In multiple myeloma, tumor cells reprogram metabolic pathways to sustain growth and monoclonal immunoglobulin production. This study examines acetyl-CoA carboxylase 1 (ACC1), the enzyme driving the rate-limiting step in de novo lipogenesis, in multiple myeloma metabolic reprogramming, particularly in c-MYC (MYC)-driven subtypes.

ACC1 expression was evaluated across multiple myeloma genetic subgroups, focusing on MYC translocations. Functional studies using ACC1 inhibitors and genetic knockdown assessed multiple myeloma cell growth, lipid synthesis, and metabolic homeostasis in vitro and in vivo. The role of MYC overexpression in ACC1 sensitivity was examined, with palmitate rescue experiments. Lipidomic analysis and assessments of endoplasmic reticulum (ER) stress, protein translation, and oxidative damage elucidated underlying mechanisms.

ACC1 was overexpressed in MYC-translocated multiple myeloma. Its inhibition or knockdown reduced multiple myeloma cell growth in vitro and in vivo, particularly in MYC-overexpressing cells. ACC1 knockdown suppressed de novo lipid synthesis, partially rescued by palmitate. Lipidomic disruptions increased cholesterol ester desaturation and altered phospholipid ratios, inducing ER stress, impaired translation, protein carbonylation, oxidative damage, and apoptosis.

ACC1 is a metabolic vulnerability in MYC-driven multiple myeloma. Inhibiting ACC1 disrupts lipid homeostasis, induces ER stress, and causes oxidative damage, impairing cell survival. Targeting lipid synthesis pathways, especially in MYC-dependent subtypes, offers a promising therapeutic strategy for multiple myeloma.

The tree of life comprises many deep-branching lineages with no or only very few cultured representatives. One such lineage is the phylum Elusimicrobiota, which contains only two described species and whose biology has been only poorly explored. We isolated three new species from this phylum from the intestinal tracts of cockroaches. Like their closest relative, Elusimicrobium minutum, the only member of the family Elusimicrobiaceae described to date, they are small, pleomorphic gram-negative rods characterized by a distinct cell cycle, and like all ultramicrobacteria, they pass through a 0.22-μm filter membrane. Physiological characterization of all isolates revealed that they are obligately anaerobic fermenters that lack catalase and cytochrome c oxidase activities but can remove oxygen from their environment in a non-respiratory manner. Their substrate range is limited to a few hexoses, such as d-glucose, d-galactose, and N-acetyl-d-glucosamine, which are fermented to lactate, acetate, ethanol, and hydrogen as major products. Comparative genome analysis, which included more than 100 MAGs of uncultured lineages of Elusimicrobiaceae, revealed the underlying metabolic pathways and outlined a new phylogenomic framework of the family. Based on phylogenomic, physiological, and morphological evidence, we describe the new isolates as Parelusimicrobium proximum gen. nov., sp. nov., Elusimicrobium posterum sp. nov., and Elusimicrobium simillimum sp. nov. under the rules of ICNP. Based on high-quality genomes of all uncultured representatives, we propose a comprehensive taxonomy of all lineages in the family under the rules of SeqCode, including the new genera Avelusimicrobium, Proelusimicrobium, and the candidate genus "Pseudelusimicrobium".

Dysbiosis, which refers to an imbalance in the composition of the gut microbiome, has been associated with a range of metabolic disorders, including type 2 diabetes, obesity, and metabolic syndrome. Although the exact mechanisms connecting gut dysbiosis to these conditions are not fully understood, various lines of evidence strongly suggest a substantial role for the interaction between the gut microbiome, mitochondria, and epigenetics. Current studies suggest that the gut microbiome has the potential to affect mitochondrial function and biogenesis through the production of metabolites. A well-balanced microbiota plays a pivotal role in supporting normal mitochondrial and cellular functions by providing metabolites that are essential for mitochondrial bioenergetics and signaling pathways. Conversely, in the context of illnesses, an unbalanced microbiota can impact mitochondrial function, leading to increased aerobic glycolysis, reduced oxidative phosphorylation and fatty acid oxidation, alterations in mitochondrial membrane permeability, and heightened resistance to cellular apoptosis. Mitochondrial activity can also influence the composition and function of the gut microbiota. Because of the intricate interplay between nuclear and mitochondrial communication, the nuclear epigenome can regulate mitochondrial function, and conversely, mitochondria can produce metabolic signals that initiate epigenetic changes within the nucleus. Given the epigenetic modifications triggered by metabolic signals from mitochondria in response to stress or damage, targeting an imbalanced microbiota through interventions could offer a promising strategy to alleviate the epigenetic alterations arising from disrupted mitochondrial signaling.

