Recent advances in cancer metabolism: a technological perspective

Searching for the optimal precondition procedure for mesenchymal stem/stromal cell treatment: Facts and perspectives

Mesenchymal stem/stromal cells are potential optimal cell sources for stem cell therapies, and pretreatment has proven to enhance cell vitality and function. In a recent publication, Li et al explored a new combination of pretreatment conditions. Here, we present an editorial to comment on their work and provide our view on mesenchymal stem/stromal cell precondition.

Recent Advances on PKM2 Inhibitors and Activators in Cancer Applications

Metabolic reprogramming of cells, from the normal mode of glucose metabolism named glycolysis, is a pivotal characteristic of impending cancerous cells. Pyruvate kinase M2 (PKM2), an important enzyme that catalyzes the final rate-limiting stage during glycolysis, is highly expressed in numerous types of tumors and aids in development of favorable conditions for the survival of tumor cells. Increasing evidence has suggested that PKM2 is one of promising targets for innovative drug discovery, especially for the developments of antitumor therapeutics. Herein, we systematically summarize the recent advancement on PKM2 modulators including inhibitors and activators in cancer applications. We also discussed the classifications of pyruvate kinases in mammals and the biological functions of PKM2 in this review. We do hope that this review would provide a comprehensive understanding of the current research on PKM2 modulators, which may benefit the development of more potent PKM2-related drug candidates to treat PKM2-associated diseases including cancers in future.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. “Classical” tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine

Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.

How CAR T Cells Breathe

The manufacture of efficacious CAR T cells represents a major challenge in cellular therapy. An important aspect of their quality concerns energy production and consumption, known as metabolism. T cells tend to adopt diverse metabolic profiles depending on their differentiation state and their stimulation level. It is therefore expected that the introduction of a synthetic molecule such as CAR, activating endogenous signaling pathways, will affect metabolism. In addition, upon patient treatment, the tumor microenvironment might influence the CAR T cell metabolism by compromising the energy resources. The access to novel technology with higher throughput and reduced cost has led to an increased interest in studying metabolism. Indeed, methods to quantify glycolysis and mitochondrial respiration have been available for decades but were rarely applied in the context of CAR T cell therapy before the release of the Seahorse XF apparatus. The present review will focus on the use of this instrument in the context of studies describing the impact of CAR on T cell metabolism and the strategies to render of CAR T cells more metabolically fit.

Probing Methionine Uptake in Live Cells by Deuterium Labeling and Stimulated Raman Scattering

The small biomolecule methionine (Met) is a fundamental amino acid required for a vast range of biological processes such as protein synthesis, cancer metabolism, and epigenetics. However, it is still difficult to visualize the subcellular distribution of small biomolecules including Met in a minimally invasive manner. Here, we demonstrate stimulated Raman scattering (SRS) imaging of cellular uptake of deuterated methionine (d₈-Met) in live HeLa cells by way of comparison to the previously used alkyne-labeled Met analogue─homopropargylglycine (Hpg). We show that the solutions of d₈-Met and Hpg have similar SRS signal intensities. Furthermore, by careful image analysis with background subtraction, we succeed in the SRS imaging of cellular uptake of d₈-Met with a much greater signal intensity than Hpg, possibly reflecting the increased and minimally invasive uptake kinetics of d₈-Met compared with Hpg. We anticipate that d₈-Met and other deuterated biomolecules will be useful for investigating metabolic processes with subcellular resolution.

Comprehensive molecular characterization and identification of prognostic signature in stomach adenocarcinoma on the basis of energy-metabolism-related genes

BACKGROUND

Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, but its molecular and prognostic characteristics has never been fully illustrated.

AIM

To describe a molecular evaluation of primary STAD and develop new therapies and identify promising prognostic signatures.

METHODS

We describe a comprehensive molecular evaluation of primary STAD based on comprehensive analysis of energy-metabolism-related gene (EMRG) expression profiles.

RESULTS

On the basis of 86 EMRGs that were significantly associated to patients’ progression-free survival (PFS), we propose a molecular classification dividing gastric cancer into two subtypes: Cluster 1, most of which are young patients and display more immune and stromal cell components in tumor microenvironment and lower tumor priority; and Cluster 2, which show early stages and better PFS. Moreover, we construct a 6-gene signature that can classify the prognostic risk of patients after a three-phase training test and validation process. Compared with patients with low-risk score, patients with high-risk score had shorter overall survival. Furthermore, calibration and DCA analysis plots indicate the excellent predictive performance of the 6-gene signature, and which present higher robustness and clinical usability compared with three previous reported prognostic gene signatures. According to gene set enrichment analysis, gene sets related to the high-risk group were participated in the ECM receptor interaction and hedgehog signaling pathway.

CONCLUSION

Identification of the EMRG-based molecular subtypes and prognostic gene model provides a roadmap for patient stratification and trials of targeted therapies.

