Modelling liver cancer microenvironment using a novel 3D culture system

Exploring in vitro modeling in hepatocarcinogenesis research: morphological and molecular features and similarities to the corresponding human disease

The hepatocellular carcinoma (HCC) features a remarkable epidemiological burden, ranking as the third most lethal cancer worldwide. As the HCC-related molecular and cellular complexity unfolds as the disease progresses, the use of a myriad of in vitro models available is mandatory in translational preclinical research setups. In this review paper, we will compile cutting-edge information on the in vitro bioassays for HCC research, (A) emphasizing their morphological and molecular parallels with human HCC; (B) delineating the advantages and limitations of their application; and (C) offering perspectives on their prospective applications. While bidimensional (2D) (co) culture setups provide a rapid low-cost strategy for metabolism and drug screening investigations, tridimensional (3D) (co) culture bioassays - including patient-derived protocols as organoids and precision cut slices - surpass some of the 2D strategies limitations, mimicking the complex microarchitecture and cellular and non-cellular microenvironment observed in human HCC. 3D models have become invaluable tools to unveil HCC pathophysiology and targeted therapy. In both setups, the recapitulation of HCC in different etiologies/backgrounds (i.e., viral, fibrosis, and fatty liver) may be considered as a fundamental guide for obtaining translational findings. Therefore, a "multimodel" approach - encompassing the advantages of different in vitro bioassays - is encouraged to circumvent "model-biased" outcomes in preclinical HCC research.

Plasma-derived extracellular matrix for xenofree and cost-effective organoid modeling for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) causes significant cancer mortality worldwide. Cancer organoids can serve as useful disease models by high costs, complexity, and contamination risks from animal-derived products and extracellular matrix (ECM) that limit its applications. On the other hand, synthetic ECM alternatives also have limitations in mimicking native biocomplexity. This study explores the development of a physiologically relevant HCC organoid model using plasma-derived extracellular matrix as a scaffold and nutritive biomatrix with different cellularity components to better mimic the heterogenous HCC microenvironment. Plasma-rich platelet is recognized for its elevated levels of growth factors, which can promote cell proliferation. By employing it as a biomatrix for organoid culture there is a potential to enhance the quality and functionality of organoid models for diverse applications in biomedical research and regenerative medicine and to better replicate the heterogeneous microenvironment of HCC.

METHOD

To generate the liver cancer organoids, HUH-7 hepatoma cells were cultured alone (homogenous model) or with human bone marrow-derived mesenchymal stromal cells and human umbilical vein endothelial cells (heterogeneous model) in plasma-rich platelet extracellular matrix (ECM). The organoids were grown for 14 days and analyzed for cancer properties including cell viability, invasion, stemness, and drug resistance.

RESULTS

HCC organoids were developed comprising HUH-7 hepatoma cells with or without human mesenchymal stromal and endothelial cells in plasma ECM scaffolds. Both homogeneous (HUH-7 only) and heterogeneous (mixed cellularity) organoids displayed viability, cancer hallmarks, and chemoresistance. The heterogeneous organoids showed enhanced invasion potential, cancer stem cell populations, and late-stage HCC genetic signatures versus homogeneous counterparts.

CONCLUSION

The engineered HCC organoids system offers a clinically relevant and cost-effective model to study liver cancer pathogenesis, stromal interactions, and drug resistance. The plasma ECM-based culture technique could enable standardized and reproducible HCC modeling. It could also provide a promising option for organoid culture and scaling up.

Jianpi Shengqing Huazhuo Formula improves abnormal glucose and lipid metabolism in obesity by regulating mitochondrial biogenesis

ETHNOPHARMACOLOGICAL RELEVANCE

Jianpi Shengqing Huazhuo Formula (JSH) is a modified prescription based on traditional Chinese medicine theory and classic prescriptions (Buzhong Yiqi Decoction and Yuye Decoction). It has been found that JSH has a good effect on obese patients with early abnormal glucose and lipid metabolism. Therefore, this experiment was conducted to study its clinical efficacy and pharmacological effect.

AIM OF THE STUDY

To observe the clinical efficacy of JSH and explore the mechanism of the formula to improve glucose and lipid metabolism in obese rats.

MATERIALS AND METHODS

1.

