Metabolite sensing and signaling in cancer

New alleles of D-2-hydroxyglutarate dehydrogenase enable studies of oncometabolite function in Drosophila melanogaster

D-2-hydroxyglutarate (D-2HG) is a potent oncometabolite capable of disrupting chromatin architecture, altering metabolism, and promoting cellular dedifferentiation. As a result, ectopic D-2HG accumulation induces neurometabolic disorders and promotes progression of multiple cancers. However, the disease-associated effects of ectopic D-2HG accumulation are dependent on genetic context. Specifically, neomorphic mutations in the mammalian genes Isocitrate dehydrogenase 1 ( IDH1 ) and IDH2 result in the production of enzymes that inappropriately generate D-2HG from α-ketoglutarate (αKG). Within this genetic background, D-2HG acts as an oncometabolite and is associated with multiple cancers, including several diffuse gliomas. In contrast, loss-of-function mutations in the gene D-2-hydroxyglutarate dehydrogenase (D2hgdh) render cells unable to degrade D-2HG, resulting in excessive buildup of this molecule. D2hgdh mutations, however, are not generally associated with elevated cancer risk. This discrepancy raises the question as to why ectopic D-2HG accumulation in humans induces context-dependent disease outcomes. To enable such genetic studies in vivo , we generated two novel loss-of-function mutations in the Drosophila melanogaster gene D2hgdh and validated that these alleles result in ectopic D-2HG. Moreover, we observed that D2hgdh mutations induce developmental and metabolomic phenotypes indicative of elevated D-2HG accumulation. Overall, our efforts provide the Drosophila community with new mutant strains that can be used to study D-2HG function in human disease models as well as in the context of normal growth, metabolism, and physiology.

Identification and analysis of amino acid metabolism-related subtypes in lung adenocarcinoma

We aimed to explore the role of amino acid metabolism (AAM) and identify biomarkers for prognosis management and treatment of lung adenocarcinoma. Differentially expressed genes (DEGs) associated with AAM in lung adenocarcinoma were selected from public databases. Samples were clustered into varying subtypes using ConsensusClusterPlus based on gene levels. Survival analysis was conducted using a survival package, and immune analysis was performed using ssGSEA and ESTIMATE. Enrichment analysis was performed using gene set enrichment analysis, and a protein-protein interaction network of DEGs between subgroups was established through STRING. Hub genes were screened and verified using survival analysis, and drug sensitivity prediction was performed. One hundred sixty-three DEGs associated with AAM in lung adenocarcinoma were obtained, and two AAM-associated subtypes were identified. Cluster 1 showed higher survival rates and immune levels compared with cluster 2. The two subtypes were mainly enriched in immune-related signaling pathways, such as B cell receptor, Jak-Stat, and natural killer cell-mediated cytotoxicity. In addition, the mutation landscape between the two groups was significantly different. F2, AHSG, and APOA1 were key hub genes that significantly affected the prognosis differences between the two subtypes. Cluster 2 showed higher sensitivity to drugs, such as mithramycin, depsipeptide, and actinomycin than cluster 1. This study identified two AAM-associated gene subtypes and their biomarkers and predicted the immune status and drug treatment sensitivity of varying subtypes. The results are instructive in the clinical treatment of lung adenocarcinoma.NEW & NOTEWORTHY Two amino acid metabolism-related subtypes were identified based on differentially expressed genes associated with amino acid metabolism. Cluster 1 showed higher survival rates and immune levels compared with cluster 2. Cluster 2 showed higher sensitivity to drugs, such as mithramycin, depsipeptide, and actinomycin compared with cluster 1.

Association of circulating metabolic biomarkers with risk of lung cancer: a population-based prospective cohort study

BACKGROUND

There is emerging evidence that metabolites might be associated with risk of lung cancer, but their relationships have not been fully characterized. We aimed to investigate the association between circulating metabolic biomarkers and lung cancer risk and the potential underlying pathways.

METHODS

Nuclear magnetic resonance metabolomic profiling was conducted on baseline plasma samples from 91,472 UK Biobank participants without cancer and pregnancy. Multivariate Cox regression models were employed to assess the hazard ratios (HRs) of 164 metabolic biomarkers (including metabolites and lipoprotein subfractions) and 9 metabolic biomarker principal components (PCs) for lung cancer, after adjusting for covariates and false discovery rate (FDR). Pathway analysis was conducted to investigate the potential metabolic pathways.

RESULTS

During a median follow-up of 11.0 years, 702 participants developed lung cancer. A total of 109 metabolic biomarkers (30 metabolites and 79 lipoprotein subfractions) were associated with the risk of lung cancer. Glycoprotein acetyls demonstrated a positive association with lung cancer risk [HR = 1.13 (95%CI: 1.04, 1.22)]. Negative associations with lung cancer were found for albumin [0.78 (95%CI: 0.72, 0.83)], acetate [0.91 (95%CI: 0.85, 0.97)], valine [0.90 (95%CI: 0.83, 0.98)], alanine [0.88 (95%CI: 0.82, 0.95)], glucose [0.91 (95%CI: 0.85, 0.99)], citrate [0.91 (95%CI: 0.85, 0.99)], omega-3 fatty acids [0.83 (95%CI: 0.77, 0.90)], linoleic acid [0.83 (95%CI: 0.77, 0.89)], etc. Nine PCs represented over 90% of the total variances, and among those with statistically significant estimates, PC1 [0.85 (95%CI: 0.80, 0.92)], PC2 [0.88 (95%CI: 0.82, 0.95)], and PC9 [0.87 (95%CI: 0.80, 0.93)] were negatively associated with lung cancer risk, whereas PC7 [1.08 (95%CI: 1.00, 1.16)] and PC8 [1.16 (95%CI: 1.08, 1.26)] showed positive associations with lung cancer risk. The pathway analysis showed that the "linoleic acid metabolism" was statistically significant after the FDR adjustment (p value 0.0496).

CONCLUSIONS

Glycoprotein acetyls had a positive association with lung cancer risk while other metabolites and lipoprotein subfractions showed negative associations. Certain metabolites and lipoprotein subfractions might be independent risk factors for lung cancer. Our findings shed new light on the etiology of lung cancer and might aid the selection of high-risk individuals for lung cancer screening.

Omics sciences for cervical cancer precision medicine from the perspective of the tumor immune microenvironment

Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer (CC). However, the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment (TIME). Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME. Furthermore, integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior. In this review, we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC, highlighting their utility in identifying metastasis dissemination, recurrence risk, and therapeutic resistance in patients treated with immunotherapeutic approaches. This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms. Additionally, an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.

Pyruvate metabolism enzyme DLAT promotes tumorigenesis by suppressing leucine catabolism

Pyruvate and branched-chain amino acid (BCAA) metabolism are pivotal pathways in tumor progression, yet the intricate interplay between them and its implications for tumor progression remain elusive. Our research reveals that dihydrolipoamide S-acetyltransferase (DLAT), a pyruvate metabolism enzyme, promotes leucine accumulation and sustains mammalian target of rapamycin (mTOR) complex activation in hepatocellular carcinoma (HCC). Mechanistically, DLAT directly acetylates the K109 residue of AU RNA-binding methylglutaconyl-coenzyme A (CoA) hydratase (AUH), a critical enzyme in leucine catabolism, inhibiting its activity and leading to leucine accumulation. Notably, DLAT upregulation correlates with poor prognosis in patients with HCC. Therefore, we developed an AUHK109R-mRNA lipid nanoparticles (LNPs) therapeutic strategy, which effectively inhibits tumor growth by restoring leucine catabolism and inhibiting mTOR activation in vivo. In summary, our findings uncover DLAT's unexpected role as an acetyltransferase for AUH, suppressing leucine catabolism. Restoring leucine catabolism with AUHK109R-mRNA LNP effectively inhibits HCC development, highlighting a novel direction for cancer research.

