Luteolin: A promising modulator of apoptosis and survival signaling in liver cancer.

Due to the increasing incidence of cancer and the difficulties in determining the safety profile of existing therapeutic approaches, cancer research has recently become heavily involved in the search for new therapeutic approaches. The therapeutic significance of natural substances, especially flavonoids, against the onset and progression of cancer has been emphasized in traditional food-based medicine. Interestingly, the flavone luteolin possesses biological effects that have been linked to its anti-inflammatory, antioxidant, and anticancer effects. Luteolin interacts with several downstream chemicals and signaling pathways, including those involved in apoptosis, autophagy, cell cycle progression, and angiogenesis, to exert its anticancer effects on various cancerous cells. A complete understanding of both intrinsic and extrinsic apoptotic pathways, autophagy, and, most critically, the nanodelivery of luteolin in liver cancer is provided in the current review.

Establishment of a multi-line immunochromatography based on magnetic nanoparticles for simultaneous screening of multiple biomarkers.

Biomarkers screening is a benefit approach for early diagnosis of major diseases. In this study, magnetic nanoparticles (MNPs) have been utilized as labels to establish a multi-line immunochromatography (MNP-MLIC) for simultaneous detection of carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA 19-9), and alpha-fetoprotein (AFP) in a single serum sample. Under the optimal parameters, the three biomarkers can be rapidly and simultaneously qualitative screening within 15 min by naked eye. As for quantitative detection, the MNP-MLIC test strips were precisely positioned and captured by a smartphone, and signals on the test and control lines were extracted by ImageJ software. The signal ratio of test and control lines has been calculated and used to plot quantitative standard curves with the logarithmic concentration, of which the correlation coefficients are more than 0.99, and the limit of detection for CEA, CA 19-9, and AFP were 0.60 ng/mL, 1.21 U/mL, and 0.93 ng/mL, respectively. The recoveries of blank serum were 75.0 ~ 112.5% with the relative standard deviation ranging from 2.5 to 15.3%, and the specificity investigation demonstrated that the MNP-MLIC is highly specific to the three biomarkers. In conclusion, the developed MNP-MLIC offers a rapid, simple, accurate, and highly specific method for simultaneously detecting multiple biomarkers in serum samples, which provides an efficient and accurate approach for the early diagnosis of diseases.

Scoring System for Predicting the Risk of Liver Cancer among Diabetes Patients: A Random Survival Forest-Guided Approach.

BACKGROUND: Most liver cancer scoring systems focus on patients with preexisting liver diseases such as chronic viral hepatitis or liver cirrhosis. Patients with diabetes are at higher risk of developing liver cancer than the general population. However, liver cancer scoring systems for patients in the absence of liver diseases or those with diabetes remain rare. This study aims to develop a risk scoring system for liver cancer prediction among diabetes patients and a sub-model among diabetes patients without cirrhosis/chronic viral hepatitis. METHODS: A retrospective cohort study was performed using electronic health records of Hong Kong. Patients who received diabetes care in general outpatient clinics between 2010 and 2019 without cancer history were included and followed up until December 2019. The outcome was diagnosis of liver cancer during follow-up. A risk scoring system was developed by applying random survival forest in variable selection, and Cox regression in weight assignment. RESULTS: The liver cancer incidence was 0.92 per 1000 person-years. Patients who developed liver cancer (n = 1995) and those who remained free of cancer (n = 1969) during follow-up (median: 6.2 years) were selected for model building. In the final time-to-event scoring system, presence of chronic hepatitis B/C, alanine aminotransferase, age, presence of cirrhosis, and sex were included as predictors. The concordance index was 0.706 (95%CI: 0.676-0.741). In the sub-model for patients without cirrhosis/chronic viral hepatitis, alanine aminotransferase, age, triglycerides, and sex were selected as predictors. CONCLUSIONS: The proposed scoring system may provide a parsimonious score for liver cancer risk prediction among diabetes patients.

Exploring Selenoprotein P in Liver Cancer: Advanced Statistical Analysis and Machine Learning Approaches.

