The relationship between prognosis and glucose metabolism of tumor cell
Ontology highlight
ABSTRACT:
DISEASE(S): Hepatocelluar Carcinoma And Colorectal Cancer
PROVIDER: 2626836 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Tumors rely on multiple nutrients to meet cellular bioenergetics and macromolecular synthesis demands of rapidly dividing cells. Although the role of glucose and glutamine in cancer metabolism is well understood, the relative contribution of acetate metabolism remains to be clarified. We show that glutamine supplementation is not sufficient to prevent loss of cell viability in a subset of glucose-deprived melanoma cells, but synergizes with acetate to support cell survival. Glucose-deprived melanoma cells depend on both oxidative phosphorylation and acetate metabolism for cell survival. Acetate supplementation significantly contributed to maintenance of ATP levels in glucose-starved cells. Unlike acetate, short chain fatty acids such as butyrate and propionate failed to prevent loss of cell viability from glucose deprivation. In vivo studies revealed that in addition to nucleo-cytoplasmic acetate assimilating enzyme ACSS2, mitochondrial ACSS1 was critical for melanoma tumor growth in mice. Our data indicate that acetate metabolism may be a potential therapeutic target for BRAF mutant melanoma.
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Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns.
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Project description:This study identified DNA methylation patterns that were associated with tumor subtypes, disease outcome, and distinct metabolome and gene expression patterns.
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Project description:Purpose: To analyze and review the progress of glucose metabolism-based molecular imaging in detecting tumors to guide clinicians for new management strategies. Summary: When metabolic abnormalities occur, termed the Warburg effect, it simultaneously enables excessive cell proliferation and inhibits cell apoptosis. Molecular imaging technology combines molecular biology and cell probe technology to visualize, characterize, and quantify processes at cellular and subcellular levels in vivo. Modern instruments, including molecular biochemistry, data processing, nanotechnology, and image processing, use molecular probes to perform real-time, non-invasive imaging of molecular and cellular events in living organisms. Conclusion: Molecular imaging is a non-invasive method for live detection, dynamic observation, and quantitative assessment of tumor glucose metabolism. It enables in-depth examination of the connection between the tumor microenvironment and tumor growth, providing a reliable assessment technique for scientific and clinical research. This new technique will facilitate the translation of fundamental research into clinical practice.
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Project description:Background To depict the immune infiltration characteristics of tumor cells in patients with lung adenocarcinoma (LUAD) and evaluate the predictive value and significance of tumor immune cells on the prognosis of LUAD patients. Methods The clinical characteristics and transcriptome of LUAD patients were obtained from The Cancer Genome Atlas (TCGA), and the immune cell abundance in LUAD tissue was evaluated using the CIBERSORT algorithm. We created a simplified immune cell-based Cox regression model according to the survival status of patients and clarified the correlation between the survival status of patients and seven types of immune cells. An immune cell-based risk prediction model was created by Cox proportional hazards regression. Subsequently, the gene expression profile of LUAD patients was obtained from the Gene Expression Omnibus (GEO) database to validate the tumor immune infiltration and patient prognosis prediction model attained using the CIBERSORT algorithm. Results The abundance of 22 tumor-infiltrating immune cells in these patients was detected using the CIBERSORT algorithm. According to Pearson correlation analysis, the immune cells appeared to be closely related to each other. The immune cell composition was remarkably different between the LUAD tumor tissue and paracancerous tissue. The simplified COX model showed that seven kinds of immune cells have predictive value for the prognosis and survival status of LUAD. The receiver operating characteristic curve (ROC) curve confirmed that the prediction model performed well for 1-, 3-, and 5-year survival status. The calibration curve suggested that the prediction model was consistent with the clinical results. Correlation analysis revealed that the clinical features were significantly related to immune cell infiltration. A total of 246 LUAD specimens were from the GEO database, and the risk score model suggested that high risk scores were indicative of a poor prognosis. Finally, enzyme-linked immunosorbent assay (ELISA) revealed that the expressions of tumor necrosis factor-α (TNF-α), interleukin 8 (IL-8), IL-6, and interferon-γ (IFN-γ) in tumor tissues were remarkably higher compared with those in adjacent tissues. Conclusions There is a close correlation between the tumor-infiltrating immune cells and the prognosis and clinical characteristics of LUAD patients. The risk score model based on TCGA and GEO designed in this study can be applied in clinical practice.
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