CLINICAL OBSERVATION

10 overweight/obese patients with abnormal glucose and lipid metabolism were selected to observe the indicators of serum glucose, serum lipids and liver damage of the patients before and after treatment with JSH. 2. Animal experiments: Fifty Sprague-Dawley (SD) rats were randomly divided into control group, model group, Metformin group (120 mg/kg/day), JSH-L group (5 g/kg/day) and JSH-H group (20 g/kg/day), with 10 rats in each group. The obese SD rat model was produced by feeding 60% high-fat diet for 8 weeks, and the drug group was given prophylactic administration for 8 weeks. At the end of the experiment, body weight, abdominal fat, plasma glucose, plasma lipids, plasma alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were measured. The levels of interleukin-6 (IL-6), interleukin 1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α) in plasma were detected by Elisa, and the changes of malondialdehyde (MDA), glutathione (GSH) and catalase (CAT) in plasma and liver tissue were detected by kits. The pathological changes and lipid deposition in liver were observed by HE staining and oil red O staining, and the changes in the number of mitochondria in liver cells were observed by transmission electron microscopy. RT-qPCR and Western Blot (WB) were used to detect the mitochondrial regulation-related indicators PGC-1α, NRF1, TFAM, MFN2, DRP1 and apoptosis-related indicators Bcl-2, Bax, caspase 8 in liver tissue.

RESULTS

1.

CLINICAL OBSERVATION

After one month administration, the patient's body weight, BMI, 2 h oral glucose tolerance test (2hOGTT), glycated hemoglobin (HbA1c), triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) decreased significantly, and the indicators of liver damage AST and ALT also decreased significantly. 2. Animal experiments: JSH can significantly reduce body weight and abdominal fat area, improve glucose and lipid metabolism, and also reduce plasma IL-6, IL-1β and TNF-α content in obese rats, and improve oxidative stress; HE staining and oil red O staining also showed that JSH can alleviate liver damage and lipid deposition in the liver. Further observations of liver cell ultrastructure showed that JSH can ameliorate the reduction of liver mitochondria caused by a high-fat diet and promote the expression of indicators of mitochondrial biogenesis related to PGC-1α, NRF1, and TFAM. Moreover, JSH could promote the expression of MFN2 and DRP1, decrease Bcl-2 and increase Bax in the liver.

CONCLUSIONS

1.

CLINICAL OBSERVATION

JSH can reduce body weight, serum glucose, serum lipid, and liver injury in overweight/obese patients. 2. Animal experiments: JSH regulates PGC-1α/NRF1/TFAM signaling pathway promotes liver mitochondrial biogenesis, improves glucose and lipid metabolism in obese rats, and regulates mitochondrial dependent apoptosis indicators Bcl-2/Bax to reduce liver injury.

Identifying hepatoprotective mechanism and effective components of Yinchenzhufu decoction in chronic cholestatic liver injury using a comprehensive strategy based on metabolomics, molecular biology, pharmacokinetics, and cytology

ETHNOPHARMACOLOGICAL RELEVANCE

In Traditional Chinese Medicine (TCM), cholestasis liver disease belongs to jaundice. Yinchenzhufu decoction (YCZFD) is a classic formula used for treating jaundice.

AIM OF THE STUDY

This study was aimed to investigate the potential mechanism and effective components of YCZFD in chronic cholestatic liver injury (CCLI).

MATERIALS AND METHODS

A chronic cholestatic mouse model induced by 3, 5-diethoxycarbonyl-1, 4-dihydroxychollidine was used to investigate the effect of YCZFD. Then, metabolomics was used to investigate the metabolites influenced by YCZFD. Serum and liver bile acid (BA) levels were measured using liquid chromatography coupled with triple quadruple mass spectrometry (LC-MS/MS), and the gene and protein expressions of BA transporters and metabolic enzymes were detected. Additionally, the pharmacokinetics of multiple components of YCZFD was explored to clarify the potential effective components. The effects of absorbed components of YCZFD on BA metabolism and transporter function, inflammation, and farnesoid X receptor (FXR) and pregnane X receptor (PXR) activation were analyzed using sandwich cultured rat hepatocytes, AML12 cells, and dual-luciferase receptor systems, respectively.

RESULTS

YCZFD decreased the liver damage in chronic cholestatic mice. Serum metabolomics results indicated that the main pathways influenced by YCZFD involved primary BA biosynthesis and arachidonic acid metabolism. YCZFD upregulated the expression of FXR, PXR, and BA efflux transporters and the metabolic enzymes of liver tissues, promoting BA excretion and metabolism in cholestatic mice. Additionally, YCZFD downregulated the expression of genes and proteins of the toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) pathway and decreased liver inflammation. The pharmacokinetic study indicated that multiple components showed different pharmacokinetic properties. Among the absorbed components of YCZFD, multiple components activated the transcription of FXR and PXR, regulated BA transporters and metabolic enzyme function, and reduced the gene expression of TLR4 and NF-κB1.

