and 2020, patients with surgically resected HCC were recruited who had undergone preoperative 4-phase CT. Those larger than 6 cm were excluded to minimize the possibility of intratumoral hemorrhage or degeneration. Two radiologists reviewed the whole images in consensus and divided cases into washout positive and negative groups. Washout positive group at the equilibrium phase was defined as "HCC showing relatively low density as compared to the surrounding background liver (BGL), irrespective of the presence of early enhancement or fibrous capsule". Several clinico-pathological and radiological features, including ECV and precontrast CT density, were correlated to the presence of washout, using uni- and multi-variable analyses.

RESULTS

27 HCC in 24 patients met the inclusion criteria. 22 (82%) and five HCC belonged to washout positive and negative groups, respectively. Univariable analysis revealed ECV of HCC and BGL, ECV difference between HCC and BGL, and presence of fibrous capsule on the equilibrium phase CT were the significant factors. Multivariable analysis showed ECV of HCC and BGL, and precontrast CT density of BGL, were the independently significant factors related to washout, suggesting washout is more likely observed with lower HCC ECV, higher BGL ECV, and higher BGL precontrast CT density.

CONCLUSION

Major determinants of washout of HCC may be ECV of HCC and BGL, and precontrast CT density of BGL.

Preoperative CT for Characterization of Aggressive Macrotrabecular-Massive Subtype and Vessels That Encapsulate Tumor Clusters Pattern in Hepatocellular Carcinoma

Background Macrotrabecular-massive (MTM) subtype and vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. Purpose To estimate the potential of preoperative CT in the prediction of MTM subtype and VETC pattern. Materials and Methods Patients who underwent surgical resection or liver transplant and preoperative CT for HCC between January 2015 and June 2018 were retrospectively included in the primary cohort. CT imaging features were evaluated by two radiologists. Predictors associated with the MTM subtype or VETC pattern were determined by using logistic regression analyses and the performance was tested in a validation cohort. Prognostic factors associated with early recurrence after surgical resection were identified by using Cox regression analyses. Results The primary cohort included 170 patients (median age, 55 years; interquartile range, 48-63 years; 152 men). Serum α-fetoprotein level higher than 100 ng/mL (odds ratio [OR], 4.3; 95% CI: 2.1, 9.2; P < .001), intratumor necrosis (OR, 5.2; 95% CI: 2.5, 11.0; P < .001), and intratumor hemorrhage (OR, 5.4; 95% CI: 1.3, 23.3; P = .02) were independent predictors for MTM subtype, whereas tumor size greater than 5 cm (OR, 3.8; 95% CI: 1.7, 8.1; P = .001) and intratumor necrosis (OR, 2.1; 95% CI: 1.0, 4.4; P = .045) were independent predictors for VETC pattern. These features were used for the construction of ANH and SN scores (where A is α-fetoprotein level, N is necrosis, H is hemorrhage, and S is size), respectively, which showed comparable prediction performance in the primary and validation cohorts. Preoperative high ANH and high SN phenotype (hazard ratio, 1.9; 95% CI: 1.2, 3.0; P = .01) was independently associated with early recurrence after surgical resection. Conclusion Preoperative CT features could be used for the characterization of macrotrabecular-massive subtype and vessels that encapsulate tumor clusters pattern and were of prognostic significance for early recurrence in patients with hepatocellular carcinoma. Online supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue. Published under a CC BY 4.0 license.

Immune microenvironment of hepatocellular carcinoma, intrahepatic cholangiocarcinoma and liver metastasis of colorectal adenocarcinoma: Relationship with histopathological and molecular classifications

Tumor tissue is composed of tumor cells and tumor stroma. Tumor stroma contains various immune cells and non-immune stromal cells, forming a complex tumor microenvironment which plays pivotal roles in regulating tumor growth. Recent successes in immunotherapies against tumors, including immune checkpoint inhibitors, have further raised interests in the immune microenvironment of liver carcinoma. The immune microenvironment of tumors is formed because of interactions among tumor cells, immune cells and non-immune stromal cells, including fibroblasts and endothelial cells. Different patterns of immune microenvironment are observed among different tumor subtypes, and their clinicopathological significance and intertumor/intratumor heterogeneity are being intensively studied. Here, we review the immune microenvironment of hepatocellular carcinoma, intrahepatic cholangiocarcinoma and liver metastasis of colorectal adenocarcinoma, focusing on its histopathological appearance, clinicopathological significance, and relationship with histological and molecular classifications. Understanding the comprehensive histopathological picture of a tumor immune microenvironment, in addition to molecular and genetic approaches, will further potentiate the effort for precision medicine in the era of tumor-targeting immunotherapy.