Tertiary lymphoid structures (TLS) in the tumor microenvironment (TME) are emerging solid-tumor indicators of prognosis and response to immunotherapy. Considering that tumorigenesis requires metabolic reprogramming and subsequent TME remodeling, the discovery of TLS metabolic regulators is expected to produce immunotherapeutic targets. To identify such metabolic regulators, we constructed a metabolism-focused sgRNA library and performed an in vivo CRISPR screening in an orthotopic lung tumor mouse model. Combined with The Cancer Genome Atlas database analysis of TLS-related metabolic hub genes, we found that the loss of Acat1 in tumor cells sensitized tumors to anti-PD1 treatment, accompanied by increased TLS in the TME. Mechanistic studies revealed that ACAT1 resulted in mitochondrial protein hypersuccinylation in lung tumor cells and subsequently enhanced mitochondrial oxidative metabolism, which impeded TLS formation. Elimination of ROS by NAC or Acat1 knockdown promoted B cell aggregation and TLS construction. Consistently, data from tissue microassays of 305 patients with lung cancer showed that TLS were more abundant in non-small cell lung cancer (NSCLC) tissues with lower ACAT1 expression. Intratumoral ACAT1 expression was associated with poor immunotherapy outcomes in patients with NSCLC. In conclusion, our results identified ACAT1 as a metabolic regulator of TLS and a promising immunotherapeutic target in NSCLC.

Background: Acute myeloid leukemia (AML), a malignant blood disease, is caused by the excessive growth of undifferentiated myeloid cells, which disrupt normal hematopoiesis and may invade several organs. Given the high heterogeneity in prognosis, identifying stable prognostic biomarkers is crucial for improved risk stratification and personalized treatment strategies. Although glycolysis has been extensively studied in cancer, its prognostic significance in AML remains unclear. Methods: Glycolysis-related prognostic genes were identified by differential expression profiles. We modeled prognostic risk by least absolute shrinkage and selection operator (LASSO) regression and validated it by Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) curves, and independent datasets (BeatAML2.0, GSE37642, GSE71014). Mechanisms were further explored through immune microenvironment analysis and drug sensitivity scores. Results: Differential expression and survival correlation analysis across the genes associated with glycolysis revealed multiple glycolytic genes associated with the outcomes of AML. We constructed a seven-gene prognostic model (G6PD, TFF3, GALM, SOD1, NT5E, CTH, FUT8). Kaplan-Meier analysis demonstrated significantly reduced survival in high-risk patients (hazard ratio (HR) = 3.4, p < 0.01). The model predicted the 1-, 3-, and 5-year survival outcomes, achieving area under the curve (AUC) values greater than 0.8. Immune profiling indicated distinct cellular compositions between risk groups: high-risk patients exhibited elevated monocytes and neutrophils but reduced Th1 cell infiltration. Drug sensitivity analysis showed that high-risk patients exhibited resistance to crizotinib and lapatinib but were more sensitive to motesanib. Conclusions: We established a novel glycolysis-related gene signature for AML prognosis, enabling effective risk classification. Combined with immune microenvironment analysis and drug sensitivity analysis, we screened metabolic characteristics and identified an immune signature to provide deeper insight into AML. Our findings may assist in identifying new therapeutic targets and more effective personalized treatment regimes.

This study aimed to explore the potential correlation between the metabolic intermediate L-2-hydroxyglutarate (L-2-HG) and T cell exhaustion, as well as the underlying mechanisms involved. In this study, we investigated the presence of exhausted T (Tex) cells in patients under certain conditions: HIV infection, chronic leukemia, and hepatocellular carcinoma. To gain insights into the epigenetic signatures and transcriptome changes in Tex cells, we employed a combination of RNA-seq and ATAC-seq analyses. To evaluate the impact of L-2-HG on mitochondrial function, differentiation, and antitumor capacity of Tex cells, we utilized in vitro cell culture experiments and animal tumor models. We observed mitochondrial depolarization and metabolic dysfunction in Tex cells, accompanied by a significant reduction in L-2-HG levels. Moreover, altered epigenetic characteristics were observed in Tex cells, including a substantial increase in H3K27me3 abundance. Culturing Tex cells with L-2-HG demonstrated improved mitochondrial metabolism, reduced H3K27me3 abundance, and enhanced memory T cell differentiation. In a mouse melanoma tumor model, L-2-HG-treated CD8+ T cells for adoptive therapy led to significantly reduced tumor volume and significantly enhanced effector function of T cells. The study revealed that L-2-HG acted as an immune metabolite through epigenetic modifications of Tex cells.

Cancer due to its heterogeneous nature and large prevalence has tremendous socioeconomic impacts on populations across the world. Therefore, it is crucial to discover effective panels of biomarkers for diagnosing cancer at an early stage. Cancer leads to alterations in cell growth and differentiation at the molecular level, some of which are very unique. Therefore, comprehending these alterations can aid in a better understanding of the disease pathology and identification of the biomolecules that can serve as effective biomarkers for cancer diagnosis. Metabolites, among other biomolecules of interest, play a key role in the pathophysiology of cancer whose levels are significantly altered while 'reprogramming the energy metabolism', a cellular condition favored in cancer cells which is one of the hallmarks of cancer. Metabolomics, an emerging omics technology has tremendous potential to contribute towards the goal of investigating cancer metabolites or the metabolic alterations during the development of cancer. Diverse metabolites can be screened in a variety of biofluids, and tumor tissues sampled from cancer patients against healthy controls to capture the altered metabolism. In this review, we provide an overview of different metabolomics approaches employed in cancer research and the potential of metabolites as biomarkers for cancer diagnosis. In addition, we discuss the challenges associated with metabolomics-driven cancer research and gaze upon the prospects of this emerging field.

The KITENIN/ErbB4 complex has been reported to participate in metastasis, which is the principal reason of death in most colorectal cancer patients.