CONCLUSION

YCZFD can ameliorate CCLI by promoting the excretion and metabolism of BAs and inhibiting inflammation via the TLR4/NF-κB signaling pathway. The multiple components of YCZFD could act on BA homeostasis regulation and anti-inflammation, exhibiting a combined effect against CCLI.

Cholangiocarcinoma-on-a-chip: A human 3D platform for personalised medicine

BACKGROUND & AIMS

Cholangiocarcinoma (CCA) is a primary liver tumour characterised by a poor prognosis and limited therapeutic options. Available 3D human CCA models fail to faithfully recapitulate the tumour niche. We aimed to develop an innovative patient-specific CCA-on-chip platform.

METHODS

A CCA tumour microenvironment was recapitulated on a microfluidic three-channel chip using primary CCA cells, cancer-associated fibroblasts (CAFs), endothelial cells, and T cells isolated from CCA specimens (n = 6). CAF and CCA cells were co-cultured in the central channel, flanked by endothelial cells in one lateral channel, recreating a tubular structure. An extensive characterisation of this platform was carried out to investigate its diffusion ability, hydrogel properties, and changes in matrix composition. Cell phenotype and functional properties were assessed.

RESULTS

Primary cells seeded on the microfluidic device were shown to reproduce the architectural structure and maintain the original phenotype and functional properties. The tumour niche underwent a deep remodelling in the 3D device, with an increase in hydrogel stiffness and extracellular matrix deposition, mimicking in vivo CCA characteristics. T cells were incorporated into the device to assess its reliability for immune cell interaction studies. Higher T cell migration was observed using cells from patients with highly infiltrated tumours. Finally, the drug trial showed the ability of the device to recapitulate different drug responses based on patient characteristics.

CONCLUSIONS

We presented a 3D CCA platform that integrates the major non-immune components of the tumour microenvironment and the T cell infiltrate, reflecting the CCA niche. This CCA-on-chip represents a reliable patient-specific 3D platform that will be of help to further elucidate the biological mechanisms involved in CCA and provide an efficient tool for personalised drug testing.

IMPACT AND IMPLICATIONS

An innovative patient-specific cholangiocarcinoma (CCA)-on-chip platform was successfully developed, integrating the major components of the tumour microenvironment (tumour cells, cancer-associated fibroblasts, endothelial cells, and immune infiltrate) and faithfully mimicking the CCA niche. This CCA-on-chip represents a powerful tool for unravelling disease-associated cellular mechanisms in CCA and provides an efficient tool for personalised drug testing.

Advancements and application prospects of three-dimensional models for primary liver cancer: a comprehensive review

Primary liver cancer (PLC) is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths. However, traditional liver cancer models fail to replicate tumor heterogeneity and the tumor microenvironment, limiting the study and personalized treatment of liver cancer. To overcome these limitations, scientists have introduced three-dimensional (3D) culture models as an emerging research tool. These 3D models, utilizing biofabrication technologies such as 3D bioprinting and microfluidics, enable more accurate simulation of the in vivo tumor microenvironment, replicating cell morphology, tissue stiffness, and cell-cell interactions. Compared to traditional two-dimensional (2D) models, 3D culture models better mimic tumor heterogeneity, revealing differential sensitivity of tumor cell subpopulations to targeted therapies or immunotherapies. Additionally, these models can be used to assess the efficacy of potential treatments, providing guidance for personalized therapy. 3D liver cancer models hold significant value in tumor biology, understanding the mechanisms of disease progression, and drug screening. Researchers can gain deeper insights into the impact of the tumor microenvironment on tumor cells and their interactions with the surrounding milieu. Furthermore, these models allow for the evaluation of treatment responses, offering more accurate guidance for clinical interventions. In summary, 3D models provide a realistic and reliable tool for advancing PLC research. By simulating tumor heterogeneity and the microenvironment, these models contribute to a better understanding of the disease mechanisms and offer new strategies for personalized treatment. Therefore, 3D models hold promising prospects for future PLC research.

Digeda-4 decoction and its disassembled prescriptions improve dyslipidemia and apoptosis by regulating AMPK/SIRT1 pathway on tyloxapol-induced nonalcoholic fatty liver disease in mice

ETHNOPHARMACOLOGICAL RELEVANCE

Nonalcoholic fatty liver disease (NAFLD) is a manifestation of metabolic syndrome in the liver and the leading cause of chronic liver disease worldwide. Digeda-4 decoction (DGD-4) is a commonly prescribed Mongolian herbal drug for treating acute and chronic liver injury and fatty liver. However, the mechanisms underlying the improvement of dislipidemia and liver injury via treatment with DGD-4 remain unclear. Disassembling a prescription is an effective approach to studying the effects and mechanisms underlying Mongolian medicine prescriptions. By disassembling a prescription, it is feasible to discover effective combinations of individual herbs to optimize a given prescription. Accordingly, we disassembled DGD-4 into two groups: the single Lomatogonium rotatum (L.) Fries ex Nym (LR) (DGD-1) and non-LR (DGD-3).