Selenoprotein P (SELENOP) acts as a crucial mediator, distributing selenium from the liver to other tissues within the body. Despite its established role in selenium metabolism, the specific functions of SELENOP in the development of liver cancer remain enigmatic. This study aims to unravel SELENOP's associations in hepatocellular carcinoma (HCC) by scrutinizing its expression in correlation with disease characteristics and investigating links to hormonal and lipid/triglyceride metabolism biomarkers as well as its potential as a prognosticator for overall survival and predictor of hypoxia. SELENOP mRNA expression was analyzed in 372 HCC patients sourced from The Cancer Genome Atlas (TCGA), utilizing statistical methodologies in R programming and machine learning techniques in Python. SELENOP expression significantly varied across HCC grades (p < 0.000001) and among racial groups (p = 0.0246), with lower levels in higher grades and Asian individuals, respectively. Gender significantly influenced SELENOP expression (p < 0.000001), with females showing lower altered expression compared to males. Notably, the Spearman correlation revealed strong positive connections of SELENOP with hormonal markers (AR, ESR1, THRB) and key lipid/triglyceride metabolism markers (PPARA, APOC3, APOA5). Regarding prognosis, SELENOP showed a significant association with overall survival (p = 0.0142) but explained only a limited proportion of variability (~10%). Machine learning suggested its potential as a predictive biomarker for hypoxia, explaining approximately 18.89% of the variance in hypoxia scores. Future directions include validating SELENOP's prognostic and diagnostic value in serum for personalized HCC treatment. Large-scale prospective studies correlating serum SELENOP levels with patient outcomes are essential, along with integrating them with clinical parameters for enhanced prognostic accuracy and tailored therapeutic strategies.

Dual-reporter fluorescent probe for precise identification of liver cancer by sequentially responding to carboxylesterase and polarity.

Early treatment significantly improves the survival rate of liver cancer patients, so the development of early diagnostic methods for liver cancer is urgent. Liver cancer can develop from viral hepatitis, alcoholic liver, and fatty liver, thus making the above diseases share common features such as elevated viscosity, reactive oxygen species, and reactive nitrogen species. Therefore, accurate differentiation between other liver diseases and liver cancer is both a paramount practical need and challenging. Numerous fluorescent probes have been reported for the diagnosis of liver cancer by detecting a single biomarker, but these probes lack specificity for liver cancer in complex biological systems. Obviously, using multiple liver cancer biomarkers as the basis for judgment can dramatically improve diagnostic accuracy. Herein, we report the first fluorescent probe, LD-TCE, that sequentially detects carboxylesterase (CE) and lipid droplet polarity in liver cancer cells with high sensitivity and selectivity, with linear detection of CE in the range of 0-6 U/mL and a 65-fold fluorescence enhancement in response to polarity. The probe first reacts with CE and releases weak fluorescence, which is then dramatically enhanced due to the decrease in lipid droplet polarity in liver cancer cells. This approach allows the probe to enable specific imaging of liver cancer with higher contrast and accuracy. The probe successfully achieved the screening of liver cancer cells and the precise identification of liver cancer in mice. More importantly, it is not disturbed by liver fibrosis, which is a common pathological feature of many liver diseases. We believe that the LD-TCE is expected to be a powerful tool for early diagnosis of liver cancer.

Attributable liver cancer deaths and disability-adjusted life years in China and worldwide: profiles and changing trends.

OBJECTIVE: Liver cancer is a major health concern globally and in China. This analysis investigated deaths and disability-adjusted life years (DALYs) with respect to etiologies and risk factors for liver cancer in China and worldwide. METHODS: Global and China-specific data were collected on liver cancer deaths, DALYs, and age-standardized rates (ASRs) from the Global Burden of Disease Study 2019 database. Liver cancer etiologies were classified into five groups and risk factors were categorized into three levels. Each proportion of liver cancer burden was calculated in different geographic regions. The joinpoint regression model were used to assess the trends from 1990-2019. RESULTS: Liver cancer accounted for 484,577 deaths worldwide in 2019 with an ASR of 5.9 per 100,000 population. China had an elevated liver cancer death ASR in 2019 and males had an ASR 1.7 times the global rate. The global ASR for DALYs peaked at 75-79 years of age but peaked earlier in China. Hepatitis B virus was the prominent etiology globally (39.5%) and in China (62.5%), followed by hepatitis C virus and alcohol consumption. In high sociodemographic index countries, non-alcoholic steatohepatitis has gained an increasing contribution as an etiologic factor. The liver cancer burden due to various etiologies has decreased globally in both genders. However, metabolic risk factors, particularly obesity, have had a growing contribution to the liver cancer burden, especially among males. CONCLUSIONS: Despite an overall decreasing trend in the liver cancer burden in China and worldwide, there has been a rising contribution from metabolic risk factors, highlighting the importance of implementing targeted prevention and control strategies that address regional and gender disparities.