New therapeutics need to be developed to suppress the malignant effects of the KITENIN/ErbB4 complex, which is related to drug resistance. The present study aimed to evaluate changes in cancer cell invasion capacity, transcriptional regulators, and cellular bioenergetics after targeting the KITENIN/ErbB4 complex with emodin. Moreover, we aimed to reveal the mechanistic effects of emodin and observe the dual blockade effects of ErbB4-targeted therapy with KH-type splicing regulatory protein (KSRP) and search for new alternative blockade pathways.

Using in vitro, in vivo, molecular-docking, and metabolomics studies, we evaluated the anticancer effect of emodin alone or in combination with DKCC14S.

Emodin treatment decreased KITENIN and ErbB4 protein levels. The dysfunctional KITENIN/ErbB4 complex suppressed KITENIN-mediated cell invasion and downregulated AP-1 activity, aerobic glycolysis, and the levels of transcriptional regulators associated with cell metabolism. We conclude that emodin targets the KITENIN/ErbB4 complex and offering a novel mechanism by which it disrupts KITENIN-mediated signaling. Furthermore, we were demonstrated that the dual blocking effect of emodin and DKC-C14S on the KITENIN complex showed synergistic effects in suppressing colorectal cancer progression under in cell-based and animal assay.

The results suggest that co-treatment with ErbB4 and KSRP-binding compounds could constitute a potential strategy for controlling colorectal cancer progression by disrupting the KITENIN complex.

Mitochondrial adaptations dynamically reprogram cellular bioenergetics and metabolism and confer key properties for human cancers. However, the selective regulation of these mitochondrial responses remains largely elusive. Here, inspired by a genetic screening in acute myeloid leukemia (AML), we identify RAS effector RREB1 as a translational regulator and uncover a unique translation control system for nuclear-encoded mitochondrial proteins in human cancers. RREB1 deletion reduces mitochondrial activities and succinate metabolism, thereby damaging leukemia stem cell (LSC) function and AML development. Replenishing complex II subunit SDHD rectifies these deficiencies. Notably, inhibition of complex II re-sensitizes AML cells to venetoclax treatment. Mechanistically, a short RREB1 variant binds to a conserved motif in the 3' UTRs and cooperates with elongation factor eEF1A1 to enhance protein translation of nuclear-encoded mitochondrial mRNAs. Overall, our findings reveal a unique translation control mechanism for mitochondrial adaptations in AML pathogenesis and provide a potential strategy for targeting this vulnerability of LSCs.

The complexity of omes - the key cellular ensembles (genome and epigenome, transcriptome, proteome, and metabolome) - is becoming increasingly understood in terms of big-data analysis, the omics. Amongst these, proteomics provides a global description of quantitative and qualitative alterations of protein expression (or protein abundance in body fluids) in response to physiologic or pathologic processes while metabolomics offers a functional portrait of the physiological state by quantifying metabolite abundances in biological samples. Here, we summarize how different techniques of proteomic and metabolic analysis can be used to define key biochemical characteristics of pheochromocytomas/paragangliomas (PPGL). The significance of omics in understanding features of PPGL biology that might translate to improved diagnosis and treatment will be highlighted.

Sleep deprivation (SD) has been reported to induce intestinal damage by several mechanisms, yet its role in modulating epithelial repair remains unclear. In this study, we find that chronic SD leads to colonic damage through continuous hypoxia. However, HIF1α, which generally responds to hypoxia to modulate barrier integrity, was paradoxically dysregulated in the colon. Further investigation revealed that a metabolic disruption during SD causes accumulation of α-ketoglutarate in the colon. The excessive α-ketoglutarate degrades HIF1α protein through PHD2 (prolyl hydroxylase 2) to abolish the intestinal repair functions of HIF1α. Collectively, these findings provide insights into how SD can exacerbate intestinal damage by fine-tuning metabolism to abolish HIF1α-mediated repair.

Growing epidemiological evidence indicates an association between obesity, type 2 diabetes, and certain cancers, suggesting the existence of common underlying mechanisms in these diseases. Frequent hyperglycemias in type 2 diabetes promote pro-inflammatory responses and stimulate intracellular metabolic flux which rewires signaling pathways and influences the onset and advancement of different types of cancers. Here, we review the provocative impact of hyperglycemia on a subset of interconnected signalling pathways that regulate (i) cell growth and survival, (ii) metabolism adjustments, (iii) protein function modulation in response to nutrient availability (iv) and cell fate and proliferation and which are driven respectively by PI3K (Phosphoinositide 3-kinase), AMPK (AMP-activated protein kinase), O-GlcNAc (O-linked N-acetylglucosamine) and Wnt/β-catenin. Specifically, we will elaborate on their involvement in glucose metabolism, inflammation, and cell proliferation, highlighting their interplay in the pathogenesis of diabetes and cancer. Furthermore, the influence of antineoplastic and antidiabetic drugs on the unbridled cellular pathways will be examined. This review aims to inspire the next molecular studies to understand how type 2 diabetes may lead to certain cancers. This will contribute to personalized medicine and direct better prevention strategies.

The catalytic activity of most epigenetic enzymes requires a metabolite produced by central carbon metabolism as a cofactor or (co-)substrate. The concentrations of these metabolites undergo dynamic changes in response to nutrient levels and environmental conditions, reprogramming metabolic processes and epigenetic landscapes. Abnormal accumulations of epigenetic modulatory metabolites resulting from mutations in metabolic enzymes contribute to tumorigenesis. In this review, we first present the concept that metabolite regulation of gene expression represents an evolutionarily conserved mechanism from prokaryotes to eukaryotes. We then review how individual metabolites affect epigenetic enzymes and cancer development. Lastly, we discuss the advancement of and opportunity for therapeutic targeting of metabolite-epigenetic regulation in cancer therapy.