AIM OF THIS STUDY

To study whether DGD-4 and its disassembled prescriptions have protective effects against tyloxapol (TY)-induced NAFLD and to explore the underlying mechanisms of action and compatibility of prescriptions.

MATERIAL AND METHODS

NAFLD mice were developed by TY induction. Biochemical horizontal analyses, enzyme-linked immunosorbent assay, and liver histological staining were performed to explore the protective effects of DGD-4 and its disassembled prescriptions DGD-3 and DGD-1. Furthermore, we performed immunohistochemical analyses and Western blotting to further explore the expression of target proteins.

RESULTS

DGD-4 and its disassembled prescriptions could inhibit TY-induced dislipidemia and liver injury. In addition, DGD-4 and its disassembled prescriptions increased the levels of p-AMPKα and p-ACC, but decreased the levels of SREBP1c, SCD-1, SREBP-2, and HMGCS1 proteins. The activation of lipid metabolic pathways SIRT1, PGC-1α, and PPARα improved lipid accumulation in the liver. Moreover, DGD-4 could inhibit hepatocyte apoptosis and treat TY-induced liver injury by upregulating the Bcl-2 expression, downregulating the expression of Bax, caspase-3, caspase-8, and the ratio of Bax/Bcl-2, and positively regulating the imbalance of oxidative stress (OxS) markers (such as superoxide dismutase [SOD], catalase [CAT], malondialdehyde [MDA], and myeloperoxidase [MPO]). DGD-1 was superior to DGD-3 in regulating lipid synthesis-related proteins such as SREBP1c, SCD-1, SREBP-2, and HMGCS1. DGD-3 significantly affected the expression of lipid metabolic proteins SIRT1, PGC-1α, PPARα, apoptotic proteins Bcl-2, Bax, caspase-3, caspase-8, and the regulation of Bax/Bcl-2 ratio. However, DGD-1 showed no regulatory effects on Bax and Bcl-2 proteins.

CONCLUSION

This study demonstrates the protective effects of DGD-4 in the TY-induced NAFLD mice through a mechanism involving improvement of dyslipidemia and apoptosis by regulating the AMPK/SIRT1 pathway. Although the Monarch drug DGD-1 reduces lipid accumulation and DGD-3 inhibits apoptosis and protects the liver from injury, DGD-4 can be more effective overall as a therapy when compared to DGD-1 and DGD-3.

Honokiol and its analogues as anticancer compounds: Current mechanistic insights and structure-activity relationship

Lignans are plant-derived polyphenolic compounds with a plethora of biological applications. Also, regarded as phytoestrogens, the lignans offer a variety of health benefits of which the anti-cancer effects are the most attractive. Honokiol is a lignan isolated from various parts of trees belonging to the genus Magnolia. The bioactivity of honokiol is attributed to its characteristic physical properties, which include small size and the presence of two phenolic groups that may interact with proteins in cell membranes via hydrophobic interactions, aromatic pi orbital co-valency, and hydrogen bonding. The hydrophobicity of honokiol enables its rapid dissolution in lipids and the crossing of physiological barriers, including the blood-brain barrier and cerebrospinal fluid. These factors contribute towards the high bioavailability of honokiol which further support its candidature in medicinal research. Therefore, the anticancer properties of honokiol are of particular interest as many of the contemporary anticancer drugs suffer from bioavailability drawbacks, which necessitates the identification and development of novel candidate molecules directed as anticancer chemotherapeutics. The antioncogenic profile of honokiol also arises from the regulation of various signalling pathways associated with oncogenesis, arresting of the cell cycle by regulation of cyclic proteins, upregulation of epithelial markers and downregulation of mesenchymal markers leading to the inhibition of epithelial-mesenchymal transition, and preventing the metastasis by restricting cell migration and invasion due to the downregulation of matrix-metalloproteinases. In this review, we discuss the anticancer properties of honokiol.

Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases, such as skin, breast, and lung cancer. AI is an advanced form of technology that uses mathematical-based algorithmic principles similar to those of the human mind for cognizing complex challenges of the healthcare unit. Cancer is a lethal disease with many etiologies, including numerous genetic and epigenetic mutations. Cancer being a multifactorial disease is difficult to be diagnosed at an early stage. Therefore, genetic variations and other leading factors could be identified in due time through AI and machine learning (ML). AI is the synergetic approach for mining the drug targets, their mechanism of action, and drug-organism interaction from massive raw data. This synergetic approach is also facing several challenges in data mining but computational algorithms from different scientific communities for multi-target drug discovery are highly helpful to overcome the bottlenecks in AI for drug-target discovery. AI and ML could be the epicenter in the medical world for the diagnosis, treatment, and evaluation of almost any disease in the near future. In this comprehensive review, we explore the immense potential of AI and ML when integrated with the biological sciences, specifically in the context of cancer research. Our goal is to illuminate the many ways in which AI and ML are being applied to the study of cancer, from diagnosis to individualized treatment. We highlight the prospective role of AI in supporting oncologists and other medical professionals in making informed decisions and improving patient outcomes by examining the intersection of AI and cancer control. Although AI-based medical therapies show great potential, many challenges must be overcome before they can be implemented in clinical practice. We critically assess the current hurdles and provide insights into the future directions of AI-driven approaches, aiming to pave the way for enhanced cancer interventions and improved patient care.

Metabolic characteristics of voriconazole - Induced liver injury in rats

Voriconazole (VOR) - induced liver injury is a common adverse reaction, and can lead to serious clinical outcomes. It is of great significance to describe the metabolic characteristics of VOR - induced liver injury and to elucidate the potential mechanisms. This study investigated the changes of plasma metabolic profiles in a rat model of VOR - induced liver injury by non - targeted metabolomics. Correlation analysis was performed between differentially expressed metabolites and plasma liver function indexes. The metabolites with strong correlation were determined for their predictive performance for liver injury using receiver operating characteristic (ROC) curve analysis. Potential biomarkers were then screened combined with liver pathological scores. Finally, the expression level of genes that involved in lipid metabolism were determined in rat liver to verify the mechanism of VOR - induced liver injury we proposed. VOR - induced liver injury in rats was characterized by plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation, the lipid droplets accumulation in liver, as well as inflammation and fibrosis. Significant changes of plasma metabolites were observed, with a decrease in lipid metabolites accounting for over 50% of all changed metabolites, and alterations of cholesterol and bile acids metabolites. The decrease of 3 phosphatidylcholine (PC) in plasma could indicate the occurrence of VOR - induced liver injury. Decreased fatty acids (FA) oxidation and bile acid excretion might be the potential mechanisms of VOR - induced liver injury. This study provided new insights into the molecular characterization of VOR - induced liver injury.

Modelling the Sorafenib-resistant Liver Cancer Microenvironment by Using 3-D Spheroids

Liver cancer is the third leading cause of cancer-related mortality, and hepatocellular carcinoma (HCC) is the most common form of liver cancer, and it usually occurs in the setting of chronic liver disease and cirrhosis. For patients with advanced HCC, systemic treatment is the first choice - however, resistance occurs frequently. Sorafenib was the first tyrosine kinase inhibitor approved for advanced HCC, and resistance to the therapy is a serious concern. When sorafenib therapy fails in a patient, it can be challenging to decide whether they can undergo a second-line therapy, and to determine which therapy they will be able to tolerate. Thus, physiologically relevant in vitro preclinical models are crucial for screening potential therapies, and 3-D tumour spheroids permit studies of tumour pathobiology. In this study, a drug-resistant 3-D tumour spheroid model was developed, based on sorafenib-resistant hepatocellular carcinoma cells, LX2 stellate cells and THP-1 monocytes. Model tumour spheroids that were formed with the sorafenib-resistant cells demonstrated lower diffusion of doxorubicin and exhibited increased resistance to regorafenib. Moreover, in the sorafenib-resistant spheroids, there was increased presence of CD68-positive cells and a reduction in inflammatory marker secretion. The sorafenib-resistant cell line-derived spheroids also showed a higher expression of FGF-19, PDGF-AA and GDF-15, which are known to be involved in malignancies. This multi-cell type spheroid model represents a potentially useful system to test drug candidates in a microenvironment that mimics the drug-resistant tumour microenvironment in HCC.