Energy Metabolism in Osteogenic Differentiation and Reprogramming: A Possible Future Strategy for Periodontal Regeneration

Energy metabolism is crucial in stem cells as they harbor various metabolic pathways depending on their developmental stages. Moreover, understanding the control of their self-renewal or differentiation via manipulation of their metabolic state may yield novel regenerative therapies. Periodontal ligament (PDL) cells existing between the tooth and alveolar bone are crucial for maintaining homeostasis in the periodontal tissue. In addition, they play a pivotal role in periodontal regeneration, as they possess the properties of mesenchymal stem cells and are capable of differentiating into osteogenic cells. Despite these abilities, the treatment outcome of periodontal regenerative therapy remains unpredictable because the biological aspects of PDL cells and the mechanisms of their differentiation remain unclear. Recent studies have revealed that metabolism and factors affecting metabolic pathways are involved in the differentiation of PDL cells. Furthermore, understanding the metabolic profile of PDL cells could be crucial in manipulating the differentiation of PDL cells. In this review, first, we discuss the energy metabolism in osteoblasts and stem cells to understand the metabolism of PDL cells. Next, we summarize the metabolic preferences of PDL cells during their maintenance and cytodifferentiation. The perspectives discussed have potential applicability for creating a platform for reliable regenerative therapies for periodontal tissue.

SIRT3 and Metabolic Reprogramming Mediate the Antiproliferative Effects of Whey in Human Colon Cancer Cells

Emerging strategies to improve healthy aging include dietary interventions as a tool to promote health benefits and reduce the incidence of aging-related comorbidities. The health benefits of milk are also linked to its richness in betaines and short-chain acylcarnitines, which act synergistically in conferring anticancer, anti-inflammatory, and antioxidant properties. Whey, despite being a dairy by-product, still has a considerable content of bioactive betaines and acylcarnitines. Here, we investigated the anticancer properties of whey from Mediterranean water buffalo (Bubalus bubalis) milk by testing its antiproliferative effects in colorectal cancer (CRC) cells HT-29, HCT 116, LoVo and SW480. Results indicated that treatment with whey for 72 h inhibited cell proliferation (p < 0.001), induced cell cycle arrest, and apoptosis via caspase-3 activation, and modulated cell metabolism by limiting glucose uptake and interfering with mitochondrial energy metabolism with the highest effects observed in HT-29 and HCT 116 cells. At molecular level, these effects were accompanied by upregulation of sirtuin 3 (SIRT3) (p < 0.01) and peroxisome proliferator-activated receptor (PPAR)-γ expression (p < 0.001), and downregulation of lactate dehydrogenase A (LDHA) (p < 0.01), sterol regulatory-element binding protein 1 (SREBP1) (p < 0.05), and PPAR-α (p < 0.01). Transient SIRT3 gene silencing blocked the effects of whey on the LDHA, PPAR-γ, and PPAR-α protein expressions (p < 0.01) suggesting that the whey capacity of perturbating the metabolic homeostasis in CRC cell lines is mediated by SIRT3.

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment

The tumor's physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.

MTHFD2 promotes ovarian cancer growth and metastasis via activation of the STAT3 signaling pathway

Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a bifunctional enzyme located in the mitochondria. MTHFD2 has been reported to be overexpressed in several malignant tumors and is implicated in cancer development. This study aimed to investigate the effect of MTHFD2 on ovarian cancer progression. The expression of MTHFD2 was detected by bioinformatic analysis, immunohistochemistry, RT‐qPCR (real‐time quantitative PCR analysis), and western blot analysis. The effects of MTHFD2 depletion on cell proliferation, migration, and invasion were determined through in vitro experiments. Cell cycle progression and apoptosis were accessed by flow cytometry. The related signaling pathway protein expression was determined by western blot analysis. We found that MTHFD2 is highly expressed in both ovarian cancer tissues and cell lines. MTHFD2 deletion suppressed cell proliferation and metastasis. Knockdown of MTHFD2 induces cell apoptosis and G2/M arrest, whereas the number of cells in S phase increased with MTHFD2 overexpression. Mechanically, our results indicate that an inhibitory effect of MTHFD2 knockdown may be mediated by the downregulation of cyclin B1/Cdc2 complex and the inhibitory effect on its activity. Additionally, MTHFD2 could regulate cell growth and aggressiveness via activation of STAT3 and the STAT3‐induced epithelial–mesenchymal transition signaling pathway. These findings indicate that MTHFD2 is overexpressed in ovarian cancer and regulates cell proliferation and metastasis, presenting an attractive therapeutic target.

Challenges in Studying Stem Cell Metabolism

The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use of these methodologies has been fruitful, many challenges are posed by the intricacies of culturing stem cells in vitro, along with the distinctive scarcity of adult tissue stem cells and the complexities of their niches in vivo. This review provides an examination of the methodologies used to characterize stem cell metabolism, highlighting their utility while placing a sharper focus on their limitations and hurdles the field needs to overcome for the optimal study of stem cell metabolic networks.

