USP39 promotes hepatocellular carcinogenesis through regulating alternative splicing in cooperation with SRSF6/HNRNPC.

Abnormal alternative splicing (AS) caused by alterations in spliceosomal factors is implicated in cancers. Standard models posit that splice site selection is mainly determined by early spliceosomal U1 and U2 snRNPs. Whether and how other mid/late-acting spliceosome components such as USP39 modulate tumorigenic splice site choice remains largely elusive. We observed that hepatocyte-specific overexpression of USP39 promoted hepatocarcinogenesis and potently regulated splice site selection in transgenic mice. In human liver cancer cells, USP39 promoted tumor proliferation in a spliceosome-dependent manner. USP39 depletion deregulated hundreds of AS events, including the oncogenic splice-switching of KANK2. Mechanistically, we developed a novel RBP-motif enrichment analysis and found that USP39 modulated exon inclusion/exclusion by interacting with SRSF6/HNRNPC in both humans and mice. Our data represented a paradigm for the control of splice site selection by mid/late-acting spliceosome proteins and their interacting RBPs. USP39 and possibly other mid/late-acting spliceosome proteins may represent potential prognostic biomarkers and targets for cancer therapy.

Edaravone Ameliorates Cerebral Ischemia-Reperfusion Injury by Downregulating Ferroptosis via the Nrf2/FPN Pathway in Rats.

Edaravone, an antioxidant protective agent, has anti-cerebral ischemic reperfusion injury (CIRI) effects, but its anti-CIRI mechanism is unclear. The aim of this study is to investigate the anti-CIRI mechanism of edaravone based on the nuclear factor-E2-related factor 2 (Nrf2)/ferroportin (FPN) pathway that regulates ferroptosis-mediated cerebral ischemia-reperfusion injury. We evaluated the brain injury by constructing a middle cerebral artery occlusion and reperfusion (MCAO/R) model in rats. The results showed that cerebral infarct volume and neurological impairment scores were increased in cerebral ischemia-reperfusion rats, with impaired sensorimotor ability; furthermore, brain tissue glutathione (GSH) content was decreased, Fe2+, malondialdehyde (MDA) and lipide peroxide (LPO) content were increased, and the expression level of glutathione peroxidase 4 (GPX4), a key protein of ferroptosis, was also decreased. Meanwhile, the Nrf2 expression level was increased and the FPN expression level was decreased after cerebral ischemia-reperfusion, while the levels of interleukin (IL)-6, IL-1ß, tumor necrosis factor (TNF)-α, and myeloperoxidase (MPO) were increased. However, edaravone exhibited a protective effect on cerebral infarct and neurological and sensorimotor function in relevant tests. In addition, we also found that edaravone decreased the contents of Fe2+, MDA, and LPO in the brain tissue of MCAO/R rats and increased GSH content to inhibit ferroptosis. Furthermore, Western blot showed that after treatment with edaravone, the expression of Nrf2, GPX4, and FPN was up-regulated, the nuclear location of Nrf2 was increased, and the levels of inflammation-related indicators IL-6, IL-1ß, TNF-α, and MPO were lower than in the MCAO/R group. Our results demonstrated that edaravone inhibits ferroptosis to attenuate CIRI, probably through the activation of the Nrf2/FPN pathway.

Pinpointing Cancer Sub-Type Specific Metabolic Tasks Facilitates Identification of Anti-cancer Targets.

Metabolic reprogramming is one of the hallmarks of tumorigenesis. Understanding the metabolic changes in cancer cells may provide attractive therapeutic targets and new strategies for cancer therapy. The metabolic states are not the same in different cancer types or subtypes, even within the same sample of solid tumors. In order to understand the heterogeneity of cancer cells, we used the Pareto tasks inference method to analyze the metabolic tasks of different cancers, including breast cancer, lung cancer, digestive organ cancer, digestive tract cancer, and reproductive cancer. We found that cancer subtypes haves different propensities toward metabolic tasks, and the biological significance of these metabolic tasks also varies greatly. Normal cells treat metabolic tasks uniformly, while different cancer cells focus on different pathways. We then integrated the metabolic tasks into the multi-objective genome-scale metabolic network model, which shows higher accuracy in the in silico prediction of cell states after gene knockout than the conventional biomass maximization model. The predicted potential single drug targets could potentially turn into biomarkers or drug design targets. We further implemented the multi-objective genome-scale metabolic network model to predict synthetic lethal target pairs of the Basal and Luminal B subtypes of breast cancer. By analyzing the predicted synthetic lethal targets, we found that mitochondrial enzymes are potential targets for drug combinations. Our study quantitatively analyzes the metabolic tasks of cancer and establishes cancer type-specific metabolic models, which opens a new window for the development of specific anti-cancer drugs and provides promising treatment plans for specific cancer subtypes.

