OGDHL silencing promotes hepatocellular carcinoma by reprogramming glutamine metabolism

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients

OBJECTIVE

The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear.

METHODS

The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored.

RESULTS

A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes.

CONCLUSION

Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.

Necroptosis-Mediated Synergistic Photodynamic and Glutamine-Metabolic Therapy Enabled by a Biomimetic Targeting Nanosystem for Cholangiocarcinoma

Targeted delivery of glutamine metabolism inhibitors holds promise for cholangiocarcinoma therapy, yet effective delivery vehicles remain a challenge. This study reports the development of a biomimetic nanosystem, termed R-CM@MSN@BC, integrating mesoporous organosilicon nanoparticles with reactive oxygen species-responsive diselenide bonds for controlled release of the glutamine metabolism inhibitor bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES) and the photosensitizer Ce6. Erythrocyte membrane coating, engineered with Arg-Gly-Asp (RGD) peptides, not only enhanced biocompatibility but also improved tumor targeting and tissue penetration. Upon laser irradiation, R-CM@MSN@BC executed both photodynamic and glutamine-metabolic therapies, inducing necroptosis in tumor cells and triggering significant immunogenic cell death. Time-of-flight mass cytometry analysis revealed that R-CM@MSN@BC can remodel the immunosuppressive tumor microenvironment by polarizing M1-type macrophages, reducing infiltration of M2-type and CX3CR1+ macrophages, and decreasing T cell exhaustion, thereby increasing the effectiveness of anti-programmed cell death ligand 1 immunotherapy. This strategy proposed in this study presents a viable and promising approach for the treatment of cholangiocarcinoma.

Cinobufacini Inhibits Survival and Metastasis of Hepatocellular Carcinoma via c-Met Signaling Pathway

OBJECTIVE

To investigate the anti-tumor effects of cinobufacini (CINO) on hepatocellular carcinoma (HCC) induced by des-gamma-carboxy-prothrombin (DCP) and to uncover the underlying mechanisms.

METHODS

The inhibitory effect of CINO on HCC cell proliferation was evaluated using the cell counting kit-8 method, and the apoptosis rate was quantified using flow cytometry. Immunofluorescence and Western blot analyses were used to investigate the differential expression of proteins associated with cell growth, apoptosis, migration, and invasion pathways after CINO treatment. The therapeutic potential of CINO for HCC was confirmed, and the possibility of combining cinobufacini with c-Met inhibitor for the treatment of primary HCC was further validated by in vivo experiments.

RESULTS

Under the induction of DCP, CINO inhibited the activity of HCC cells, induced apoptosis, and inhibited migration and invasion. Upon the induction of DCP, CINO regulated c-Met activation and the activation of the phosphatidylinositol-3 kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase kinase/extracellular signal-regulated kinase (MEK/ERK) pathways. In a mouse model of HCC, CINO exhibited significant antitumor effects by inhibiting the phosphorylation of c-Met and the downstream PI3K/AKT and MEK/ERK pathways in tumor tissues.

CONCLUSIONS

CINO inhibited HCC cell growth, promoted apoptosis, and suppressed HCC cell invasion and migration by targeting c-Met and PI3K/AKT and MEK/ERK signaling pathways under DCP induction.

Research progress in the metabolic reprogramming of hepatocellular carcinoma (Review)

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and its morbidity is increasing worldwide due to increasing prevalence. Metabolic reprogramming has been recognized as a hallmark of cancer and serves a role in cancer progression. Glucose, lipids and amino acids are three major components whose altered metabolism can directly affect the energy production of cells, including liver cancer cells. Nutrients and energy are indispensable for the growth and proliferation of cancer cells, thus altering the metabolism of hepatoma cells can inhibit the progression of HCC. The present review summarizes recent studies on tumour regulatory molecules, including numerous noncoding RNAs, oncogenes and tumour suppressors, which regulate the metabolic activities of glucose, lipids and amino acids by targeting key enzymes, signalling pathways or interactions between the two. These regulatory molecules can regulate the rapid proliferation of cancer cells, tumour progression and treatment resistance. It is thought that these tumour regulatory factors may serve as therapeutic targets or valuable biomarkers for HCC, with the potential to mitigate HCC drug resistance. Furthermore, the advantages and disadvantages of metabolic inhibitors as a treatment approach for HCC, as well as possible solutions are discussed, providing insights for developing more effective treatment strategies for HCC.

Modulating PCGF4/BMI1 Stability Is an Efficient Metastasis-Regulatory Strategy Used by Distinct Subtypes of Cancer-Associated Fibroblasts in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm prone to metastasis. Whether cancer-associated fibroblasts (CAFs) affect the metastasis of ICC is unclear. Herein, ICC patient-derived CAF lines and related cancerous cell lines were established and the effects of CAFs on the tumor progressive properties of the ICC cancerous cells were analyzed. CAFs could be classified into cancer-restraining or cancer-promoting categories based on distinct tumorigenic effects. The RNA-sequencing analyses of ICC cancerous cell lines identified polycomb group ring finger 4 (PCGF4; alias BMI1) as a potential metastasis regulator. The changes of PCGF4 levels in ICC cells mirrored the restraining or promoting effects of CAFs on ICC migration. Immunohistochemical analyses on the ICC tissue microarrays indicated that PCGF4 was negatively correlated with overall survival of ICC. The promoting effects of PCGF4 on cell migration, drug resistance activity, and stemness properties were confirmed. Mechanistically, cancer-restraining CAFs triggered the proteasome-dependent degradation of PCGF4, whereas cancer-promoting CAFs enhanced the stability of PCGF4 via activating the IL-6/phosphorylated STAT3 pathway. In summary, the current data identified the role of CAFs in ICC metastasis and revealed a new mechanism of the CAFs on ICC progression in which PCGF4 acted as the key effector by both categories of CAFs. These findings shed light on developing comprehensive therapeutic strategies for ICC.

Harnessing CD8+ T cell dynamics in hepatitis B virus-associated liver diseases: Insights, therapies and future directions

Hepatitis B virus (HBV) infection playsa significant role in the etiology and progression of liver-relatedpathologies, encompassing chronic hepatitis, fibrosis, cirrhosis, and eventual hepatocellularcarcinoma (HCC). Notably, HBV infection stands as the primary etiologicalfactor driving the development of HCC. Given the significant contribution ofHBV infection to liver diseases, a comprehensive understanding of immunedynamics in the liver microenvironment, spanning chronic HBV infection,fibrosis, cirrhosis, and HCC, is essential. In this review, we focused on thefunctional alterations of CD8+ T cells within the pathogenic livermicroenvironment from HBV infection to HCC. We thoroughly reviewed the roles ofhypoxia, acidic pH, metabolic reprogramming, amino acid deficiency, inhibitory checkpointmolecules, immunosuppressive cytokines, and the gut-liver communication in shapingthe dysfunction of CD8+ T cells in the liver microenvironment. Thesefactors significantly impact the clinical prognosis. Furthermore, we comprehensivelyreviewed CD8+ T cell-based therapy strategies for liver diseases,encompassing HBV infection, fibrosis, cirrhosis, and HCC. Strategies includeimmune checkpoint blockades, metabolic T-cell targeting therapy, therapeuticT-cell vaccination, and adoptive transfer of genetically engineered CD8+ T cells, along with the combined usage of programmed cell death protein-1/programmeddeath ligand-1 (PD-1/PD-L1) inhibitors with mitochondria-targeted antioxidants.Given that targeting CD8+ T cells at various stages of hepatitis Bvirus-induced hepatocellular carcinoma (HBV + HCC) shows promise, we reviewedthe ongoing need for research to elucidate the complex interplay between CD8+ T cells and the liver microenvironment in the progression of HBV infection toHCC. We also discussed personalized treatment regimens, combining therapeuticstrategies and harnessing gut microbiota modulation, which holds potential forenhanced clinical benefits. In conclusion, this review delves into the immunedynamics of CD8+ T cells, microenvironment changes, and therapeuticstrategies within the liver during chronic HBV infection, HCC progression, andrelated liver diseases.

