Exometabolom analysis of breast cancer cell lines: Metabolic signature

Accurate Quantification of Ten Methylated Purine Nucleosides by Highly Sensitive and Stable Isotope-Diluted UHPLC-MS/MS

The dynamic landscape of cellular nucleotides/nucleosides associated with RNA metabolism, particularly in diseases like cancer, has spurred intensive interest. Here, we report a robust stable isotope-diluted UHPLC-ESI-MS/MS method for accurate quantification of 12 purine ribonucleosides, including 10 methylated purine nucleosides. By the use of thermally decomposable ammonium bicarbonate (NH4HCO3) as a mobile phase additive for UHPLC-MS/MS detection, the ESI-MS/MS signal responses of these target compounds were enhanced by 1.7-24.5 folds. Noteworthily, three methylated guanosine isomers (m1G, m2G, and m7G) and two methylated adenosine isomers (m1A and m6A) that are indistinguishable directly by mass spectrometry were well resolved with optimal UHPLC separation. Combined with methanol extraction and solid-phase extraction (SPE) pretreatment, the method quantified intracellular concentrations of three modified nucleosides (Gm, m1G, and m2G), which would otherwise be undetectable because of significant suppression of their signals by the interfering cellular matrix. Nine purine nucleosides were simultaneously quantified in 293T cells, and their concentrations ranged by 4 orders of magnitude. Overall, the method presents high recovery rates over 90% for endogenous modified purine nucleosides in cultured cells, along with good precision, linearity, and LOD ranging from 0.30 fmol to 0.37 pmol per 5 × 105 cells. The developed UHPLC-MS/MS method holds potential for screening purine nucleosides as diagnostic and prognostic biomarkers and for quantifying purine epigenetic nucleosides post-cell metabolome analysis, thereby providing a valuable analytical tool for intracellular nucleoside quantification in future clinical research.

Serum Metabolic Fingerprints Characterize Systemic Lupus Erythematosus

Metabolic fingerprints in serum characterize diverse diseases for diagnostics and biomarker discovery. The identification of systemic lupus erythematosus (SLE) by serum metabolic fingerprints (SMFs) will facilitate precision medicine in SLE in an early and designed manner. Here, a discovery cohort of 731 individuals including 357 SLE patients and 374 healthy controls (HCs), and a validation cohort of 184 individuals (SLE/HC, 91/93) are constructed. Each SMF is directly recorded by nano-assisted laser desorption/ionization mass spectrometry (LDI MS) within 1 minute using 1 µL of native serum, which contains 908 mass to charge features. Sparse learning of SMFs achieves the SLE identification with sensitivity/specificity and area-under-the-curve (AUC) up to 86.0%/92.0% and 0.950 for the discovery cohort. For the independent validation cohort, it exhibits no performance loss by affording the sensitivity/specificity and AUC of 89.0%/100.0% and 0.992. Notably, a metabolic biomarker panel is screened out from the SMFs, demonstrating the unique metabolic pattern of SLE patients different from both HCs and rheumatoid arthritis patients. In conclusion, SMFs characterize SLE by revealing its unique metabolic pattern. Different regulation of small molecule metabolites contributes to the precise diagnosis of autoimmune disease and further exploration of the pathogenic mechanisms.

Analysis of the microbial diversity in takin (Budorcas taxicolor) feces

Introduction

The intestinal tract of animals is a complex and dynamic microecosystem that is inextricably linked to the health of the host organism. Takin (Budorcas taxicolor) is a threatened species, and its gut microbiome is poorly understood. Therefore, this study aimed to analyze the microbial community structure and potential pathogens of takin.

Methods

Takin fecal samples were collected from five sites in a nature reserve to ensure the uniformity of sample collection, determine the effects of different geographical locations on gut microbes, and analyze the differences in microbial communities between sites. Subsequently, high-throughput 16S rDNA gene sequencing was performed to analyze the microbial diversity and potential pathogens in the gut; the findings were verified by isolating and culturing bacteria and metagenomic sequencing.

Results and discussion

The takin gut microflora consisted mainly of four phyla: Firmicutes (69.72%), Bacteroidota (13.55%), Proteobacteria (9.02%), and Verrucomicrobiota (3.77%), representing 96.07% of all microorganisms. The main genera were UCG-005 (20.25%), UCG-010_unclassified (12.35%), Firmicus_unclassified (4.03%), and Rumino coccsea_unclassified (3.49%), while the main species were assigned to Bacteria_unclassified. Potential pathogens were also detected, which could be used as a reference for the protection of takin. Pseudomonas presented the highest abundance at Shuichiping and may represent the main pathogen responsible for the death of takin at the site. This study provides an important reference for investigating the composition of the bacterial community in the intestine of takin.