The tricarboxylic acid (TCA) cycle is an essential interface that coordinates cellular metabolism and is as a primary route determining the fate of a variety of fuel sources, including glucose, fatty acid and glutamate. The crosstalk of nutrients replenished TCA cycle regulates breast cancer (BC) progression by changing substrate levels-induced epigenetic alterations, especially the methylation, acetylation, succinylation and lactylation. Long non-coding RNAs (lncRNA) have dual roles in inhibiting or promoting energy reprogramming, and so altering the metabolic flux of fuel sources to the TCA cycle, which may regulate epigenetic modifications at the cellular level of BC. This narrative review discussed the central role of the TCA cycle in interconnecting numerous fuels and the induced epigenetic modifications, and the underlying regulatory mechanisms of lncRNAs in BC.

Cancer is traditionally approached as a genetic disease, with standard treatments including chemotherapy, radiation, targeted therapy, immunotherapy, and surgery significantly improving survival rates and patient outcomes. However, there is a growing recognition of the need for integrative oncology, which expands cancer management by considering cancer as a metabolic disease. Integrative medicine physicians employ holistic therapies focused on patients' needs, aiming to correct the metabolic imbalances associated with cancer and alleviate cancer-related symptoms. Viewing cancer as a metabolic disease involves addressing factors such as an acidic microenvironment, vitamin C deficiency, mitochondrial dysfunction, reduced intracellular oxygen levels, elevated oxidative stress, dysfunctional autophagy, and psychological stress. This paper presents an overview of the evidence and comprehensive strategies supporting integrative medicine approaches in addressing cancer metabolism in integrative oncology settings. Furthermore, the paper underscores the necessity of integrating different cancer theories-genetic and metabolic-for improved patient outcomes and experiences. By combining these perspectives, integrative oncology offers a more holistic, patient-centered approach to cancer treatment.

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.

Organic acid metabolites exhibit acidic properties. These metabolites serve as intermediates in major carbon metabolic pathways and are involved in several biochemical pathways, including the tricarboxylic acid (TCA) cycle and glycolysis. They also regulate cellular activity and play crucial roles in epigenetics, tumorigenesis, and cellular signal transduction. Knowledge of the binding proteins of organic acid metabolites is crucial for understanding their biological functions. However, identifying the binding proteins of these metabolites has long been a challenging task owing to the transient and weak nature of their interactions. Moreover, traditional methods are unsuitable for the structural modification of the ligands of organic acid metabolites because these metabolites have simple and similar structures. Even minor structural modifications can significantly affect protein interactions. Thermal proteome profiling (TPP) provides a promising avenue for identifying binding proteins without the need for structural modifications. This approach has been successfully applied to the identification of the binding proteins of several metabolites. In this study, we investigated the binding proteins of two TCA cycle intermediates, i.e., succinate and fumarate, and lactate, an end-product of glycolysis, using the matrix thermal shift assay (mTSA) technique. This technique involves combining single-temperature (52 ℃) TPP and dose-response curve analysis to identify ligand-binding proteins with high levels of confidence and determine the binding affinity between ligands and proteins. To this end, HeLa cells were lysed, followed by protein desalting to remove endogenous metabolites from the cell lysates. The desalted cell lysates were treated with fumarate or succinate at final concentrations of 0.004, 0.04, 0.4, and 2 mmol/L in the experimental groups or 2 mmol/L sodium chloride in the control group. Considering that the cellular concentration of lactate can be as high as 2-30 mmol/L, we then applied lactate at final concentrations of 0.2, 1, 5, 10, and 25 mmol/L in the experimental groups or 25 mmol/L sodium chloride in the control group. Using high-sensitivity mass spectrometry coupled with data-independent acquisition (DIA) quantification, we quantified 5870, 5744, and 5816 proteins in succinate, fumarate, and lactate mTSA experiments, respectively. By setting stringent cut-off values (i.e., significance of changes in protein thermal stability (p-value)<0.001 and quality of the dose-response curve fitting (square of Pearson's correlation coefficient, R2)>0.95), multiple binding proteins for these organic acid metabolites from background proteins were confidently determined. Several known binding proteins were identified, notably fumarate hydratase (FH) as a binding protein for fumarate, and α-ketoglutarate-dependent dioxygenase (FTO) as a binding protein for both fumarate and succinate. Additionally, the affinity data for the interactions between these metabolites and their binding proteins were obtained, which closely matched those reported in the literature. Interestingly, ornithine aminotransferase (OAT), which is involved in amino acid biosynthesis, and 3-mercaptopyruvate sulfurtransferase (MPST), which acts as an antioxidant in cells, were identified as lactate-binding proteins. Subsequently, an orthogonal assay technique developed in our laboratory, the solvent-induced precipitation (SIP) technique, was used to validate the mTSA results. SIP identified OAT as the top target candidate, validating the mTSA-based finding that OAT is a novel lactate-binding protein. Although MPST was not identified as a lactate-binding protein by SIP, statistical analysis of MPST in the mTSA experiments with 10 or 25 mmol/L lactate revealed that MPST is a lactate-binding protein with a high level of confidence. Peptide-level empirical Bayes t-tests combined with Fisher's exact test also supported the conclusion that MPST is a lactate-binding protein. Lactate is structurally similar to pyruvate, the known binding protein of MPST. Therefore, assuming that lactate could potentially occupy the binding site of pyruvate on MPST. Overall, the novel binding proteins identified for lactate suggest their potential involvement in amino acid synthesis and redox balance regulation.