HOGA1 Suppresses Renal Cell Carcinoma Growth via Inhibiting the Wnt/β-Catenin Signalling Pathway

Changes in hydroxyproline metabolism are reported to promote tumorigenesis. HOGA1 is a useful marker for diagnosing primary hyperoxaluria 3, catalysing the final step of mitochondrial hydroxyproline metabolism from 4-hydroxy-2-oxoglutarate (HOG) to glyoxylate and pyruvate; however, its specific mechanism in RCC remains unclear. This study investigated the role of HOGA1 in the pathogenesis of ccRCC. The results showed that HOGA1 was decreased significantly in tumour tissues, with this low expression associated with a poor prognosis in patients with ccRCC. QTL mapping showed that Hoga1 was cis-regulated. Gene enrichment analyses showed that Hoga1 co-expressed genes were enriched in the Wnt/β-catenin signalling pathway. Furthermore, in vitro and in vivo assays demonstrated that HOGA1 significantly inhibited the proliferation, invasion and migration of renal carcinoma cells via the Wnt/β-catenin-c-Myc/CyclinD1 axis, probably via regulating the level of HOG. In conclusion, this study demonstrates that HOGA1 has a tumour suppressor role by inhibiting the Wnt/β-catenin signalling pathway. This finding provides new insights into the function of HOGA1 in ccRCC.

Methylmalonic acid at the serum level in the elderly contributes to cell growth via mitochondrial dysfunction in colorectal cancer cell spheroids

Methylmalonic acid (MMA) is a small molecule produced during the metabolism of propionate and branched-chain amino acids. Recently, it has been reported that the blood concentration of MMA increases with age and promotes lung cancer metastasis. However, little is known regarding its effects on cancers other than lung cancer. In the present study, we examined the effects of MMA on colorectal cancer cell spheroids. We found that MMA promoted the proliferation of colorectal cancer spheroids at physiological concentrations that can be exhibited by the elderly and induced mitochondrial reactive oxygen species generation, which in turn affected the promotion of cell growth. MMA treatment also induces a metabolic shift in the glycolytic system. These results suggest that MMA may promote cancer cell proliferation by decreasing mitochondrial function, inducing a metabolic shift, and provide new insights into the effects of aging on cancer.

Pan-Cancer Insights: A Study of Microbial Metabolite Receptors in Malignancy Dynamics

BACKGROUND/OBJECTIVES

The role of the gut microbiome in cancer biology has become an increasingly prominent area of research, particularly regarding the role of microbial metabolites and their receptors (MMRs). These metabolites, through the various gut-organ axes, have been proven to influence several pathogenetic mechanisms. This study conducted a comprehensive pan-cancer analysis of MMR transcriptomic profiles across twenty-three cancer types, exploring the mechanisms through which they can influence cancer development and progression.

METHODS

Utilizing both cancer cell lines from CCLE (Cancer Cell Line Encyclopedia) and human tumor samples from TCGA (The Cancer Gene Atlas), we analyzed 107 MMRs interacting with microbial metabolites such as short-chain fatty acids, bile acids, indole derivatives, and others while studying their interactions with key known cancer genes.

RESULTS

Our results revealed that certain MMRs, such as GPR84 and serotonin receptors, are consistently upregulated in various malignancies, while others, like ADRA1A, are frequently downregulated, suggesting diverse roles in cancer pathophysiology. Furthermore, we identified significant correlations between MMR expression and cancer hallmark genes and pathways, including immune evasion, proliferation, and metastasis.

CONCLUSIONS

These findings suggest that the interactions between microbial metabolites and MMRs may serve as potential biomarkers for cancer diagnosis, prognosis, and therapy, highlighting their therapeutic potential. This study underscores the significance of the microbiota-cancer axis and provides novel insights into microbiome-based strategies for cancer treatment.

STAT3 drives the expression of HIF1alpha in cancer cells through a novel super-enhancer

Aerobic glycolysis is one of the major hallmarks of malignant tumors. This metabolic reprogramming benefits the rapid proliferation of cancer cells, facilitates the formation of tumor microenvironment to support their growth and survival, and impairs the efficacy of various tumor therapies. Therefore, the elucidation of the mechanisms driving aerobic glycolysis in tumors represents a pivotal breakthrough in developing therapeutic strategies for solid tumors. HIF1α serves as a central regulator of aerobic glycolysis with elevated mRNA and protein expression across multiple tumor types. However, the mechanisms contributing to this upregulation remain elusive. This study reports the identification of a novel HIF1α super enhancer (HSE) in multiple cancer cells using bioinformatics analysis, chromosome conformation capture (3C), chromatin immunoprecipitation (ChIP), and CRISPR/Cas9 genome editing techniques. Deletion of HSE in cancer cells significantly reduces the expression of HIF1α, glycolysis, cell proliferation, colony and tumor formation ability, confirming the role of HSE as the enhancer of HIF1α in cancer cells. Particularly, we demonstrated that STAT3 promotes the expression of HIF1α by binding to HSE. The discovery of HSE will help elucidate the pathways driving tumor aerobic glycolysis, offering new therapeutic targets and potentially resolving the bottleneck in solid tumor treatment.

Ketogenesis promotes triple-negative breast cancer metastasis via calpastatin β-hydroxybutyrylation

Triple-negative breast cancer (TNBC) continues to pose a significant obstacle in the field of oncology. Dysregulation of lipid metabolism, notably upregulated ketogenesis, has emerged as a hallmark of TNBC, yet its role in metastasis has been elusive. Here, by utilizing clinical specimens and experimental models, the study demonstrates that increased ketogenesis fosters TNBC metastasis by promoting the up-regulation of β-hydroxybutyrate (β-OHB), a key ketone body. Mechanistically, β-OHB facilitates β-hydroxybutyrylation (Kbhb) of Calpastatin (CAST), an endogenous calpain (CAPN) inhibitor, at K43, blocking the interaction with CAPN and subsequently promoting FAK phosphorylation and epithelial‒mesenchymal transition (EMT). In conclusion, the study reveals a novel regulatory axis linking ketogenesis to TNBC metastasis, shedding light on the intricate interplay between metabolic reprogramming and tumor progression.

A new perspective on the therapeutic potential of tumor metastasis: targeting the metabolic interactions between TAMs and tumor cells

Tumor-associated macrophages (TAMs) undergo metabolic reprogramming, encompassing glucose, amino acid, fatty acid metabolism, tricarboxylic acid (TCA) cycle, purine metabolism, and autophagy, within the tumor microenvironment (TME). The metabolic interdependencies between TAMs and tumor cells critically influence macrophage recruitment, differentiation, M2 polarization, and secretion of epithelial-mesenchymal transition (EMT)-related factors, thereby activating intratumoral EMT pathways and enhancing tumor cell invasion and metastasis. Tumor cell metabolic alterations, including hypoxia, metabolite secretion, aerobic metabolism, and autophagy, affect the TME's metabolic landscape, driving macrophage recruitment, differentiation, M2 polarization, and metabolic reprogramming, ultimately facilitating EMT, invasion, and metastasis. Additionally, macrophages can induce tumor cell EMT by reprogramming their aerobic glycolysis. Recent experimental and clinical studies have focused on the metabolic interactions between macrophages and tumor cells to control metastasis and inhibit tumor progression. This review highlights the regulatory role of TAM-tumor cell metabolic codependencies in EMT, offering valuable insights for TAM-targeted therapies in highly metastatic tumors. Modulating the metabolic interplay between tumors and TAMs represents a promising therapeutic strategy for treating patients with metastatic cancers.

Investigation on the mechanisms of scorpion venom in hepatocellular carcinoma model mice via untargeted metabolomics profiling

Metabolic reprogramming is frequently accompanied by hepatocellular carcinoma (HCC) progression. Disrupted metabolites act as potential biomarkers and drug therapeutic targets for HCC. Peptide extract of scorpion venom (PESV) induces cytotoxic anti-proliferative effects and apoptosis in tumors. However, the action mechanisms of PESV remain unknown. This study aimed to explore the serum metabolic profiles of tumor-bearing mouse model. We generated an orthotopic HCC xenograft mouse model by implanting H22 cells into the left hepatic lobe of male C57BL/6 mice. After surgery, the mice were assigned to two groups randomly: PESV (PESV-treated 40 mg/kg daily, i.g.; n = 6) and control (treated with the solvent equally for 14 d, n = 6) groups. Based on an untargeted metabolomics approach using ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry, differential metabolites were screened via univariate and multivariate data analyses. A total of 48 differential metabolites in negative ion mode and 63 in positive ion mode were identified in the serum samples. Furthermore, metabolic pathway analysis revealed that aminoacyl-tRNA biosynthesis, amino acid pathway, glutathione metabolism, protein transports, protein digestion and absorption, and cAMP signaling pathways play vital roles in PESV-induced inhibition of tumors. These findings highlight the distinct changes in the metabolic profiles of HCC-bearing mice after PESV treatment, suggesting the potential of the identified metabolic molecules as therapeutic targets for HCC.