Effects of Interleukin-10 -1082G/A and -592C/A Gene Polymorphisms on the Risk of Human Immunodeficiency Virus-1 Infection: An Updated Meta-analysis.

This paper has aimed to review the available evidence on the association between Interleukin (IL) -10 -1082G/A, -592C/A gene polymorphisms and the risk of human immunodeficiency virus-1(HIV-1) infection. The data of PubMed updated in May 2021 were retrieved. The HIV infection risks were estimated in allelic, recessive, dominant, homozygous, heterozygous, over-dominant models of IL-10-1082G/A and-592C/A gene locus as odds ratio (OR) with the corresponding 95% confidence interval (95% CI). The correlation was not significant between -1082G/A polymorphism and HIV-1 susceptibility (allelic model (G vs. A: OR (95% CI)=0.968 (0.878-1.067)); recessive model (GG vs. AA+AG: OR (95% CI)=0.940, (0.771-1.146)); dominant model (GG+AG vs. AA: OR (95% CI)=0.967(0.846-1.106)); homozygous model (GG vs. AA: OR (95% CI)=0.971(0.780-1.209)); heterozygous model (AG vs. AA: OR (95% CI)=0.988(0.797-1.224)) and over-dominant model (GG+AA vs. AG: OR (95% CI)=0.969(0.781-1.201)). IL-10-592C/A polymorphism might be related to HIV-1 in allelic model, dominant model, homozygous model and heterozygous model (OR (95% CI)(0.796-0.965); OR (95% CI)=0.793(0.664-0.948); OR (95% CI)=0.755,(0.612-0.930); OR (95% CI)=0.820(0.679-0.991), respectively), but not to recessive model and over-dominant model (OR (95% CI)=0.882(0.770-1.010) and OR (95% CI)=1.009(0.897-1.148)).

Jiangzhi Ligan Decoction Inhibits GSDMD-Mediated Canonical/Noncanonical Pyroptosis Pathways and Alleviates High-Fat Diet-Induced Nonalcoholic Fatty Liver Disease.

Increasing evidence suggests that gasdermin D (GSDMD) mediated pyroptosis signaling pathways play a vital role in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Jiangzhi Ligan Decoction (JZLGD) has been verified to prevent NAFLD, but its specific mechanism has not been determined. In this study, an NAFLD model was established in Sprague-Dawley rats by a high-fat diet (HFD). After 12 weeks, JZLGD was orally administered once a day for 6 additional weeks. We investigated the effects of JZLGD on NAFLD rats and determined the GSDMD pathway-associated proteins to explore whether such effects were associated with pyroptosis. Our data show that JZLGD significantly reduced the liver index; improved serum lipid levels, liver function parameters, and lipid droplet content; and relieved NAFLD. We further found that the serum levels of the proinflammatory factors interleukin-1ß (IL-1ß), IL-18, tumor necrosis factor-α, and IL-6 were obviously decreased in the JZLGD group. HFD rats treated with GSDMD exhibited NLRP3, caspase-1, lipopolysaccharide (LPS), and caspase-11 activation; however, these effects were blunted by JZLGD treatment. Taken together, JZLGD may exert hepatoprotective effects against NAFLD in a rat HFD model by regulating GSDMD-mediated canonical/noncanonical pyroptosis pathways.

Cellular stress signaling activates type-I IFN response through FOXO3-regulated lamin posttranslational modification.