GLS and GLS2 Glutaminase Isoenzymes in the Antioxidant System of Cancer Cells

A pathway frequently altered in cancer is glutaminolysis, whereby glutaminase (GA) catalyzes the main step as follows: the deamidation of glutamine to form glutamate and ammonium. There are two types of GA isozymes, named GLS and GLS2, which differ considerably in their expression patterns and can even perform opposing roles in cancer. GLS correlates with tumor growth and proliferation, while GLS2 can function as a context-dependent tumor suppressor. However, both isoenzymes have been described as essential molecules handling oxidant stress because of their involvement in glutathione production. We reviewed the literature to highlight the critical roles of GLS and GLS2 in restraining ROS and regulating both cellular signaling and metabolic stress due to their function as indirect antioxidant enzymes, as well as by modulating both reductive carboxylation and ferroptosis. Blocking GA activity appears to be a potential strategy in the dual activation of ferroptosis and inhibition of cancer cell growth in a ROS-mediated mechanism.

Sweet dreams could be made of this: carbohydrate-responsive element-binding protein (ChREBP) as a target for hepatocellular carcinoma therapy

Rewiring of cellular metabolism is now fully recognized as a hallmark of cancer. Tumor cells reprogram metabolic pathways to meet the energetic and macromolecular demands to support unrestricted growth and survival under unfavorable conditions. It is becoming apparent that these adaptations underpin most of the traits that define a cancer cell's identity, including the ability to avoid immune surveillance, endure nutrient and oxygen restrictions, detach and migrate from their natural histological niche, and avert human-made aggressions (i.e., therapy). In a recent study, Benichou and collaborators identify carbohydrate-responsive element-binding protein (ChREBP), a master regulator of physiological glucose metabolism, as an oncogene in hepatocellular carcinoma (HCC) development. Upregulation of ChREBP expression results in a self-stimulatory loop interconnecting PI3K/AKT signaling and glucose metabolism to feed fatty acid and nucleotide synthesis supporting tumorigenesis. Importantly, pharmacological inhibition of ChREBP activity quells in vivo HCC tumor growth without causing systemic toxicity. This study identifies novel oncometabolic pathways and open up new avenues to improve the treatment of a deadly tumor.

Exploring the dynamic three-dimensional chromatin architecture and transcriptional landscape in goose liver tissues underlying metabolic adaptations induced by a high-fat diet

BACKGROUND

Goose, descendants of migratory ancestors, have undergone extensive selective breeding, resulting in their remarkable ability to accumulate fat in the liver and exhibit a high tolerance for significant energy intake. As a result, goose offers an excellent model for studying obesity, metabolic disorders, and liver diseases in mammals. Although the impact of the three-dimensional arrangement of chromatin within the cell nucleus on gene expression and transcriptional regulation is widely acknowledged, the precise functions of chromatin architecture reorganization during fat deposition in goose liver tissues still need to be fully comprehended.

RESULTS

In this study, geese exhibited more pronounced changes in the liver index and triglyceride (TG) content following the consumption of the high-fat diet (HFD) than mice without significant signs of inflammation. Additionally, we performed comprehensive analyses on 10 goose liver tissues (5 HFD, 5 normal), including generating high-resolution maps of chromatin architecture, conducting whole-genome gene expression profiling, and identifying H3K27ac peaks in the livers of geese and mice subjected to the HFD. Our results unveiled a multiscale restructuring of chromatin architecture, encompassing Compartment A/B, topologically associated domains, and interactions between promoters and enhancers. The dynamism of the three-dimensional genome architecture, prompted by the HFD, assumed a pivotal role in the transcriptional regulation of crucial genes. Furthermore, we identified genes that regulate chromatin conformation changes, contributing to the metabolic adaptation process of lipid deposition and hepatic fat changes in geese in response to excessive energy intake. Moreover, we conducted a cross-species analysis comparing geese and mice exposed to the HFD, revealing unique characteristics specific to the goose liver compared to a mouse. These chromatin conformation changes help elucidate the observed characteristics of fat deposition and hepatic fat regulation in geese under conditions of excessive energy intake.

CONCLUSIONS

We examined the dynamic modifications in three-dimensional chromatin architecture and gene expression induced by an HFD in goose liver tissues. We conducted a cross-species analysis comparing that of mice. Our results contribute significant insights into the chromatin architecture of goose liver tissues, offering a novel perspective for investigating mammal liver diseases.

Multi-Enzyme Activity of MIL-101 (Fe)-Derived Cascade Nano-Enzymes for Antitumor and Antimicrobial Therapy

The clinical application of oncology therapy is hampered by high glutathione concentrations, hypoxia, and inefficient activation of cell death mechanisms in cancer cells. In this study, Fe and Mo bimetallic sulfide nanomaterial (FeS2@MoS2) based on metal-organic framework structure is rationally prepared with peroxidase (POD)-, catalase (CAT)-, superoxide dismutase (SOD)-like activities and glutathione depletion ability, which can confer versatility for treating tumors and mending wounds. In the lesion area, FeS2@MoS2 with SOD-like activity can facilitate the transformation of superoxide anions (O2 -) to hydrogen peroxide (H2O2), and then the resulting H2O2 serves as a substrate for the Fenton reaction with FMS to produce highly toxic hydroxyl radicals (∙OH). Simultaneously, FeS2@MoS2 has an ability to deplete glutathione (GSH) and catalyze the decomposition of nicotinamide adenine dinucleotide phosphate (NADPH) to curb the regeneration of GSH from the source. Thus it can realize effective tumor elimination through synergistic apoptosis-ferroptosis strategy. Based on the alteration of the H2O2 system, free radical production, glutathione depletion and the alleviation of hypoxia in the tumor microenvironment, FeS2@MoS2 NPS can not only significantly inhibit tumors in vivo and in vitro, but also inhibit multidrug-resistant bacteria and hasten wound healing. It may open the door to the development of cascade nanoplatforms for effective tumor treatment and overcoming wound infection.

Effects of dietary intervention on human diseases: molecular mechanisms and therapeutic potential

Diet, serving as a vital source of nutrients, exerts a profound influence on human health and disease progression. Recently, dietary interventions have emerged as promising adjunctive treatment strategies not only for cancer but also for neurodegenerative diseases, autoimmune diseases, cardiovascular diseases, and metabolic disorders. These interventions have demonstrated substantial potential in modulating metabolism, disease trajectory, and therapeutic responses. Metabolic reprogramming is a hallmark of malignant progression, and a deeper understanding of this phenomenon in tumors and its effects on immune regulation is a significant challenge that impedes cancer eradication. Dietary intake, as a key environmental factor, can influence tumor metabolism. Emerging evidence indicates that dietary interventions might affect the nutrient availability in tumors, thereby increasing the efficacy of cancer treatments. However, the intricate interplay between dietary interventions and the pathogenesis of cancer and other diseases is complex. Despite encouraging results, the mechanisms underlying diet-based therapeutic strategies remain largely unexplored, often resulting in underutilization in disease management. In this review, we aim to illuminate the potential effects of various dietary interventions, including calorie restriction, fasting-mimicking diet, ketogenic diet, protein restriction diet, high-salt diet, high-fat diet, and high-fiber diet, on cancer and the aforementioned diseases. We explore the multifaceted impacts of these dietary interventions, encompassing their immunomodulatory effects, other biological impacts, and underlying molecular mechanisms. This review offers valuable insights into the potential application of these dietary interventions as adjunctive therapies in disease management.

CREB3L4 promotes hepatocellular carcinoma progression and decreases sorafenib chemosensitivity by promoting RHEB-mTORC1 signaling pathway

This study was designed to explore the roles of CREB3L4 in the pathogenesis and drug resistance of hepatocellular carcinoma (HCC). The proliferation of HCC lines was determined in the presence of CREB3L4 over-expression and silencing. Chromatin immunoprecipitation (ChIP) assay and dual-luciferase reporter assay were performed to screen the potential target of CREB3L4 on mTORC1. Xenografted tumor model was established to define the regulatory effects of CREB3L4 in the tumorigenesis. Then we evaluated the roles of CREB3L4 in chemosensitivity to sorafenib treatment. CREB3L4 significantly induced the HCC cell proliferation by modulating the activation of mTROC1-S6K1 signaling pathway via binding with RHEB promoter. Moreover, CREB3L4 dramatically inhibited the chemosensitivity to sorafenib treatment via up-regulating RHEB-mTORC1 signaling. CREB3L4 promoted HCC progression and decreased its chemosensitivity to sorafenib through up-regulating RHEB-mTORC1 signaling pathway, indicating a potential treatment strategy for HCC through targeting CREB3L4.