Integrated network pharmacology and metabolomics to study the potential mechanism of Jiawei Yinchenhao decoction in chronic hepatitis B

Chronic hepatitis B infection (CHB) is a major risk factor for the development of hepatocellular carcinoma (HCC) globally and continues to pose a significant global health challenge. Jiawei Yinchenhao decoction (JWYCH) is a modified version of Yinchenhao decoction (YCHD), which is widely used to treat liver diseases including icteric hepatitis, cholelithiasis, and hepatic ascites. However, the effectiveness and underlying mechanism of JWYCH on CHB are still unclear. This study aimed to investigate the impact of JWYCH on CHB and explore the underlying mechanism via network pharmacology and metabolomics. C57BL/6 mice were administered rAAV-HBV1.3 via hydrodynamic injection (HDI) to establish the CHB model. The infected mice were orally administered JWYCH for 4 weeks. HBsAg, HBeAg, HBV DNA, the serum liver function index, and histopathology were detected. In addition, network pharmacology was used to investigate potential targets, whereas untargeted metabolomics analysis was employed to explore the hepatic metabolic changes in JWYCH in CHB mice and identify relevant biomarkers and metabolic pathways. JWYCH was able to reduce HBeAg levels and improve liver pathological changes in mice with CHB. Additionally, metabolomics analysis indicated that JWYCH can influence 105 metabolites, including pipecolic acid, alpha-terpinene, adenosine, and L-phenylalanine, among others. Bile acid metabolism, arachidonic acid metabolism, and retinol metabolism are suggested to be potential targets of JWYCH in CHB. In conclusion, JWYCH demonstrated a hepatoprotective effect on a mouse model of CHB, suggesting a potential alternative therapeutic strategy for CHB. The effect of JWYCH is associated mainly with regulating the metabolism of bile acid, arachidonic acid, and retinol. These differentially abundant metabolites may serve as potential biomarkers and therapeutic targets for CHB.

Tricarboxylic Acid Cycle Relationships with Non-Metabolic Processes: A Short Story with DNA Repair and Its Consequences on Cancer Therapy Resistance

Metabolic changes involving the tricarboxylic acid (TCA) cycle have been linked to different non-metabolic cell processes. Among them, apart from cancer and immunity, emerges the DNA damage response (DDR) and specifically DNA damage repair. The oncometabolites succinate, fumarate and 2-hydroxyglutarate (2HG) increase reactive oxygen species levels and create pseudohypoxia conditions that induce DNA damage and/or inhibit DNA repair. Additionally, by influencing DDR modulation, they establish direct relationships with DNA repair on at least four different pathways. The AlkB pathway deals with the removal of N-alkylation DNA and RNA damage that is inhibited by fumarate and 2HG. The MGMT pathway acts in the removal of O-alkylation DNA damage, and it is inhibited by the silencing of the MGMT gene promoter by 2HG and succinate. The other two pathways deal with the repair of double-strand breaks (DSBs) but with opposite effects: the FH pathway, which uses fumarate to help with the repair of this damage, and the chromatin remodeling pathway, in which oncometabolites inhibit its repair by impairing the homologous recombination repair (HRR) system. Since oncometabolites inhibit DNA repair, their removal from tumor cells will not always generate a positive response in cancer therapy. In fact, their presence contributes to longer survival and/or sensitization against tumor therapy in some cancer patients.

Cell-free ascites from ovarian cancer patients induces Warburg metabolism and cell proliferation through TGFβ-ERK signaling

Ascites plays a key role in supporting the metastatic potential of ovarian cancer cells. Shear stress and carry-over of cancer cells by ascites flow support carcinogenesis and metastasis formation. In addition, soluble factors may participate in the procarcinogenic effects of ascites in ovarian cancer. This study aimed to determine the biological effects of cell-free ascites on carcinogenesis in ovarian cancer cells. Cell-free ascites from ovarian cancer patients (ASC) non-selectively induced cell proliferation in multiple models of ovarian cancer and untransformed primary human dermal fibroblasts. Furthermore, ASC induced a Warburg-type rearrangement of cellular metabolism in A2780 ovarian cancer cells characterized by increases in cellular oxygen consumption and glycolytic flux; increases in glycolytic flux were dominant. ASC induced mitochondrial uncoupling and fundamentally reduced fatty acid oxidation. Ascites-elicited effects were uniform among ascites specimens. ASC-elicited transcriptomic changes in A2780 ovarian cancer cells included induction of the TGFβ-ERK/MEK pathway, which plays a key role in inducing cell proliferation and oncometabolism. ASC-induced gene expression changes, as well as the overexpression of members of the TGFβ signaling system, were associated with poor survival in ovarian cancer patients. We provided evidence that the activation of the autocrine/paracrine of TGFβ signaling system may be present in bladder urothelial carcinoma and stomach adenocarcinoma. Database analysis suggests that the TGFβ system may feed forward bladder urothelial carcinoma and stomach adenocarcinoma. Soluble components of ASC support the progression of ovarian cancer. These results suggest that reducing ascites production may play an essential role in the treatment of ovarian cancer by inhibiting the progression and reducing the severity of the disease.

Significance and Possible Biological Mechanism for CLDN8 Downregulation in Kidney Renal Clear Cell Carcinoma Tissues

Background

The clinical role of claudin 8 (CLDN8) in kidney renal clear cell carcinoma (KIRC) remains unclarified. Herein, the expression level and potential molecular mechanisms of CLDN8 underlying KIRC were determined.

Methods

High-throughput datasets of KIRC were collected from GEO, ArrayExpress, SRA, and TCGA databases to determine the mRNA expression level of the CLDN8. In-house tissue microarrays and immunochemistry were performed to examine CLDN8 protein expression. A summary receiver operating characteristic curve (SROC) and standardized mean difference (SMD) forest plot were generated using Stata v16.0. Single-cell analysis was conducted to further prove the expression level of CLDN8. A clustered regularly interspaced short palindromic repeats knockout screen analysis was executed to assess the growth impact of CLDN8. Functional enrichment analysis was conducted using the Metascape database. Additionally, single-sample gene set enrichment analysis was implied to explore immune cell infiltration in KIRC.

Results

A total of 17 mRNA datasets comprising 1,060 KIRC samples and 452 non-cancerous control samples were included in this study. Additionally, 105 KIRC and 16 non-KIRC tissues were analyzed using in-house immunohistochemistry. The combined SMD was -5.25 (95% confidence interval (CI): -6.13 to -4.37), and CLDN8 downregulation yielded an SROC area under the curve (AUC) close to 1.00 (95% CI: 0.99 - 1.00). CLDN8 downregulation was also confirmed at the single-cell level. Knocking out CLDN8 stimulated KIRC cell proliferation. Lower CLDN8 expression was correlated with worse overall survival of KIRC patients (hazard ratio of CLDN8 downregulation = 1.69, 95% CI: 1.2 - 2.4). Functional pathways associated with CLDN8 co-expressed genes were centered on carbon metabolism obstruction, with key hub genes ACADM, ACO2, NDUFS1, PDHB, SDHD, SUCLA2, SUCLG1, and SUCLG2.

Conclusions

CLDN8 is downregulated in KIRC and is considered a potential tumor suppressor. CLDN8 deficiency may promote the initiation and progression of KIRC, potentially in conjunction with metabolic dysfunction.