Investigating the tumor-immune microenvironment through extracellular vesicles from frozen patient biopsies and 3D cultures

Melanomas are highly immunogenic tumors that have been shown to activate the immune response. Nonetheless, a significant portion of melanoma cases are either unresponsive to immunotherapy or relapsed due to acquired resistance. During melanomagenesis, melanoma and immune cells undergo immunomodulatory mechanisms that aid in immune resistance and evasion. The crosstalk within melanoma microenvironment is facilitated through the secretion of soluble factors, growth factors, cytokines, and chemokines. In addition, the release and uptake of secretory vesicles known as extracellular vesicles (EVs) play a key role in shaping the tumor microenvironment (TME). Melanoma-derived EVs have been implicated in immune suppression and escape, promoting tumor progression. In the context of cancer patients, EVs are usually isolated from biofluids such as serum, urine, and saliva. Nonetheless, this approach neglects the fact that biofluid-derived EVs reflect not only the tumor, but also include contributions from different organs and cell types. For that, isolating EVs from tissue samples allows for studying different cell populations resident at the tumor site, such as tumor-infiltrating lymphocytes and their secreted EVs, which play a central anti-tumor role. Herein, we outline the first instance of a method for EV isolation from frozen tissue samples at high purity and sensitivity that can be easily reproduced without the need for complicated isolation methods. Our method of processing the tissue not only circumvents the need for hard-to-acquire freshly isolated tissue samples, but also preserves EV surface proteins which allows for multiplex surface markers profiling. Tissue-derived EVs provide insight into the physiological role of EVs enrichment at tumor sites, which can be overlooked when studying circulating EVs coming from different sources. Tissue-derived EVs could be further characterized in terms of their genomics and proteomics to identify possible mechanisms for regulating the TME. Additionally, identified markers could be correlated to overall patient survival and disease progression for prognostic purposes.

Selective CDK9 knockdown sensitizes TRAIL response by suppression of antiapoptotic factors and NF-kappaB pathway

The aberrantly up-regulated CDK9 can be targeted for cancer therapy. The CDK inhibitor dinaciclib (Dina) has been found to drastically sensitizes cancer response to TRAIL-expressing extracellular vesicle (EV-T). However, the low selectivity of Dina has limited its application for cancer. We propose that CDK9-targeted siRNA (siCDK9) may be a good alternative to Dina. The siCDK9 molecules were encapsulated into EV-Ts to prepare a complexed nanodrug (siEV-T). It was shown to efficiently suppress CDK9 expression and overcome TRAIL resistance to induce strikingly augmented apoptosis in lung cancer both in vitro and in vivo, with a mechanism related to suppression of both anti-apoptotic factors and nuclear factor-kappa B pathway. Therefore, siEV-T potentially constitutes a novel, highly effective and safe therapy for cancers.

Deciphering the underlying mechanism of liver diseases through utilization of multicellular hepatic spheroid models

Hepatocellular carcinoma (HCC) is a very common form of cancer worldwide and is often fatal. Although the histopathology of HCC is characterized by metabolic pathophysiology, fibrosis, and cirrhosis, the focus of treatment has been on eliminating HCC. Recently, three-dimensional (3D) multicellular hepatic spheroid (MCHS) models have provided a) new therapeutic strategies for progressive fibrotic liver diseases, such as antifibrotic and anti-inflammatory drugs, b) molecular targets, and c) treatments for metabolic dysregulation. MCHS models provide a potent anti-cancer tool because they can mimic a) tumor complexity and heterogeneity, b) the 3D context of tumor cells, and c) the gradients of physiological parameters that are characteristic of tumors in vivo. However, the information provided by an multicelluar tumor spheroid (MCTS) model must always be considered in the context of tumors in vivo. This mini-review summarizes what is known about tumor HCC heterogeneity and complexity and the advances provided by MCHS models for innovations in drug development to combat liver diseases. [BMB Reports 2023; 56(4): 225-233].

Three-Dimensional Cell Co-Culture Liver Models and Their Applications in Pharmaceutical Research

As the primary site for the biotransformation of drugs, the liver is the most focused on organ type in pharmaceutical research. However, despite being widely used in pharmaceutical research, animal models have inherent species differences, while two-dimensional (2D) liver cell monocultures or co-cultures and three-dimensional (3D) liver cell monoculture in vitro liver models do not sufficiently represent the complexity of the human liver’s structure and function, making the evaluation results from these tools less reliable. Therefore, there is a pressing need to develop more representative in vitro liver models for pharmaceutical research. Fortunately, an exciting new development in recent years has been the emergence of 3D liver cell co-culture models. These models hold great promise as in vitro pharmaceutical research tools, because they can reproduce liver structure and function more practically. This review begins by explaining the structure and main cell composition of the liver, before introducing the potential advantages of 3D cell co-culture liver models for pharmaceutical research. We also discuss the main sources of hepatocytes and the 3D cell co-culture methods used in constructing these models. In addition, we explore the applications of 3D cell co-culture liver models with different functional states and suggest prospects for their further development.