Integrated Metabolomic and Transcriptomic Analysis of Modified Nucleosides for Biomarker Discovery in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for ~75% of kidney cancers. The biallelic inactivation of the von Hippel-Lindau tumor suppressor gene (VHL) is the truncal driver mutation of most cases of ccRCC. Cancer cells are metabolically reprogrammed and excrete modified nucleosides in larger amounts due to their increased RNA turnover. Modified nucleosides occur in RNAs and cannot be recycled by salvage pathways. Their potential as biomarkers has been demonstrated for breast or pancreatic cancer. To assess their suitability as biomarkers in ccRCC, we used an established murine ccRCC model, harboring Vhl, Trp53 and Rb1 (VPR) knockouts. Cell culture media of this ccRCC model and primary murine proximal tubular epithelial cells (PECs) were investigated by HPLC coupled to triple-quadrupole mass spectrometry using multiple-reaction monitoring. VPR cell lines were significantly distinguishable from PEC cell lines and excreted higher amounts of modified nucleosides such as pseudouridine, 5-methylcytidine or 2'-O-methylcytidine. The method's reliability was confirmed in serum-starved VPR cells. RNA-sequencing revealed the upregulation of specific enzymes responsible for the formation of those modified nucleosides in the ccRCC model. These enzymes included Nsun2, Nsun5, Pus1, Pus7, Naf1 and Fbl. In this study, we identified potential biomarkers for ccRCC for validation in clinical trials.

A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology

Since genes do not function individually, the gene module is considered an important tool for interpreting gene expression profiles. In order to consider both functional similarity and expression similarity in module identification, GMIGAGO, a functional Gene Module Identification algorithm based on Genetic Algorithm and Gene Ontology, was proposed in this work. GMIGAGO is an overlapping gene module identification algorithm, which mainly includes two stages: In the first stage (initial identification of gene modules), Improved Partitioning Around Medoids Based on Genetic Algorithm (PAM-GA) is used for the initial clustering on gene expression profiling, and traditional gene co-expression modules can be obtained. Only similarity of expression levels is considered at this stage. In the second stage (optimization of functional similarity within gene modules), Genetic Algorithm for Functional Similarity Optimization (FSO-GA) is used to optimize gene modules based on gene ontology, and functional similarity within gene modules can be improved. Without loss of generality, we compared GMIGAGO with state-of-the-art gene module identification methods on six gene expression datasets, and GMIGAGO identified the gene modules with the highest functional similarity (much higher than state-of-the-art algorithms). GMIGAGO was applied in BRCA, THCA, HNSC, COVID-19, Stem, and Radiation datasets, and it identified some interesting modules which performed important biological functions. The hub genes in these modules could be used as potential targets for diseases or radiation protection. In summary, GMIGAGO has excellent performance in mining molecular mechanisms, and it can also identify potential biomarkers for individual precision therapy.

Ultrasensitive Simultaneous Detection of Multiple Rare Modified Nucleosides as Promising Biomarkers in Low-Put Breast Cancer DNA Samples for Clinical Multi-Dimensional Diagnosis

Early cancer diagnosis is essential for successful treatment and prognosis, and modified nucleosides have attracted widespread attention as a promising group of cancer biomarkers. However, analyzing these modified nucleosides with an extremely low abundance is a great challenge, especially analyzing multiple modified nucleosides with a different abundance simultaneously. In this work, an ultrasensitive quantification method based on chemical labeling, coupled with LC-MS/MS analysis, was established for the simultaneous quantification of 5hmdC, 5fdC, 5hmdU and 5fdU. Additionally, the contents of 5mdC and canonical nucleosides could be obtained at the same time. Upon derivatization, the detection sensitivities of 5hmdC, 5fdC, 5hmdU and 5fdU were dramatically enhanced by several hundred times. The established method was further applied to the simultaneous detection of nine nucleosides with different abundances in about 2 μg genomic DNA of breast tissues from 20 breast cancer patients. The DNA consumption was less than other overall reported quantification methods, thereby providing an opportunity to monitor rare, modified nucleosides in precious samples and biology processes that could not be investigated before. The contents of 5hmdC, 5hmdU and 5fdU in tumor tissues and normal tissues adjacent to the tumor were significantly changed, indicating that these three modified nucleosides may play certain roles in the formation and development of tumors and be potential cancer biomarkers. While the detection rates of 5hmdC, 5hmdU and 5fdU alone as a biomarker for breast cancer samples were 95%, 75% and 85%, respectively, by detecting these three cancer biomarkers simultaneously, two of the three were 100% consistent with the overall trend. Therefore, simultaneous detection of multiple cancer biomarkers in clinical samples greatly improved the accuracy of cancer diagnosis, indicating that our method has great application potential in clinical multidimensional diagnosis.