Branch Chain Amino Acid Metabolism Promotes Brain Metastasis of NSCLC through EMT Occurrence by Regulating ALKBH5 activity

Metabolic reprogramming is one of the essential features of tumors that may dramatically contribute to cancer metastasis. Employing liquid chromatography-tandem mass spectrometry-based metabolomics, we analyzed the metabolic profile from 12 pairwise serum samples of NSCLC brain metastasis patients before and after CyberKnife Stereotactic Radiotherapy. We evaluated the histopathological architecture of 144 surgically resected NSCLC brain metastases. Differential metabolites were screened and conducted for functional clustering and annotation. Metabolomic profiling identified a pathway that was enriched in the metabolism of branched-chain amino acids (BCAAs). Pathologically, adenocarcinoma with a solid growth pattern has a higher propensity for brain metastasis. Patients with high BCAT1 protein levels in lung adenocarcinoma tissues were associated with a poor prognosis. We found that brain NSCLC cells had elevated catabolism of BCAAs, which led to a depletion of α-KG. This depletion, in turn, reduced the expression and activity of the m6A demethylase ALKBH5. Thus, ALKBH5 inhibition participated in maintaining the m6A methylation of mesenchymal genes and promoted the occurrence of epithelial-mesenchymal transition (EMT) in NSCLC cells and the proliferation of NSCLC cells in the brain. BCAA catabolism plays an essential role in the metastasis of NSCLC cells.

Lactylation: the novel histone modification influence on gene expression, protein function, and disease

Lactic acid, traditionally considered as a metabolic waste product arising from glycolysis, has undergone a resurgence in scientific interest since the discovery of the Warburg effect in tumor cells. Numerous studies have proved that lactic acid could promote angiogenesis and impair the function of immune cells within tumor microenvironments. Nevertheless, the precise molecular mechanisms governing these biological functions remain inadequately understood. Recently, lactic acid has been found to induce a posttranslational modification, lactylation, that may offer insight into lactic acid's non-metabolic functions. Notably, the posttranslational modification of proteins by lactylation has emerged as a crucial mechanism by which lactate regulates cellular processes. This article provides an overview of the discovery of lactate acidification, outlines the potential "writers" and "erasers" responsible for protein lactylation, presents an overview of protein lactylation patterns across different organisms, and discusses the diverse physiological roles of lactylation. Besides, the article highlights the latest research progress concerning the regulatory functions of protein lactylation in pathological processes and underscores its scientific significance for future investigations.

Friend or Foe: Exploring the Relationship between the Gut Microbiota and the Pathogenesis and Treatment of Digestive Cancers

Digestive cancers are among the leading causes of cancer death in the world. However, the mechanisms of cancer development and progression are not fully understood. Accumulating evidence in recent years pointing to the bidirectional interactions between gut dysbiosis and the development of a specific type of gastrointestinal cancer is shedding light on the importance of this "unseen organ"-the microbiota. This review focuses on the local role of the gut microbiota imbalance in different digestive tract organs and annexes related to the carcinogenic mechanisms. Microbiota modulation, either by probiotic administration or by dietary changes, plays an important role in the future therapies of various digestive cancers.

Post-Graphene 2D Materials: Structures, Properties, and Cancer Therapy Applications

Cancer is one of the most serious diseases challenging human health and life span. Cancer has claimed millions of lives worldwide. Early diagnosis and effective treatment of cancer are very important for the survival of patients. In recent years, 2D nanomaterials have shown great potential in the development of anticancer treatment by combining their inherent physicochemical properties after surface modification. 2D nanomaterials have attracted great interest due to their unique nanosheet structure, large surface area, and extraordinary physicochemical properties. This article reviews the advantages and application status of emerging 2D nanomaterials for targeted tumor synergistic therapy compared with traditional therapeutic strategies. In order to investigate novel potential anticancer strategies, this paper focuses on the surface modification, cargo delivery capability, and unique optical properties of emerging 2D nanomaterials. Finally, the current problems and challenges in cancer treatment are summarized and prospected.

Malonate differentially affects cell survival and confers chemoresistance in cancer cells via the induction of p53-dependent autophagy

Metabolic network intertwines with cancerous signaling and drug responses. Malonate is a prevailing metabolite in cancer and a competitive inhibitor of succinate dehydrogenase (SDH). Recent studies showed that malonate induced reactive oxygen species (ROS)-dependent apoptosis in neuroblastoma cells, but protected cells from ischemia-reperfusion injury. We here revealed that malonate differentially regulated cell death and survival in cancer cells. While high-dose malonate triggered ROS-dependent apoptosis, the low-dose malonate induced autophagy and conferred resistance to multiple chemotherapeutic agents. Mechanistically, our results showed that malonate increased p53 stability and transcriptionally up-regulated autophagy modulator DRAM (damage-regulated autophagy modulator), thus promoting autophagy. We further proved that autophagy is required for malonate-associated chemoresistance. Collectively, our findings suggest that malonate plays a double-edge function in cancer response to stressors, and highlights a pro-cancer impact of p53-induced autophagy in response to malonate.

The Metformin Immunoregulatory Actions in Tumor Suppression and Normal Tissues Protection

The immune system is the key player in a wide range of responses in normal tissues and tumors to anticancer therapy. Inflammatory and fibrotic responses in normal tissues are the main limitations of chemotherapy, radiotherapy, and also some newer anticancer drugs such as immune checkpoint inhibitors (ICIs). Immune system responses within solid tumors including anti-tumor and tumor-promoting responses can suppress or help tumor growth. Thus, modulation of immune cells and their secretions such as cytokines, growth factors and epigenetic modulators, pro-apoptosis molecules, and some other molecules can be suggested to alleviate side effects in normal tissues and drug-resistance mechanisms in the tumor. Metformin as an anti-diabetes drug has shown intriguing properties such as anti-inflammation, anti-fibrosis, and anticancer effects. Some investigations have uncovered that metformin can ameliorate radiation/chemotherapy toxicity in normal cells and tissues through the modulation of several targets in cells and tissues. These effects of metformin may ameliorate severe inflammatory responses and fibrosis after exposure to ionizing radiation or following treatment with highly toxic chemotherapy drugs. Metformin can suppress the activity of immunosuppressive cells in the tumor through the phosphorylation of AMP-activated protein kinase (AMPK). In addition, metformin may stimulate antigen presentation and maturation of anticancer immune cells, which lead to the induction of anticancer immunity in the tumor. This review aims to explain the detailed mechanisms of normal tissue sparing and tumor suppression during cancer therapy using adjuvant metformin with an emphasis on immune system responses.

Targeting the lactic acid metabolic pathway for antitumor therapy

Lactic acid is one of the most abundant products of cellular metabolism and has historically been considered a cell-damaging metabolic product. However, as research has deepened, the beneficial effects of lactic acid on tumor cells and the tumor microenvironment have received increasing attention from the oncology community. Lactic acid can not only provide tumor cells with energy but also act as a messenger molecule that promotes tumor growth and progression and protects tumor cells from immune cells and killing by radiation and chemotherapy. Thus, the inhibition of tumor cell lactic acid metabolism has emerged as a novel antitumor treatment strategy that can also effectively enhance the efficacy of conventional antitumor therapies. In this review, we classify the currently available therapies targeting lactic acid metabolism and examine their prospects for clinical application.

Circulating metabolites may illustrate relationship of alcohol consumption with cardiovascular disease

BACKGROUND

Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD.

METHODS

Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine, and liquor on average of 19 years in 2428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure).

RESULTS

We identified 60 metabolites associated with cumulative average alcohol consumption (p < 0.05/211 ≈ 0.00024). For example, 1 g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta = 0.023 ± 0.002, p = 6.3e - 45) and phosphatidylcholine (e.g., PC 32:1, beta = 0.021 ± 0.002, p = 3.1e - 38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11 (95% CI = [1.02, 1.21], p = 0.02) vs 0.88 (95% CI = [0.78, 0.98], p = 0.02).

CONCLUSIONS

We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

Metabolome Sequencing Reveals that Protein Arginine-N-Methyltransferase 1 Promotes the Progression of Invasive Micropapillary Carcinoma of the Breast and Predicts a Poor Prognosis

Invasive micropapillary carcinoma (IMPC) of the breast is a special histopathologic type of cancer with a high recurrence rate and the biological features of invasion and metastasis. Previous spatial transcriptome studies indicated extensive metabolic reprogramming in IMPC, which contributes to tumor cell heterogeneity. However, the impact of metabolome alterations on IMPC biological behavior is unclear. Herein, endogenous metabolite-targeted metabolomic analysis was done on frozen tumor tissue samples from 25 patients with breast IMPC and 34 patients with invasive ductal carcinoma not otherwise specified (IDC-NOS) by liquid chromatography-mass spectrometry. An IMPC-like state, which is an intermediate transitional morphologic phenotype between IMPC and IDC-NOS, was observed. The metabolic type of IMPC and IDC-NOS was related to breast cancer molecular type. Arginine methylation modification and 4-hydroxy-phenylpyruvate metabolic changes play a major role in the metabolic reprogramming of IMPC. High protein arginine-N-methyltransferase (PRMT) 1 expression was an independent factor related to the poor prognosis of patients with IMPC in terms of disease-free survival. PRMT1 promoted H4R3me2a, which induced tumor cell proliferation via cell cycle regulation and facilitated tumor cell metastasis via the tumor necrosis factor signaling pathway. This study identified the metabolic type-related features and intermediate transition morphology of IMPC. The identification of potential targets of PRMT1 has the potential to provide a basis for the precise diagnosis and treatment of breast IMPC.

