HKDC1 reprograms lipid metabolism to enhance gastric cancer metastasis and cisplatin resistance via forming a ribonucleoprotein complex

Analysis of metabolic characteristics of metabolic syndrome in elderly patients with gastric cancer by non-targeted metabolomics

BACKGROUND

The relationship between metabolic syndrome (MetS) and gastric cancer (GC), which is a common metabolic disease, has attracted much attention. However, the specific metabolic characteristics of MetS in elderly patients with GC remain unclear.

AIM

To investigate the differentially abundant metabolites and metabolic pathways between preoperative frailty and MetS in elderly patients with GC based on nontargeted metabolomics techniques.

METHODS

In this study, 125 patients with nonfrail nonmeal GC were selected as the control group, and 50 patients with GC in the frail group were selected as the frail group. Sixty-five patients with GC combined with MetS alone were included in the MetS group, and 50 patients with GC combined with MetS were included in the MetS group. Nontargeted metabolomics techniques were used to measure plasma metabolite levels by ultrahigh-performance liquid chromatography-mass spectrometry. Multivariate statistical analysis was performed by principal component analysis, orthogonal partial least squares, pattern recognition analysis, cluster analysis, and metabolic pathway annotation.

RESULTS

A total of 125 different metabolites, including amino acids, glycerophospholipids, sphingolipids, fatty acids, sugars, nucleosides and nucleotides, and acidic compounds, were identified via nontargeted metabolomics techniques. Compared with those in the control group, there were 41, 32, and 52 different metabolites in the MetS group, the debilitated group, and the combined group, respectively. Lipid metabolites were significantly increased in the MetS group. In the weak group, amino acids and most glycerol phospholipid metabolites decreased significantly, and fatty acids and sphingosine increased significantly. The combined group was characterized by significantly increased levels of nucleotide metabolites and acidic compounds. The alanine, aspartic acid, and glutamate metabolic pathways were obviously enriched in the asthenic group, and the glycerol and phospholipid metabolic pathways were obviously enriched in the combined group.

CONCLUSION

Elderly GC patients with simple frailty, simple combined MetS, and frailty combined with MetS have different metabolic characteristics, among which amino acid and glycerophospholipid metabolite levels are significantly lower in frail elderly GC patients, and comprehensive supplementation of fat and protein should be considered. Many kinds of metabolites, such as amino acids, lipids, nucleotides, and acidic compounds, are abnormally abundant in patients with MetS combined with fthenia, which may be related to tumor-related metabolic disorders.

Analysis of metabolic characteristics of metabolic syndrome in elderly patients with gastric cancer by non-targeted metabolomics

BACKGROUND

The relationship between metabolic syndrome (MetS) and gastric cancer (GC), which is a common metabolic disease, has attracted much attention. However, the specific metabolic characteristics of MetS in elderly patients with GC remain unclear.

AIM

To investigate the differentially abundant metabolites and metabolic pathways between preoperative frailty and MetS in elderly patients with GC based on nontargeted metabolomics techniques.

METHODS

In this study, 125 patients with nonfrail nonmeal GC were selected as the control group, and 50 patients with GC in the frail group were selected as the frail group. Sixty-five patients with GC combined with MetS alone were included in the MetS group, and 50 patients with GC combined with MetS were included in the MetS group. Nontargeted metabolomics techniques were used to measure plasma metabolite levels by ultrahigh-performance liquid chromatography-mass spectrometry. Multivariate statistical analysis was performed by principal component analysis, orthogonal partial least squares, pattern recognition analysis, cluster analysis, and metabolic pathway annotation.

RESULTS

A total of 125 different metabolites, including amino acids, glycerophospholipids, sphingolipids, fatty acids, sugars, nucleosides and nucleotides, and acidic compounds, were identified via nontargeted metabolomics techniques. Compared with those in the control group, there were 41, 32, and 52 different metabolites in the MetS group, the debilitated group, and the combined group, respectively. Lipid metabolites were significantly increased in the MetS group. In the weak group, amino acids and most glycerol phospholipid metabolites decreased significantly, and fatty acids and sphingosine increased significantly. The combined group was characterized by significantly increased levels of nucleotide metabolites and acidic compounds. The alanine, aspartic acid, and glutamate metabolic pathways were obviously enriched in the asthenic group, and the glycerol and phospholipid metabolic pathways were obviously enriched in the combined group.

CONCLUSION

Elderly GC patients with simple frailty, simple combined MetS, and frailty combined with MetS have different metabolic characteristics, among which amino acid and glycerophospholipid metabolite levels are significantly lower in frail elderly GC patients, and comprehensive supplementation of fat and protein should be considered. Many kinds of metabolites, such as amino acids, lipids, nucleotides, and acidic compounds, are abnormally abundant in patients with MetS combined with fthenia, which may be related to tumor-related metabolic disorders.