Amino Acid Transporters on the Guard of Cell Genome and Epigenome

Tumorigenesis is driven by metabolic reprogramming. Oncogenic mutations and epigenetic alterations that cause metabolic rewiring may also upregulate the reactive oxygen species (ROS). Precise regulation of the intracellular ROS levels is critical for tumor cell growth and survival. High ROS production leads to the damage of vital macromolecules, such as DNA, proteins, and lipids, causing genomic instability and further tumor evolution. One of the hallmarks of cancer metabolism is deregulated amino acid uptake. In fast-growing tumors, amino acids are not only the source of energy and building intermediates but also critical regulators of redox homeostasis. Amino acid uptake regulates the intracellular glutathione (GSH) levels, endoplasmic reticulum stress, unfolded protein response signaling, mTOR-mediated antioxidant defense, and epigenetic adaptations of tumor cells to oxidative stress. This review summarizes the role of amino acid transporters as the defender of tumor antioxidant system and genome integrity and discusses them as promising therapeutic targets and tumor imaging tools.

Mutual regulation of metabolic processes and proinflammatory NF-κB signaling

The nuclear factor kappa B (NF-κB) signaling system, a key regulator of immunologic processes, also affects a plethora of metabolic changes associated with inflammation and the immune response. NF-κB-regulating signaling cascades, in concert with NF-κB-mediated transcriptional events, control the metabolism at several levels. NF-κB modulates apical components of metabolic processes including metabolic hormones such as insulin and glucagon, the cellular master switches 5' AMP-activated protein kinase and mTOR, and also numerous metabolic enzymes and their respective regulators. Vice versa, metabolic enzymes and their products also exert multilevel control of NF-κB activity, thereby creating a highly connected regulatory network. These insights have resulted in the identification of the noncanonical IκB kinase kinases IκB kinase ɛ and TBK1, which are upregulated by overnutrition, and may therefore be suitable potential therapeutic targets for metabolic syndromes. An inhibitor interfering with the activity of both kinases reduces obesity-related metabolic dysfunctions in mouse models and the encouraging results from a recent clinical trial indicate that targeting these NF-κB pathway components improves glucose homeostasis in a subset of patients with type 2 diabetes.

Hydroxycitric acid potentiates the cytotoxic effect of tamoxifen in MCF-7 breast cancer cells through inhibition of ATP citrate lyase

Hydroxycitric acid (HCA), a dietary-derived weight loss supplement, competitively inhibits ATP citrate lyase (ACLY). Tamoxifen (TAM) is the most frequently used therapy for estrogen receptor (ER)-positive breast cancer patients, but its application was restricted due to efficacy related issues. Lipid metabolic reprogramming plays a key role in cancer progression and response to treatment. This study will test the hypothesis that targeting lipid metabolic enzymes could enhance TAM effect against breast cancer cells. MCF-7 ER-positive breast cancer cell line was used, and the cytotoxic effect of TAM treatment, alone and in combination with HCA was evaluated. Flowcytometric analysis of apoptosis following TAM and/or HCA treatment was additionally performed. Besides, the effects of TAM and/or HCA on ACLY, acetyl CoA carboxylase alpha (ACC-α) and fatty acid synthase (FAS) expression were investigated. Likewise, expression of ER-α protein through TAM and/or HCA treatment was examined. Cell contents of cholesterol and triglyceride were quantified. Treatment with TAM or HCA significantly reduced cell viability in a concentration-dependent manner whereas co-treatment synergistically reduced cell viability, promoted apoptosis, and decreased the expression of ACLY, ACC-α, and FAS. Intracellular triglyceride and cholesterol were accumulated in response to treatment with TAM and/or HCA. Moreover, either solitary TAM or TAM/ HCA co-treatment increased ER-α protein levels non significantly. Our results revealed that TAM effects on breast cancer are mediated, in part, through the regulation of key genes involved in lipid metabolism. Accordingly, inhibition of ACLY by HCA might be beneficial to enhance the therapeutic index of TAM against breast cancer.

IsoSearch: An Untargeted and Unbiased Metabolite and Lipid Isotopomer Tracing Strategy from HR-LC-MS/MS Datasets

Stable isotopic tracer analysis is a technique used to determine carbon or nitrogen atom incorporation into biological systems. A number of mass spectrometry based approaches have been developed for this purpose, including high-resolution tandem mass spectrometry (HR-LC-MS/MS), selected reaction monitoring (SRM) and parallel reaction monitoring (PRM). We have developed an approach for analyzing untargeted metabolomic and lipidomic datasets using high-resolution mass spectrometry with polarity switching and implemented our approach in the open-source R script IsoSearch and in Scaffold Elements software. Using our strategy, which requires an unlabeled reference dataset and isotope labeled datasets across various biological conditions, we traced metabolic isotopomer alterations in breast cancer cells (MCF-7) treated with the metabolic drugs 2-deoxy-glucose, 6-aminonicotinamide, compound 968, and rapamycin. Metabolites and lipids were first identified by the commercial software Scaffold Elements and LipidSearch, then IsoSearch successfully profiled the ¹³C-isotopomers extracted metabolites and lipids from ¹³C-glucose labeled MCF-7 cells. The results interpreted known models, such as glycolysis and pentose phosphate pathway inhibition, but also helped to discover new metabolic/lipid flux patterns, including a reactive oxygen species (ROS) defense mechanism induced by 6AN and triglyceride accumulation in rapamycin treated cells. The results suggest the IsoSearch/Scaffold Elements platform is effective for studying metabolic tracer analysis in diseases, drug metabolism, and metabolic engineering for both polar metabolites and non-polar lipids.