Circulating Metabolites May Illustrate Relationship of Alcohol Consumption with Cardiovascular Disease

Background

Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD.

Methods

Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine and liquor on average of 19 years in 2,428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure).

Results

We identified 60 metabolites associated with cumulative average alcohol consumption (p<0.05/211≈0.00024). For example, one g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta=0.023±0.002, p=6.3e-45) and phosphatidylcholine (e.g., PC 32:1, beta=0.021±0.002, p=3.1e-38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11(95% CI=[1.02, 1.21],p=0.02) vs 0.88 (95% CI=[0.78, 0.98], p=0.02).

Summary

We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

[Latest Findings on the Effect of Gastrointestinal Microecology Remodeling of Tumor Microenvironment on Tumor Stemness]

Gastrointestinal microecology (GM) system is composed of normal gut microbiota and its living environment. The impact of GM on human health and many diseases has been widely studied. The impact of GM system on tumors is mainly reflected in the remodeling of the tumor microenvironment (TME). TME, a special microenvironment that tumors live in, can regulate the characteristics of tumor cells and affect the occurrence and development of tumors through intercellular contact and the secretion of cytokines. At present, cancer stem cell (CSC) model is considered an important theory that explains the origin and malignant progression of tumors. The formation and proliferation of CSC usually represent increased tumor invasion, metastasis, and chemotherapy resistance, resulting in poor clinical prognosis in patients. Therefore, it is important to study the role and mechanism through which GM system affects the acquisition of CSC characteristics through remodeling TME, thereby affecting tumor invasion, metastasis, and chemotherapy resistance. Studies on this topic are of great significance for clinical understanding of tumor malignant progression and improving tumor treatment outcomes. However, due to the low content of single bacteria in the gastrointestinal model, high heterogeneity, and difficulty in tracing distant metastasis, there are still great limitations in the previous research. Herein, we reviewed the research progress in the effect of GM remodeling of TME on the acquisition of tumor stemness, tumor invasion and metastasis, and the resistance to chemotherapy.

Metabolomics and network analysis uncovered profound inflammation-associated alterations in hepatitis B virus-related cirrhosis patients with early hepatocellular carcinoma

Patients with hepatitis B virus (HBV)-related liver cirrhosis (LC) are at high risk for hepatocellular carcinoma (HCC). Limitations in the early detection of HCC give rise to poor survival in this high-risk population. Here, we performed comprehensive metabolomics on health individuals and HBV-related LC patients with and without early HCC. Compared to non-HCC patients (N = 108) and health controls (N = 80), we found that patients with early HCC (N = 224) exhibited a specific plasma metabolome map dominated by lipid alterations, including lysophosphatidylcholines, lysophosphatidic acids and bile acids. Pathway and function network analyses indicated that these metabolite alterations were closely associated with inflammation responses. Using multivariate regression and machine learning approaches, we identified a five-metabolite combination that showed significant performances in differentiating early-HCC from non-HCC than α-fetoprotein (area under the curve values, 0.981 versus 0.613). At metabolomic levels, this work provides additional insights of metabolic dysfunction related to HCC progressions and demonstrates the plasma metabolites might be measured to identify early HCC in patients with HBV-related LC.

Metabolite interactions between host and microbiota during health and disease: Which feeds the other?

Metabolites produced by the host and microbiota play a crucial role in how human bodies develop and remain healthy. Most of these metabolites are produced by microbiota and hosts in the digestive tract. Metabolites in the gut have important roles in energy metabolism, cellular communication, and host immunity, among other physiological activities. Although numerous host metabolites, such as free fatty acids, amino acids, and vitamins, are found in the intestine, metabolites generated by gut microbiota are equally vital for intestinal homeostasis. Furthermore, microbiota in the gut is the sole source of some metabolites, including short-chain fatty acids (SCFAs). Metabolites produced by microbiota, such as neurotransmitters and hormones, may modulate and significantly affect host metabolism. The gut microbiota is becoming recognized as a second endocrine system. A variety of chronic inflammatory disorders have been linked to aberrant host-microbiota interplays, but the precise mechanisms underpinning these disturbances and how they might lead to diseases remain to be fully elucidated. Microbiome-modulated metabolites are promising targets for new drug discovery due to their endocrine function in various complex disorders. In humans, metabolotherapy for the prevention or treatment of various disorders will be possible if we better understand the metabolic preferences of bacteria and the host in specific tissues and organs. Better disease treatments may be possible with the help of novel complementary therapies that target host or bacterial metabolism. The metabolites, their physiological consequences, and functional mechanisms of the host-microbiota interplays will be highlighted, summarized, and discussed in this overview.

Metaboverse enables automated discovery and visualization of diverse metabolic regulatory patterns

Metabolism is intertwined with various cellular processes, including controlling cell fate, influencing tumorigenesis, participating in stress responses and more. Metabolism is a complex, interdependent network, and local perturbations can have indirect effects that are pervasive across the metabolic network. Current analytical and technical limitations have long created a bottleneck in metabolic data interpretation. To address these shortcomings, we developed Metaboverse, a user-friendly tool to facilitate data exploration and hypothesis generation. Here we introduce algorithms that leverage the metabolic network to extract complex reaction patterns from data. To minimize the impact of missing measurements within the network, we introduce methods that enable pattern recognition across multiple reactions. Using Metaboverse, we identify a previously undescribed metabolite signature that correlated with survival outcomes in early stage lung adenocarcinoma patients. Using a yeast model, we identify metabolic responses suggesting an adaptive role of citrate homeostasis during mitochondrial dysfunction facilitated by the citrate transporter, Ctp1. We demonstrate that Metaboverse augments the user's ability to extract meaningful patterns from multi-omics datasets to develop actionable hypotheses.

Dietary Folate Deficiency Promotes Lactate Metabolic Disorders to Sensitize Lung Cancer Metastasis through MTOR-Signaling-Mediated Druggable Oncotargets

Lactate metabolism plays a pivotal role in cancers but is often overlooked in lung cancer (LC). Folate deficiency has been linked to lung cancer development, but its impact on lactate metabolism and cancer malignancy is unclear. To investigate this, mice were fed either a folate-deficient (FD) or control diet and intrapleurally implanted with lung cancer cells pre-exposed to FD growth medium. Results showed that FD promoted lactate over-production and the formation of tumor oncospheroids (LCSs) with increased metastatic, migration, and invasion potential. Mice implanted with these cells and fed an FD diet developed hyperlactatemia in blood and lungs. This coincided with increased expression of hexokinase 2 (HK2), lactate dehydrogenase (LDH), and decreased expression of pyruvate dehydrogenase (PDH). Pre-treatment of the FD-LCS-implanted mice with the mTORC1 inhibitor, rapamycin, and the anti-metabolic drug metformin abolished FD/LCS-activated mTORC1 and its targets including HIF1α, HK2, LDH, and monocarboxylate transporters (MCT1 and MCT4), which coincided with the reduction in lactate disorders and prevention of LC metastasis. The findings suggest that dietary FD promotes lactate metabolic disorders that sensitize lung cancer metastasis through mTOR-signaling-mediated targets.

Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer

Introduction

Nowadays, it has been recognized that gut microbiome can indirectly modulate cancer susceptibility or progression. However, whether intratumor microbes are parasitic, symbiotic, or merely bystanders in breast cancer is not fully understood. Microbial metabolite plays a pivotal role in the interaction of host and microbe via regulating mitochondrial and other metabolic pathways. And the relationship between tumor-resident microbiota and cancer metabolism remains an open question.