Metabolism is inextricably linked to every aspect of cellular function. In addition to energy production and biosynthesis, metabolism plays a crucial role in regulating signal transduction and gene expression. Altered metabolic states have been shown to maintain aberrant signaling and transcription, contributing to diseases like cancer, cardiovascular disease, and neurodegeneration. Metabolic gene polymorphisms and defects are also associated with chronic pain conditions, as are increased levels of nerve growth factor (NGF). However, the mechanisms by which NGF may modulate sensory neuron metabolism remain unclear. This study demonstrated that intraplantar NGF injection reprograms sensory neuron metabolism. Nerve growth factor suppressed mitochondrial pyruvate oxidation and enhanced lactate extrusion, requiring 24 hours to increase lactate dehydrogenase A and pyruvate dehydrogenase kinase 1 (PDHK1) expression. Inhibiting these metabolic enzymes reversed NGF-mediated effects. Remarkably, directly disrupting mitochondrial pyruvate oxidation induced severe, persistent allodynia, implicating this metabolic dysfunction in chronic pain. Nanopore long-read sequencing of poly(A) mRNA uncovered extensive transcriptomic changes upon metabolic disruption, including altered gene expression, splicing, and poly(A) tail lengths. By linking metabolic disturbance of dorsal root ganglia to transcriptome reprogramming, this study enhances our understanding of the mechanisms underlying persistent nociceptive sensitization. These findings imply that impaired mitochondrial pyruvate oxidation may drive chronic pain, possibly by impacting transcriptomic regulation. Exploring these metabolite-driven mechanisms further might reveal novel therapeutic targets for intractable pain.

In the USA, the prolonged effective survival of cancer population has brought significant attention to the rising risk of cardiometabolic morbidity and mortality in this population. This heightened risk underscores the urgent need for research into effective pharmacological interventions for cancer survivors. Notably, metformin, a well-known metabolic regulator with pleiotropic effects, has shown protective effects against cardiometabolic disorders in diabetic individuals. Despite these promising indications, evidence supporting its efficacy in improving cardiometabolic outcomes in cancer survivors remains scarce.

A prospective cohort was established using a nationally representative sample of cancer survivors enrolled in the US National Health and Nutrition Examination Survey (NHANES), spanning 2003 to 2018. Outcomes were derived from patient interviews, physical examinations, and public-access linked mortality archives up to 2019. The Oxidative Balance Score was utilized to assess participants' levels of oxidative stress. To evaluate the correlations between metformin use and the risk of cardiometabolic diseases and related mortality, survival analysis of cardiometabolic mortality was performed by Cox proportional hazards model, and cross-sectional analysis of cardiometabolic diseases outcomes was performed using logistic regression models. Interaction analyses were conducted to explore the specific pharmacological mechanism of metformin.

Among 3995 cancer survivors (weighted population, 21,671,061, weighted mean [SE] age, 62.62 [0.33] years; 2119 [53.04%] females; 2727 [68.26%] Non-Hispanic White individuals), 448 reported metformin usage. During the follow-up period of up to 17 years (median, 6.42 years), there were 1233 recorded deaths, including 481 deaths from cardiometabolic causes. Multivariable models indicated that metformin use was associated with a lower risk of all-cause (hazard ratio [HR], 0.62; 95% confidence interval [CI], 0.47-0.81) and cardiometabolic (HR, 0.65; 95% CI, 0.44-0.97) mortality compared with metformin nonusers. Metformin use was also correlated with a lower risk of total cardiovascular disease (odds ratio [OR], 0.41; 95% CI, 0.28-0.59), stroke (OR, 0.44; 95% CI, 0.26-0.74), hypertension (OR, 0.27; 95% CI, 0.14-0.52), and coronary heart disease (OR, 0.41; 95% CI, 0.21-0.78). The observed inverse associations were consistent across subgroup analyses in four specific cancer populations identified as cardiometabolic high-risk groups. Interaction analyses suggested that metformin use as compared to non-use may counter-balance oxidative stress.

In this cohort study involving a nationally representative population of US cancer survivors, metformin use was significantly correlated with a lower risk of cardiometabolic diseases, all-cause mortality, and cardiometabolic mortality.

Mitochondrial respiration complexes play a crucial function. As a result, dysfunction or change is intimately associated with many different diseases, among them cancer. The epigenetic, evolutionary, and metabolic effects of mitochondrial complex IΙ are the primary concerns of our review. Provides novel insight into the vital role of naringenin (NAR) as an intriguing flavonoid phytochemical in cancer treatment. NAR is a significant phytochemical that is a member of the flavanone group of polyphenols and is mostly present in citrus fruits, such as grapefruits, as well as other fruits and vegetables, like tomatoes and cherries, as well as foods produced from medicinal herbs. The evidence that is now available indicates that NAR, an herbal remedy, has significant pharmacological qualities and anti-cancer effects. Through a variety of mechanisms, including the induction of apoptosis, cell cycle arrest, restriction of angiogenesis, and modulation of several signaling pathways, NAR prevents the growth of cancer. However, the hydrophobic and crystalline structure of NAR is primarily responsible for its instability, limited oral bioavailability, and water solubility. Furthermore, there is no targeting and a high rate of breakdown in an acidic environment. These shortcomings are barriers to its efficient medical application. Improvement targeting NAR to mitochondrial complex ΙΙ by loading it on chitosan nanoparticles is a promising strategy.

