Metabolic heterogeneity of human hepatocellular carcinoma: implications for personalized pharmacological treatment

Recreating metabolic interactions of the tumour microenvironment

Tumours are heterogeneous tissues containing diverse populations of cells and an abundant extracellular matrix (ECM). This tumour microenvironment prompts cancer cells to adapt their metabolism to survive and grow. Besides epigenetic factors, the metabolism of cancer cells is shaped by crosstalk with stromal cells and extracellular components. To date, most experimental models neglect the complexity of the tumour microenvironment and its relevance in regulating the dynamics of the metabolism in cancer. We discuss emerging strategies to model cellular and extracellular aspects of cancer metabolism. We highlight cancer models based on bioengineering, animal, and mathematical approaches to recreate cell-cell and cell-matrix interactions and patient-specific metabolism. Combining these approaches will improve our understanding of cancer metabolism and support the development of metabolism-targeting therapies.

The Role of Metabolic Reprogramming in the Tumor Immune Microenvironment: Mechanisms and Opportunities for Immunotherapy in Hepatocellular Carcinoma

As one of the emerging hallmarks of tumorigenesis and tumor progression, metabolic remodeling is common in the tumor microenvironment. Hepatocellular carcinoma (HCC) is the third leading cause of global tumor-related mortality, causing a series of metabolic alterations in response to nutrient availability and consumption to fulfill the demands of biosynthesis and carcinogenesis. Despite the efficacy of immunotherapy in treating HCC, the response rate remains unsatisfactory. Recently, research has focused on metabolic reprogramming and its effects on the immune state of the tumor microenvironment, and immune response rate. In this review, we delineate the metabolic reprogramming observed in HCC and its influence on the tumor immune microenvironment. We discuss strategies aimed at enhancing response rates and overcoming immune resistance through metabolic interventions, focusing on targeting glucose, lipid, or amino acid metabolism, as well as systemic regulation.

Characterizing Metabolic Heterogeneity of Hepatocellular Carcinoma with Hyperpolarized 13C Pyruvate MRI and Mass Spectrometry

Purpose To characterize the metabolomic profiles of two hepatocellular carcinoma (HCC) rat models, track evolution of these profiles to a stimulated tumor state, and assess their effect on lactate flux with hyperpolarized (HP) carbon 13 (13C) MRI. Materials and Methods Forty-three female adult Fischer rats were implanted with N1S1 or McA-RH7777 HCC tumors. In vivo lactate-to-pyruvate ratio (LPR) was measured with HP 13C MRI at 9.4 T. Ex vivo mass spectrometry was used to measure intratumoral metabolites, and Ki67 labeling was used to quantify proliferation. Tumors were first compared with three normal liver controls. The tumors were then compared with stimulated variants via off-target hepatic thermal ablation treatment. All comparisons were made using the Mann-Whitney test. Results HP 13C pyruvate MRI showed greater LPR in N1S1 tumors compared with normal liver (mean [SD], 0.564 ± 0.194 vs 0.311 ± 0.057; P < .001 [n = 9]), but not for McA-RH7777 (P = .44 [n = 8]). Mass spectrometry confirmed that the glycolysis pathway was increased in N1S1 tumors and decreased in McA-RH7777 tumors. The pentose phosphate pathway was also decreased only in McA-RH7777 tumors. Increased proliferation in stimulated N1S1 tumors corresponded to a net increase in LPR (six stimulated vs six nonstimulated, 0.269 ± 0.148 vs 0.027 ± 0.08; P = .009), but not in McA-RH7777 (eight stimulated vs six nonstimulated, P = .13), despite increased proliferation and metastases. Mass spectrometry demonstrated relatively increased lactate production with stimulation in N1S1 tumors only. Conclusion Two HCC subtypes showed divergent glycolytic dependency at baseline and during transformation to a high proliferation state. This metabolic heterogeneity in HCC should be considered with use of HP 13C MRI for diagnosis and tracking. Keywords: Molecular Imaging-Probe Development, Liver, Abdomen/GI, Oncology, Hepatocellular Carcinoma © RSNA, 2024 See also commentary by Ohliger in this issue.