Methods

1085 breast cancer patients with normalized intratumor microbial abundance data and 32 single-cell RNA sequencing samples were retrieved from public datasets. We used the gene set variation analysis to evaluate the various metabolic activities of breast cancer samples. Furthermore, we applied Scissor method to identify microbe-associated cell subpopulations from single-cell data. Then, we conducted comprehensive bioinformatic analyses to explore the association between host and microbe in breast cancer.

Results

Here, we found that the metabolic status of breast cancer cells was highly plastic, and some microbial genera were significantly correlated with cancer metabolic activity. We identified two distinct clusters based on microbial abundance and tumor metabolism data. And dysregulation of the metabolic pathway was observed among different cell types. Metabolism-related microbial scores were calculated to predict overall survival in patients with breast cancer. Furthermore, the microbial abundance of the specific genus was associated with gene mutation due to possible microbe-mediated mutagenesis. The infiltrating immune cell compositions, including regulatory T cells and activated NK cells, were significantly associated with the metabolism-related intratumor microbes, as indicated in the Mantel test analysis. Moreover, the mammary metabolism-related microbes were related to T cell exclusion and response to immunotherapy.

Conclusions

Overall, the exploratory study shed light on the potential role of the metabolism-related microbiome in breast cancer patients. And the novel treatment will be realized by further investigating the metabolic disturbance in host and intratumor microbial cells.

Association between methionine sulfoxide and risk of moyamoya disease

Objective

Methionine sulfoxide (MetO) has been identified as a risk factor for vascular diseases and was considered as an important indicator of oxidative stress. However, the effects of MetO and its association with moyamoya disease (MMD) remained unclear. Therefore, we performed this study to evaluate the association between serum MetO levels and the risk of MMD and its subtypes.

Methods

We eventually included consecutive 353 MMD patients and 88 healthy controls (HCs) with complete data from September 2020 to December 2021 in our analyzes. Serum levels of MetO were quantified using liquid chromatography-mass spectrometry (LC-MS) analysis. We evaluated the role of MetO in MMD using logistic regression models and confirmed by receiver-operating characteristic (ROC) curves and area under curve (AUC) values.

Results

We found that the levels of MetO were significantly higher in MMD and its subtypes than in HCs (p < 0.001 for all). After adjusting for traditional risk factors, serum MetO levels were significantly associated with the risk of MMD and its subtypes (p < 0.001 for all). We further divided the MetO levels into low and high groups, and the high MetO level was significantly associated with the risk of MMD and its subtypes (p < 0.05 for all). When MetO levels were assessed as quartiles, we found that the third (Q3) and fourth (Q4) MetO quartiles had a significantly increased risk of MMD compared with the lowest quartile (Q3, OR: 2.323, 95%CI: 1.088-4.959, p = 0.029; Q4, OR: 5.559, 95%CI: 2.088-14.805, p = 0.001).

Conclusion

In this study, we found that a high level of serum MetO was associated with an increased risk of MMD and its subtypes. Our study raised a novel perspective on the pathogenesis of MMD and suggested potential therapeutic targets.

Metabolism in Hematopoiesis and Its Malignancy

Hematopoietic stem cells (HSCs) are multipotent stem cells that can self-renew and generate all blood cells of different lineages. The system is under tight control in order to maintain a precise equilibrium of the HSC pool and the effective production of mature blood cells to support various biological activities. Cell metabolism can regulate different molecular activities, such as epigenetic modification and cell cycle regulation, and subsequently affects the function and maintenance of HSC. Upon malignant transformation, oncogenic drivers in malignant hematopoietic cells can remodel the metabolic pathways for supporting the oncogenic growth. The dysregulation of metabolism results in oncogene addiction, implying the development of malignancy-specific metabolism-targeted therapy. In this chapter, we will discuss the significance of different metabolic pathways in hematopoiesis, specifically, the distinctive metabolic dependency in hematopoietic malignancies and potential metabolic therapy.

Prior metabolite extraction fully preserves RNAseq quality and enables integrative multi-'omics analysis of the liver metabolic response to viral infection

Here, we provide an in-depth analysis of the usefulness of single-sample metabolite/RNA extraction for multi-'omics readout. Using pulverized frozen livers of mice injected with lymphocytic choriomeningitis virus (LCMV) or vehicle (Veh), we isolated RNA prior (RNA) or following metabolite extraction (MetRNA). RNA sequencing (RNAseq) data were evaluated for differential expression analysis and dispersion, and differential metabolite abundance was determined. Both RNA and MetRNA clustered together by principal component analysis, indicating that inter-individual differences were the largest source of variance. Over 85% of LCMV versus Veh differentially expressed genes were shared between extraction methods, with the remaining 15% evenly and randomly divided between groups. Differentially expressed genes unique to the extraction method were attributed to randomness around the 0.05 FDR cut-off and stochastic changes in variance and mean expression. In addition, analysis using the mean absolute difference showed no difference in the dispersion of transcripts between extraction methods. Altogether, our data show that prior metabolite extraction preserves RNAseq data quality, which enables us to confidently perform integrated pathway enrichment analysis on metabolomics and RNAseq data from a single sample. This analysis revealed pyrimidine metabolism as the most LCMV-impacted pathway. Combined analysis of genes and metabolites in the pathway exposed a pattern in the degradation of pyrimidine nucleotides leading to uracil generation. In support of this, uracil was among the most differentially abundant metabolites in serum upon LCMV infection. Our data suggest that hepatic uracil export is a novel phenotypic feature of acute infection and highlight the usefulness of our integrated single-sample multi-'omics approach.

Metabolic pathway analysis of hyperuricaemia patients with hyperlipidaemia based on high-throughput mass spectrometry: a case‒control study

BACKGROUND

Both hyperuricaemia and hyperlipidaemia are common metabolic diseases that are closely related to each other, and both are independent risk factors for the development of a variety of diseases. HUA combined with hyperlipidaemia increases the risk of nonalcoholic fatty liver disease and coronary heart disease. This study aimed to investigate the relationship between HUA and hyperlipidaemia and study the metabolic pathway changes in patients with HUA associated with hyperlipidaemia using metabolomics.

METHODS

This was a case‒control study. The prevalence of hyperlipidaemia in HUA patients in the physical examination population of Tianjin Union Medical Centre in 2018 was investigated. Metabolomics analysis was performed on 308 HUA patients and 100 normal controls using Orbitrap mass spectrometry. A further metabolomics study of 30 asymptomatic HUA patients, 30 HUA patients with hyperlipidaemia, and 30 age-and sex-matched healthy controls was conducted. Differential metabolites were obtained from the three groups by orthogonal partial least-squares discrimination analysis, and relevant metabolic pathways changes were analysed using MetaboAnalyst 5.0 software.

RESULTS

The prevalence of hyperlipidaemia in HUA patients was 69.3%. Metabolomic analysis found that compared with the control group, 33 differential metabolites, including arachidonic acid, alanine, aspartate, phenylalanine and tyrosine, were identified in asymptomatic HUA patients. Pathway analysis showed that these changes were mainly related to 3 metabolic pathways, including the alanine, aspartate and glutamate metabolism pathway. Thirty-eight differential metabolites, including linoleic acid, serine, glutamate, and tyrosine, were identified in HUA patients with hyperlipidaemia. Pathway analysis showed that they were mainly related to 7 metabolic pathways, including the linoleic acid metabolism pathway, phenylalanine, tyrosine and tryptophan biosynthesis pathway, and glycine, serine and threonine metabolism pathway.

CONCLUSIONS

Compared to the general population, the HUA population had a higher incidence of hyperlipidaemia. HUA can cause hyperlipidaemia. by affecting the metabolic pathways of linoleic acid metabolism and alanine, aspartate and glutamate metabolism. Fatty liver is closely associated with changes in the biosynthesis pathway of pahenylalanine, tyrosine, and tryptophan in HUA patients with hyperlipidaemia. Changes in the glycine, serine and threonine metabolism pathway in HUA patients with hyperlipidaemia may lead to chronic kidney disease.