Wnt/β-catenin signalling activates IMPDH2-mediated purine metabolism to facilitate oxaliplatin resistance by inhibiting caspase-dependent apoptosis in colorectal cancer

BACKGROUND

Oxaliplatin resistance usually leads to therapeutic failure and poor prognosis in colorectal cancer (CRC), while the underlying mechanisms are not yet fully understood. Metabolic reprogramming is strongly linked to drug resistance, however, the role and mechanism of metabolic reprogramming in oxaliplatin resistance remain unclear. Here, we aim to explore the functions and mechanisms of purine metabolism on the oxaliplatin-induced apoptosis of CRC.

METHODS

An oxaliplatin-resistant CRC cell line was generated, and untargeted metabolomics analysis was conducted. The inosine 5'-monophosphate dehydrogenase type II (IMPDH2) expression in CRC cell lines was determined by quantitative real-time polymerase chain reaction (qPCR) and western blotting analysis. The effects of IMPDH2 overexpression, knockdown and pharmacological inhibition on oxaliplatin resistance in CRC were assessed by flow cytometry analysis of cell apoptosis in vivo and in vitro.

RESULTS

Metabolic analysis revealed that the levels of purine metabolites, especially guanosine monophosphate (GMP), were markedly elevated in oxaliplatin-resistant CRC cells. The accumulation of purine metabolites mainly arose from the upregulation of IMPDH2 expression. Gene set enrichment analysis (GSEA) indicated high IMPDH2 expression in CRC correlates with PURINE_METABOLISM and MULTIPLE-DRUG-RESISTANCE pathways. CRC cells with higher IMPDH2 expression were more resistant to oxaliplatin-induced apoptosis. Overexpression of IMPDH2 in CRC cells resulted in reduced cell death upon treatment with oxaliplatin, whereas knockdown of IMPDH2 led to increased sensitivity to oxaliplatin through influencing the activation of the Caspase 7/8/9 and PARP1 proteins on cell apoptosis. Targeted inhibition of IMPDH2 by mycophenolic acid (MPA) or mycophenolate mofetil (MMF) enhanced cell apoptosis in vitro and decreased in vivo tumour burden when combined with oxaliplatin treatment. Mechanistically, the Wnt/β-catenin signalling was hyperactivated in oxaliplatin-resistant CRC cells, and a reciprocal positive regulatory mechanism existed between Wnt/β-catenin and IMPDH2. Blocking the Wnt/β-catenin pathway could resensitize resistant cells to oxaliplatin, which could be restored by the addition of GMP.

CONCLUSIONS

IMPDH2 is a predictive biomarker and therapeutic target for oxaliplatin resistance in CRC.

Deficiency in SLC25A15, a hypoxia-responsive gene, promotes hepatocellular carcinoma by reprogramming glutamine metabolism

BACKGROUND & AIMS

The role of solute carrier family 25 member 15 (SLC25A15), a critical component of the urea cycle, in hepatocellular carcinoma (HCC) progression remains poorly understood. This study investigated the impact of SLC25A15 on HCC progression and its mechanisms.

METHODS

We systematically investigated the function of SLC25A15 in HCC progression using large-scale data mining and cell, animal, and organoid models. Furthermore, we analyzed its involvement in reprogramming glutamine metabolism.

RESULTS

SLC25A15 expression was significantly decreased in HCC tissues, and patients with low SLC25A15 levels had a poorer prognosis. Hypoxia-exposed HCC cells or tissues had lower SLC25A15 expression. A positive correlation between HNF4A, a transcription factor suppressed by hypoxia, and SLC25A15 was observed in both HCC tissues and cells. Modulating HNF4A levels altered SLC25A15 mRNA levels. SLC25A15 upregulated SLC1A5, increasing glutamine uptake. The reactive metabolic pathway of glutamine was increased in SLC25A15-deficient HCC cells, providing energy for HCC progression through additional lipid synthesis. Ammonia accumulation due to low SLC25A15 levels suppressed the expression of OGDHL (oxoglutarate dehydrogenase L), a switch gene that mediates SLC25A15 deficiency-induced reprogramming of glutamine metabolism. SLC25A15-deficient HCC cells were more susceptible to glutamine deprivation and glutaminase inhibitors. Intervening in glutamine metabolism increased SLC25A15-deficient HCC cells' response to anti-PD-L1 treatment.

CONCLUSION

SLC25A15 is hypoxia-responsive in HCC, and low SLC25A15 levels result in glutamine reprogramming through SLC1A5 and OGDHL regulation, promoting HCC progression and regulating cell sensitivity to anti-PD-L1. Interrupting the glutamine-derived energy supply is a potential therapeutic strategy for treating SLC25A15-deficient HCC.

IMPACT AND IMPLICATIONS

We first demonstrated the tumor suppressor role of solute carrier family 25 member 15 (SLC25A15) in hepatocellular carcinoma (HCC) and showed that its deficiency leads to reprogramming of glutamine metabolism to promote HCC development. SLC25A15 can serve as a potential biomarker to guide the development of precision therapeutic strategies aimed at targeting glutamine deprivation. Furthermore, we highlight that the use of an inhibitor of glutamine utilization can enhance the sensitivity of low SLC25A15 HCC to anti-PD-L1 therapy.

Metabolic reprogramming in the tumor microenvironment of liver cancer

The liver is essential for metabolic homeostasis. The onset of liver cancer is often accompanied by dysregulated liver function, leading to metabolic rearrangements. Overwhelming evidence has illustrated that dysregulated cellular metabolism can, in turn, promote anabolic growth and tumor propagation in a hostile microenvironment. In addition to supporting continuous tumor growth and survival, disrupted metabolic process also creates obstacles for the anticancer immune response and restrains durable clinical remission following immunotherapy. In this review, we elucidate the metabolic communication between liver cancer cells and their surrounding immune cells and discuss how metabolic reprogramming of liver cancer impacts the immune microenvironment and the efficacy of anticancer immunotherapy. We also describe the crucial role of the gut-liver axis in remodeling the metabolic crosstalk of immune surveillance and escape, highlighting novel therapeutic opportunities.

Prognostic and immune predictive roles of a novel tricarboxylic acid cycle-based model in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. Since the tricarboxylic acid cycle is widely involved in tumor metabolic reprogramming and cuproptosis, investigating related genes may help to identify prognostic signature of patients with HCC. Data on patients with HCC were sourced from public datasets, and were divided into train, test, and single-cell cohorts. A variety of machine learning algorithms were used to identify different molecular subtypes and determine the prognostic risk model. Our findings revealed that the risk score (TRscore), based on the genes OGDHL, CFHR4, and SPP1, showed excellent predictive performance in different datasets. Pathways related to cell cycle and immune inflammation were enriched in the high-risk group, whereas metabolism-related pathways were significantly enriched in the low-risk group. The high-risk group was associated with a greater number of mutations of detrimental biological behavior and higher levels of immune infiltration, immune checkpoint expression, and anti-cancer immunotherapy response. Low-risk patients demonstrated greater sensitivity to erlotinib and phenformin. SPP1 was mainly involved in the interaction among tumor-associated macrophages, T cells, and malignant cells via SPP1-CD44 and SPP1-(ITGA5 + ITGB1) ligand-receptor pairs. In summary, our study established a prognostic model, which may contribute to individualized treatment and clinical management of patients with HCC.

Lactate dehydrogenase A promotes nasopharyngeal carcinoma progression through the TAK1/NF-κB Axis

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a malignant tumor that originates in the nasopharyngeal mucosa and is common in China and Southeast Asian countries. Cancer cells reprogram glycolytic metabolism to promote their growth, survival and metastasis. Glycolysis plays an important role in NPC development, but the underlying mechanisms remain incompletely elucidated. Lactate dehydrogenase A (LDHA) is a crucial glycolytic enzyme, catalyzing the last step of glycolysis. This study aims to investigate the exact role of LDHA, which catalyzes the conversion of pyruvate into lactate, in NPC development.