Kinetic Modeling of Hepatic Metabolism and Simulation of Treatment Effects

Mathematical modeling is a promising strategy to fill the experimentally unapproachable knowledge gaps about the relative contribution of various molecular processes to cellular metabolic function. To this end, we developed detailed kinetic models of the central metabolism of different cell types, comprising multiple metabolic functionalities. We used the model to simulate metabolic changes in several cell types under different experimental settings in health and disease. In this way, we show that it is possible to decipher and characterize the relative influence of various metabolic pathways and enzymes to overall metabolic performance and phenotype.Quantitative Systems Metabolism (QSM™) allows quantitative assessment of metabolic functionality and metabolic profiling based on proteomic data. Here, we describe the technique, namely, molecular resolved kinetic modeling, underlying QSM™. We explain the necessary steps for the generation of cell-specific models to functionally interpret proteomic data and point out some unresolved challenges and open questions.

Glycolysis, a new mechanism of oleuropein against liver tumor

BACKGROUND

Benign and malignant liver tumors are prevalent worldwide. However, there is no effective and comprehensive treatment option for many patients with malignant tumors. Thus, it is critical to prevent benign tumors from worsening, increasing the number of treatment options and effective medications against malignant liver tumors. Oleuropein is a natural and non-toxic product and inhibits tumor growth in various ways.

METHODS

We employed bioinformatics analysis and molecular docking to identify potential targets of oleuropein. Surface plasmon resonance (SPR) was used to determine the direct binding strength of the target and compounds. Essential functionalities of the targets were analyzed using gene interference approaches. Transcriptomic studies were performed to observe the global genomic alterations occurring inside cells. Changes in glycolytic metabolites and gene and protein expressions were also detected. The anti-tumor benefits of oleuropein in vivo were determined using a tumor-bearing mouse model.

RESULTS

Glucose-6-phosphate isomerase (GPI) was found to be a direct target of oleuropein. GPI discontinuation in liver tumor cells altered the expression of many genes, causing glycogenolysis. GPI interference was associated with PYGM and PFKFB4 inhibitors to inhibit glycolysis in liver tumors. Oleuropein inhibited glycolysis and showed good anti-tumor activity in vivo without adverse side effects.

CONCLUSIONS

GPI is a crucial enzyme in glycolysis and the immediate target of oleuropein. GPI expression inside tumor cells affects different physiological functions and signal transduction. Oleuropein has depicted anti-tumor action in vivo without harmful side effects. Moreover, it can control tumor glycolysis through GPI.

On the relationship between metabolic capacities and in vivo viscoelastic properties of the liver

The liver is the central metabolic organ. It constantly adapts its metabolic capacity to current physiological requirements. However, the relationship between tissue structure and hepatic function is incompletely understood; this results in a lack of diagnostic markers in medical imaging that can provide information about the liver's metabolic capacity. Therefore, using normal rabbit livers, we combined magnetic resonance elastography (MRE) with proteomics-based kinetic modeling of central liver metabolism to investigate the potential role of MRE for predicting the liver's metabolic function in vivo. Nineteen New Zealand white rabbits were investigated by multifrequency MRE and positron emission tomography (PET). This yielded maps of shear wave speed (SWS), penetration rate (PR) and standardized uptake value (SUV). Proteomic analysis was performed after the scans. Hepatic metabolic functions were assessed on the basis of the HEPATOKIN1 model in combination with a model of hepatic lipid-droplet metabolism using liquid chromatography-mass spectrometry. Our results showed marked differences between individual livers in both metabolic functions and stiffness properties, though not in SUV. When livers were divided into 'stiff' and 'soft' subgroups (cutoff SWS = 1.6 m/s), stiff livers showed a lower capacity for triacylglycerol storage, while at the same time showing an increased capacity for gluconeogenesis and cholesterol synthesis. Furthermore, SWS was correlated with gluconeogenesis and PR with urea production and glutamine exchange. In conclusion, our study indicates a close relationship between the viscoelastic properties of the liver and metabolic function. This could be used in future studies to predict non-invasively the functional reserve capacity of the liver in patients.