Neural stem/progenitor cells (NSPCs) persist over the lifespan while encountering constant challenges from age or injury related brain environmental changes like elevated oxidative stress. But how oxidative stress regulates NSPC and its neurogenic differentiation is less clear. Here we report that acutely elevated cellular oxidative stress in NSPCs modulates neurogenic differentiation through induction of Forkhead box protein O3 (FOXO3)-mediated cGAS/STING and type I interferon (IFN-I) responses. We show that oxidative stress activates FOXO3 and its transcriptional target glycine-N-methyltransferase (GNMT) whose upregulation triggers depletion of s-adenosylmethionine (SAM), a key co-substrate involved in methyl group transfer reactions. Mechanistically, we demonstrate that reduced intracellular SAM availability disrupts carboxymethylation and maturation of nuclear lamin, which induce cytosolic release of chromatin fragments and subsequent activation of the cGAS/STING-IFN-I cascade to suppress neurogenic differentiation. Together, our findings suggest the FOXO3-GNMT/SAM-lamin-cGAS/STING-IFN-I signaling cascade as a critical stress response program that regulates long-term regenerative potential.

Urinary Tumor Necrosis Factor-Like Weak Inducer of Apoptosis as a Biomarker for Diagnosis and Evaluating Activity in Lupus Nephritis: A Meta-analysis.

OBJECTIVE: Urinary tumor necrosis factor-like weak inducer of apoptosis (uTWEAK) has been identified as a candidate biomarker for lupus nephritis (LN). However, its diagnostic value remains unclear. This meta-analysis was conducted to comprehensively evaluate the value of uTWEAK for diagnosis and evaluating activity in LN. METHODS: Medline, Web of Science, Chinese Biomedical Medical, and Chinese National Knowledge Infrastructure databases were searched to acquire eligible studies published before September 30, 2019. The quality of the studies was evaluated by Quality Assessment of Diagnostic Accuracy Studies-2. Summary receiver operating characteristic curve and area under the curve were applied to summarize the overall diagnostic performances. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated with the fixed-effects model. RevMan 5.3, Stata 12.0, and Meta-disc 1.4 software were used. RESULTS: A total of 7 studies were included. Of these, 4 studies were available for comparison between SLE with and without LN, and 3 studies were for active and inactive LN. The total area under the curve was 0.8640, and DOR was 14.89 (95% confidence interval [CI], 7.95-27.86). For LN diagnosis, the pooled sensitivity, specificity, and DOR were 0.55 (95% CI, 0.47-0.63), 0.92 (95% CI, 0.86-0.96), and 16.54 (95% CI, 7.57-36.15), respectively. For assessing LN activity, the pooled sensitivity, specificity, and DOR were 0.91 (95% CI, 0.82-0.96), 0.70 (95% CI, 0.58-0.81), and 18.45 (95% CI, 7.45-45.87), respectively. CONCLUSIONS: This meta-analysis indicated that uTWEAK has relatively moderate sensitivity and specificity for diagnosis and evaluating activity in LN, suggesting that uTWEAK can serve as a helpful biomarker for LN.

The evolving metabolic landscape of chromatin biology and epigenetics.

Molecular inputs to chromatin via cellular metabolism are modifiers of the epigenome. These inputs - which include both nutrient availability as a result of diet and growth factor signalling - are implicated in linking the environment to the maintenance of cellular homeostasis and cell identity. Recent studies have demonstrated that these inputs are much broader than had previously been known, encompassing metabolism from a wide variety of sources, including alcohol and microbiotal metabolism. These factors modify DNA and histones and exert specific effects on cell biology, systemic physiology and pathology. In this Review, we discuss the nature of these molecular networks, highlight their role in mediating cellular responses and explore their modifiability through dietary and pharmacological interventions.

Metabolism in the tumor microenvironment: insights from single-cell analysis.

The metabolism of both cancer and immune cells in the tumor microenvironment (TME) is poorly understood since most studies have focused on analysis in bulk samples and ex vivo cell culture models. Our recent analyses of single-cell RNA sequencing data suggest that the metabolic features of single cells within TME differ greatly from those of the bulk measurements. Here, we discuss some key findings about metabolism in cancer and immune cells and discuss possible relevance to immunotherapy.