Epigenetic mechanisms and the hallmarks of cancer: an intimate affair

Epigenetic mechanisms comprising DNA methylation, histone modifications, and noncoding RNAs affect chromatin structure and regulate gene expression. These mechanisms control normal embryonic development and adult life and their deregulation contributes to several diseases including cancer. The process of tumorigenesis is complex and results from the evolution of different "hallmarks of cancer". Hanahan and Weinberg presented in 2000 and 2011 seminal contributions in the cancer field, first the six hallmarks of cancer and a decade later two additional hallmarks and two enabling characteristics were added. Here, we surmise that epigenetic mechanisms regulate and contribute to every single hallmark in cancer, and thus represent the hallmark of hallmarks in tumorigenesis. Focusing on epigenetics as a major hallmark in cancer formation has profound preventive, therapeutic, and clinical implications.

Co-expression based cancer staging and application

A novel method is developed for predicting the stage of a cancer tissue based on the consistency level between the co-expression patterns in the given sample and samples in a specific stage. The basis for the prediction method is that cancer samples of the same stage share common functionalities as reflected by the co-expression patterns, which are distinct from samples in the other stages. Test results reveal that our prediction results are as good or potentially better than manually annotated stages by cancer pathologists. This new co-expression-based capability enables us to study how functionalities of cancer samples change as they evolve from early to the advanced stage. New and exciting results are discovered through such functional analyses, which offer new insights about what functions tend to be lost at what stage compared to the control tissues and similarly what new functions emerge as a cancer advances. To the best of our knowledge, this new capability represents the first computational method for accurately staging a cancer sample. The R source code used in this study is available at GitHub (https://github.com/yxchspring/CECS).

Glycolysis-Independent Glucose Metabolism Distinguishes TE from ICM Fate during Mammalian Embryogenesis

The mouse embryo undergoes compaction at the 8-cell stage, and its transition to 16 cells generates polarity such that the outer apical cells are trophectoderm (TE) precursors and the inner cell mass (ICM) gives rise to the embryo. Here, we report that this first cell fate specification event is controlled by glucose. Glucose does not fuel mitochondrial ATP generation, and glycolysis is dispensable for blastocyst formation. Furthermore, glucose does not help synthesize amino acids, fatty acids, and nucleobases. Instead, glucose metabolized by the hexosamine biosynthetic pathway (HBP) allows nuclear localization of YAP1. In addition, glucose-dependent nucleotide synthesis by the pentose phosphate pathway (PPP), along with sphingolipid (S1P) signaling, activates mTOR and allows translation of Tfap2c. YAP1, TEAD4, and TFAP2C interact to form a complex that controls TE-specific gene transcription. Glucose signaling has no role in ICM specification, and this process of developmental metabolism specifically controls TE cell fate.

Nitrogen Metabolism in Cancer and Immunity

As one of the fundamental requirements for cell growth and proliferation, nitrogen acquisition and utilization must be tightly regulated. Nitrogen can be generated from amino acids (AAs) and utilized for biosynthetic processes through transamination and deamination reactions. Importantly, limitations of nitrogen availability in cells can disrupt the synthesis of proteins, nucleic acids, and other important nitrogen-containing compounds. Rewiring cellular metabolism to support anabolic processes is a feature common to both cancer and proliferating immune cells. In this review, we discuss how nitrogen is utilized in biosynthetic pathways and highlight different metabolic and oncogenic programs that alter the flow of nitrogen to sustain biomass production and growth, an important emerging feature of cancer and immune cell proliferation.

Bioinformatics and computational approaches for analyzing patient-derived disease models in cancer research

Patient-derived organoids (PDO) and patient-derived xenografts (PDX) continue to emerge as important preclinical platforms for investigations into the molecular landscape of cancer. While the advantages and disadvantage of these models have been described in detail, this review focuses in particular on the bioinformatics and state-of-the art techniques that accompany preclinical model development. We discuss the strength and limitations of currently used technologies, particularly 'omics profiling and bioinformatics analyses, in addressing the 'efficacy' of preclinical models, both for tumour characterization as well as their use in identifying potential therapeutics. We select pancreatic ductal adenocarcinoma (PDAC) as a case study to highlight the state of the art of the field, and address new avenues for improved bioinformatics characterization of preclinical models.