Chemokine clouding and liver cancer heterogeneity: Does it impact clinical outcomes?

Tumor heterogeneity is a predominant feature of hepatocellular carcinoma (HCC) that plays a crucial role in chemoresistance and limits the efficacy of available chemo/immunotherapy regimens. Thus, a better understanding regarding the molecular determinants of tumor heterogeneity will help in developing newer strategies for effective HCC management. Chemokines, a sub-family of cytokines are one of the key molecular determinants of tumor heterogeneity in HCC and are involved in cell survival, growth, migration, and angiogenesis. Herein, we provide a panoramic insight into the role of chemokines in HCC heterogeneity at genetic, epigenetic, metabolic, immune cell composition, and tumor microenvironment levels and its impact on clinical outcomes. Interestingly, our in-silico analysis data showed that expression of chemokine receptors impacts infiltration of various immune cell populations into the liver tumor and leads to heterogeneity. Thus, it is evident that aberrant chemokines clouding impacts HCC tumor heterogeneity and understanding this phenomenon in depth could be harnessed for the development of personalized medicine strategies in future.

Critical Investigation of the Usability of Hepatoma Cell Lines HepG2 and Huh7 as Models for the Metabolic Representation of Resectable Hepatocellular Carcinoma

Metabolic alterations in hepatocellular carcinoma (HCC) are fundamental for the development of diagnostic screening and therapeutic intervention since energy metabolism plays a central role in differentiated hepatocytes. In HCC research, hepatoma cell lines (HCLs) like HepG2 and Huh7 cells are still the gold standard. In this study, we characterized the metabolic profiles of primary human hepatoma cells (PHCs), HCLs and primary human hepatocytes (PHHs) to determine their differentiation states. PHCs and PHHs (HCC-PHHs) were isolated from surgical specimens of HCC patients and their energy metabolism was compared to PHHs from non-HCC patients and the HepG2 and Huh7 cells at different levels (transcript, protein, function). Our analyses showed successful isolation of PHCs with a purity of 50–73% (CK18+). The transcript data revealed that changes in mRNA expression levels had already occurred in HCC-PHHs. While many genes were overexpressed in PHCs and HCC-PHHs, the changes were mostly not translated to the protein level. Downregulated metabolic key players of PHCs revealed a correlation with malign transformation and were predominantly pronounced in multilocular HCC. Therefore, HCLs failed to reflect these expression patterns of PHCs at the transcript and protein levels. The metabolic characteristics of PHCs are closer to those of HCC-PHHs than to HCLs. This should be taken into account for future optimized tumor metabolism research.

E2F1‐mediated AUF1 upregulation promotes HCC development and enhances drug resistance via stabilization of AKR1B10

The AU‐rich binding factor 1 (AUF1) is one of the well known adenylate‐uridylate‐rich element (ARE)‐specific RNA‐binding proteins (ARE‐BPs) for which dysregulation has been reported in various human cancers. However, the involvement of AUF1 in the initiation and progression of hepatocellular carcinoma (HCC) is still elusive. In this study, we aimed at exploring the clinical significance, function, and mechanism of the abnormal expression of AUF1 in HCC. Using a bioinformatics analysis of The Cancer Genome Atlas (TCGA) and Liver Cancer Institute (LCI) database, we identified that AUF1 was abnormally highly expressed in HCC tissues and that the high expression of AUF1 was correlated with poor prognosis in patients with HCC. We also confirmed the increased AUF1 expression and its prognostic value in our HBV‐related HCC cohorts. AUF1 overexpression in hepatoma cells promoted cell proliferation and increased the resistance of hepatoma cells toward doxorubicin, whereas knockdown of AUF1 exerted the opposite effects. Mechanistically, we demonstrated that AKR1B10 was a critical target of AUF1 and was essential for sustaining the AUF1‐induced proliferation and drug resistance of hepatoma cells. AUF1 increased AKR1B10 expression by binding to the 3′UTR region of AKR1B10 mRNA and stabilizing AKR1B10 mRNA. Additionally, we demonstrated that E2F1 enhanced AUF1 expression in HCC at the transcription level. Our study revealed a novel role of AUF1 in promoting the development and drug resistance of HCC via the post‐transcriptional regulation of AKR1B10 expression. The E2F1/AUF1/AKR1B10 axis can serve as a potential therapeutic target in HCC.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