Research progress of ferroptosis regulating lipid peroxidation and metabolism in occurrence and development of primary liver cancer.

As a highly aggressive tumor, the pathophysiological mechanism of primary liver cancer has attracted much attention. In recent years, factors such as ferroptosis regulation, lipid peroxidation and metabolic abnormalities have emerged in the study of liver cancer, providing a new perspective for understanding the development of liver cancer. Ferroptosis regulation, lipid peroxidation and metabolic abnormalities play important roles in the occurrence and development of liver cancer. The regulation of ferroptosis is involved in apoptosis and necrosis, affecting cell survival and death. Lipid peroxidation promotes oxidative damage and promotes the invasion of liver cancer cells. Metabolic abnormalities, especially the disorders of glucose and lipid metabolism, directly affect the proliferation and growth of liver cancer cells. Studies of ferroptosis regulation and lipid peroxidation may help to discover new therapeutic targets and improve therapeutic outcomes. The understanding of metabolic abnormalities can provide new ideas for the prevention of liver cancer, and reduce the risk of disease by adjusting the metabolic process. This review focuses on the key roles of ferroptosis regulation, lipid peroxidation and metabolic abnormalities in this process.

Dynamic contrast enhanced ultrasound in differential diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis.

BACKGROUND: Non-invasive differential diagnosis between hepatocellular carcinoma (HCC) and other liver cancer (i.e. cholangiocarcinoma or metastasis) is highly challenging and definitive diagnosis still relies on histological exam. The patterns of enhancement and wash-out of liver nodules can be used to stratify the risk of malignancy only in cirrhotic patients and HCC frequently shows atypical features. Dynamic contrast-enhanced ultrasound (DCEUS) with standardized software could help to overcome these obstacles, providing functional and quantitative parameters and potentially improving accuracy in the evaluation of tumor perfusion. AIM: To explore clinical evidence regarding the application of DCEUS in the differential diagnosis of liver nodules. METHODS: A comprehensive literature search of clinical studies was performed to identify the parameters of DCEUS that could relate to histological diagnosis. In accordance with the study protocol, a qualitative and quantitative analysis of the evidence was planned. RESULTS: Rise time was significantly higher in HCC patients with a standardized mean difference (SMD) of 0.83 (95%CI: 0.48-1.18). Similarly, other statistically significant parameters were mean transit time local with a SMD of 0.73 (95%CI: 0.20-1.27), peak enhancement with a SMD of 0.37 (95%CI: 0.03-0.70), area wash-in area under the curve with a SMD of 0.47 (95%CI: 0.13-0.81), wash-out area under the curve with a SMD of 0.55 (95%CI: 0.21-0.89) and wash-in and wash-out area under the curve with SMD of 0.51 (95%CI: 0.17-0.85). SMD resulted not significant in fall time and wash-in rate, but the latter presented a trend towards greater values in HCC compared to intrahepatic cholangiocarcinoma. CONCLUSION: DCEUS could improve non-invasive diagnosis of HCC, leading to less liver biopsy and early treatment. This quantitative analysis needs to be applied on larger cohorts to confirm these preliminary results.

Comprehensive analysis of clinical and biological value of ING family genes in liver cancer.