METHODS AND RESULTS

The western blot and immunohistochemical (IHC) results indicated that LDHA was significantly upregulated in NPC cells and clinical samples. LDHA knockdown by shRNA significantly inhibited NPC cell proliferation and invasion. Further knockdown of LDHA dramatically weakened the tumorigenicity of NPC cells in vivo. Mechanistic studies showed that LDHA activated TGF-β-activated kinase 1 (TAK1) and subsequent nuclear factor κB (NF-κB) signaling to promote NPC cell proliferation and invasion. Exogenous lactate supplementation restored NPC cell proliferation and invasion inhibited by LDHA knockdown, and this restorative effect was reversed by NF-κB inhibitor (BAY 11-7082) or TAK1 inhibitor (5Z-7-oxozeaenol) treatment. Moreover, clinical sample analyses showed that LDHA expression was positively correlated with TAK1 Thr187 phosphorylation and poor prognosis.

CONCLUSIONS

Our results suggest that LDHA and its major metabolite lactate drive NPC progression by regulating TAK1 and its downstream NF-κB signaling, which could become a therapeutic target in NPC.

Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning

BACKGROUND

Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking.

METHODS

This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149.

RESULTS

Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results.

CONCLUSIONS

This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

RORα inhibits gastric cancer proliferation through attenuating G6PD and PFKFB3 induced glycolytic activity

BACKGROUND

Glycolysis is critical for harvesting abundant energy to maintain the tumor microenvironment in malignant tumors. Retinoic acid-related orphan receptor α (RORα) has been identified as a circadian gene. However, the association of glycolysis with RORα in regulating gastric cancer (GC) proliferation remains poorly understood.

METHODS

Bioinformatic analysis and retrospective study were utilized to explore the role of RORα in cell cycle and glycolysis in GC. The mechanisms were performed in vitro and in vivo including colony formation, Cell Counting Kit-8 (CCK-8), Epithelial- mesenchymal transition (EMT) and subcutaneous tumors of mice model assays. The key drives between RORα and glycolysis were verified through western blot and chip assays. Moreover, we constructed models of high proliferation and high glucose environments to verify a negative feedback and chemoresistance through a series of functional experiments in vitro and in vivo.

RESULTS

RORα was found to be involved in the cell cycle and glycolysis through a gene set enrichment analysis (GSEA) algorithm. GC patients with low RORα expression were not only associated with high circulating tumor cells (CTC) and high vascular endothelial growth factor (VEGF) levels. However, it also presented a positive correlation with the standard uptake value (SUV) level. Moreover, the SUVmax levels showed a positive linear relation with CTC and VEGF levels. In addition, RORα expression levels were associated with glucose 6 phosphate dehydrogenase (G6PD) and phosphofructokinase-2/fructose-2,6-bisphosphatase (PFKFB3) expression levels, and GC patients with low RORα and high G6PD or low RORα and high PFKFB3 expression patterns had poorest disease-free survival (DFS). Functionally, RORα deletion promoted GC proliferation and drove glycolysis in vitro and in vivo. These phenomena were reversed by the RORα activator SR1078. Moreover, RORα deletion promoted GC proliferation through attenuating G6PD and PFKFB3 induced glycolytic activity in vitro and in vivo. Mechanistically, RORα was recruited to the G6PD and PFKFB3 promoters to modulate their transcription. Next, high proliferation and high glucose inhibited RORα expression, which indicated that negative feedback exists in GC. Moreover, RORα deletion improved fluorouracil chemoresistance through inhibition of glucose uptake.

CONCLUSION

RORα might be a novel biomarker and therapeutic target for GC through attenuating glycolysis.

Analysis of clinical significance and molecular characteristics of methionine metabolism and macrophage-related patterns in hepatocellular carcinoma based on machine learning

BACKGROUND

Increasing evidence has indicated that abnormal methionine metabolic activity and tumour-associated macrophage infiltration are correlated with hepatocarcinogenesis. However, the relationship between methionine metabolic activity and tumour-associated macrophage infiltration is unclear in hepatocellular carcinoma, and it contributes to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we systematically analysed the expression patterns of methionine metabolism and macrophage infiltration in hepatocellular carcinoma using bioinformatics and machine learning methods and constructed novel diagnostic and prognostic models of HCC.

METHODS

In this study, we first mined the four largest HCC mRNA microarray datasets with patient clinical data in the GEO database, including 880 tissue mRNA expression datasets. Using GSVA analysis and the CIBERSORT and EPIC algorithms, we quantified the methionine metabolic activity and macrophage infiltration degree of each sample. WGCNA was used to identify the gene modules most related to methionine metabolism and tumour-associated macrophage infiltration in HCC. The KNN algorithm was used to cluster gene expression patterns in HCC. Random forest, logistic regression, Cox regression analysis and other algorithms were used to construct the diagnosis and prognosis model of HCC. The above bioinformatics analysis results were also verified by independent datasets (TCGA-LIHC, ICGC-JP and CPTAC datasets) and immunohistochemical fluorescence based on our external HCC panel. Furthermore, we carried out pancancer analysis to verify the specificity of the above model and screened a wide range of drug candidates.

RESULTS

We identified two methionine metabolism and macrophage infiltration expression patterns, and their prognoses were different in hepatocellular carcinoma. We constructed novel diagnostic and prognostic models of hepatocellular carcinoma with good diagnostic efficacy and differentiation ability.

CONCLUSIONS

Methionine metabolism is closely related to tumour-associated macrophage infiltration in hepatocellular carcinoma and can help in the clinical diagnosis and prognosis of HCC.

Magnetic vagus nerve stimulation alleviates myocardial ischemia-reperfusion injury by the inhibition of pyroptosis through the M2AChR/OGDHL/ROS axis in rats

BACKGROUND

Myocardial ischemia-reperfusion (I/R) injury is accompanied by an imbalance in the cardiac autonomic nervous system, characterized by over-activated sympathetic tone and reduced vagal nerve activity. In our preceding study, we pioneered the development of the magnetic vagus nerve stimulation (mVNS) system. This system showcased precise vagus nerve stimulation, demonstrating remarkable effectiveness and safety in treating myocardial infarction. However, it remains uncertain whether mVNS can mitigate myocardial I/R injury and its specific underlying mechanisms. In this study, we utilized a rat model of myocardial I/R injury to delve into the therapeutic potential of mVNS against this type of injury.

RESULTS

Our findings revealed that mVNS treatment led to a reduction in myocardial infarct size, a decrease in ventricular fibrillation (VF) incidence and a curbing of inflammatory cytokine release. Mechanistically, mVNS demonstrated beneficial effects on myocardial I/R injury by inhibiting NLRP3-mediated pyroptosis through the M2AChR/OGDHL/ROS axis.

CONCLUSIONS

Collectively, these outcomes highlight the promising potential of mVNS as a treatment strategy for myocardial I/R injury.

Mining cancer genomes for change-of-metabolic-function mutations

Enzymes with novel functions are needed to enable new organic synthesis techniques. Drawing inspiration from gain-of-function cancer mutations that functionally alter proteins and affect cellular metabolism, we developed METIS (Mutated Enzymes from Tumors In silico Screen). METIS identifies metabolism-altering cancer mutations using mutation recurrence rates and protein structure. We used METIS to screen 298,517 cancer mutations and identify 48 candidate mutations, including those previously identified to alter enzymatic function. Unbiased metabolomic profiling of cells exogenously expressing a candidate mutant (OGDHLp.A400T) supports an altered phenotype that boosts in vitro production of xanthosine, a pharmacologically useful chemical that is currently produced using unsustainable, water-intensive methods. We then applied METIS to 49 million cancer mutations, yielding a refined set of candidates that may impart novel enzymatic functions or contribute to tumor progression. Thus, METIS can be used to identify and catalog potentially-useful cancer mutations for green chemistry and therapeutic applications.

Systematic analysis of glutamine metabolism family genes and exploration of the biological role of GPT in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and development of CRC. However, no research has systematically analyzed the biological role of glutamine metabolism-related genes (GMRGs) in CRC.

METHODS

We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.

RESULTS

A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.

CONCLUSIONS

GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.

