An asparagine metabolism-based classification reveals the metabolic and immune heterogeneity of hepatocellular carcinoma

The glycolytic characteristics of hepatocellular carcinoma and its interaction with the microenvironment: a comprehensive omics study

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor characterized by a high recurrence rate and poor prognosis. This study aimed to identify glycolysis-related prognostic markers and immunological abnormalities in patients with HCC.

METHODS

We collected samples from cancerous and adjacent non-cancerous tissues for transcriptomic, metabolomic, and 16 S rRNA sequencing analyses. Glycolysis-related prognostic markers were identified by integrating public data from The Cancer Genome Atlas, GSE14520, and GSE76427 datasets. Additionally, single-cell sequencing data (GSE202642) were used to analyze the significantly infiltrated cellular subpopulations in HCC and investigate the expression of prognostic markers across different cell types. Spatial transcriptomics and mass cytometry (CyTOF) data were used to examine the expression differences in immune cells across tumor, peritumoral, and control tissues. Key prognostic markers were validated using reverse transcription-quantitative polymerase chain reaction, western blotting, and immunohistochemistry.

RESULTS

Differentially expressed genes (DEGs) between HCC and control tissues were primarily clustered in cell cycle and metabolic pathways, particularly in the glycolysis pathway. Metabolomic analysis identified 175 differentially expressed metabolites that were mainly enriched in digestive and amino acid metabolism pathways. 16 S rRNA analysis revealed a significant increase in the abundance of Aenigmarchaeota and a decrease in the abundance of Proteobacteria in HCC tissues. The former was positively associated with glycolysis, whereas the latter showed a negative association. Through public data integration, 17 glycolysis-related DEGs were identified and 101 predictive models were constructed using machine learning. The StepCox[both] + random survival forest model using AGL, G6PD, GOT2, and KIF20A exhibited the best diagnostic performance among the three datasets. Single-cell RNA sequencing indicated significant infiltration of CD8 + Tex, CD8 + T, CD8 + Trm, and epithelial cells in HCC tissues. AGL, G6PD, GOT2, and KIF20A were highly expressed in CD8 + Tex cells, CD8 + Trm cells, macrophages, and monocytes, respectively. Spatial transcriptomics and CyTOF analyses showed greater infiltration of CD8 + Tex and CD8 + Trm cells in tumor tissues than in controls. Molecular assays further confirmed that G6PD and KIF20A expression levels were significantly higher, whereas AGL and GOT2 expression levels were lower, in HCC tissues than in control tissues.

CONCLUSION

Through integrative multi-omics analysis, we identified glycolysis-related prognostic markers with distinct expression profiles across immune cell subsets in HCC. Our findings identify potential biomarkers and therapeutic targets for the diagnosis and treatment of HCC.

A human-like glutaminase-free asparaginase is highly efficacious in ASNSlow leukemia and solid cancer mouse xenograft models

L-asparaginase (L-ASNase) is crucial in treating pediatric acute lymphoblastic leukemia (ALL), but its use is hampered by side effects from the immunogenicity and L-glutaminase (L-GLNase) co-activity of FDA-approved bacterial L-ASNases, often leading to treatment discontinuation and poor outcomes. The toxicity of these L-ASNases makes them especially challenging to use in adult cancer patients. To overcome these issues, we developed EBD-200, a humanized guinea pig L-ASNase with low Km and no L-GLNase activity, eliminating glutamine-related toxicity. EBD-200 showed comparable anti-cancer effects to PEGylated L-ASNase in ASNSlow ALL, melanoma and liver cancer models, with improved tolerability. Its potent anti-cancer efficacy and enhanced safety profile suggest that EBD-200 could benefit ALL patients and broaden treatment options for ASNSlow solid cancers.

IGF2BP1 accelerates the aerobic glycolysis to boost its immune escape in hepatocellular carcinoma microenvironment

INTRODUCTION

Energy metabolism abnormity emerges as a crucial factor that facilitates tumorigenesis by accelerating aerobic glycolysis. However, the function of N6-methyladenosine (m6A) on hepatocellular carcinoma (HCC) aerobic glycolysis and immune escape is still unclear. Here, this investigation was intended to elucidate the regulation of m6A 'reader' IGF2BP1 involved in HCC aerobic glycolysis and immune escape.

METHODS

The aerobic glycolysis was tested by glucose uptake, lactate, ATP generation and ECAR. The CD8+ T cell-mediated killing effect was tested by cytotoxicity, IFN-γ and granzyme B. The molecular interaction was confirmed by luciferase reporter assay, immunoprecipitation assay and chromatin immunoprecipitation (ChIP)-PCR.