Glioblastoma is a highly malignant brain tumor consisting of a heterogeneous cellular population. The transformed metabolism of glioblastoma cells supports their growth and division on the background of their milieu. One might hypothesize that the transformed metabolism of a primary glioblastoma could be well adapted to limitations in the variety and number of substrates imported into the brain parenchyma and present it their microenvironment. Additionally, the phenotypic heterogeneity of cancer cells could promote the variations among their metabolic capabilities regarding the utilization of available substrates and release of metabolic intermediates. With the aim to identify the putative metabolic footprint of different types of glioblastoma cells, we exploited the possibility for separation of polar and ionic molecules present in culture media or cell lysates by hydrophilic interaction liquid chromatography (HILIC). The mass spectrometry (MS) was then used to identify and quantify the eluted compounds. The introduced method allows the detection and quantification of more than 150 polar and ionic metabolites in a single run, which may be present either in culture media or cell lysates and provide data for polaromic studies within metabolomics. The method was applied to analyze the culture media and cell lysates derived from two types of glioblastoma cells, T98G and U118. The analysis revealed that even both types of glioblastoma cells share several common metabolic aspects, and they also exhibit differences in their metabolic capability. This finding agrees with the hypothesis about metabolic heterogeneity of glioblastoma cells. Furthermore, the combination of both analytical methods, HILIC-MS, provides a valuable tool for metabolomic studies based on the simultaneous identification and quantification of a wide range of polar and ionic metabolites-polaromics.

Isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are metabolic enzymes that interconvert isocitrate and 2-oxoglutarate (2OG). Gain-of-function mutations in IDH1 and IDH2 occur in a number of cancers, including acute myeloid leukemia, glioma, cholangiocarcinoma, and chondrosarcoma. These mutations cripple the wild-type activity of IDH and cause the enzymes to catalyze a partial reverse reaction in which 2OG is reduced but not carboxylated, resulting in production of the (R)-enantiomer of 2-hydroxyglutarate ((R)-2HG). (R)-2HG accumulation in IDH-mutant tumors results in profound dysregulation of cellular metabolism. The most well-characterized oncogenic effects of (R)-2HG involve the dysregulation of 2OG-dependent epigenetic tumor-suppressor enzymes. However, (R)-2HG has many other effects in IDH-mutant cells, some that promote transformation and others that induce metabolic dependencies. Herein, we review how cancer-associated IDH mutations impact epigenetic regulation and cellular metabolism and discuss how these effects can potentially be leveraged to therapeutically target IDH-mutant tumors.

RNA modification, especially RNA methylation, is a critical posttranscriptional process influencing cellular functions and disease progression, accounting for over 60% of all RNA modifications. It plays a significant role in RNA metabolism, affecting RNA processing, stability, and translation, thereby modulating gene expression and cell functions essential for proliferation, survival, and metastasis. Increasing studies have revealed the disruption in RNA metabolism mediated by RNA methylation has been implicated in various aspects of cancer progression, particularly in metabolic reprogramming and immunity. This disruption of RNA methylation has profound implications for tumor growth, metastasis, and therapy response. Herein, we elucidate the fundamental characteristics of RNA methylation and their impact on RNA metabolism and gene expression. We highlight the intricate relationship between RNA methylation, cancer metabolic reprogramming, and immunity, using the well-characterized phenomenon of cancer metabolic reprogramming as a framework to discuss RNA methylation's specific roles and mechanisms in cancer progression. Furthermore, we explore the potential of targeting RNA methylation regulators as a novel approach for cancer therapy. By underscoring the complex mechanisms by which RNA methylation contributes to cancer progression, this review provides a foundation for developing new prognostic markers and therapeutic strategies aimed at modulating RNA methylation in cancer treatment.

Pheochromocytomas and paragangliomas (PPGLs) have emerged as one of the most common endocrine tumors. It epitomizes fascinating crossroads of genetic, metabolic, and endocrine oncology, providing a canvas to explore the molecular intricacies of tumor biology. Predominantly rooted in the aberration of metabolic pathways, particularly the Krebs cycle and related enzymatic functionalities, PPGLs manifest an intriguing metabolic profile, highlighting elevated levels of oncometabolites like succinate and fumarate, and furthering cellular malignancy and genomic instability. This comprehensive review aims to delineate the multifaceted aspects of tumor metabolism in PPGLs, encapsulating genetic factors, oncometabolites, and potential therapeutic avenues, thereby providing a cohesive understanding of metabolic disturbances and their ramifications in tumorigenesis and disease progression. Initial investigations into PPGLs metabolomics unveiled a stark correlation between specific genetic mutations, notably in the succinate dehydrogenase complex (SDHx) genes, and the accumulation of oncometabolites, establishing a pivotal role in epigenetic alterations and hypoxia-inducible pathways. By scrutinizing voluminous metabolic studies and exploiting technologies, novel insights into the metabolic and genetic aspects of PPGLs are perpetually being gathered elucidating complex interactions and molecular machinations. Additionally, the exploration of therapeutic strategies targeting metabolic abnormalities has burgeoned harboring potential for innovative and efficacious treatment modalities. This review encapsulates the profound metabolic complexities of PPGLs, aiming to foster an enriched understanding and pave the way for future investigations and therapeutic innovations in managing these metabolically unique tumors.