Transcriptome analyses reveal transcriptional profiles of horse oocytes before and after in vitro maturation

Oocyte in vitro maturation is necessary for the study and application of animal-assisted reproduction technology in animal reproduction and breeding. The comprehensive transcriptional profile of equine oocyte maturated in vitro has not been fully mined yet, which makes many key transcriptional events still unidentified. Here, Smart-seq2 was performed to analyse the gene expression pattern and the underlying regulatory mechanism of horse germinal vesicle (GV) and in vitro metaphase II (MII) oocytes. The results showed that 6402 genes (2640 up-regulated and 3762 down-regulated in MII samples compared to GV) and 4021 lncRNA transcripts (1210 up-regulated and 2811 down-regulated in MII samples compared to GV) were differentially expressed in GV and MII oocytes. Further, GO and KEGG analysis found that differentially expressed mRNAs and lncRNAs were mainly enriched in the pathways related to energy and lipid metabolism. In addition, LGALS3 was found a key gene in mediating the regulation of oocyte meiosis recovery and fertilization ability. This study provides novel knowledge about gene expression and energy metabolism during equine oocyte maturation and a reference for the further study and application of assisted reproductive technology in horse reproduction and breeding.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients

BACKGROUND

Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.

METHODS

This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).

RESULTS

Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.

CONCLUSIONS

This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

The m6A modification-mediated OGDHL exerts a tumor suppressor role in ccRCC by downregulating FASN to inhibit lipid synthesis and ERK signaling

Metabolic reprogramming is a hallmark of cancer, and the impact of lipid metabolism as a crucial aspect of metabolic reprogramming on clear cell renal cell carcinoma (ccRCC) progression has been established. However, the regulatory mechanisms underlying the relationship between metabolic abnormalities and ccRCC progression remain unclear. Therefore, this study aimed to identify key regulatory factors of metabolic reprogramming in ccRCC and provide potential therapeutic targets for ccRCC patients. Potential metabolic regulatory factors in ccRCC were screened using bioinformatics analysis. Public databases and patient samples were used to investigate the aberrant expression of Oxoglutarate dehydrogenase-like (OGDHL) in ccRCC. The function of OGDHL in ccRCC growth and metastasis was evaluated through in vitro and in vivo functional experiments. Mechanistic insights were obtained through luciferase reporter assays, chromatin immunoprecipitation, RNA methylation immunoprecipitation, and mutagenesis studies. OGDHL mRNA and protein levels were significantly downregulated in ccRCC tissues. Upregulation of OGDHL expression effectively inhibited ccRCC growth and metastasis both in vitro and in vivo. Furthermore, FTO-mediated OGDHL m6A demethylation suppressed its expression in ccRCC. Mechanistically, low levels of OGDHL promoted TFAP2A expression by inhibiting ubiquitination levels, which then bound to the FASN promoter region and transcriptionally activated FASN expression, thereby promoting lipid accumulation and ERK pathway activation. Our findings demonstrate the impact of OGDHL on ccRCC progression and highlight the role of the FTO/OGDHL/TFAP2A/FASN axis in regulating ccRCC lipid metabolism and progression, providing new targets for ccRCC therapy.

Glutamine metabolic reprogramming in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a lethal disease with limited management strategies and poor prognosis. Metabolism alternations have been frequently unveiled in HCC, including glutamine metabolic reprogramming. The components of glutamine metabolism, such as glutamine synthetase, glutamate dehydrogenase, glutaminase, metabolites, and metabolite transporters, are validated to be potential biomarkers of HCC. Increased glutamine consumption is confirmed in HCC, which fuels proliferation by elevated glutamate dehydrogenase or upstream signals. Glutamine metabolism also serves as a nitrogen source for amino acid or nucleotide anabolism. In addition, more glutamine converts to glutathione as an antioxidant in HCC to protect HCC cells from oxidative stress. Moreover, glutamine metabolic reprogramming activates the mTORC signaling pathway to support tumor cell proliferation. Glutamine metabolism targeting therapy includes glutamine deprivation, related enzyme inhibitors, and transporters inhibitors. Together, glutamine metabolic reprogramming plays a pivotal role in HCC identification, proliferation, and progression.

Oxoglutarate dehydrogenase-like inhibits the progression of hepatocellular carcinoma by inducing DNA damage through non-canonical function

Oxoglutarate dehydrogenase-like (OGDHL) is considered to be the isoenzyme of oxyglutarate dehydrogenase (OGDH) in the OGDH complex, which degrades glucose and glutamate. OGDHL was reported to reprogram glutamine metabolism to suppress HCC progression in an enzyme-activity-dependent manner. However, the potential subcellular localization and non-canonical function of OGDHL is poorly understood. We investigated the expression of OGDHL and its effect on HCC progression. By employing a variety of molecular biology techniques, we revealed the underlying mechanism of OGDHL-induced DNA damage in HCC cells in vitro and in vivo. AAV loaded with OGDHL exerts therapeutic effect on mouse HCC and prolongs survival time. OGDHL induces DNA damage in HCC cells in vitro and in vivo. We also observed that OGDHL possesses nuclear localization in HCC cells and OGDHL-induced DNA damage was independent of its enzymatic activity. Mechanistically, it was demonstrated that OGDHL binds to CDK4 in the nucleus to inhibit the phosphorylation of CDK4 by CAK, which in turn attenuates E2F1 signaling. Inhibition of E2F1 signaling downregulates pyrimidine and purine synthesis, thereby inducing DNA damage through dNTP depletion. We clarified the nuclear localization of OGDHL and its non-canonical function to induce DNA damage, which demonstrated that OGDHL may serve as a select potential therapeutic target for HCC.

Combining WGCNA and machine learning to construct immune-related EMT patterns to predict HCC prognosis and immune microenvironment

Hepatocellular carcinoma (HCC) is a malignancy with a very high mortality rate. Because of its high heterogeneity, there is an urgent need to find biomarkers that accurately predict prognosis. Epithelial-mesenchymal transition (EMT) is closely associated with frequent recurrence and high mortality of HCC. Therefore, it is necessary to comprehensively analyze the prognostic value and immunological properties of EMT gene in HCC. In our study, we performed bioinformatics analysis of the TCGA and ICGC liver cancer cohorts and identified the module genes of immune-associated EMTs (iEMT) by Weighted Gene Co-Expression Network Analysis (WGCNA). Further we used machine learning (support vector machines-recursive feature elimination and Lasso) to identify three central iEMT genes (ARMC9, ADAM15 and STC2) and construct iEMT_score. Subsequently, in the training and validation cohorts, it was demonstrated that the overall survival (OS) of patients in the high iEMT_score group was worse than that of patients in the low iEMT_score group. Based on this, we have constructed a nomogram that is easy for clinicians to use. In addition, our study explored differences in pathway enrichment, immunological properties, and sensitivity to common chemotherapy and targeted drugs in different subgroups of iEMT_score. Finally, we showed through in vitro experiments that knockdown of ARMC9 could significantly inhibit the proliferation, migration and invasion of HCC cells BEL7402. Taken together, our findings suggest that iEMT_score is an excellent biomarker for predicting prognosis and provide some new insights for personalized treatment of HCC patients.

N6AMT1 is a novel potential diagnostic, prognostic and immunotherapy response biomarker in pan-cancer

BACKGROUND

The N-6-adenine-specific DNA methyltransferase 1 (N6AMT1) is the only writer responsible for DNA 6mA modifications. At present, its role in cancer is still unclear, and further systematic pan-cancer analysis is needed to explore its value in diagnosis, prognosis and immunological function.

METHODS

The subcellular localization of N6AMT1 was explored by UniProt and HPA database. The expression data and prognosis data of N6AMT1 were downloaded from the UCSC (cohort: TCGA pan-cancer), and the diagnostic and prognostic value of N6AMT1 in pan-cancer was explored. The value of N6AMT1-guided immunotherapy was explored through three cohorts (GSE168204, GSE67501 and IMvigor210 cohort). The correlation between N6AMT1 expression and tumor immune microenvironment was explored using CIBERSORT and ESTIMATE calculation methods, combined with TISIDB database. The biological role of N6AMT1 in specific tumors was explored by GSEA method. Finally, we explored chemicals affecting N6AMT1 expression through the CTD.