RESULTS

Elevated IGF2BP1 expression was associated with poor prognosis in HCC patients. Functionally, IGF2BP1 emerged as an oncogenic factor that accelerated HCC aerobic glycolysis (glucose uptake, lactate, ATP generation and ECAR) and oxaliplatin resistance. Meanwhile, IGF2BP1 repressed the activated CD8+ T cell-mediated killing effect (cytotoxicity, IFN-γ and granzyme B) and apoptosis of HCC cells, indicating a suppressed cytotoxic T-cell response. By recognizing and binding to the m6A-modified sites on c-Myc mRNA, IGF2BP1 enhanced the stability of c-Myc mRNA, consequently upregulating c-Myc expression. In addition, transcription factor c-Myc targeted the programmed death ligand 1 (PD-L1) promoter region to strengthen its transcription.

DISCUSSION

Taken together, this study illustrates IGF2BP1 as a potential therapeutic target in HCC, aiming to disrupt the interplay between aberrant metabolism and immune escape.

Asparagine: A key metabolic junction in targeted tumor therapy

Nutrient bioavailability in the tumor microenvironment plays a pivotal role in tumor proliferation and metastasis. Among these nutrients, glutamine is a key substance that promotes tumor growth and proliferation, and its downstream metabolite asparagine is also crucial in tumors. Studies have shown that when glutamine is exhausted, tumor cells can rely on asparagine to sustain their growth. Given the reliance of tumor cell proliferation on asparagine, restricting its bioavailability has emerged as promising strategy in cancer treatment. For instance, the use of asparaginase, an enzyme that depletes asparagine, has been one of the key chemotherapies for acute lymphoblastic leukemia (ALL). However, tumor cells can adapt to asparagine restriction, leading to reduced chemotherapy efficacy, and the mechanisms by which different genetically altered tumors are sensitized or adapted to asparagine restriction vary. We review the sources of asparagine and explore how limiting its bioavailability impacts the progression of specific genetically altered tumors. It is hoped that by targeting the signaling pathways involved in tumor adaptation to asparagine restriction and certain factors within these pathways, the issue of drug resistance can be addressed. Importantly, these strategies offer precise therapeutic approaches for genetically altered cancers.

Pan-cancer molecular signatures connecting aspartate transaminase (AST) to cancer prognosis, metabolic and immune signatures

Background

Serum aspartate transaminase (sAST) level is used routinely in conjunction with other clinical assays to assess liver health and disease. Increasing evidence suggests that sAST is associated with all-cause mortality and has prognostic value in several cancers, including gastrointestinal and urothelial cancers. Here, we undertake a systems approach to unravel molecular connections between AST and cancer prognosis, metabolism, and immune signatures at the transcriptomic and proteomic levels.

Methods

We mined public gene expression data across multiple normal and cancerous tissues using the Genotype Tissue Expression (GTEX) resource and The Cancer Genome Atlas (TCGA) to assess the expression of genes encoding AST isoenzymes (GOT1 and GOT2) and their association with disease prognosis and immune infiltration signatures across multiple tumors. We examined the associations between AST and previously reported pan-cancer molecular subtypes characterized by distinct metabolic and immune signatures. We analyzed human protein-protein interaction networks for interactions between GOT1 and GOT2 with cancer-associated proteins. Using public databases and protein-protein interaction networks, we determined whether the subset of proteins that interact with AST (GOT1 and GOT2 interactomes) are enriched with proteins associated with specific diseases, miRNAs and transcription factors.

Results

We show that AST transcript isoforms (GOT1 and GOT2) are expressed across a wide range of normal tissues. AST isoforms are upregulated in tumors of the breast, lung, uterus, and thymus relative to normal tissues but downregulated in tumors of the liver, colon, brain, kidney and skeletal sarcomas. At the proteomic level, we find that the expression of AST is associated with distinct pan-cancer molecular subtypes with an enrichment of specific metabolic and immune signatures. Based on human protein-protein interaction data, AST physically interacts with multiple proteins involved in tumor initiation, suppression, progression, and treatment. We find enrichments in the AST interactomes for proteins associated with liver and lung cancer and dermatologic diseases. At the regulatory level, the GOT1 interactome is enriched with the targets of cancer-associated miRNAs, specifically mir34a - a promising cancer therapeutic, while the GOT2 interactome is enriched with proteins that interact with cancer-associated transcription factors.

Conclusions

Our findings suggest that perturbations in the levels of AST within specific tissues reflect pathophysiological changes beyond tissue damage and have implications for cancer metabolism, immune infiltration, prognosis, and treatment personalization.