The promising therapeutic effects of metformin on metabolic reprogramming of cancer-associated fibroblasts in solid tumors

Tumor-infiltrated lymphocytes are exposed to many toxic metabolites and molecules in the tumor microenvironment (TME) that suppress their anti-tumor activity. Toxic metabolites, such as lactate and ketone bodies, are produced mainly by catabolic cancer-associated fibroblasts (CAFs) to feed anabolic cancer cells. These catabolic and anabolic cells make a metabolic compartment through which high-energy metabolites like lactate can be transferred via the monocarboxylate transporter channel 4. Moreover, a decrease in molecules, including caveolin-1, has been reported to cause deep metabolic changes in normal fibroblasts toward myofibroblast differentiation. In this context, metformin is a promising drug in cancer therapy due to its effect on oncogenic signal transduction pathways, leading to the inhibition of tumor proliferation and downregulation of key oncometabolites like lactate and succinate. The cross-feeding and metabolic coupling of CAFs and tumor cells are also affected by metformin. Therefore, the importance of metabolic reprogramming of stromal cells and also the pivotal effects of metformin on TME and oncometabolites signaling pathways have been reviewed in this study.

The impact of the microbiome in cancer: Targeting metabolism of cancer cells and host

Abnormal metabolic alterations of cancer cells and the host play critical roles in the occurrence and development of tumors. Targeting cancer cells and host metabolism can provide novel diagnosis indicators and intervention targets for tumors. In recent years, it has been found that gut microbiota is involved in the metabolism of the host and cancer cells. Increasingly, gut microbiome and their metabolites have been demonstrated great influence on the tumor formation, prognosis and treatment. Specific gut microbial composition and metabolites are associated with the status of tumor in the host. Interventions on the gut microbiota can exert the protective effects on the tumor, through the manipulation of structure and its related metabolites. This may be the new approach to improve the efficacy of tumor prevention and treatment. Here, we discuss the effects and the underlying mechanisms of gut microbiota and microbial-derived metabolites in tumor progression and treatment.

Deregulated transcription factors in cancer cell metabolisms and reprogramming

Metabolic reprogramming is an important cancer hallmark that plays a key role in cancer malignancies and therapy resistance. Cancer cells reprogram the metabolic pathways to generate not only energy and building blocks but also produce numerous key signaling metabolites to impact signaling and epigenetic/transcriptional regulation for cancer cell proliferation and survival. A deeper understanding of the mechanisms by which metabolic reprogramming is regulated in cancer may provide potential new strategies for cancer targeting. Recent studies suggest that deregulated transcription factors have been observed in various human cancers and significantly impact metabolism and signaling in cancer. In this review, we highlight the key transcription factors that are involved in metabolic control, dissect the crosstalk between signaling and transcription factors in metabolic reprogramming, and offer therapeutic strategies targeting deregulated transcription factors for cancer treatment.

Pan-Cancer Gene Analysis of m6A Modification and Immune Infiltration in Uterine Corpus Endometrial Carcinoma

Objective

This investigation was to test the potential role of m6A-related long non-coding RNAs (lncRNAs) and immune infiltration as crucial factors in the diagnosis and treatment of uterine corpus endometrial cancer (UCEC).

Method

The UCEC RNA-seq data were downloaded in the Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/). There were 587 samples totally, containing 543 UCEC cases and 35 healthy cases. The clinical information of UCEC cases included survival time, survival status, gender, age, stage, and TMN stage. Twenty-three m6A-related genes were found in published journals. The RNA-seq documents of UCEC were downloaded in the Cancer Genome Atlas (TCGA). The hub gene data of UCEC were downloaded from GEPIA2 database. The different packages of R language were applied to calculate and analyze in this research.

Results

Among 587 cases in our study, we discovered 3039 lncRNAs in the TCGA-UCEC database. After the differential analysis, 23 m6A-associated genetics were screened and twenty-one m6A-associated differential genetics were found. In the end, we obtained 20 m6A-related lncRNAs. LNCTAM34A was considered as a predictive gene through univariate and multivariate Cox regression analysis. In addition to the above, patients with high LNCTAM34A expression had better outcomes than those with low LNCTAM34A expression. The high-risk cohort had greater scores of activated dendritic cells (aDCs), B cells, and T cell regulatory (Tregs) than low-risk cohort; in the meanwhile, high-risk cohort had lower scores of DCs and iDCs. Then, the high-risk cohort displayed greater scores in the immune functions of MHC class I, para-inflammation, and type I IFN response than those of low-risk cohort. Among 27 immune-inducible genes, the level of CD244, KIR3DLI, NRP1, PDCD1LG2, and TNFRSF8 was reduced in UCEC samples and the level of CD27, CD28, CD70, CD80, CD86, HAVCR2, ICOS, IDO1, LAIR1, PDCD1, TIGIT, TNFRSF18, -25, -9, -14, and VTCN1 was increased in UCEC samples.

Conclusion

The key role of M6A-related lncRNAs in immune microenvironment in high-risk patients of UCEC. The patients with strong expression of LNCTAM34A have a good prognosis, and LNCTAM34A can be used as a prognostic gene for UCEC. m6A-related lncRNAs can be used as a potential treatment for UCEC. Our observations can be used as a hypothetical basis for future in vitro and animal experiments.

Investigation of the Role of PUFA Metabolism in Breast Cancer Using a Rank-Based Random Forest Algorithm

Simple Summary

Polyunsaturated fatty acids (PUFAs) and their derivatives, oxylipins, are a constant focus of cancer research due to the relationship between cancer and processes of energy metabolism and inflammation, where a PUFA system is an active player. Only recently have methods been developed that allow for studying such complex systems. Using the Rank-based Random Forest (RF) model, we show that PUFA metabolism genes are critical for the pathogenesis of breast cancer (BC); BC subtypes differ in PUFA metabolism gene expression. The enrichment of BC subtypes with various genes associated with oxylipin signaling pathways indicates a different contribution of these compounds to the biology of subtypes.

Abstract

Polyunsaturated fatty acid (PUFA) metabolism is currently a focus in cancer research due to PUFAs functioning as structural components of the membrane matrix, as fuel sources for energy production, and as sources of secondary messengers, so called oxylipins, important players of inflammatory processes. Although breast cancer (BC) is the leading cause of cancer death among women worldwide, no systematic study of PUFA metabolism as a system of interrelated processes in this disease has been carried out. Here, we implemented a Boruta-based feature selection algorithm to determine the list of most important PUFA metabolism genes altered in breast cancer tissues compared with in normal tissues. A rank-based Random Forest (RF) model was built on the selected gene list (33 genes) and applied to predict the cancer phenotype to ascertain the PUFA genes involved in cancerogenesis. It showed high-performance of dichotomic classification (balanced accuracy of 0.94, ROC AUC 0.99) We also retrieved a list of the important PUFA genes (46 genes) that differed between molecular subtypes at the level of breast cancer molecular subtypes. The balanced accuracy of the classification model built on the specified genes was 0.82, while the ROC AUC for the sensitivity analysis was 0.85. Specific patterns of PUFA metabolic changes were obtained for each molecular subtype of breast cancer. These results show evidence that (1) PUFA metabolism genes are critical for the pathogenesis of breast cancer; (2) BC subtypes differ in PUFA metabolism genes expression; and (3) the lists of genes selected in the models are enriched with genes involved in the metabolism of signaling lipids.

COVID-19 metabolism: Mechanisms and therapeutic targets

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS-CoV-2-induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID-19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS-CoV-2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID-19 metabolism. SARS-CoV-2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS-CoV-2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID-19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS-CoV-2-induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID-19 pandemic.

REGLIV: Molecular regulation data of diverse living systems facilitating current multiomics research

Multiomics is a powerful technique in molecular biology that facilitates the identification of new associations among different molecules (genes, proteins & metabolites). It has attracted tremendous research interest from the scientists worldwide and has led to an explosive number of published studies. Most of these studies are based on the regulation data provided in available databases. Therefore, it is essential to have molecular regulation data that are strictly validated in the living systems of various cell lines and in vivo models. However, no database has been developed yet to provide comprehensive molecular regulation information validated by living systems. Herein, a new database, Molecular Regulation Data of Living System Facilitating Multiomics Study (REGLIV) is introduced to describe various types of molecular regulation tested by the living systems. (1) A total of 2996 regulations describe the changes in 1109 metabolites triggered by alterations in 284 genes or proteins, and (2) 1179 regulations describe the variations in 926 proteins induced by 125 endogenous metabolites. Overall, REGLIV is unique in (a) providing the molecular regulation of a clearly defined regulatory direction other than simple correlation, (b) focusing on molecular regulations that are validated in a living system not simply in an in vitro test, and (c) describing the disease/tissue/species specific property underlying each regulation. Therefore, REGLIV has important implications for the future practice of not only multiomics, but also other fields relevant to molecular regulation. REGLIV is freely accessible at: https://idrblab.org/regliv/.