RESULTS

N6AMT1 is mainly localized in the nucleus and differentially expressed in 9 cancer types. In addition, N6AMT1 showed early diagnostic value in 7 cancers and showed potential prognostic value in multiple cancer types. We also demonstrated that N6AMT1 expression was significantly associated with immunomodulator-related molecules, infiltration of lymphocyte subsets, and biomarkers of immunotherapy response. Furthermore, we show that N6AMT1 is differentially expressed in the immunotherapy cohort. Finally, we explored 43 chemicals that can affect N6AMT1 expression.

CONCLUSIONS

N6AMT1 has shown excellent diagnostic and prognostic capabilities in a variety of cancers, and it may reshape the tumor microenvironment and contribute to the ability to predict response to immunotherapy.

Polyphyllin D punctures hypertrophic lysosomes to reverse drug resistance of hepatocellular carcinoma by targeting acid sphingomyelinase

Hypertrophic lysosomes are critical for tumor progression and drug resistance; however, effective and specific lysosome-targeting compounds for cancer therapy are lacking. Here we conducted a lysosomotropic pharmacophore-based in silico screen in a natural product library (2,212 compounds), and identified polyphyllin D (PD) as a novel lysosome-targeted compound. PD treatment was found to cause lysosomal damage, as evidenced by the blockade of autophagic flux, loss of lysophagy, and the release of lysosomal contents, thus exhibiting anticancer effects on hepatocellular carcinoma (HCC) cell both in vitro and in vivo. Closer mechanistic examination revealed that PD suppressed the activity of acid sphingomyelinase (SMPD1), a lysosomal phosphodieserase that catalyzes the hydrolysis of sphingomyelin to produce ceramide and phosphocholine, by directly occupying its surface groove, with Trp148 in SMPD1 acting as a major binding residue; this suppression of SMPD1 activity irreversibly triggers lysosomal injury and initiates lysosome-dependent cell death. Furthermore, PD-enhanced lysosomal membrane permeabilization to release sorafenib, augmenting the anticancer effect of sorafenib both in vivo and in vitro. Overall, our study suggests that PD can potentially be further developed as a novel autophagy inhibitor, and a combination of PD with classical chemotherapeutic anticancer drugs could represent a novel therapeutic strategy for HCC intervention.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

Metabolic codependencies in the tumor microenvironment and gastric cancer: Difficulties and opportunities

Oncogenesis and the development of tumors affect metabolism throughout the body. Metabolic reprogramming (also known as metabolic remodeling) is a feature of malignant tumors that is driven by oncogenic changes in the cancer cells themselves as well as by cytokines in the tumor microenvironment. These include endothelial cells, matrix fibroblasts, immune cells, and malignant tumor cells. The heterogeneity of mutant clones is affected by the actions of other cells in the tumor and by metabolites and cytokines in the microenvironment. Metabolism can also influence immune cell phenotype and function. Metabolic reprogramming of cancer cells is the result of a convergence of both internal and external signals. The basal metabolic state is maintained by internal signaling, while external signaling fine-tunes the metabolic process based on metabolite availability and cellular needs. This paper reviews the metabolic characteristics of gastric cancer, focusing on the intrinsic and extrinsic mechanisms that drive cancer metabolism in the tumor microenvironment, and interactions between tumor cell metabolic changes and microenvironment metabolic changes. This information will be helpful for the individualized metabolic treatment of gastric cancers.

Combining WGCNA and machine learning to construct basement membrane-related gene index helps to predict the prognosis and tumor microenvironment of HCC patients and verifies the carcinogenesis of key gene CTSA

Hepatocellular carcinoma (HCC) is a malignant tumor with high recurrence and metastasis rates and poor prognosis. Basement membrane is a ubiquitous extracellular matrix and is a key physical factor in cancer metastasis. Therefore, basement membrane-related genes may be new targets for the diagnosis and treatment of HCC. We systematically analyzed the expression pattern and prognostic value of basement membrane-related genes in HCC using the TCGA-HCC dataset, and constructed a new BMRGI based on WGCNA and machine learning. We used the HCC single-cell RNA-sequencing data in GSE146115 to describe the single-cell map of HCC, analyzed the interaction between different cell types, and explored the expression of model genes in different cell types. BMRGI can accurately predict the prognosis of HCC patients and was validated in the ICGC cohort. In addition, we also explored the underlying molecular mechanisms and tumor immune infiltration in different BMRGI subgroups, and confirmed the differences in response to immunotherapy in different BMRGI subgroups based on the TIDE algorithm. Then, we assessed the sensitivity of HCC patients to common drugs. In conclusion, our study provides a theoretical basis for the selection of immunotherapy and sensitive drugs in HCC patients. Finally, we also considered CTSA as the most critical basement membrane-related gene affecting HCC progression. In vitro experiments showed that the proliferation, migration and invasion abilities of HCC cells were significantly impaired when CTSA was knocked down.

Cell metabolism-based therapy for liver fibrosis, repair, and hepatocellular carcinoma

Progression of chronic liver injury to fibrosis, abnormal liver regeneration, and HCC is driven by a dysregulated dialog between epithelial cells and their microenvironment, in particular immune, fibroblasts, and endothelial cells. There is currently no antifibrogenic therapy, and drug treatment of HCC is limited to tyrosine kinase inhibitors and immunotherapy targeting the tumor microenvironment. Metabolic reprogramming of epithelial and nonparenchymal cells is critical at each stage of disease progression, suggesting that targeting specific metabolic pathways could constitute an interesting therapeutic approach. In this review, we discuss how modulating intrinsic metabolism of key effector liver cells might disrupt the pathogenic sequence from chronic liver injury to fibrosis/cirrhosis, regeneration, and HCC.

Identification of afatinib-associated ADH1B and potential small-molecule drugs targeting ADH1B for hepatocellular carcinoma

Background: Afatinib is an irreversible epidermal growth factor receptor tyrosine kinase inhibitor, and it plays a role in hepatocellular carcinoma (LIHC). This study aimed to screen a key gene associated with afatinib and identify its potential candidate drugs. Methods: We screened afatinib-associated differential expressed genes based on transcriptomic data of LIHC patients from The Cancer Genome Atlas, Gene Expression Omnibus, and the Hepatocellular Carcinoma Database (HCCDB). By using the Genomics of Drug Sensitivity in Cancer 2 database, we determined candidate genes using analysis of the correlation between differential genes and half-maximal inhibitory concentration. Survival analysis of candidate genes was performed in the TCGA dataset and validated in HCCDB18 and GSE14520 datasets. Immune characteristic analysis identified a key gene, and we found potential candidate drugs using CellMiner. We also evaluated the correlation between the expression of ADH1B and its methylation level. Furthermore, Western blot analysis was performed to validate the expression of ADH1B in normal hepatocytes LO2 and LIHC cell line HepG2. Results: We screened eight potential candidate genes (ASPM, CDK4, PTMA, TAT, ADH1B, ANXA10, OGDHL, and PON1) associated with afatinib. Patients with higher ASPM, CDK4, PTMA, and TAT exhibited poor prognosis, while those with lower ADH1B, ANXA10, OGDHL, and PON1 had unfavorable prognosis. Next, ADH1B was identified as a key gene negatively correlated with the immune score. The expression of ADH1B was distinctly downregulated in tumor tissues of pan-cancer. The expression of ADH1B was negatively correlated with ADH1B methylation. Small-molecule drugs panobinostat, oxaliplatin, ixabepilone, and seliciclib were significantly associated with ADH1B. The protein level of ADH1B was significantly downregulated in HepG2 cells compared with LO2 cells. Conclusion: Our study provides ADH1B as a key afatinib-related gene, which is associated with the immune microenvironment and can be used to predict the prognosis of LIHC. It is also a potential target of candidate drugs, sharing a promising approach to the development of novel drugs for the treatment of LIHC.

A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy

Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.

Lactylation-Related Gene Signature Effectively Predicts Prognosis and Treatment Responsiveness in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignant tumor associated with high morbidity and mortality. Therefore, it is of great importance to develop effective prognostic models and guide clinical treatment in HCC. Protein lactylation is found in HCC tumors and is associated with HCC progression.

METHODS

The expression levels of lactylation-related genes were identified from the TCGA database. A lactylation-related gene signature was constructed using LASSO regression. The prognostic value of the model was assessed and further validated in the ICGC cohort, with the patients split into two groups based on risk score. Glycolysis and immune pathways, treatment responsiveness, and the mutation of signature genes were analyzed. The correlation between PKM2 expression and the clinical characteristics was investigated.