Deep Learning Based Drug Metabolites Prediction

Drug metabolism research plays a key role in the discovery and development of drugs. Based on the discovery of drug metabolites, new chemical entities can be identified and potential safety hazards caused by reactive or toxic metabolites can be minimized. Nowadays, computational methods are usually complementary tools for experiments. However, current metabolites prediction methods tend to have high false positive rates with low accuracy and are usually only used for specific enzyme systems. In order to overcome this difficulty, a method was developed in this paper by first establishing a database with broad coverage of SMARTS-coded metabolic reaction rule, and then extracting the molecular fingerprints of compounds to construct a classification model based on deep learning algorithms. The metabolic reaction rule database we built can supplement chemically reasonable negative reaction examples. Based on deep learning algorithms, the model could determine which reaction types are more likely to occur than the others. In the test set, our method can achieve the accuracy of 70% (Top-10), which is significantly higher than that of random guess and the rule-based method SyGMa. The results demonstrated that our method has a certain predictive ability and application value.

Metabolomics studies in gastrointestinal cancer: a systematic review

Introduction: This systemic review provides an overview of metabolic perturbations and possible mechanisms in gastrointestinal cancer. The authors discuss emerging challenges of technical and clinical applications.Areas covered: In this systemic review, the authors summarized the currently available results of metabolomic biomarkers linked to GI cancer, and discussed the altered metabolism pathways including carbohydrate metabolism, amino acid metabolism, lipids, and nucleotide metabolism and other metabolisms. Furthermore, future efforts need to adhere to normalize analysis procedures, validate with the larger cohort and utilize multiple-omics technologies. The search was conducted in PubMed with the following search terms (biomarker, gastrointestinal cancer, colorectal cancer, and esophageal cancer) from 2013 to 2019.Expert opinion: This systemic review summarized the currently available results of metabolomic biomarkers linked to gastrointestinal cancer, and discussed the altered metabolism pathways. The authors believe that metabolomics will benefit deeper understandings of the pathogenic mechanism, discovery of biomarkers and aid the search for drug targets as we move toward the era of personalized medicine. Personalized medication for tumors can improve the curative effect, avoid side effects and medical resource waste. As a promisingtool, metabolomics that targets the entire cancer-specific metabolite network should be applied more widely in cancer research.

A systematic flux analysis approach to identify metabolic vulnerabilities in human breast cancer cell lines

Background

Increased flux through both glycolytic and oxidative metabolic pathways is a hallmark of breast cancer cells and is critical for their growth and survival. As such, targeting this metabolic reprograming has received much attention as a potential treatment approach. However, the heterogeneity of breast cancer cell metabolism, even within classifications, suggests a necessity for an individualised approach to treatment in breast cancer patients.

Methods

The metabolic phenotypes of a diverse panel of human breast cancer cell lines representing the major breast cancer classifications were assessed using real-time metabolic flux analysis. Flux linked to ATP production, pathway reserve capacities and specific macromolecule oxidation rates were quantified. Suspected metabolic vulnerabilities were targeted with specific pathway inhibitors, and relative cell viability was assessed using the crystal violet assay. Measures of AMPK and mTORC1 activity were analysed through immunoblotting.

Results

Breast cancer cells displayed heterogeneous energy requirements and utilisation of non-oxidative and oxidative energy-producing pathways. Quantification of basal glycolytic and oxidative reserve capacities identified cell lines that were highly dependent on individual pathways, while assessment of substrate oxidation relative to total oxidative capacity revealed cell lines that were highly dependent on individual macromolecules. Based on these findings, mild mitochondrial inhibition in ESH-172 cells, including with the anti-diabetic drug metformin, and mild glycolytic inhibition in Hs578T cells reduced relative viability, which did not occur in non-transformed MCF10a cells. The effects on viability were associated with AMPK activation and inhibition of mTORC1 signalling. Hs578T were also found to be highly dependent on glutamine oxidation and inhibition of this process also impacted viability.

Conclusions

Together, these data highlight that systematic flux analysis in breast cancer cells can identify targetable metabolic vulnerabilities, despite heterogeneity in metabolic profiles between individual cancer cell lines.

Glycolytic suppression dramatically changes the intracellular metabolic profile of multiple cancer cell lines in a mitochondrial metabolism-dependent manner

Most cancer cells rely on glycolysis to generate ATP, even when oxygen is available. However, merely inhibiting the glycolysis is insufficient for the eradication of cancer cells. One main reason for this is that cancer cells have the potential to adapt their metabolism to their environmental conditions. In this study, we investigated how cancer cells modify their intracellular metabolism when glycolysis is suppressed, using PANC-1 pancreatic cancer cells and two other solid tumor cell lines, A549 and HeLa. Our study revealed that glycolytically suppressed cells upregulated mitochondrial function and relied on oxidative phosphorylation (OXPHOS) to obtain the ATP necessary for their survival. Dynamic changes in intracellular metabolic profiles were also observed, reflected by the reduced levels of TCA cycle intermediates and elevated levels of most amino acids. Glutamine and glutamate were important for this metabolic reprogramming, as these were largely consumed by influx into the TCA cycle when the glycolytic pathway was suppressed. During the reprogramming process, activated autophagy was involved in modulating mitochondrial function. We conclude that upon glycolytic suppression in multiple types of tumor cells, intracellular energy metabolism is reprogrammed toward mitochondrial OXPHOS in an autophagy-dependent manner to ensure cellular survival.

