Direct and quantitative analysis of altered metabolic flux distributions and cellular ATP production pathway in fumarate hydratase-diminished cells

Ferroptosis: a promising target for fumarate hydratase-deficient tumor therapeutics literature review

Background and Objective

This review aims to investigate the ferroptosis mechanism of fumarate hydratase (FH)-related tumors for the purpose of possible treatment of tumors. Ferroptosis is an iron (Fe)-dependent form of regulated cell death caused by lipid peroxidation on the cell membrane. Studies have implicated FH in tumorigenesis. As mutations in the FH gene alter cellular metabolism and increase tumorigenesis risk, particularly in the kidneys. As most tumor cells require higher amounts of ferrous ions (Fe2+) than normal cells, they are more susceptible to ferroptosis. Recent studies have indicated that ferroptosis is inhibited the pathogenesis and progression of FH-deficient tumors by regulating lipid and iron metabolism, glutathione-glutathione peroxidase 4 (GSH-GPX4), nuclear factor-erythroid 2-related factor 2 (NRF2)/heme oxygenase-1 (HO-1) pathways. While the Fe2+ content is significantly lower in FH-deficient tumor cells, than that in normal cells. It is promising to promote ferroptosis by increasing the concentration of Fe2+ in cells to achieve the purpose of tumor treatment.

Methods

In this study, we searched for relevant articles on ferroptosis and FH-deficient tumors using PubMed database.

Key Content and Findings

FH is a tumor suppressor. A number of basic studies have shown that the loss of FH plays an important role in hereditary leiomyomas and tumors such as renal cell carcinoma, ovarian cancer, and other tumors. This type of tumor cells can through induce ferroptosis, inhibit proliferation, migration and invasion of tumor cells, increase the sensitivity of tumor cells to chemotherapy, and reverse the drug resistance through various molecular mechanisms. At present, the research on ferroptosis in FH-related tumors is still in the basic experimental stage.

Conclusions

This article reviews the anti-tumor effects and mechanisms of FH and ferroptosis, in order to further explore the medical value of ferroptosis in FH-related tumor therapy.

Metabolic Patterns of High-Invasive and Low-Invasive Oral Squamous Cell Carcinoma Cells Using Quantitative Metabolomics and 13C-Glucose Tracing

Most current metabolomics studies of oral squamous cell carcinoma (OSCC) are mainly focused on identifying potential biomarkers for early screening and diagnosis, while few studies have investigated the metabolic profiles promoting metastasis. In this study, we aimed to explore the altered metabolic pathways associated with metastasis of OSCC. Here, we identified four OSCC cell models (CAL27, HN6, HSC-3, SAS) that possess different invasive heterogeneity via the transwell invasion assay and divided them into high-invasive (HN6, SAS) and low-invasive (CAL27, HSC-3) cells. Quantitative analysis and stable isotope tracing using [U-13C6] glucose were performed to detect the altered metabolites in high-invasive OSCC cells, low-invasive OSCC cells and normal human oral keratinocytes (HOK). The metabolic changes in the high-invasive and low-invasive cells included elevated glycolysis, increased fatty acid metabolism and an impaired TCA cycle compared with HOK. Moreover, pathway analysis demonstrated significant differences in fatty acid biosynthesis; arachidonic acid (AA) metabolism; and glycine, serine and threonine metabolism between the high-invasive and low-invasive cells. Furthermore, the high-invasive cells displayed a significant increase in the percentages of 13C-glycine, 13C-palmitate, 13C-stearic acid, 13C-oleic acid, 13C-AA and estimated FADS1/2 activities compared with the low-invasive cells. Overall, this exploratory study suggested that the metabolic differences related to the metastatic phenotypes of OSCC cells were concentrated in glycine metabolism, de novo fatty acid synthesis and polyunsaturated fatty acid (PUFA) metabolism, providing a comprehensive understanding of the metabolic alterations and a basis for studying related molecular mechanisms in metastatic OSCC cells.

Succinylation of a KEAP1 sensor lysine promotes NRF2 activation

Cross talk between metabolism and stress-responsive signaling is essential for maintaining cellular homeostasis. This cross talk is often achieved through covalent modification of proteins by endogenous, reactive metabolites that regulate key stress-responsive transcription factors like NRF2. Metabolites including methylglyoxal, glyceraldehyde 3-phosphate, fumarate, and itaconate covalently modify sensor cysteines of the NRF2 repressor KEAP1, resulting in stabilization of NRF2 and activation of its cytoprotective transcriptional program. Here, we employed a shRNA-based screen targeting the enzymes of central carbon metabolism to identify additional regulatory nodes bridging metabolism to NRF2 activation. Succinic anhydride, increased by genetic depletion of the TCA cycle enzyme succinyl-CoA synthetase or by direct administration, results in N-succinylation of lysine 131 of KEAP1 to activate NRF2 signaling. This study identifies KEAP1 as capable of sensing reactive metabolites not only by several cysteine residues but also by a conserved lysine residue, indicating its potential to sense an expanded repertoire of reactive metabolic messengers.