RESULTS

Sixteen prognostic differentially expressed lactylation-related genes were identified. An 8-gene signature was constructed and validated. Patients with higher risk scores had poorer clinical outcomes. The two groups were different in immune cell abundance. The high-risk group patients were more sensitive to most chemical drugs and sorafenib, while the low-risk group patients were more sensitive to some targeted drugs such as lapatinib and FH535. Moreover, the low-risk group had a higher TIDE score and was more sensitive to immunotherapy. PKM2 expression correlated with clinical characteristics and immune cell abundance in the HCC samples.

CONCLUSIONS

The lactylation-related model exhibited robust predictive efficiency in HCC. The glycolysis pathway was enriched in the HCC tumor samples. A low-risk score indicated better treatment response to most targeted drugs and immunotherapy. The lactylation-related gene signature could be used as a biomarker for the effective clinical treatment of HCC.

Development and investigation of metabolism-associated risk assessment models for patients with viral hepatitis

Dysregulation of metabolism plays an important role in the onset and progression of multiple pathogenic diseases, including viral hepatitis. However, a model to predict viral hepatitis risk by metabolic pathways is still lacking. Thus, we developed two risk assessment models for viral hepatitis based on metabolic pathways identified through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The first model is designed to assess the progression of the disease by evaluating changes in the Child–Pugh class, hepatic decompensation, and the development of hepatocellular carcinoma. The second model is focused on determining the prognosis of the illness, taking into account the patient’s cancer status. Our models were further validated by Kaplan–Meier plots of survival curves. In addition, we investigated the contribution of immune cells in metabolic processes and identified three distinct subsets of immune cells—CD8+ T cells, macrophages, and NK cells—that have significantly affected metabolic pathways. Specifically, our findings suggest that resting or inactive macrophages and NK cells contribute to maintaining metabolic homeostasis, particularly with regard to lipid and α-amino acid metabolism, thereby potentially reducing the risk of viral hepatitis progression. Moreover, maintaining metabolic homeostasis ensures a balance between killer-proliferative and exhausted CD8+ T cells, which helps in mitigating CD8+ T cell-mediated liver damage while preserving energy reserves. In conclusion, our study offers a useful tool for early disease detection in viral hepatitis patients through metabolic pathway analysis and sheds light on the immunological understanding of the disease through the examination of immune cell metabolic disorders.

Glutamine metabolism targeting liposomes for synergistic chemosensitization and starvation therapy in ovarian cancer

Platinum-based chemotherapy is a first-line therapeutic regimen against ovarian cancer (OC); however, the therapeutic potential is always reduced by glutamine metabolism. Herein, a valid strategy of inhibiting glutamine metabolism was proposed to cause tumor starvation and chemosensitization. Specifically, reactive oxygen species-responsive liposomes were developed to co-deliver cisplatin (CDDP) and bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES) [C@B LPs]. The C@B LPs induced effective tumor cell starvation and significantly sensitized OC cells to CDDP by reducing glutathione generation to prevent CDDP detoxification, suppressing ATP production to avoid CDDP efflux, hindering nucleotide synthesis to aggravate DNA damage induced by CDDP, and blocking mammalian target of rapamycin (mTOR) signaling to promote cell apoptosis. More importantly, C@B LPs remarkably inhibited tumor growth in vivo and reduced the side effects. Taken together, this study provided a successful strategy of synergistic chemosensitization and starvation therapy escalating the rate of therapeutic success in OCs. STATEMENT OF SIGNIFICANCE: This work proposed a valid strategy of inhibiting glutamine metabolism to cause tumor starvation and chemosensitization. Specifically, ROS-responsive liposomes were developed to co-deliver cisplatin CDDP and BPTES [C@B LPs]. The C@B LPs induced effective tumor cell starvation and significantly sensitized OC cells to cisplatin by reducing glutathione generation to prevent cisplatin detoxification, suppressing ATP production to avoid cisplatin efflux, hindering nucleotide synthesis to aggravate DNA damage induced by cisplatin, and blocking mTOR signaling to promote cell apoptosis. More importantly, C@B LPs remarkably inhibited tumor growth in vivo and reduced the side effects. Taken together, this study provided a successful strategy of synergistic chemosensitization and starvation therapy escalating the rate of therapeutic success in OCs.

Potential Treatment Strategies for Hepatocellular Carcinoma Cell Sensitization to Sorafenib

Liver cancer is highly malignant, has a low sensitivity to chemotherapy, and is associated with poor patient prognosis. The last 3 years have seen the emergence of promising targeted therapies for the treatment of hepatocellular carcinoma (HCC). For over 10 years, before the discovery of lenvatinib, sorafenib was only first-line therapeutic agent available for the treatment of advanced HCC. However, several clinical studies have shown that a considerable proportion liver cancer patients are insensitive to sorafenib. Very few patients actually substantially benefit from treatment with sorafenib, and the overall efficacy of the drug has not been satisfactory; therefore, sorafenib has attracted considerable research attention. This study, which is based on previous studies and reports, reviews the potential mechanisms underlying sorafenib resistance and summarizes combination therapies and potential drugs that can be used to sensitize HCC cells to sorafenib.

c-Myc-IMPDH1/2 axis promotes tumourigenesis by regulating GTP metabolic reprogramming

BACKGROUND

Metabolic reprogramming is a hallmark of cancer. Metabolic rate-limiting enzymes and oncogenic c-Myc (Myc) play critical roles in metabolic reprogramming to affect tumourigenesis. However, a systematic assessment of metabolic rate-limiting enzymes and their relationship with Myc in human cancers is lacking.

METHODS

Multiple Pan-cancer datasets were used to develop the transcriptome, genomic alterations, clinical outcomes and Myc correlation landscapes of 168 metabolic rate-limiting enzymes across 20 cancers. Real-time quantitative PCR and immunoblotting were, respectively, used to examine the mRNA and protein of inosine monophosphate dehydrogenase 1 (IMPDH1) in human colorectal cancer (CRC), azoxymethane/dextran sulphate sodium-induced mouse CRC and spontaneous intestinal tumours from APCMin/+ mice. Clone formation, CCK-8 and subcutaneous xenograft model were applied to investigate the possible mechanisms connecting IMPDH1 to CRC growth. Co-immunoprecipitation and protein half-life assay were used to explore the mechanisms underlying the regulation of IMPDH1.

RESULTS

We explored the global expression patterns, dysregulation profiles, genomic alterations and clinical relevance of 168 metabolic rate-limiting enzymes across human cancers. Importantly, a series of enzymes were associated with Myc, especially top three upregulated enzymes (TK1, RRM2 and IMPDH1) were positively correlated with Myc in multiple cancers. As a proof-of-concept exemplification, we demonstrated that IMPDH1, a rate-limiting enzyme in GTP biosynthesis, is highly upregulated in CRC and promotes CRC growth in vitro and in vivo. Mechanistically, IMPDH2 stabilizes IMPDH1 by decreasing the polyubiquitination levels of IMPDH1, and Myc promotes the de novo GTP biosynthesis by the transcriptional activation of IMPDH1/2. Finally, we confirmed that the Myc-IMPDH1/2 axis is dysregulated across human cancers.

CONCLUSIONS

Our study highlights the essential roles of metabolic rate-limiting enzymes in tumourigenesis and their crosstalk with Myc, and the Myc-IMPDH1/2 axis promotes tumourigenesis by altering GTP metabolic reprogramming. Our results propose the inhibition of IMPDH1 as a viable option for cancer treatment.

Immune Checkpoint Inhibitor-Based Combination Therapy for Colorectal Cancer: An Overview

Colorectal cancer (CRC) is one of the most common diseases in the world. Tumor immunotherapy is an innovative cancer treatment that acts by activating the human body's autoimmune system. Immune checkpoint block has been shown to be effective in DNA deficient mismatch repair/microsatellite instability-high CRC. However, the therapeutic effect for proficient mismatch repair/microsatellite stability patients still requires further study and optimization. At present, the main CRC strategy is to combine other therapeutic methods, such as chemotherapy, targeted therapy, and radiotherapy. Here, we review the current status and the latest progress of immune checkpoint inhibitors in the treatment of CRC. At the same time, we consider therapeutic opportunities for transforming cold to hot, as well as perspectives on possible future therapies, which may be in great demand for drug-resistant patients.