Using antagonistic pleiotropy to design a chemotherapy-induced evolutionary trap to target drug resistance in cancer.

Local adaptation directs populations towards environment-specific fitness maxima through acquisition of positively selected traits. However, rapid environmental changes can identify hidden fitness trade-offs that turn adaptation into maladaptation, resulting in evolutionary traps. Cancer, a disease that is prone to drug resistance, is in principle susceptible to such traps. We therefore performed pooled CRISPR-Cas9 knockout screens in acute myeloid leukemia (AML) cells treated with various chemotherapies to map the drug-dependent genetic basis of fitness trade-offs, a concept known as antagonistic pleiotropy (AP). We identified a PRC2-NSD2/3-mediated MYC regulatory axis as a drug-induced AP pathway whose ability to confer resistance to bromodomain inhibition and sensitivity to BCL-2 inhibition templates an evolutionary trap. Across diverse AML cell-line and patient-derived xenograft models, we find that acquisition of resistance to bromodomain inhibition through this pathway exposes coincident hypersensitivity to BCL-2 inhibition. Thus, drug-induced AP can be leveraged to design evolutionary traps that selectively target drug resistance in cancer.

Evolved resistance to partial GAPDH inhibition results in loss of the Warburg effect and in a different state of glycolysis.

Aerobic glycolysis or the Warburg effect (WE) is characterized by increased glucose uptake and incomplete oxidation to lactate. Although the WE is ubiquitous, its biological role remains controversial, and whether glucose metabolism is functionally different during fully oxidative glycolysis or during the WE is unknown. To investigate this question, here we evolved resistance to koningic acid (KA), a natural product that specifically inhibits glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a rate-controlling glycolytic enzyme, during the WE. We found that KA-resistant cells lose the WE but continue to conduct glycolysis and surprisingly remain dependent on glucose as a carbon source and also on central carbon metabolism. Consequently, this altered state of glycolysis led to differential metabolic activity and requirements, including emergent activities in and dependences on fatty acid metabolism. These findings reveal that aerobic glycolysis is a process functionally distinct from conventional glucose metabolism and leads to distinct metabolic requirements and biological functions.

Identification of Cancer-associated metabolic vulnerabilities by modeling multi-objective optimality in metabolism.

BACKGROUND: Cancer cells undergo global reprogramming of cellular metabolism to satisfy demands of energy and biomass during proliferation and metastasis. Computational modeling of genome-scale metabolic models is an effective approach for designing new therapeutics targeting dysregulated cancer metabolism by identifying metabolic enzymes crucial for satisfying metabolic goals of cancer cells, but nearly all previous studies neglect the existence of metabolic demands other than biomass synthesis and trade-offs between these contradicting metabolic demands. It is thus necessary to develop computational models covering multiple metabolic objectives to study cancer metabolism and identify novel metabolic targets. METHODS: We developed a multi-objective optimization model for cancer cell metabolism at genome-scale and an integrated, data-driven workflow for analyzing the Pareto optimality of this model in achieving multiple metabolic goals and identifying metabolic enzymes crucial for maintaining cancer-associated metabolic phenotypes. Using this workflow, we constructed cell line-specific models for a panel of cancer cell lines and identified lists of metabolic targets promoting or suppressing cancer cell proliferation or the Warburg Effect. The targets were then validated using knockdown and over-expression experiments in cultured cancer cell lines. RESULTS: We found that the multi-objective optimization model correctly predicted phenotypes including cell growth rates, essentiality of metabolic genes and cell line specific sensitivities to metabolic perturbations. To our surprise, metabolic enzymes promoting proliferation substantially overlapped with those suppressing the Warburg Effect, suggesting that simply targeting the overlapping enzymes may lead to complicated outcomes. We also identified lists of metabolic enzymes important for maintaining rapid proliferation or high Warburg Effect while having little effect on the other. The importance of these enzymes in cancer metabolism predicted by the model was validated by their association with cancer patient survival and knockdown and overexpression experiments in a variety of cancer cell lines. CONCLUSIONS: These results confirm this multi-objective optimization model as a novel and effective approach for studying trade-off between metabolic demands of cancer cells and identifying cancer-associated metabolic vulnerabilities, and suggest novel metabolic targets for cancer treatment.