Updates on Organoid Model for the Study of Liver Cancer

Liver cancer remains one of the most common cancers worldwide with limited therapy options. The main risk factors for hepatocellular carcinoma (HCC), the most common form of liver cancer, include chronic infection with hepatitis B or hepatitis C viruses, alcohol abuse, and metabolic disease. Current systemic therapies for advanced HCCs have greatly improved in the last decade, but there is still a need to develop more targeted drug therapy for HCCs. The development of liver organoids, a self-organising and self-renewal three-dimensional cell culture model, has greatly improved cancer research, including liver cancer. The generation of liver organoids provides a physiologically relevant model to study cancer drug screening and development, personalized medicine, liver disease modeling, and liver regeneration. However, the advent of organoid development also comes with few shortcomings that must be overcome, including the high cost of the model, the availability of origin tissues, and the need for multilineage liver organoids to replicate the true cellular heterogeneity of the liver. Despite all the limitations, liver organoids provide a reliable in vitro model for translational applications to develop more effective HCC therapy and to understand the underlying pathogenic mechanism in various liver diseases.

Integration of transcriptomics data into agent-based models of solid tumor metastasis

Recent progress in our understanding of cancer mostly relies on the systematic profiling of patient samples with high-throughput techniques like transcriptomics. With this approach, one can find gene signatures and networks underlying cancer aggressiveness and therapy resistance. However, omics data alone cannot generate insights into the spatiotemporal aspects of tumor progression. Here, multi-level computational modeling is a promising approach that would benefit from protocols to integrate the data generated by the high-throughput profiling of patient samples. We present a computational workflow to integrate transcriptomics data from tumor patients into hybrid, multi-scale cancer models. In the method, we conduct transcriptomics analysis to select key differentially regulated pathways in therapy responders and non-responders and link them to agent-based model parameters. We then determine global and local sensitivity through systematic model simulations that assess the relevance of parameter variations in triggering therapy resistance. We illustrate the methodology with a de novo generated agent-based model accounting for the interplay between tumor and immune cells in a melanoma micrometastasis. The application of the workflow identifies three distinct scenarios of therapy resistance.

Identification of the Collagen Types Essential for Mammalian Breast Acinar Structures

Modeling human breast tissue architecture is essential to study the pathophysiological conditions of the breast. We report that normal mammary epithelial cells grown in human breast extracellular matrix (ECM) hydrogel formed acini structurally similar to those of human and pig mammary tissues. Type I, II, III and V collagens were commonly identified in human, pig, and mouse breast ECM. Mammary epithelial cells formed acini on certain types or combinations of the four collagens at normal levels of breast tissue elasticity. Comparison of the collagen species in mouse normal breast and breast tumor ECM revealed common and distinct sets of collagens within the two types of tissues. Elevated expression of collagen type I alpha 1 chain (Col1a1) was found in mouse and human breast cancers. Collagen type XXV alpha 1 chain (Col25a1) was identified in mouse breast tumors but not in normal breast tissues. Our data provide strategies for modeling human breast pathophysiological structures and functions using native tissue-derived hydrogels and offer insight into the potential contributions of different collagen types in breast cancer development.

Exploring Dynamic Metabolome of the HepG2 Cell Line: Rise and Fall

Both biological and technical variations can discredit the reliability of obtained data in omics studies. In this technical note, we investigated the effect of prolonged cultivation of the HepG2 hepatoma cell line on its metabolomic profile. Using the GC × GC-MS approach, we determined the degree of metabolic variability across HepG2 cells cultured in uniform conditions for 0, 5, 10, 15, and 20 days. Post-processing of obtained data revealed substantial changes in relative abundances of 110 metabolites among HepG2 samples under investigation. Our findings have implications for interpreting metabolomic results obtained from immortal cells, especially in longitudinal studies. There are still plenty of unanswered questions regarding metabolomics variability and many potential areas for future targeted and panoramic research. However, we suggest that the metabolome of cell lines is unstable and may undergo significant transformation over time, even if the culture conditions remain the same. Considering metabolomics variability on a relatively long-term basis, careful experimentation with particular attention to control samples is required to ensure reproducibility and relevance of the research results when testing both fundamentally and practically significant hypotheses.