SMYD2 Promotes Hepatocellular Carcinoma Progression by Reprogramming Glutamine Metabolism via c-Myc/GLS1 Axis

Metabolic reprogramming, such as alterations in glutamine metabolism or glycolysis, is the hallmark of hepatocellular carcinoma (HCC). However, the underlying mechanisms are still incompletely elucidated. Previous studies have identified that methyltransferase SET and MYND domain-containing protein 2(SMYD2) is responsible for the pathogenesis of numerous types of cancer. Here, we innovatively uncover how SMYD2 regulates glutamine metabolism in HCC cells and promotes HCC progression. We identified that SMYD2 expression is upregulated in HCC tissues, which correlates with unfavorable clinical outcomes. Our in vitro and in vivo results showed that the depletion of SMYD2 inhibits HCC cell growth. Mechanistically, c-Myc methylation by SMYD2 increases its protein stability through the ubiquitin-proteasome system. We showed SMYD2 depletion destabilized c-Myc protein by increasing the conjugated K48-linked polyubiquitin chain. SMYD2 increased c-Myc expression and further upregulated glutaminase1 (GLS1), a crucial enzyme that catalyzes the conversion of glutamine to glutamic acid, in HCC cells. GLS1 plays an important role in SMYD2-mediated HCC progression and glutamine metabolism regulation. The knockdown of SMYD2 inhibited glutamine metabolism in HCC cells and overcame their chemoresistance to sorafenib. Collectively, our findings demonstrated a novel mechanism of how SMYD2 promotes HCC progression by regulating glutamine metabolism through the c-Myc/GLS1signaling, implicating the therapeutic potential of targeting SMYD2 in HCC patients.

Comprehensive analysis of the amino acid metabolism-related gene signature for prognosis, tumor immune microenvironment, and candidate drugs in hepatocellular carcinoma

Introduction

Metabolic rewiring satisfies increased nutritional demands and modulates many oncogenic processes in tumors. Amino acid metabolism is abnormal in many malignancies. Metabolic reprogramming of amino acids not only plays a crucial role in sustaining tumor cell proliferation but also influences the tumor immune microenvironment. Herein, the aim of our study was to elucidate the metabolic signature of amino acids in hepatocellular carcinoma (HCC).

Methods

Transcriptome profiles of HCC were obtained from the TCGA and ICGC databases. Based on the expression of amino acid metabolism-related genes (AAMRGs), we clustered the HCC samples into two molecular subtypes using the non-negative matrix factorization algorithm. Then, we constructed the amino acid metabolism-related gene signature (AAMRGS) by Cox regression and LASSO regression. Afterward, the clinical significance of the AAMRGS was evaluated. Additionally, we comprehensively analyzed the differences in mutational profiles, immune cell infiltration, immune checkpoint expression, and drug sensitivity between different risk subgroups. Furthermore, we examined three key gene expressions in liver cancer cells by quantitative real-time PCR and conducted the CCK8 assay to evaluate the influence of two chemotherapy drugs on different liver cancer cells.

Results

A total of 81 differentially expressed AAMRGs were screened between the two molecular subtypes, and these AAMRGs were involved in regulating amino acid metabolism. The AAMRGS containing GLS, IYD, and NQO1 had a high value for prognosis prediction in HCC patients. Besides this, the two AAMRGS subgroups had different genetic mutation probabilities. More importantly, the immunosuppressive cells were more enriched in the AAMRGS-high group. The expression level of inhibitory immune checkpoints was also higher in patients with high AAMRGS scores. Additionally, the two AAMRGS subgroups showed different susceptibility to chemotherapeutic and targeted drugs. In vitro experiments showed that gemcitabine significantly reduced the proliferative capacity of SNU449 cells, and rapamycin remarkedly inhibited Huh7 proliferation. The five HCC cells displayed different mRNA expression levels of GLS, IYD, and NQO1.

Conclusions

Our study explored the features of amino acid metabolism in HCC and identified the novel AAMRGS to predict the prognosis, immune microenvironment, and drug sensitivity of HCC patients. These findings might help to guide personalized treatment and improve the clinical outcomes of HCC.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients’ willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.

Identification of tryptophan metabolic gene-related subtypes, development of prognostic models, and characterization of tumor microenvironment infiltration in gliomas

BACKGROUND

Epigenetic regulation and immunotherapy of tumor microenvironment (TME) is a hot topic in recent years. However, the potential value of tryptophan metabolism genes in regulating TME and immunotherapy is still unclear.

MATERIALS AND METHODS

A comprehensive study of glioma patients was carried out based on 40 tryptophan metabolic genes. Subsequently, these prognostic tryptophan metabolic genes are systematically associated with immunological characteristics and immunotherapy. A risk score model was constructed and verified in the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients.

RESULTS

We described the changes of tryptophan metabolism genes in 966 glioma samples from genetic and transcriptional fields and evaluated their expression patterns from two independent data sets. We identified two different molecular subtypes and found that two subtypes were associated with clinicopathological features, prognosis, TME cell infiltration, and immune checkpoint blockers (ICBs). Then, four genes (IL4I1, CYP1A1, OGDHL, and ASMT) were screened out by univariate and multivariate cox regression analysis of tryptophan metabolism genes, and a risk score model for predicting the overall survival (OS) of glioma patients was constructed. And its predictive ability is verified using the CGGA database. At the same time, we verified the expression of IL4I1, CYP1A1, OGDHL, and ASMT four genes in glioma specimens and cell lines in GES4260 and GES15824. Therefore, we constructed a nomogram to improve the clinical applicability of the risk assessment model. The high risk score group, characterized by increased TMB and immune cell infiltration, was also sensitive to temozolomide immunotherapy. Our comprehensive analysis of tryptophan metabolic genes in gliomas shows that they play a potential role in tumor immune stromal microenvironment, clinicopathological features, and prognosis.

CONCLUSION

Tryptophan metabolism genes play an indispensable role in the complexity, diversity, and prognosis of TME. This risk score model based on tryptophan metabolism gene is a new predictor of clinical prognosis and immunotherapy response of glioma, and guides a more appropriate immunotherapy strategy for glioma patients.

A prognostic signature of cuproptosis and TCA-related genes for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver. Cuproptosis is a newly defined form of cell death. Copper ion induces cell death by binding to the tricarboxylic acid cycle (TCA). The effect of cuproptosis-related and TCA-related genes on the clinical prognosis of HCC is still unclear. In this study, we explores the genetic changes of cuproptosis-related genes that affect the TCA process and their potential therapeutic value in HCC patients.

Methods

The cuproptosis and TCA-related genes were obtained from cuproptosis-related articles and the molecular signatures database. The prognosis signatures of eight related genes were constructed using the last absolute shrinkage and selection operator (LASSO), and Receiver Operating Characteristic (ROC) curves were used to evaluate the signature. In addition, we analyzed downstream functional enrichment and immune infiltration to explore cuproptosis-inducing drugs and immunotherapeutic responses. All these analyses were validated using multiple datasets of the International Cancer Genome Consortium (ICGC).

Results

TCA and copper malnutrition-related genes (CDKN2A, IDH1, OGDHL, IDH3G, IDH3B, GLS, DLAT, LIPT1) were finally included. According to the risk score, they were divided into high-risk and low-risk groups. Survival analysis showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. We established a risk prognostic feature to predict the OS of patients with HCC. Based on this feature and the clinical stage, we constructed a nomogram. Functional enrichment analysis revealed pathways related to organelle division and the cell cycle. Different risk scores had different immune abundances in immune cells (including macrophages and regulatory T-cells) and immune pathways (including antigen-presenting cells co-stimulation). Moreover, the drug sensitivity of eleschomol and PD-L1 in the high-risk group was better than that in the low-risk group. The status of TP53 somatic mutation was also closely related to the risk score.

Conclusion

In this study, we established a new prediction signature of eight genes related to cuproptosis and the TCA process, which can effectively predict the prognosis of HCC patients.

Analysis on heterogeneity of hepatocellular carcinoma immune cells and a molecular risk model by integration of scRNA-seq and bulk RNA-seq

Background

Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics.

Methods

From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)–Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed.

Results

Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO–Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability.

Conclusion

To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.