Characterization of metabolic landscape in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, accounting for approximately 75%-85% of primary liver cancers. Metabolic alterations have been labeled as an emerging hallmark of tumors. Specially, the last decades have registered a significant improvement in our understanding of the role of metabolism in driving the carcinogenesis and progression of HCC. In this paper, we provide a review of recent studies that investigated the metabolic traits of HCC with a specific focus on three common metabolic alterations involving glycolysis, lipid metabolism, and glutamine addiction which have been gaining much attention in the field of HCC. Next, we describe some representative diagnostic markers or tools, and promising treatment agents that are proposed on the basis of the aforementioned metabolic alterations for HCC. Finally, we present some challenges and directions that may promisingly speed up the process of developing objective diagnostic markers and therapeutic options underlying HCC. Specifically, we recommend future investigations to carefully take into account the influence of heterogeneity, control for study-specific confounds, and invite the validation of existing biomarkers.

PlGF knockdown attenuates hypoxia-induced stimulation of cell proliferation and glycolysis of lung adenocarcinoma through inhibiting Wnt/β-catenin pathway

Background

Angiogenic placental growth factor (PlGF) plays a role in hypoxia-induced angiogenesis. Here, we aimed to investigate the biological roles of PlGF in cell proliferation and glycolysis of lung adenocarcinoma (LUAD) and the underlying molecular mechanisms.

Methods

PlGF was knocked down in H358 and H1975 cells by lentiviruses, which were then cultured under hypoxia (90% N₂, 5%CO₂ and 5%O₂) for 24 h. PlGF was overexpressed in PC9 cells treated with XAV939, inhibitor of Wnt/β-catenin signaling pathway. PlGF-silencing H1975 cells were implanted into mice, and tumor xenografts were harvested and analyzed.

Results

Hypoxia treatment led to up-regulation of PlGF, C-myc, lactate dehydrogenase A (LDHA), and β-catenin, promotion of cell proliferation and glycolysis in H358 and H1975 cells, which were obviously reversed by knocking down PlGF. In tumors, PlGF knockdown significantly prohibited cell proliferation and glycolysis, and decreased expression of C-myc, LDHA, and β-catenin. PlGF overexpression markedly strengthened cell proliferation, which was inhibited by β-catenin knockdown. Consistently, XAV939, inhibitor of Wnt/β-catenin pathway, also inhibited PlGF-induced cell proliferation, glycolysis, and β-catenin expression in PC9 cells.

Conclusion

PlGF knockdown inhibited the stimulatory effect of hypoxia on cell proliferation and glycolysis of LUAD through deactivating Wnt/β-catenin pathway.

Metformin: Metabolic Rewiring Faces Tumor Heterogeneity

Tumor heterogeneity impinges on all the aspects of tumor history, from onset to metastasis and relapse. It is growingly recognized as a propelling force for tumor adaptation to environmental and micro-environmental cues. Metabolic heterogeneity perfectly falls into this process. It strongly contributes to the metabolic plasticity which characterizes cancer cell subpopulations-capable of adaptive switching under stress conditions, between aerobic glycolysis and oxidative phosphorylation-in both a convergent and divergent modality. The mitochondria appear at center-stage in this adaptive process and thus, targeting mitochondria in cancer may prove of therapeutic value. Metformin is the oldest and most used anti-diabetic medication and its relationship with cancer has witnessed rises and falls in the last 30 years. We believe it is useful to revisit the main mechanisms of action of metformin in light of the emerging views on tumor heterogeneity. We first analyze the most consolidated view of its mitochondrial mechanism of action and then we frame the latter in the context of tumor adaptive strategies, cancer stem cell selection, metabolic zonation of tumors and the tumor microenvironment. This may provide a more critical point of view and, to some extent, may help to shed light on some of the controversial evidence for metformin's anticancer action.