Methionine metabolism in health and cancer: a nexus of diet and precision medicine.

Methionine uptake and metabolism is involved in a host of cellular functions including methylation reactions, redox maintenance, polyamine synthesis and coupling to folate metabolism, thus coordinating nucleotide and redox status. Each of these functions has been shown in many contexts to be relevant for cancer pathogenesis. Intriguingly, the levels of methionine obtained from the diet can have a large effect on cellular methionine metabolism. This establishes a link between nutrition and tumour cell metabolism that may allow for tumour-specific metabolic vulnerabilities that can be influenced by diet. Recently, a number of studies have begun to investigate the molecular and cellular mechanisms that underlie the interaction between nutrition, methionine metabolism and effects on health and cancer.

Dietary methionine influences therapy in mouse cancer models and alters human metabolism.

Nutrition exerts considerable effects on health, and dietary interventions are commonly used to treat diseases of metabolic aetiology. Although cancer has a substantial metabolic component1, the principles that define whether nutrition may be used to influence outcomes of cancer are unclear2. Nevertheless, it is established that targeting metabolic pathways with pharmacological agents or radiation can sometimes lead to controlled therapeutic outcomes. By contrast, whether specific dietary interventions can influence the metabolic pathways that are targeted in standard cancer therapies is not known. Here we show that dietary restriction of the essential amino acid methionine-the reduction of which has anti-ageing and anti-obesogenic properties-influences cancer outcome, through controlled and reproducible changes to one-carbon metabolism. This pathway metabolizes methionine and is the target of a variety of cancer interventions that involve chemotherapy and radiation. Methionine restriction produced therapeutic responses in two patient-derived xenograft models of chemotherapy-resistant RAS-driven colorectal cancer, and in a mouse model of autochthonous soft-tissue sarcoma driven by a G12D mutation in KRAS and knockout of p53 (KrasG12D/+;Trp53-/-) that is resistant to radiation. Metabolomics revealed that the therapeutic mechanisms operate via tumour-cell-autonomous effects on flux through one-carbon metabolism that affects redox and nucleotide metabolism-and thus interact with the antimetabolite or radiation intervention. In a controlled and tolerated feeding study in humans, methionine restriction resulted in effects on systemic metabolism that were similar to those obtained in mice. These findings provide evidence that a targeted dietary manipulation can specifically affect tumour-cell metabolism to mediate broad aspects of cancer outcome.

Metabolic landscape of the tumor microenvironment at single cell resolution.

The tumor milieu consists of numerous cell types each existing in a different environment. However, a characterization of metabolic heterogeneity at single-cell resolution is not established. Here, we develop a computational pipeline to study metabolic programs in single cells. In two representative human cancers, melanoma and head and neck, we apply this algorithm to define the intratumor metabolic landscape. We report an overall discordance between analyses of single cells and those of bulk tumors with higher metabolic activity in malignant cells than previously appreciated. Variation in mitochondrial programs is found to be the major contributor to metabolic heterogeneity. Surprisingly, the expression of both glycolytic and mitochondrial programs strongly correlates with hypoxia in all cell types. Immune and stromal cells could also be distinguished by their metabolic features. Taken together this analysis establishes a computational framework for characterizing metabolism using single cell expression data and defines principles of the tumor microenvironment.

Nutrient availability shapes methionine metabolism in p16/MTAP-deleted cells.

Codeletions of gene loci containing tumor suppressors and neighboring metabolic enzymes present an attractive synthetic dependency in cancers. However, the impact that these genetic events have on metabolic processes, which are also dependent on nutrient availability and other environmental factors, is unknown. As a proof of concept, we considered panels of cancer cells with homozygous codeletions in CDKN2a and MTAP, genes respectively encoding the commonly-deleted tumor suppressor p16 and an enzyme involved in methionine metabolism. A comparative metabolomics analysis revealed that while a metabolic signature of MTAP deletion is apparent, it is not preserved upon restriction of nutrients related to methionine metabolism. Furthermore, re-expression of MTAP exerts heterogeneous consequences on metabolism across isogenic cell pairs. Together, this study demonstrates that numerous factors, particularly nutrition, can overwhelm the effects of metabolic gene deletions on metabolism. These findings may also have relevance to drug development efforts aiming to target methionine metabolism.