Citric acid of ovarian cancer metabolite induces pyroptosis via the caspase-4/TXNIP-NLRP3-GSDMD pathway in ovarian cancer

Malignant tumors display profound changes in cellular metabolism, yet how these altered metabolites affect the development and growth of tumors is not fully understood. Here, we used metabolomics to analyze the metabolic profile differences in ovarian cancer and found that citric acid (CA) is the most significantly downregulated metabolite. Recently, CA has been reported to inhibit the growth of a variety of tumor cells, but whether it is involved in pyroptosis of ovarian cancer and its potential molecular mechanisms still remains to be further investigated. Here, we demonstrated that CA inhibits the growth of ovarian cancer cells in a dose-dependent manner. RNA-seq analysis revealed that CA significantly promoted the expression of thioredoxin interacting protein (TXNIP) and caspase-4 (CASP4). Morphologic examination by transmission electron microscopy indicated that CA-treated ovarian cancer cells exhibited typical pyroptosis characteristics. Further mechanistic analyses showed that CA facilitates pyroptosis via the CASP4/TXNIP-NLRP3-Gesdermin-d (GSDMD) pathway in ovarian cancer. This study elucidated that CA induces ovarian cancer cell death through classical and non-classical pyroptosis pathways, which may be beneficial as an ovarian cancer therapy.

Cholesterol suppresses GOLM1-dependent selective autophagy of RTKs in hepatocellular carcinoma

Aberrant activation of receptor tyrosine kinases (RTKs) and the subsequent metabolic reprogramming play critical roles in cancer progression. Our previous study has shown that Golgi membrane protein 1 (GOLM1) promotes hepatocellular carcinoma (HCC) metastasis by enhancing the recycling of RTKs. However, how this RTK recycling process is regulated and coupled with RTK degradation remains poorly defined. Here, we demonstrate that cholesterol suppresses the autophagic degradation of RTKs in a GOLM1-dependent manner. Further mechanistic studies reveal that GOLM1 mediates the selective autophagy of RTKs by interacting with LC3 through an LC3-interacting region (LIR), which is regulated by a cholesterol-mTORC1 axis. Lowering cholesterol by statins improves the efficacy of multiple tyrosine kinase inhibitors (TKIs) in vivo. Our findings indicate that cholesterol serves as a signal to switch GOLM1-RTK degradation to GOLM1-RTK recycling and suggest that lowering cholesterol by statin may be a promising combination strategy to improve the TKI efficiency in HCC.

Microbial communities form rich extracellular metabolomes that foster metabolic interactions and promote drug tolerance

Microbial communities are composed of cells of varying metabolic capacity, and regularly include auxotrophs that lack essential metabolic pathways. Through analysis of auxotrophs for amino acid biosynthesis pathways in microbiome data derived from >12,000 natural microbial communities obtained as part of the Earth Microbiome Project (EMP), and study of auxotrophic–prototrophic interactions in self-establishing metabolically cooperating yeast communities (SeMeCos), we reveal a metabolically imprinted mechanism that links the presence of auxotrophs to an increase in metabolic interactions and gains in antimicrobial drug tolerance. As a consequence of the metabolic adaptations necessary to uptake specific metabolites, auxotrophs obtain altered metabolic flux distributions, export more metabolites and, in this way, enrich community environments in metabolites. Moreover, increased efflux activities reduce intracellular drug concentrations, allowing cells to grow in the presence of drug levels above minimal inhibitory concentrations. For example, we show that the antifungal action of azoles is greatly diminished in yeast cells that uptake metabolites from a metabolically enriched environment. Our results hence provide a mechanism that explains why cells are more robust to drug exposure when they interact metabolically.

Using microbiome data analysis and a self-establishing metabolically cooperating yeast community model, the authors show that the presence of auxotrophs in a microbial community increases metabolic interactions between cells and fosters antimicrobial drug tolerance.

A method establishment and comparison of in vivo lung cancer model development platforms for evaluation of tumour metabolism and pharmaceutical efficacy

BACKGROUND

Currently, the identification of accurate biomarkers for the diagnosis of patients with early-stage lung cancer remains difficult. Fortunately, metabolomics technology can be used to improve the detection of plasma metabolic biomarkers for lung cancer. In a previous study, we successfully utilised machine learning methods to identify significant metabolic markers for early-stage lung cancer diagnosis. However, a related research platform for the investigation of tumour metabolism and drug efficacy is still lacking.

HYPOTHESIS/PURPOSE

A novel methodology for the comprehensive evaluation of the internal tumour-metabolic profile and drug evaluation needs to be established.

METHODS

The optimal location for tumour cell inoculation was identified in mouse chest for the non-traumatic orthotopic lung cancer mouse model. Microcomputed tomography (micro-CT) was applied to monitor lung tumour growth. Proscillaridin A (P.A) and cisplatin (CDDP) were utilised to verify the anti-lung cancer efficacy of the platform. The top five clinically valid biomarkers, including proline, L-kynurenine, spermidine, taurine and palmitoyl-L-carnitine, were selected as the evaluation indices to obtain a suitable lung cancer mouse model for clinical metabolomics research by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

RESULTS

The platform was successfully established, achieving 100% tumour development rate and 0% surgery mortality. P.A and CDDP had significant anti-lung cancer efficacy in the platform. Compared with the control group, four biomarkers in the orthotopic model and two biomarkers in the metastatic model had significantly higher abundance. Principal component analysis (PCA) showed a significant separation between the orthotopic/metastatic model and the control/subcutaneous/KRAS transgenic model. The platform was mainly involved in arginine and proline metabolism, tryptophan metabolism, and taurine and hypotaurine metabolism.

CONCLUSION

This study is the first to simulate clinical metabolomics by comparing the metabolic phenotype of plasma in different lung cancer mouse models. We found that the orthotopic model was the most suitable for tumour metabolism. Furthermore, the anti-tumour drug efficacy was verified in the platform. The platform can very well match the clinical reality, providing better lung cancer diagnosis and securing more precise evidence for drug evaluation in the future.

Sphingolipid metabolism is associated with osteosarcoma metastasis and prognosis: Evidence from interaction analysis

BACKGROUND

Metabolism is widely involved in the occurrence and development of cancer. However, its role in osteosarcoma (OS) has not been elucidated.

METHODS

The open-accessed data included in this study were downloaded from The Cancer Genome Atlas (TCGA) database (TARGET-OS project). All the analysis was performed in R environments.

RESULTS

Based on the single sample gene set enrichment analysis algorithm, we quantified 21 metabolism terms in OS patients. Among these, sphingolipid metabolism was upregulated in the metastatic OS tissue and associated with a worse prognosis, therefore aroused our interest and selected for further analysis. Our result showed that sphingolipid metabolism could activate the Notch signaling and angiogenesis pathway, which might be responsible for the metastasis ability and poor prognosis. A protein-protein interaction network was constructed to illustrate the interaction of the differentially expressed genes between high and low sphingolipid metabolism. Immune analysis showed that multiple immune terms were upregulated in patients with high sphingolipid metabolism activity. Then, a prognosis model was established based on the identified DEGs between patients with high and low sphingolipid metabolism, which showed great prediction efficiency. Pathway enrichment showed the pathway of myogenesis, spermatogenesis, peroxisome, KRAS signaling, pancreas beta cells, apical surface, MYC target, WNT beta-catenin signaling, late estrogen response and apical junction was significantly enriched in high risk patients. Moreover, we found that the model genes MAGEB1, NPIPA2, PLA2G4B and MAGEA3 could effectively indicate sphingolipid metabolism and risk group.

CONCLUSIONS

In summary, our result showed that sphingolipid metabolism is associated with osteosarcoma metastasis and prognosis, which has the potential to be a therapeutic target for OS.