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls.

Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138).

Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients.

This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Tumor cells can acquire a large amount of energy and structural components by reprogramming energy metabolism; moreover, metabolic profiles slightly differ according to cancer type. This study compared and assessed the metabolic profile of head and neck squamous cell carcinoma (HNSCC) and normal tissues, which were collected from patients without cancer.

Overall, 23 patients with HNSCC and 6 patients without cancer were included in the analysis. Metabolomic profiles were analyzed using capillary electrophoresis-mass spectrometry. Gene expression was evaluated using real-time reverse transcription-polymerase chain reaction.

Glycolysis, the pentose phosphate pathway, tricarboxylic acid cycle, and glutamine metabolism were upregulated in HNSCC tissues based on gene expression analysis. HNSCC could then have enhanced energy production and structural component. The levels of lactate, succinate, glutathione, 2-hydroxyglutarate, and S-adenosylmethionine, considered as oncometabolites, increased and these had accumulated in HNSCC tissues.

The level of metabolites and the expression of enzymes differ between HNSCC and normal tissues. Reprogramming metabolism in HNSCC provides an energy source as well as structural components, creating a system that offers rapid proliferation, progression, and is less likely to be eliminated.

Uncontrolled pathogenic genome mutations in germline cells might impair adult fertility, lead to birth defects or even affect the adaptability of a species. Understanding the sources of DNA damage, as well as the features of damage response in germline cells are the overarching tasks to reduce the mutations in germline cells. With the accumulation of human genome data and genetic reports, genome variants formed in germline cells are being extensively explored. However, the sources of DNA damage, the damage repair mechanisms, and the effects of DNA damage or mutations on the development of germline cells are still unclear. Besides exogenous triggers of DNA damage such as irradiation and genotoxic chemicals, endogenous exposure to inflammation may also contribute to the genome instability of germline cells. In this review, we summarized the features of de novo mutations and the specific DNA damage responses in germline cells and explored the possible roles of inflammation on the genome stability of germline cells.

Cancer is amongst the most dreadful ailments of modern times, and its impact continuously worsens global health systems. Early diagnosis and suitable therapeutic agents are the prime keys to managing this disease. Metabolomics deals with the complete profiling of cells and physiological phenomena in their organelles, thus helping in keen knowledge of the pathological status of the disease. It has been proven to be one of the best strategies in the early screening of cancer.

This review has covered the recent updates on the promising role of metabolomics in the identification of significant biochemical markers in cancer-prone individuals that could lead to the identification of cancer in the early stages.

The literature was collected through various databases, like Scopus, PubMed, and Google Scholar, with stress laid on the last ten years' publications.

It was assessed in this review that early recognition of cancerous growth could be achieved via complete metabolic profiling in association with transcriptomics and proteomics. The outcomes are rooted in various clinical studies that anticipated various biomarkers like tryptophan, phenylalanine, lactates, and different metabolic pathways associated with the Warburg effect. This metabolite imaging has been a fundamental step for the target acquisition, evaluation of predictive cancer biomarkers for early detection, and outlooks into cancer therapy along with critical evaluation. Significant efforts should be made to make this technique most reliable and easy.

Analysis of endogenous metabolites in various diseases is useful for searching diagnostic biomarkers and elucidating the molecular mechanisms of pathophysiology. The author and collaborators have developed some LC/tandem mass spectrometry (LC/MS/MS) methods for metabolites and applied them to disease-related samples. First, we identified urinary conjugated cholesterol metabolites and serum N-palmitoyl-O-phosphocholine serine as useful biomarkers for Niemann-Pick disease type C (NPC). For the purpose of intraoperative diagnosis of glioma patients, we developed the LC/MS/MS analysis methods for 2-hydroxyglutaric acid or cystine and found that they could be good differential biomarkers. For renal cell carcinoma, we searched for various biomarkers for early diagnosis, malignancy evaluation and recurrence prediction by global metabolome analysis and targeted LC/MS/MS analysis. In pathological analysis, we developed a simultaneous LC/MS/MS analysis method for 13 steroid hormones and applied it to NPC cells, we found 6 types of reductions in NPC model cells. For non-alcoholic steatohepatitis (NASH), model mice were prepared with special diet and plasma bile acids were measured, and as a result, hydrophilic bile acids were significantly increased. In addition, we developed an LC/MS/MS method for 17 sterols and analyzed liver cholesterol metabolites and found a decrease in phytosterols and cholesterol synthetic markers and an increase in non-enzymatic oxidative sterols in the pre-onset stage of NASH. We will continue to challenge themselves to add value to clinical practice based on cutting-edge analytical chemistry methodology.