BACKGROUND: Liver cancer (LIHC) is a malignant tumor that occurs in the liver and has a high mortality in cancer. The ING family genes were identified as tumor suppressor genes. Dysregulated expression of these genes can lead to cell cycle arrest, senescence and/or apoptosis. ING family genes are promising targets for anticancer therapy. However, their role in LIHC is still not well understood. AIM: To have a better understanding of the important roles of ING family members in LIHC. METHODS: A series of bioinformatics approaches (including gene expression analysis, genetic alteration analysis, survival analysis, immune infiltration analysis, prediction of upstream microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) of ING1, and ING1-related gene functional enrichment analysis) was applied to study the expression profile, clinical relationship, prognostic significance and immune infiltration of ING in LIHC. The relationship between ING family genes expression and tumor associated immune checkpoints was investigated in LIHC. The molecular mechanism of ING1 mediated hepatocarcinogenesis was preliminarily discussed. RESULTS: mRNA/protein expression of different ING family genes in LIHC was analyzed in different databases, showing that ING family genes were highly expressed in LIHC. In 47 samples from 366 LIHC patients, the ING family genes were altered at a rate of 13%. By comprehensively analyzing the expression, clinical pathological parameters and prognostic value of ING family genes, ING1/5 was identified. ING1/5 was related to poor prognosis of LIHC, suggesting that they may play key roles in LIHC tumorigenesis and progression. One of the target miRNAs of ING1 was identified as hsa-miR-214-3p. Two upstream lncRNAs of hsa-miR-214-3p, U91328.1, and HCG17, were identified. At the same time, we found that the expression of ING family genes was correlated with immune cell infiltration and immune checkpoint genes. CONCLUSION: This study lays a foundation for further research on the potential mechanism and clinical value of ING family genes in the treatment and prognosis of LIHC.

N-glycosylation of Wnt3 regulates the progression of hepatocellular carcinoma by affecting Wnt/ß-catenin signal pathway.

BACKGROUND: Wnt/FZD-mediated signaling pathways are activated in more than 90% of hepatocellular carcinoma (HCC) cell lines. As a well-known secretory glycoprotein, Wnt3 can interact with FZD receptors on the cell surface, thereby activating the Wnt/ß-catenin signaling pathway. However, the N-glycosylation modification site of Wnt3 and the effect of this modification on the biological function of the protein are still unclear. AIM: To investigate the effect of Wnt3 N-glycosylation on the biological function of HCC cells. METHODS: Site-directed mutagenesis was used to verify the Wnt3 N-glycosylation sites, actinomycin D treatment was used to detect the stability of Wnt3 after site-directed mutation, the binding of the N-glycosylation site-directed mutant Wnt3 to FZD7 was observed by laser confocal microscopy, and the effects of the N-glycosylation site-directed mutation of Wnt3 on the Wnt/ß-catenin signaling pathway and the progression of HCC cells were detected by western blot and cell function experiments. RESULTS: Wnt3 has two N-glycosylation-modified sites (Asn90 and Asn301); when a single site at amino acid 301 is mutated, the stability of Wnt3 is weakened; the binding ability of Wnt3 to FZD7 decreases when both sites are mutated simultaneously; and the level of proteins related to the Wnt/ß-catenin signaling pathway is downregulated. Cell proliferation, migration and invasion are also weakened in the case of single 301 site and double-site mutations. CONCLUSION: These results indicate that by inhibiting the N-glycosylation of Wnt3, the proliferation, migration, invasion and colony formation abilities of liver cancer cells can be weakened, which might provide new therapeutic strategies for clinical liver cancer in the future.

Anticancer therapeutic potential of multimodal targeting agent- "phosphorylated galactosylated chitosan coated magnetic nanoparticles" against N-nitrosodiethylamine-induced hepatocellular carcinoma.

Superparamagnetic iron oxide nanoparticles (SPIONs) are extensively used as carriers in targeted drug delivery and has several advantages in the field of magnetic hyperthermia, chemodynamic therapy and magnet assisted radionuclide therapy. The characteristics of SPIONs can be tailored to deliver drugs into tumor via "passive targeting" and they can also be coated with tissue-specific agents to enhance tumor uptake via "active targeting". In our earlier studies, we developed HCC specific targeting agent- "phosphorylated galactosylated chitosan"(PGC) for targeting asialoglycoprotein receptors. Considering their encouraging results, in this study we developed a multifunctional targeting system- "phosphorylated galactosylated chitosan-coated magnetic nanoparticles"(PGCMNPs) for targeting HCC. PGCMNPs were synthesized by co-precipitation method and characterized by DLS, XRD, TEM, VSM, elemental analysis and FT-IR spectroscopy. PGCMNPs were evaluated for in vitro antioxidant properties, uptake in HepG2 cells, biodistribution, in vivo toxicity and were also evaluated for anticancer therapeutic potential against NDEA-induced HCC in mice model in terms of tumor status, electrical properties, antioxidant defense status and apoptosis. The characterization studies confirmed successful formation of PGCMNPs with superparamagnetic properties. The internalization studies demonstrated (99-100)% uptake of PGCMNPs in HepG2 cells. These results were also supported by biodistribution studies in which increased iron content (296%) was noted inside the hepatocytes. Further, PGCMNPs exhibited no in vivo toxicity. The anticancer therapeutic potential was evident from observation that PGCMNPs treatment decreased tumor bearing animals (41.6%) and significantly (p ≤ 0.05) lowered tumor multiplicity. Overall, this study indicated that PGCMNPs with improved properties are efficiently taken-up by hepatoma cells and has therapeutic potential against HCC. Further, this agent can be tagged with 32P and hence can offer multimodal cancer treatment options via radiation ablation as well as magnetic hyperthermia.