Serine synthesis through PHGDH coordinates nucleotide levels by maintaining central carbon metabolism.

Phosphoglycerate dehydrogenase (PHGDH) catalyzes the committed step in de novo serine biosynthesis. Paradoxically, PHGDH and serine synthesis are required in the presence of abundant environmental serine even when serine uptake exceeds the requirements for nucleotide synthesis. Here, we establish a mechanism for how PHGDH maintains nucleotide metabolism. We show that inhibition of PHGDH induces alterations in nucleotide metabolism independent of serine utilization. These changes are not attributable to defects in serine-derived nucleotide synthesis and redox maintenance, another key aspect of serine metabolism, but result from disruption of mass balance within central carbon metabolism. Mechanistically, this leads to simultaneous alterations in both the pentose phosphate pathway and the tri-carboxylic acid cycle, as we demonstrate based on a quantitative model. These findings define a mechanism whereby disruption of one metabolic pathway induces toxicity by simultaneously affecting the activity of multiple related pathways.

Methionine metabolism influences genomic architecture and gene expression through H3K4me3 peak width.

Nutrition and metabolism are known to influence chromatin biology and epigenetics through post-translational modifications, yet how this interaction influences genomic architecture and connects to gene expression is unknown. Here we consider, as a model, the metabolically-driven dynamics of H3K4me3, a histone methylation mark that is known to encode information about active transcription, cell identity, and tumor suppression. We analyze the genome-wide changes in H3K4me3 and gene expression in response to alterations in methionine availability in both normal mouse physiology and human cancer cells. Surprisingly, we find that the location of H3K4me3 peaks is largely preserved under methionine restriction, while the response of H3K4me3 peak width encodes almost all aspects of H3K4me3 biology including changes in expression levels, and the presence of cell identity and cancer-associated genes. These findings may reveal general principles for how nutrient availability modulates specific aspects of chromatin dynamics to mediate biological function.

Molecular mechanism of 15-lipoxygenase allosteric activation and inhibition.

Human reticulocyte 15-lipoxygenase (15-LOX) plays an important role in inflammation resolution and is also involved in many cancer-related processes. Both an activator and an inhibitor will serve as research tools for understanding the biological functions of 15-LOX and provide opportunities for drug discovery. In a previous study, both allosteric activators and inhibitors of 15-LOX were discovered through a virtual screening based computational approach. However, why molecules binding to the same site causes different effects remains to be disclosed. In the present study, we used previously reported activator and inhibitor molecules as probes to elucidate the mechanism of allosteric regulation of 15-LOX. We measured the influences of the allosteric activator and inhibitor on the enzymatic reaction rate and found that the activator increases 15-LOX activity by preventing substrate inhibition instead of increasing the turnover number. The inhibitor can also prevent substrate inhibition but decreases the turnover number at the same time, resulting in inhibition. Molecular dynamics simulations were conducted to help explain the underlying mechanism of allostery. Both the activator and inhibitor were demonstrated to be able to prevent 15-LOX from transforming into potentially inactive conformations. Compared to the activator, the inhibitor molecule restrains the motions of residues around the substrate binding site and reduces the flexibility of 15-LOX. These results explained the different effects between the activator and the inhibitor and shed light on how to effectively design novel activator molecules.

The impact of cellular metabolism on chromatin dynamics and epigenetics.

The substrates used to modify nucleic acids and chromatin are affected by nutrient availability and the activity of metabolic pathways. Thus, cellular metabolism constitutes a fundamental component of chromatin status and thereby of genome regulation. Here we describe the biochemical and genetic principles of how metabolism can influence chromatin biology and epigenetics, discuss the functional roles of this interplay in developmental and cancer biology, and present future directions in this rapidly emerging area.