The role of pyruvate kinase M2 in anticancer therapeutic treatments

Cancer cells are characterized by a high glycolytic rate, which leads to energy regeneration and anabolic metabolism; a consequence of this is the abnormal expression of pyruvate kinase isoenzyme M2 (PKM2). Multiple studies have demonstrated that the expression levels of PKM2 are upregulated in numerous cancer types. Consequently, the mechanism of action of certain anticancer drugs is to downregulate PKM2 expression, indicating the significance of PKM2 in a chemotherapeutic setting. Furthermore, it has previously been highlighted that the downregulation of PKM2 expression, using either inhibitors or short interfering RNA, enhances the anticancer effect exerted by THP treatment on bladder cancer cells, both in vitro and in vivo. The present review summarizes the detailed mechanisms and therapeutic relevance of anticancer drugs that inhibit PKM2 expression. In addition, the relationship between PKM2 expression levels and drug resistance were explored. Finally, future directions, such as the targeting of PKM2 as a strategy to explore novel anticancer agents, were suggested. The current review explored and highlighted the important role of PKM2 in anticancer treatments.

Probing carbohydrate metabolism using hyperpolarized 13 C-labeled molecules

Glycolysis is a fundamental metabolic process in all organisms. Anomalies in glucose metabolism are linked to various pathological conditions. In particular, elevated aerobic glycolysis is a characteristic feature of rapidly growing cells. Glycolysis and the closely related pentose phosphate pathway can be monitored in real time by hyperpolarized 13 C-labeled metabolic substrates such as 13 C-enriched, deuterated D-glucose derivatives, [2-13 C]-D-fructose, [2-13 C] dihydroxyacetone, [1-13 C]-D-glycerate, [1-13 C]-D-glucono-δ-lactone and [1-13 C] pyruvate in healthy and diseased tissues. Elevated glycolysis in tumors (the Warburg effect) was also successfully imaged using hyperpolarized [U-13 C6 , U-2 H7 ]-D-glucose, while the size of the preexisting lactate pool can be measured by 13 C MRS and/or MRI with hyperpolarized [1-13 C]pyruvate. This review summarizes the application of various hyperpolarized 13 C-labeled metabolites to the real-time monitoring of glycolysis and related metabolic processes in normal and diseased tissues.

The Multiple Roles and Therapeutic Potential of Molecular Chaperones in Prostate Cancer

Prostate cancer (PCa) is one of the most common cancer types in men worldwide. Heat shock proteins (HSPs) are molecular chaperones that are widely implicated in the pathogenesis, diagnosis, prognosis, and treatment of many cancers. The role of HSPs in PCa is complex and their expression has been linked to the progression and aggressiveness of the tumor. Prominent chaperones, including HSP90 and HSP70, are involved in the folding and trafficking of critical cancer-related proteins. Other members of HSPs, including HSP27 and HSP60, have been considered as promising biomarkers, similar to prostate-specific membrane antigen (PSMA), for PCa screening in order to evaluate and monitor the progression or recurrence of the disease. Moreover, expression level of chaperones like clusterin has been shown to correlate directly with the prostate tumor grade. Hence, targeting HSPs in PCa has been suggested as a promising strategy for cancer therapy. In the current review, we discuss the functions as well as the role of HSPs in PCa progression and further evaluate the approach of inhibiting HSPs as a cancer treatment strategy.

Molecular Mechanisms Underlying Cancer Preventive and Therapeutic Potential of Algal Polysaccharides

Background:

Algal polysaccharide and oligosaccharide derivatives have been shown to possess a variety of therapeutic potentials and drug delivery applications. Algal polysaccharides contain sulfated sugar monomers derived from seaweed including brown, red, and green microalgae. Here, in this review, the recent progress of algal polysaccharides’ therapeutic applications as anticancer agents, as well as underlying cellular and molecular mechanisms was investigated. Moreover, recent progress in the structural chemistry of important polysaccharides with anticancer activities were illustrated.

Methods:

Electronic databases including “Scopus”, “PubMed”, and “Cochrane library” were searched using the keywords “cancer”, or “tumor”, or “malignancy” in title/abstract, along with “algae”, or “algal” in the whole text until July 2018. Only English language papers were included.