Fasting in combination with the cocktail Sorafenib:Metformin blunts cellular plasticity and promotes liver cancer cell death via poly-metabolic exhaustion.

PURPOSE: Dual-Interventions targeting glucose and oxidative metabolism are receiving increasing attention in cancer therapy. Sorafenib (S) and Metformin (M), two gold-standards in liver cancer, are known for their mitochondrial inhibitory capacity. Fasting, a glucose-limiting strategy, is also emerging as chemotherapy adjuvant. Herein, we explore the anti-carcinogenic response of nutrient restriction in combination with sorafenib:metformin (NR-S:M). RESULTS: Our data demonstrates that, independently of liver cancer aggressiveness, fasting synergistically boosts the anti-proliferative effects of S:M co-treatment. Metabolic and Cellular plasticity was determined by the examination of mitochondrial and glycolytic activity, cell cycle modulation, activation of cellular apoptosis, and regulation of key signaling and metabolic enzymes. Under NR-S:M conditions, early apoptotic events and the pro-apoptotic Bcl-xS/Bcl-xL ratio were found increased. NR-S:M induced the highest retention in cellular SubG1 phase, consistent with the presence of DNA fragments from cellular apoptosis. Mitochondrial functionality, Mitochondrial ATP-linked respiration, Maximal respiration and Spare respiratory capacity, were all found blunted under NR-S:M conditions. Basal Glycolysis, Glycolytic reserve, and glycolytic capacity, together with the expression of glycogenic (PKM), gluconeogenic (PCK1 and G6PC3), and glycogenolytic enzymes (PYGL, PGM1, and G6PC3), were also negatively impacted by NR-S:M. Lastly, a TMT-proteomic approach corroborated the synchronization of liver cancer metabolic reprogramming with the activation of molecular pathways to drive a quiescent-like status of energetic-collapse and cellular death. CONCLUSION: Altogether, we show that the energy-based polytherapy NR-S:M blunts cellular, metabolic and molecular plasticity of liver cancer. Notwithstanding the in vitro design of this study, it holds a promising therapeutic tool worthy of exploration for this tumor pathology.

Nano co-delivery of doxorubicin and plumbagin achieves synergistic chemotherapy of hepatocellular carcinoma.

Doxorubicin (DOX) is a chemotherapy drug used for hepatocellular carcinoma (HCC) treatment, but its effectiveness can be dramatically dampened by cancer cell chemoresistance. Signal transducer and activator of transcription 3 (STAT3) is implicated with drug resistance in a range of cancers (e.g., HCC), and the STAT3 inhibition can reverse the resistance of cancer cells to chemotherapeutic drugs. In the present study, a combination regimen to improve the efficiency of DOX was provided via the STAT3 blockade using plumbagin (PLB). A poly(lactic-co-glycolic acid) decorated by polyethylene glycol and aminoethyl anisamide was produced in the present study with the hope of generating the nanoparticles for co-delivery of DOX and PLB. The resulting co-formulation suppressed the STAT3 activity and achieved the synergistic chemotherapy, which led to tumor inhibition in the mice with subcutaneous DOX-resistant HCC, without causing any toxicity. The present study reveals the synergism of DOX and PLB, and demonstrates a promising combinatorial approach for treating HCC.

Exploring the diagnostic potential of immunoglobulin A-microbiota interplay in liver cirrhosis and spontaneous bacterial peritonitis.