CD69 serves as a potential diagnostic and prognostic biomarker for hepatocellular carcinoma

The prevalence and mortality of hepatocellular carcinoma (HCC) are still increasing. This study aimed to identify potential therapeutic targets related to patient prognosis. Data were downloaded from TCGA, GSE25097, GSE36376, and GSE76427 datasets. Differential analysis and enrichment analysis were performed in HCC. Cell deaths were evaluated, and least absolute shrinkage and selection operator regression (LASSO) regression was analyzed to screen candidate genes. Additionally, immune cell infiltration in HCC was assessed. We identified 4088 common DEGs with the same direction of differential expression in all four datasets, they were mainly enriched in immunoinflammation and cell cycle pathways. Apoptosis was significantly suppressed in HCC in GSEA and GSVA. After LASSO regression analysis, we screened CD69, CDC25B, MGMT, TOP2A, and TXNIP as candidate genes. Among them, CD69 significantly influenced the overall survival of HCC patients in both TCGA and GSE76427. CD69 may be a protective factor for outcome of HCC patients. In addition, CD69 was positive correlation with T cells and CD3E. CD69, CDC25B, MGMT, TOP2A, and TXNIP were potential diagnostic and prognostic target for HCC, especially CD69.

Metabolic Reprogramming of HCC: A New Microenvironment for Immune Responses

Hepatocellular carcinoma is the most common primary liver cancer, ranking third among the leading causes of cancer-related mortality worldwide and whose incidence varies according to geographical area and ethnicity. Metabolic rewiring was recently introduced as an emerging hallmark able to affect tumor progression by modulating cancer cell behavior and immune responses. This review focuses on the recent studies examining HCC's metabolic traits, with particular reference to the alterations of glucose, fatty acid and amino acid metabolism, the three major metabolic changes that have gained attention in the field of HCC. After delivering a panoramic picture of the peculiar immune landscape of HCC, this review will also discuss how the metabolic reprogramming of liver cancer cells can affect, directly or indirectly, the microenvironment and the function of the different immune cell populations, eventually favoring the tumor escape from immunosurveillance.

Influenced tumor microenvironment and tumor immunity by amino acids

It is widely accepted that tumors are a complex tissue composed of cancer cells, extracellular matrix, inflammatory cells, immune cells, and other cells. Deregulation of tumor microenvironment promotes tumor aggressiveness by sustaining cell growth, invasion, and survival from immune surveillance. The concepts that some dietary nutrients could change tumor microenvironment are extremely attractive. Many studies demonstrated that high-fat diet-induced obesity shaped metabolism to suppress anti-tumor immunity, but how amino acids changed the tumor microenvironment and impacted tumor immunity was still not totally understood. In fact, amino acid metabolism in different signaling pathways and their cross-talk shaped tumor immunity and therapy efficacy in cancer patients. Our review focused on mechanisms by which amino acid influenced tumor microenvironment, and found potential drug targets for immunotherapy in cancer.

A High-Throughput Sequencing Data-Based Classifier Reveals the Metabolic Heterogeneity of Hepatocellular Carcinoma

Metabolic heterogeneity plays a key role in poor outcomes in malignant tumors, but its role in hepatocellular carcinoma (HCC) remains largely unknown. In the present study, we aim to disentangle the metabolic heterogeneity features of HCC by developing a classification system based on metabolism pathway activities in high-throughput sequencing datasets. As a result, HCC samples were classified into two distinct clusters: cluster 1 showed high levels of glycolysis and pentose phosphate pathway activity, while cluster 2 exhibited high fatty acid oxidation and glutaminolysis status. This metabolic reprogramming-based classifier was found to be highly correlated with several clinical variables, including overall survival, prognosis, TNM stage, and 𝛼-fetoprotein (AFP) expression. Of note, activated oncogenic pathways, a higher TP53 mutation rate, and increased stemness were also observed in cluster 1, indicating a causal relationship between metabolic reprogramming and carcinogenesis. Subsequently, distinct metabolism-targeted therapeutic strategies were proven in human HCC cell lines, which exhibit the same metabolic properties as corresponding patient samples based on this classification system. Furthermore, the metabolic patterns and effects of different types of cells in the tumor immune microenvironment were explored by referring to both bulk and single-cell data. It was found that malignant cells had the highest overall metabolic activities, which may impair the anti-tumor capacity of CD8+ T cells through metabolic competition, and this provided a potential explanation for why immunosuppressive cells had higher overall metabolic activities than those with anti-tumor functions. Collectively, this study established an HCC classification system based on the gene expression of energy metabolism pathways. Its prognostic and therapeutic value may provide novel insights into personalized clinical practice in patients with metabolic heterogeneity.