Serum Anti-Fumarate Hydratase Autoantibody as a Biomarker for Predicting Prognosis of Acute-on-Chronic Liver Failure

Background/Aims

To investigate the autoantibody against fumarate hydratase (FH), which is a specific liver failure-associated antigen (LFAA) and determine whether it can be used as a biomarker to evaluate the prognosis of acute-on-chronic liver failure (ACLF).

Methods

An immunoproteomic approach was applied to screen specific LFAAs related to differential prognosis of ACLF (n=60). Enzyme-linked immunosorbent assay (ELISA) technology was employed for the validation of the frequency and titer of autoantibodies against FH in ACLF patients with different prognoses (n=82). Moreover, we clarified the expression of autoantibodies against FH in patients with chronic hepatitis B (n=60) and hepatitis B virus-related liver cirrhosis (n=60). The dynamic changes in the titers of autoantibodies against FH were analyzed by sample collection at multiple time points during the clinical course of eight ACLF patients with different prognoses.

Results

Ultimately, 15 LFAAs were screened and identified by the immunoproteomic approach. Based on ELISA-based verification, anti-FH/Fumarate hydratase protein autoantibody was chosen to verify its expression in ACLF patients. ACLF patients had a much higher anti-FH autoantibody frequency (76.8%) than patients with liver cirrhosis (10%, p=0.000), patients with chronic hepatitis B (6.7%, p=0.022), and normal humans (0%, p=0.000). More importantly, the frequency and titer of anti-FH protein autoantibodies in the serum of ACLF patients with a good prognosis were much higher than that of patients with a poor prognosis (83.9% vs 61.5%, p=0.019; 1.41±0.85 vs 0.94±0.56, p=0.017, respectively). The titer of anti-FH autoantibodies showed dynamic changes in the clinical course of ACLF.

Conclusions

The anti-FH autoantibody in serum may be a potential biomarker for predicting the prognosis of ACLF.

Interpreting metabolic complexity via isotope-assisted metabolic flux analysis

Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output). We then describe how iMFA enables analysis of metabolic complexities and discovery of metabolic pathways. Our goal is to expand the use of iMFA in metabolism research, which is essential to maximizing the impact of metabolic experiments and continuing to advance iMFA and biocomputational techniques.

Succinylation of a KEAP1 sensor lysine promotes NRF2 activation

Crosstalk between metabolism and stress-responsive signaling is essential to maintaining cellular homeostasis. One way this crosstalk is achieved is through the covalent modification of proteins by endogenous, reactive metabolites that regulate the activity of key stress-responsive transcription factors such as NRF2. Several metabolites including methylglyoxal, glyceraldehyde 3-phosphate, fumarate, and itaconate covalently modify sensor cysteines of the NRF2 regulatory protein KEAP1, resulting in stabilization of NRF2 and activation of its cytoprotective transcriptional program. Here, we employed a shRNA-based screen targeting the enzymes of central carbon metabolism to identify additional regulatory nodes bridging metabolic pathways to NRF2 activation. We found that succinic anhydride, increased by genetic depletion of the TCA cycle enzyme succinyl-CoA synthetase or by direct administration, results in N-succinylation of lysine 131 of KEAP1 to activate NRF2 transcriptional signaling. This study identifies KEAP1 as capable of sensing reactive metabolites not only by several cysteine residues but also by a conserved lysine residue, indicating its potential to sense an expanded repertoire of reactive metabolic messengers.

Isotope-Assisted Metabolic Flux Analysis: A Powerful Technique to Gain New Insights into the Human Metabolome in Health and Disease

Cell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured. Instead, flux quantification requires sophisticated mathematical and computational analysis of data from isotope labeling experiments. In this review, we describe isotope-assisted metabolic flux analysis (iMFA), a rigorous computational approach to fluxome quantification that integrates metabolic network models and experimental data to generate quantitative metabolic flux maps. We highlight practical considerations for implementing iMFA in mammalian models, as well as iMFA applications in in vitro and in vivo studies of physiology and disease. Finally, we identify promising new frontiers in iMFA which may enable us to fully unlock the potential of iMFA in biomedical research.