The human gut microbiota significantly impacts health, including liver conditions like liver cirrhosis (LC) and spontaneous bacterial peritonitis (SBP). Immunoglobulin A (IgA) plays a central role in maintaining gut microbial balance. Understanding IgA's interplay with gut microbiota and liver health is crucial. This study explores the relationship between fecal IgA levels, gut microbiota, and liver injury severity. A total of 69 LC patients and 30 healthy controls were studied. Fecal IgA levels were measured using ELISA, and IgA-coated bacteria were quantified via flow cytometry. Microbiota diversity and composition were assessed through 16S rRNA sequencing. Liver injury severity was graded using the Child-Pugh score. Statistical analyses determined correlations. LC patients had higher fecal IgA levels than controls, correlating positively with liver injury severity. Microbiota diversity decreased with severity, accompanied by shifts in composition favoring pro-inflammatory species. Ralstonia abundance positively correlated with liver injury, whereas Faecalibacterium showed a negative correlation. Specific microbial markers for SBP were identified. Functional profiling revealed altered microbial functionalities in LC and SBP. Elevated fecal IgA levels, coupled with microbiota alterations, correlate with liver injury severity in LC patients. Modulating gut microbiota could be a promising strategy for managing liver-related conditions. Further research is needed to understand underlying mechanisms and translate findings into clinical practice, potentially improving patient outcomes.

Applications of single-cell multi-omics in liver cancer.

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Albumin-Based MUC13 Peptide Nanomedicine Suppresses Liver Cancer Stem Cells via JNK-ERK Signaling Pathway-Mediated Autophagy Inhibition.

Targeting liver cancer stem cells (LCSCs) is a promising strategy for hepatocellular carcinoma (HCC) therapy. Target selection and corresponding inhibitor screening are of vital importance for eliminating the stemness of LCSCs. Peptide-based agents are hopeful but have long been hindered for in vivo application. Herein, we selected a clinically significant target MUC13 and screened out a suitable peptide for preparation of an albumin-based MUC13 peptide nanomedicine, P3@HSA, which suppressed liver cancer stem cells via JNK-ERK signaling pathway-mediated autophagy inhibition. The selected target MUC13 was highly expressed in LCSCs and associated with the prognosis of liver cancer patients. Encouraged by this observation, we screened the corresponding peptide-based inhibitor P3 for further evaluation. P3 could interact with albumin through the intrinsic hydrophobic force and formed the nanomedicine P3@HSA. The prepared nanomedicine could inhibit LCSCs through JNK-ERK signaling pathway-mediated autophagy inhibition and exert potent antitumor effect both in vitro and in vivo. Together, this study provides a promising peptide-based nanomedicine for high-performance HCC treatment.

Liver and bile duct organoids and tumoroids.

Organoids refer to 3D cultures established to recapitulate histology, pathology, architecture, and genetic traits of various organs and tissues in the body, thereby replacing 2D cell cultures, xenograft, and animal models. Organoids form a 3D in vitro mimic of original tissues like the liver and are derived from embryonic or adult tissue stem cells. Liver and bile duct tumor organoids, also called, tumoroids capture genetic diversity, cellular, and pathophysiological properties of original tumors. Moreover, co-culture techniques along with genetic modulation of organoids allow for using tumoroids in liver and bile duct cancer research and drug screening/testing. Therefore, tumoroids are promising platforms for studying liver and bile duct cancer, which paves the way for the new era of personalized therapies. In the current review, we aimed to discuss liver and bile duct organoids with special emphasis on tumoroids and their applications, advantages, and shortcomings.

Non-Linear Association Between Liver Fibrosis Scores and Viral Load in Patients with Chronic Hepatitis B.