Assessment of the hepatic tumor extracellular matrix using elastin-specific molecular magnetic resonance imaging in an experimental rabbit cancer model

To investigate the imaging performance of an elastin-specific molecular magnetic resonance imaging (MRI) probe with respect to the extracellular matrix (ECM) in an experimental hepatic cancer model. Twelve rabbits with hepatic VX2 tumors were examined using 3 T MRI 14, 21, and 28 days after tumor implantation for two subsequent days (gadobutrol, day 1; elastin-specific probe, day 2). The relative enhancement (RE) of segmented tumor regions (central and margin) and the peritumoral matrix was calculated using pre-contrast and delayed-phase T1w sequences. MRI measurements were correlated to histopathology and element-specific and spatially resolved mass spectrometry (MS). Mixed-model analysis was performed to assess the performance of the elastin-specific probe. In comparison to gadobutrol, the elastin probe showed significantly stronger RE, which was pronounced in the tumor margin (day 14–28: P ≤ 0.007). In addition, the elastin probe was superior in discriminating between tumor regions (χ²(4) = 65.87; P < 0.001). MRI-based measurements of the elastin probe significantly correlated with the ex vivo elastinstain (R = .84; P <0 .001) and absolute gadolinium concentrations (ICP-MS: R = .73, P <0 .01). LA-ICP-MS imaging confirmed the colocalization of the elastin-specific probe with elastic fibers. Elastin-specific molecular MRI is superior to non-specific gadolinium-based contrast agents in imaging the ECM of hepatic tumors and the peritumoral tissue.

Three Distinct Stroma Types in Human Pancreatic Cancer Identified by Image Analysis of Fibroblast Subpopulations and Collagen

PURPOSE

Cancer-associated fibroblasts have emerged to be highly heterogenous and can play multifaceted roles in dictating pancreatic ductal adenocarcinoma (PDAC) progression, immunosuppression, and therapeutic response, highlighting the need for a deeper understanding of stromal heterogeneity between patients and even within a single tumor. We hypothesized that image analysis of fibroblast subpopulations and collagen in PDAC tissues might guide stroma-based patient stratification to predict clinical outcomes and tumor characteristics.

EXPERIMENTAL DESIGN

A novel multiplex IHC-based image analysis system was established to digitally differentiate fibroblast subpopulations. Using whole-tissue slides from 215 treatment-naïve PDACs, we performed concurrent quantification of principal fibroblast subpopulations and collagen and defined three stroma types: collagen-rich stroma, fibroblast activation protein α (FAP)-dominant fibroblast-rich stroma, and α smooth muscle actin (ACTA2)-dominant fibroblast-rich stroma. These stroma types were assessed for the associations with cancer-specific survival by multivariable Cox regression analyses and with clinicopathologic factors, including CD8⁺ cell density.

RESULTS

FAP-dominant fibroblasts and ACTA2-dominant fibroblasts represented the principal distinct fibroblast subpopulations in tumor stroma. Stroma types were associated with patient survival, SMAD4 status, and transcriptome signatures. Compared with FAP-dominant fibroblast-rich stroma, collagen-rich stroma correlated with prolonged survival [HR, 0.57; 95% confidence interval (CI), 0.33-0.99], while ACTA2-dominant fibroblast-rich stroma exhibited poorer prognosis (HR, 1.65; 95% CI, 1.06-2.58). FAP-dominant fibroblast-rich stroma was additionally characterized by restricted CD8⁺ cell infiltrates and intense neutrophil infiltration.

CONCLUSIONS

This study identified three distinct stroma types differentially associated with survival, immunity, and molecular features, thereby underscoring the importance of stromal heterogeneity in subtyping pancreatic cancers and supporting the development of antistromal therapies.

Overexpression of COL24A1 in Hepatocellular Carcinoma Predicts Poor Prognosis: A Study Based on Multiple Databases, Clinical Samples and Cell Lines

Purpose

Hepatocellular carcinoma (HCC) ranks as the second leading cause of cancer-related deaths worldwide and its incidence tends to increase globally. Current biomarkers can hardly reflect diagnostic significance and therapeutic efficiency accurately. The role of collagen 24A1 (COL24A1) in HCC, as a member of the collagen family, remains unclear and needs to be proved.

Methods

HCC-associated RNA sequencing datasets were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Oncomine databases. R language was used to screen and analyze the differential expression genes (DEGs). Gene Ontology (GO) pathway analyses of DEGs were carried out using g:profiler. Then, the STRING database and cytoscape software were applied to estimate the correlations between DEGs. GEPIA and HCCDB database were used to verify and analyze these results. Finally, qPCR and immunohistochemistry staining on clinical samples and HCC cell lines were conducted to further verify the above results.

Results

The expression of COL24A1 in HCC tissues was significantly higher than that in normal hepatic (NH) tissues. The analysis of TCGA and Oncomine database samples proved that COL24A1 expression was connected with tumor grade, tumor stage and pathologic stage. Meanwhile, the overall survival (OS) curve also validated that high expression of COL24A1 indicated poor prognosis. And the above results have been verified in our clinical samples and HCC cell lines. Furthermore, there is a significant increase of the expression of COL24A1 in various tumors. COL24A1, together with other interactive proteins, has a significant effect on the prognosis of HCC.

Conclusion

Overall, COL24A1 may be an oncogene in the development of HCC. Also, the overexpression of COL24A1 in HCC may help diagnose HCC and evaluate prognosis.