Results:

The most common polysaccharides involved in cancer management were sulfated polysaccharides, Fucoidans, Carageenans, and Ulvan from different species of algae that have been recognized in vitro and in vivo. The underlying anticancer mechanisms of algal polysaccharides included induction of apoptosis, cell cycle arrest, modulation of transduction signaling pathways, suppression of migration and angiogenesis, as well as activation of immune responses and antioxidant system. VEGF/VEGFR2, TGFR/Smad/Snail, TLR4/ROS/ER, CXCL12/ CXCR4, TGFR/Smad7/Smurf2, PI3K/AKT/mTOR, PBK/TOPK, and β-catenin/Wnt are among the main cellular signaling pathways which have a key role in the preventive and therapeutic effects of algal polysaccharides against oncogenesis.

Conclusion:

Algal polysaccharides play a crucial role in the management of cancer and may be considered the next frontier in pharmaceutical research. Further well-designed clinical trials are mandatory to evaluate the efficacy and safety of algal polysaccharides in patients with cancer.

The roles of glucose metabolic reprogramming in chemo- and radio-resistance

Reprogramming of cancer metabolism is a newly recognized hallmark of malignancy. The aberrant glucose metabolism is associated with dramatically increased bioenergetics, biosynthetic, and redox demands, which is vital to maintain rapid cell proliferation, tumor progression, and resistance to chemotherapy and radiation. When the glucose metabolism of cancer is rewiring, the characters of cancer will also occur corresponding changes to regulate the chemo- and radio-resistance of cancer. The procedure is involved in the alteration of many activities, such as the aberrant DNA repairing, enhanced autophagy, oxygen-deficient environment, and increasing exosomes secretions, etc. Targeting altered metabolic pathways related with the glucose metabolism has become a promising anti-cancer strategy. This review summarizes recent progress in our understanding of glucose metabolism in chemo- and radio-resistance malignancy, and highlights potential molecular targets and their inhibitors for cancer treatment.

Synthesis of novel 7-azaindole derivatives containing pyridin-3-ylmethyl dithiocarbamate moiety as potent PKM2 activators and PKM2 nucleus translocation inhibitors

Multiple lines of evidence have indicated that pyruvate kinase M2 (PKM2) is upregulated in most cancer cells and it is increasingly recognized as a potential therapeutic target in oncology. In a continuation of our discovery of lead compound 5 and SAR study, the 7-azaindole moiety in compound 5 was systematically optimized. The results showed that compound 6f, which has a difluoroethyl substitution on the 7-azaindole ring, exhibited high PKM2 activation potency and anti-proliferation activities on A375 cell lines. In a xenograft mouse model, oral administration of compound 6f led to significant tumor regression without obvious toxicity. Further mechanistic studies revealed that 6f could influence the translocation of PKM2 into nucleus, as well as induction of apoptosis and autophagy of A375 cells. More importantly, compound 6f significantly inhibited migration of A375 cells in a concentration-dependent manner. Collectively, 6f may serve as a lead compound in the development of potent PKM2 activators for cancer therapy.

Proposing a validation scheme for 13C metabolite tracer studies in high-resolution mass spectrometry

¹³C metabolite tracer and metabolic flux analyses require upfront experimental planning and validation tools. Here, we present a validation scheme including a comparison of different LC methods that allow for customization of analytical strategies for tracer studies with regard to the targeted metabolites. As the measurement of significant changes in labeling patterns depends on the spectral accuracy, we investigate this aspect comprehensively for high-resolution orbitrap mass spectrometry combined with reversed-phase chromatography, hydrophilic interaction liquid chromatography, or anion-exchange chromatography. Moreover, we propose a quality control protocol based on (1) a metabolite containing selenium to assess the instrument performance and on (2) in vivo synthesized isotopically enriched Pichia pastoris to validate the accuracy of carbon isotopologue distributions (CIDs), in this case considering each isotopologue of a targeted metabolite panel. Finally, validation involved a thorough assessment of procedural blanks and matrix interferences. We compared the analytical figures of merit regarding CID determination for over 40 metabolites between the three methods. Excellent precisions of less than 1% and trueness bias as small as 0.01-1% were found for the majority of compounds, whereas the CID determination of a small fraction was affected by contaminants. For most compounds, changes of labeling pattern as low as 1% could be measured. Graphical abstract.

Spheroid-Induced Epithelial-Mesenchymal Transition Provokes Global Alterations of Breast Cancer Lipidome: A Multi-Layered Omics Analysis