Background/Aims: Serum hepatitis B virus (HBV) DNA levels and non-invasive liver fibrosis scores are significantly associated with hepatocellular carcinoma (HCC) risk in chronic hepatitis B (CHB) patients. Nonetheless, the relationship between HBV DNA levels and liver fibrosis scores is unclear. Methods: A historical cohort comprising 6,949 non-cirrhotic Korean CHB patients without significant alanine aminotransferase elevation was investigated. The association of HBV DNA levels with the aspartate aminotransferase to platelet ratio index (APRI) and fibrosis (FIB)-4 score at baseline was analyzed using general linear models. Results: In HBeAg-negative patients (n=4,868), HBV DNA levels correlated linearly with both APRI and FIB-4 scores. In contrast, in HBeAg-positive patients (n=2,081), HBV DNA levels correlated inversely with both APRI and FIB-4 scores. Across the entire cohort, a significant non-linear parabolic relationship was identified between HBV DNA levels and fibrosis scores, independent of age and other covariates. Notably, moderate viral loads (6-7 log10 IU/mL) corresponded to the highest APRI and FIB-4 scores (P<0.001). Over a median 10-year follow-up, 435 patients (6.3%) developed HCC. Higher APRI scores ≥0.5 and FIB-4 scores ≥1.45 were significantly associated with elevated HCC risk (P<0.001 for both). HBV DNA level remained a significant predictive factor for HCC development, even after adjusting for APRI or FIB-4 scores. Conclusions: HBV viral load is significantly correlated with APRI and FIB-4 scores, and is also associated with HCC risk independent of those scores in CHB patients. These findings suggest that HBV DNA level is associated with hepatocarcinogenesis through both direct and indirect pathways.

Metabolomics research on treatment of primary liver cancer with Cortex Juglandis Mandshuricae on LC-MS/MS technology.

Diethylnitrosamine (DEN) was applied to create the primary liver cancer (PLC) animal model. In the study, the normal group, model group, cyclophosphamide (CTX) group, Cortex Juglandis Mandshuricae (CJM) extract group, myricetin group and myricitrin group were divided. LC-MS/MS technology was applied to determine the metabolites of liver tissue samples from different locations (nodular and non-nodular parts of liver tissue) in each group of rats. Through metabolomics research, the connection and difference of anti-PLC induced by the CJM extract, myricetin and myricitrin was analyzed. The surface of the liver tissues of rats in the model group was rough, dimly colored, inelastic, on which there were scattered gray white cancer nodules and blood stasis points. The number of cancer nodules was significantly reduced, and the degree of cell malignancy was low, but there were some inflammatory cell infiltrations, necrosis area and karyokinesis in the CJM extract group, myricetin group, myricitrin group and CTX group. The result of metabolic research indicated that 45 potential biomarkers of the PLC were found, as gamma-aminoisobutyrate, taurochenodeoxycholate, xanthurenic acid, etc. There were 22 differential metabolites in the CTX group, 16 differential metabolites in the CJM extract group, 14 differential metabolites in the myricetin group, 14 differential metabolites in the myricitrin group.

Dataset for analysis of metabolic pathways and their reversibility associated with anti-proliferative effect of metformin in liver cancer cells.

Despite epidemiological indications, utility of metformin in liver cancer remains debated and the understanding of the mechanism underlying its anti-cancer effects remains incomplete. Particularly, whether it operates via similar mechanism under glucose-sufficient and glucose- deficient environments or whether these effects are reversible remains unexplored. This metabolomic dataset was collected from liver cancer (HepG2) cells treated with metformin or placebo over a period of 3 h to 48 h as well as from cells recovering after metformin withdrawal. Cells were exposed to placebo or 2.5 mM metformin with or without glucose (5 mM) supplementation. The cells were harvested at 3, 6, 12, 24, and 48 h post-treatment. Cells were also harvested after 24 h of treatment under one of these conditions followed by reversal of glucose and/or metformin exposure status for 48 h. Metabolites from six biological replicates of each experimental group were extracted using chilled monophasic metabolite extraction solvent (Water: Acetonitrile: Isopropanol= 2:3:3) containing homovanillic acid as an internal standard. Samples were derivatized using MOX reagent followed by MSTFA. Untargeted metabolomic profiling of derivatized samples were performed using an Agilent 7890B gas chromatograph coupled to a 5977B single quadrupole mass spectrometer. Analytes were injected through a splitless liner and separated on a HP-5MS ultra-inert column using ultrapure helium as the carrier gas. Peak alignment, annotation, and integration were done using Agilent MassHunter Quantitative analysis software. Multivariate analysis was performed using MetaboAnalyst 5.0. These experiments were performed to unravel the longitudinal evolution of cellular metabolome in response to metformin treatment, its glucose dependence, as well as to examine the reversibility of these changes. The dataset can help to identify glucose-independent pathways involved in anti-cancer effect of metformin. The dataset can be used to design experiments to develop novel therapeutic combinations synergistically acting with metformin to cripple the metabolic fitness of cancer cells. It can also help to develop experiments to test the effect of metformin withdrawal in liver cancer.