Targeting PRKDC activates the efficacy of antitumor immunity while sensitizing to chemotherapy and targeted therapy in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) ranks among the malignancies with the highest mortality rates, primarily due to chemoresistance culminating in treatment failure. Despite its impact, predictive models addressing disease progression, tumor microenvironment, and drug sensitivity remain elusive for LIHC patients. Recognizing the significant influence of various programmed cell death (PCD) modes on tumor evolution, this study investigates PCD genes to elucidate their implications on the prognosis and immune landscape of LIHC.

METHODS

To develop the classification and model, we employed a total of 17 genes associated with PCD patterns. To collect data, we acquired gene expression profiles, somatic mutation information, copy number variation data, and corresponding clinical data from the TCGA database, specifically from LIHC patients. Moreover, we obtained spatial transcriptome data and additional bulk datasets from the Gene Expression Omnibus (GEO) database to conduct further analysis. Various experiments were conducted to validate the role of the PCD gene PRKDC in proliferation, migration, invasion, EMT, cell cycle, therapeutic sensitivity, and antitumor immunity.

RESULTS

A novel LIHC classification based on these genes divided patients into two clusters, C1 and C2. The C2 cluster exhibited characteristics indicative of poor prognosis and an immune-activated microenvironment. This group showed greater response potential to immune checkpoint inhibitors, displaying higher levels of certain immune signatures and receptors. A programmed cell death index (PCDI) was constructed using 17 selected PCD genes. This index could effectively predict patient prognosis, with higher PCDI indicating poorer survival rates and a more pro-tumor microenvironment. Immune landscapes revealed varying interactions with PCDI, suggesting therapeutic targets and insights into treatment resistance. Moreover, experiments results suggested that PRKDC can augment the invasive nature and growth of malignant cells and it can serve as a potential target for therapy, offering hope for ameliorating the prognosis of LIHC patients.

CONCLUSIONS

The study uncovers the insights of programmed cell death in the prognosis and potential therapeutic interventions. And we found that PRKDC can serve as a target for enhancing the efficacy of antitumor immunity while sensitizing chemotherapy and targeted therapy in liver hepatocellular carcinoma.

The stromal microenvironment endows pancreatic neuroendocrine tumors with spatially specific invasive and metastatic phenotypes

Cancer-associated fibroblasts (CAFs) play an important role in a variety of cancers. However, the role of tumor stroma in nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs) is often neglected. Profiling the heterogeneity of CAFs can reveal the causes of malignant phenotypes in NF-PanNETs. Here, we found that patients with high stromal proportion had poor prognosis, especially for that with infiltrating stroma (stroma and tumor cells that presented an infiltrative growth pattern and no regular boundary). In addition, myofibroblastic CAFs (myCAFs), characterized by FAP+ and α-SMAhigh, were spatially closer to tumor cells and promoted the EMT and tumor growth. Intriguingly, only tumor cells which were spatially closer to myCAFs underwent EMT. We further elucidated that myCAFs stimulate TGF-β expression in nearby tumor cells. Then, TGF-β promoted the EMT in adjacent tumor cells and promoted the expression of myCAFs marker genes in tumor cells, resulting in distant metastasis. Our results indicate that myCAFs cause spatial heterogeneity of EMT, which accounts for liver metastasis of NF-PanNETs. The findings of this study might provide possible targets for the prevention of liver metastasis.

The effect of lipid metabolism on cuproptosis-inducing cancer therapy

Cuproptosis provides a new therapeutic strategy for cancer treatment and is thought to have broad clinical application prospects. Nevertheless, some oncological clinical trials have yet to demonstrate favorable outcomes, highlighting the need for further research into the molecular mechanisms underlying cuproptosis in tumors. Cuproptosis primarily hinges on the intracellular accumulation of copper, with lipid metabolism exerting a profound influence on its course. The interaction between copper metabolism and lipid metabolism is closely related to cuproptosis. Copper imbalance can affect mitochondrial respiration and lipid metabolism changes, while lipid accumulation can promote copper uptake and absorption, and inhibit cuproptosis induced by copper. Anomalies in lipid metabolism can disrupt copper homeostasis within cells, potentially triggering cuproptosis. The interaction between cuproptosis and lipid metabolism regulates the occurrence, development, metastasis, chemotherapy drug resistance, and tumor immunity of cancer. Cuproptosis is a promising new target for cancer treatment. However, the influence of lipid metabolism and other factors should be taken into consideration. This review provides a brief overview of the characteristics of the interaction between cuproptosis and lipid metabolism in cancer and analyses potential strategies of applying cuproptosis for cancer treatment.