T-cell development of resistance to apoptosis is driven by a metabolic shift in carbon source and altered activation of death pathways

The impact of glucose metabolism on inflammatory processes in sepsis-induced acute lung injury

Acute lung injury (ALI) is a prevalent and critical complication of sepsis, marked by high incidence and mortality rates, with its pathogenesis still not being fully elucidated. Recent research has revealed a significant correlation between the metabolic reprogramming of glucose and sepsis-associated ALI (S-ALI). Throughout the course of S-ALI, immune cells, including macrophages and dendritic cells, undergo metabolic shifts to accommodate the intricate demands of immune function that emerge as sepsis advances. Indeed, glucose metabolic reprogramming in S-ALI serves as a double-edged sword, fueling inflammatory immune responses in the initial stages and subsequently initiating anti-inflammatory responses as the disease evolves. In this review, we delineate the current research progress concerning the pathogenic mechanisms linked to glucose metabolic reprogramming in S-ALI, with a focus on the pertinent immune cells implicated. We encapsulate the impact of glucose metabolic reprogramming on the onset, progression, and prognosis of S-ALI. Ultimately, by examining key regulatory factors within metabolic intermediates and enzymes, We have identified potential therapeutic targets linked to metabolic reprogramming, striving to tackle the inherent challenges in diagnosing and treating Severe Acute Lung Injury (S-ALI) with greater efficacy.

Construction and validation of a prognostic model for hepatocellular carcinoma: Inflammatory ferroptosis and mitochondrial metabolism indicate a poor prognosis

Background

An increasing number of innovations have been discovered for treating hepatocellular carcinoma (HCC or commonly called HCC) therapy, Ferroptosis and mitochondrial metabolism are essential mechanisms of cell death. These pathways may act as functional molecular biomarkers that could have important clinical significance for determining individual differences and the prognosis of HCC. The aim of this study was to construct a stable and reliable comprehensive model of genetic features and clinical factors associated with HCC prognosis.

Methods

In this study, we used RNA-sequencing (fragments per kilobase of exon model per million reads mapped value) data from the Cancer Genome Atlas (TCGA) database to establish a prognostic model. We enrolled 104 patients for further validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analyses (KEGG) analysis were used for the functional study of differentially expressed genes. Pan-cancer analysis was performed to evaluate the function of the Differentially Expressed Genes (DEGs). Thirteen genes were identified by univariate and least absolute contraction and selection operation (LASSO) Cox regression analysis. The prognostic model was visualized using a nomogram.

Results

We found that eight genes, namely EZH2, GRPEL2, PIGU, PPM1G, SF3B4, TUBG1, TXNRD1 and NDRG1, were hub genes for HCC and differentially expressed in most types of cancer. EZH2, GRPEL2 and NDRG1 may indicate a poor prognosis of HCC as verified by tissue samples. Furthermore, a gene set variation analysis algorithm was created to analyze the relationship between these eight genes and oxidative phosphorylation, mitophagy, and FeS-containing proteins, and it showed that ferroptosis might affect inflammatory-related pathways in HCC.

Conclusion

EZH2, GRPEL2, NDRG1, and the clinical factor of tumor size, were included in a nomogram for visualizing a prognostic model of HCC. This nomogram based on a functional study and verification by clinical samples, shows a reliable performance of patients with HCC.

Metabolic reprogramming and apoptosis sensitivity: Defining the contours of a T cell response

An effective adaptive immune response hinges on the rapid clonal expansion of T cells in response to antigen. The sensitivity of these T cells to programmed cell death (i.e. apoptosis) is carefully calibrated at various stages to ensure a robust yet measured reaction that resolves without inflicting unintended damage to host tissues. To meet bioenergetic demands associated with vigorous proliferation, acquisition of effector functions, and memory formation, T cells also undergo dynamic changes in their metabolism at every stage of this response. In this review, we focus on relatively recent studies that illuminate intimate links between metabolic programs and apoptosis sensitivity in T cells. We then examine how these connections ultimately influence T cell survival and function within the metabolically taxing environs of the tumor microenvironment.

Teaching the basics of cancer metabolism: Developing antitumor strategies by exploiting the differences between normal and cancer cell metabolism

This review of the basics of cancer metabolism focuses on exploiting the metabolic differences between normal and cancer cells. The first part of the review covers the different metabolic pathways utilized in normal cells to generate cellular energy, or ATP, and the glycolytic intermediates required to build the cellular machinery. The second part of the review discusses aerobic glycolysis, or the Warburg effect, and the metabolic reprogramming involving glycolysis, tricarboxylic acid cycle, and glutaminolysis in the context of developing targeted inhibitors in cancer cells. Finally, the selective targeting of cancer mitochondrial metabolism using positively charged lipophilic compounds as potential therapeutics and their ability to mitigate the toxic side effects of conventional chemotherapeutics in normal cells are discussed. I hope this graphical review will be useful in helping undergraduate, graduate, and medical students understand how investigating the basics of cancer cell metabolism could provide new insight in developing potentially new anticancer treatment strategies.

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Exploiting biochemical and metabolic differences between normal and cancer cells.

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Mitigating reverse Warburg effect in the tumor stroma or microenvironment to hinder tumor growth.

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Dual targeting of glycolysis and mitochondrial metabolism to inhibit tumor cell proliferation.