Effects of Cancer Cell-Derived Nanovesicle Vaccines Produced by the Oxidative Stress-Induced Expression of DAMP and Spontaneous Release/Filter Extrusion in the Interplay of Cancer Cells and Macrophages

Photodynamic therapy (PDT)-based cancer vaccines are shown to be more effective modalities for treating cancer in animal models compared to other methods used to generate cancer cell-derived vaccines. The higher efficacy seems to stem from the generation of cell membrane nanovesicles or fragments that carry both cancer cell-specific antigens and high surface content of damage-associated molecular pattern (DAMP) molecules induced by oxidative stress. To develop more effective cancer vaccines in this direction, we explored the generation of cancer vaccines by applying different sources of oxidative stress on cancer cell cultures followed by spontaneous release or filter extrusions to produce cancer cell-derived DAMP-expressing nanovesicles. Through an in-vitro test based on the co-culture of cancer cells and macrophages, it was found that the nanovesicle vaccines generated by H2O2 are as effective as those generated by PDT in diminishing cancer cell culture masses, providing a simpler way to manufacture vaccines. In addition, the nanovesicle vaccines produced by filter extrusion are as potent as those produced by spontaneous release, rendering a more stable way for vaccine production.

Identification of Endoplasmic Reticulum Stress-Related Subtypes, Infiltration Analysis of Tumor Microenvironment, and Construction of a Prognostic Model in Colorectal Cancer

Simple Summary

Understanding how endoplasmic reticulum stress influences colorectal cancer progression and the composition of the tumor microenvironment is important for developing novel strategies in the treatment of colorectal cancer. In this study, we identified two endoplasmic reticulum stress-related subtypes of colorectal cancer with distinct prognosis and infiltration patterns in the tumor microenvironment. Besides, we constructed a prognostic model for predicting patients’ survival, which involved an endoplasmic reticulum stress-related 14-gene signature. Furthermore, by utilizing spatial transcriptomics data from two untreated colorectal cancer patients, we explored endoplasmic reticulum stress-related gene signatures at a subcellular level and found that colorectal cancer cells and regulatory T cells showed an evidently increased expression of endoplasmic reticulum stress-related gene signature, and cancer-associated fibroblasts might be the leading characteristic that distinguishes the endoplasmic reticulum stress-related subtypes of colorectal cancer. We suggest that targeting endoplasmic reticulum stress in colorectal cancer might reshape the exhausted tumor microenvironment and mitigate tumor progression.

Abstract

Recently, endoplasmic reticulum (ER) stress has been shown to influence tumor progression and immune cell function in the tumor microenvironment (TME). However, the underlying role of ER stress-related gene patterns in colorectal cancer (CRC) development remains unclear. We analyzed the ER stress-related gene patterns in 884 patients with CRC from the Gene Expression Omnibus database and evaluated the cell-infiltrating patterns in the TME. Two ER stress-related patterns were identified in patients with CRC that had distinct cell-infiltrating patterns in the TME and clinical characteristics. A risk score and nomogram based on 14 screened prognosis-correlated genes was built and validated to predict patient survival. Patients with a higher risk score were shown to have an unfavorable prognosis, and the risk score was associated with cell infiltration and drug sensitivity. Furthermore, spatial transcriptomics data were utilized to explore ER stress-related gene patterns in CRC tissues, and it was shown that ER stress phenotype involves in the formation of the immunosuppressive TME. This study demonstrated that ER stress-related gene patterns play a role in influencing the TME and predicting prognosis. These analyses of ER stress in the TME of CRC might deepen our understanding of CRC progression and immune escape and provide novel insights into therapeutic strategies.

Characterisation of 3D Bioprinted Human Breast Cancer Model for In Vitro Drug and Metabolic Targeting

Monolayer cultures, the less standard three-dimensional (3D) culturing systems, and xenografts are the main tools used in current basic and drug development studies of cancer research. The aim of biofabrication is to design and construct a more representative in vivo 3D environment, replacing two-dimensional (2D) cell cultures. Here, we aim to provide a complex comparative analysis of 2D and 3D spheroid culturing, and 3D bioprinted and xenografted breast cancer models. We established a protocol to produce alginate-based hydrogel bioink for 3D bioprinting and the long-term culturing of tumour cells in vitro. Cell proliferation and tumourigenicity were assessed with various tests. Additionally, the results of rapamycin, doxycycline and doxorubicin monotreatments and combinations were also compared. The sensitivity and protein expression profile of 3D bioprinted tissue-mimetic scaffolds showed the highest similarity to the less drug-sensitive xenograft models. Several metabolic protein expressions were examined, and the in situ tissue heterogeneity representing the characteristics of human breast cancers was also verified in 3D bioprinted and cultured tissue-mimetic structures. Our results provide additional steps in the direction of representing in vivo 3D situations in in vitro studies. Future use of these models could help to reduce the number of animal experiments and increase the success rate of clinical phase trials.