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

DNA methylation is an epigenetic process altered in cancer and ageing. Age-related methylation drift can be used to estimate lifespan and can be influenced by extrinsic factors such as diet. Here, we report that non-pathogenic microbiota accelerate age-related methylation drift in the colon when compared with germ-free mice. DNA methylation analyses showed that microbiota and IL10KO were associated with changes in 5% and 4.1% of CpG sites, while mice with both factors had 18% alterations. Microbiota, IL10KO, and their combination altered 0.4%, 0.4%, and 4% of CpG island methylation, respectively. These are comparable to what is seen in colon cancer. Ageing changes were accelerated in the IL10KO mice with microbiota, and the affected genes were more likely to be altered in colon cancer. Thus, the microbiota affect DNA methylation of the colon in patterns reminiscent of what is observed in ageing and colorectal cancer.

Prostate cancer (PC) is a heterogenous multifocal disease ranging from indolent to lethal states. For improved treatment-stratification, reliable approaches are needed to faithfully differentiate between high- and low-risk tumors and to predict therapy response at diagnosis.

A metabolomic approach based on high resolution magic angle spinning nuclear magnetic resonance (HR MAS NMR) analysis was applied on intact biopsies samples (n = 111) obtained from patients (n = 31) treated by prostatectomy, and combined with advanced multi- and univariate statistical analysis methods to identify metabolomic profiles reflecting tumor differentiation (Gleason scores and the International Society of Urological Pathology (ISUP) grade) and subtypes based on tumor immunoreactivity for Ki67 (cell proliferation) and prostate specific antigen (PSA, marker for androgen receptor activity).

Validated metabolic profiles were obtained that clearly distinguished cancer tissues from benign prostate tissues. Subsequently, metabolic signatures were identified that further divided cancer tissues into two clinically relevant groups, namely ISUP Grade 2 (n = 29) and ISUP Grade 3 (n = 17) tumors. Furthermore, metabolic profiles associated with different tumor subtypes were identified. Tumors with low Ki67 and high PSA (subtype A, n = 21) displayed metabolite patterns significantly different from tumors with high Ki67 and low PSA (subtype B, n = 28). In total, seven metabolites; choline, peak for combined phosphocholine/glycerophosphocholine metabolites (PC + GPC), glycine, creatine, combined signal of glutamate/glutamine (Glx), taurine and lactate, showed significant alterations between PC subtypes A and B.

The metabolic profiles of intact biopsies obtained by our non-invasive HR MAS NMR approach together with advanced chemometric tools reliably identified PC and specifically differentiated highly aggressive tumors from less aggressive ones. Thus, this approach has proven the potential of exploiting cancer-specific metabolites in clinical settings for obtaining personalized treatment strategies in PC.

Metabolic reprogramming has been considered a core hallmark of cancer, in which excessive accumulation of lipids promote cancer initiation, progression and metastasis. Lipid metabolism often includes the digestion and absorption of dietary fat, and the ways in which cancer cells utilize lipids are often influenced by the complex interactions within the tumor microenvironment. Among multiple cancer risk factors, obesity has a positive association with multiple cancer types, while diets like calorie restriction and fasting improve health and delay cancer. Impact of these diets on tumorigenesis or cancer prevention are generally studied on cancer cells, despite heterogeneity of the tumor microenvironment. Cancer cells regularly interact with these heterogeneous microenvironmental components, including immune and stromal cells, to promote cancer progression and metastasis, and there is an intricate metabolic crosstalk between these compartments. Here, we focus on discussing fat metabolism and response to dietary fat in the tumor microenvironment, focusing on both immune and stromal components and shedding light on therapeutic strategies surrounding lipid metabolic and signaling pathways.

Metabolic assays serve as pivotal tools in biomedical research, offering keen insights into cellular physiological and pathological states. While mass spectrometry (MS)-based metabolomics remains the gold standard for comprehensive, multiplexed analyses of cellular metabolites, innovative technologies are now emerging for the targeted, quantitative scrutiny of metabolites and metabolic pathways at the single-cell level. In this review, we elucidate an array of these advanced methodologies, spanning synthetic and surface chemistry techniques, imaging-based methods, and electrochemical approaches. We summarize the rationale, design principles, and practical applications for each method, and underscore the synergistic benefits of integrating single-cell metabolomics (scMet) with other single-cell omics technologies. Concluding, we identify prevailing challenges in the targeted scMet arena and offer a forward-looking commentary on future avenues and opportunities in this rapidly evolving field.

Metastasis is the leading cause of high ovarian-cancer-related mortality worldwide. Three major processes constitute the whole metastatic cascade: invasion, intravasation, and extravasation. Tumor cells often reprogram their metabolism to gain advantages in proliferation and survival. However, whether and how those metabolic alterations contribute to the invasiveness of tumor cells has yet to be fully understood. Here we performed a genome-wide CRISPR-Cas9 screening to identify genes participating in tumor cell dissemination and revealed that PTGES3 acts as an invasion suppressor in ovarian cancer. Mechanistically, PTGES3 binds to phosphofructokinase, liver type (PFKL) and generates a local source of prostaglandin E2 (PGE2) to allosterically inhibit the enzymatic activity of PFKL. Repressed PFKL leads to downgraded glycolysis and the subsequent TCA cycle for glucose metabolism. However, ovarian cancer suppresses the expression of PTGES3 and disrupts the PTGES3-PGE2-PFKL inhibitory axis, leading to hyperactivation of glucose oxidation, eventually facilitating ovarian cancer cell motility and invasiveness.