Metabolic rewiring has been recognized as an important feature to the progression of cancer. However, the essential components and functions of lipid metabolic networks in breast cancer progression are not fully understood. In this study, we investigated the roles of altered lipid metabolism in the malignant phenotype of breast cancer. Using a spheroid-induced epithelial-mesenchymal transition (EMT) model, we conducted multi-layered lipidomic and transcriptomic analysis to comprehensively describe the rewiring of the breast cancer lipidome during the malignant transformation. A tremendous homeostatic disturbance of various complex lipid species including ceramide, sphingomyelin, ether-linked phosphatidylcholines, and ether-linked phosphatidylethanolamine was found in the mesenchymal state of cancer cells. Noticeably, polyunsaturated fatty acids composition in spheroid cells was significantly decreased, accordingly with the gene expression patterns observed in the transcriptomic analysis of associated regulators. For instance, the up-regulation of SCD, ACOX3, and FADS1 and the down-regulation of PTPLB, PECR, and ELOVL2 were found among other lipid metabolic regulators. Significantly, the ratio of C22:6n3 (docosahexaenoic acid, DHA) to C22:5n3 was dramatically reduced in spheroid cells analogously to the down-regulation of ELOVL2. Following mechanistic study confirmed the up-regulation of SCD and down-regulation of PTPLB, PECR, ELOVL2, and ELOVL3 in the spheroid cells. Furthermore, the depletion of ELOVL2 induced metastatic characteristics in breast cancer cells via the SREBPs axis. A subsequent large-scale analysis using 51 breast cancer cell lines demonstrated the reduced expression of ELOVL2 in basal-like phenotypes. Breast cancer patients with low ELOVL2 expression exhibited poor prognoses (HR = 0.76, CI = 0.67–0.86). Collectively, ELOVL2 expression is associated with the malignant phenotypes and appear to be a novel prognostic biomarker in breast cancer. In conclusion, the present study demonstrates that there is a global alteration of the lipid composition during EMT and suggests the down-regulation of ELOVL2 induces lipid metabolism reprogramming in breast cancer and contributes to their malignant phenotypes.

In silico approaches and tools for the prediction of drug metabolism and fate: A review

The fate of administered drugs is largely influenced by their metabolism. For example, endogenous enzyme-catalyzed conversion of drugs may result in therapeutic inactivation or activation or may transform the drugs into toxic chemical compounds. This highlights the importance of drug metabolism in drug discovery and development, and accounts for the wide variety of experimental technologies that provide insights into the fate of drugs. In view of the high cost of traditional drug development, a number of computational approaches have been developed for predicting the metabolic fate of drug candidates, allowing for screening of large numbers of chemical compounds and then identifying a small number of promising candidates. In this review, we introduce in silico approaches and tools that have been developed to predict drug metabolism and fate, and assess their potential to facilitate the virtual discovery of promising drug candidates. We also provide a brief description of various recent models for predicting different aspects of enzyme-drug reactions and provide a list of recent in silico tools used for drug metabolism prediction.

Spermidine/spermine N1-acetyltransferase-1 as a diagnostic biomarker in human cancer

Aim:

SSAT-1 is an enzyme that plays a critical role in cell growth. Amantadine, a FDA-approved antiviral drug, is a substrate for SSAT-1. The utility of amantadine as an agent to demonstrate elevated SSAT-1 activity linked to cancer was conducted.

Results:

High levels of SSAT-1 expression were measured in tumor human cell lines, and in breast, prostate and lung tumor tissue. An increase in the urinary levels of acetylated amantadine in cancer patients was observed.

Conclusion:

Increases in SSAT-1 contents in tumor tissue could be of value in targeting cancers with high SSAT-1 expression for confirmation/quantification. The high levels of acetylated amantadine could be used as a simple and useful screening test for the presence of cancer.

In response to cancer, cells tend to overproduce specific enzymes as a self-defense mechanism. By using a safe and reliable method to capture and measure the excess enzyme spermidine/spermine N1-acetyltransferase-1, the presence of cancer can be established. This study describes a novel approach of detecting and screening cancer noninvasively in the urine of cancer patients using a safe and approved drug called amantadine that acts as a smart-tracking agent. Higher levels of the acetylated form of amantadine are detectable in the urine of cancer patients, which may serve as a detection tool. In addition, increases in the amount of spermidine/spermine N1-acetyltransferase-1 in tumor tissue may provide a tool for determining the presence of cancer during pathology assessment.

Microenvironmental regulation of cancer cell metabolism: implications for experimental design and translational studies

Cancers have an altered metabolism, and there is interest in understanding precisely how oncogenic transformation alters cellular metabolism and how these metabolic alterations can translate into therapeutic opportunities. Researchers are developing increasingly powerful experimental techniques to study cellular metabolism, and these techniques have allowed for the analysis of cancer cell metabolism, both in tumors and in ex vivo cancer models. These analyses show that, while factors intrinsic to cancer cells such as oncogenic mutations, alter cellular metabolism, cell-extrinsic microenvironmental factors also substantially contribute to the metabolic phenotype of cancer cells. These findings highlight that microenvironmental factors within the tumor, such as nutrient availability, physical properties of the extracellular matrix, and interactions with stromal cells, can influence the metabolic phenotype of cancer cells and might ultimately dictate the response to metabolically targeted therapies. In an effort to better understand and target cancer metabolism, this Review focuses on the experimental evidence that microenvironmental factors regulate tumor metabolism, and on the implications of these findings for choosing appropriate model systems and experimental approaches.