Role of N6-methyladenosine RNA modification in the imbalanced inflammatory homeostasis of arsenic-induced skin lesions

This study aimed to investigate the effect of N6-methyladenosine (m⁶ A) modification in modulating inflammatory homeostasis of arsenic (As)-induced skin lesions. Our bioinformatic analysis revealed abnormal expression of m⁶ A RNA methylation regulators and cytokines in the arsenic-exposed population. In human keratinocytes, arsenite increased the levels of m⁶ A methylation by upregulating the RNA methyltransferase like 3 (METTL3), mediating the disordered secretion of indicators that reflect inflammatory homeostasis (IL-6, IL-17, and IL-10). The indicators reflecting arsenic-induced skin lesions (Krt1 and Krt10) were also significantly elevated, which contributed to the occurrence of skin lesions. Our results also confirmed the association between METTL3 with inflammatory homeostasis and arsenic-induced skin lesions using arsenic-exposed human skin samples. In the arsenic-exposed group, the upregulation of METTL3 exacerbated the increase in cytokine levels (IL-6, IL-17, and IL-10), which was associated with the upregulation of keratins (Krt1 and Krt10). In addition, significant correlations among these factors corroborate the theoretical links. Finally, alteration of the m⁶ A levels via knockdown or enhancement of the METTL3 protein could antagonize or aggravate arsenite-induced imbalanced inflammatory homeostasis and human keratinocyte damage in HaCaT cells. Collectively, our study reveals some evidence that regulation of m⁶ A modification plays an important role in arsenic-induced skin lesions, which provide a new perspective on the mechanism of arsenite-induced imbalanced inflammatory homeostasis in the field of RNA epigenetics.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer

Purpose

Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy.

Methods

We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ^® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch^™ assay.

Results

We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only.

Conclusion

We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

Deciphering nucleotide modification-induced structure and stability changes

Nucleotide modification in RNA controls a bevy of biological processes, including RNA degradation, gene expression, and gene editing. In turn, misregulation of modified nucleotides is associated with a host of chronic diseases and disorders. However, the molecular mechanisms driving these processes remain poorly understood. To partially address this knowledge gap, we used alchemical and temperature replica exchange molecular dynamics (TREMD) simulations on an RNA duplex and an analogous hairpin to probe the structural effects of modified and/or mutant nucleotides. The simulations successfully predict the modification/mutation-induced relative free energy change for complementary duplex formation, and structural analyses highlight mechanisms driving stability changes. Furthermore, TREMD simulations for a hairpin-forming RNA with and without modification provide reliable estimations of the energy landscape. Illuminating the impact of methylated and/or mutated nucleotides on the structure-function relationship and the folding energy landscape, the simulations provide insights into modification-induced alterations to the folding mechanics of the hairpin. The results here may be biologically significant as hairpins are widespread structure motifs that play critical roles in gene expression and regulation. Specifically, the tetraloop of the probed hairpin is phylogenetically abundant, and the stem mirrors a miRNA seed region whose modification has been implicated in epilepsy pathogenesis.

Pseudouridine as a novel biomarker in prostate cancer

Epitranscriptomic analysis has recently led to the profiling of modified nucleosides in cancer cell biological matrices, helping to elucidate their functional roles in cancer and reigniting interest in exploring their use as potential markers of cancer development and progression. Pseudouridine, one of the most well-known and the most abundant of the RNA nucleotide modifications, is the C5-glycoside isomer of uridine and its distinctive physiochemical properties allows it to perform many essential functions. Pseudouridine functionally (a) confers rigidity to local RNA structure by enhancing RNA stacking, engaging in a cooperative effect on neighboring nucleosides that overall contributes to RNA stabilization (b) refines the structure of tRNAs, which influences their decoding activity (c) facilitates the accuracy of decoding and proofreading during translation and efficiency of peptide bond formation, thus collectively improving the fidelity of protein biosynthesis and (e) dynamically regulates mRNA coding and translation. Biochemical synthesis of pseudouridine is carried out by pseudouridine synthases. In this review we discuss the evidence supporting an association between elevated pseudouridine levels with the incidence and progression of human prostate cancer and the translational significance of the value of this modified nucleotide as a novel biomarker in prostate cancer progression to advanced disease.

Nicotinamide N-methyltransferase decreases 5-fluorouracil sensitivity in human esophageal squamous cell carcinoma through metabolic reprogramming and promoting the Warburg effect

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with poor prognosis. And different individuals respond to the same drug differently. Increasing evidence has confirmed that metabolism reprogramming was involved in the drug sensitivity of tumor cells. However, the potential molecular mechanism of 5-fluorouracil (5-FU) sensitivity remains to be elucidated in ESCC cells. In this study, we found that the 5-FU sensitivity of TE1 cells was lower than that of EC1 and Eca109 cells. Gas chromatography-mass spectrometry analysis results showed that nicotinate and nicotinamide metabolism and tricarboxylic acid cycle were significantly different in these three cell lines. Nicotinamide N-methyltransferase (NNMT), a key enzyme of nicotinate and nicotinamide metabolism, was significantly higher expressed in TE1 cells than that in EC1 and Eca109 cells. Therefore, the function of NNMT on 5-FU sensitivity was analyzed in vitro and in vivo. NNMT downregulation significantly increased 5-FU sensitivity in TE1 cells. Meanwhile, the glucose consumption and lactate production were decreased, and the expression of glycolysis-related enzymes hexokinase 2, lactate dehydrogenase A, and phosphoglycerate mutase 1 were downregulated in NNMT knockdown TE1 cells. Besides, overexpression of NNMT in EC1 and Eca109 cells caused the opposite effects. Moreover, when glycolysis was inhibited by 2-deoxyglucose, the roles of NNMT on 5-FU sensitivity was weakened. In vivo experiments showed that NNMT knockdown significantly increased the sensitivity of xenografts to 5-FU and suppressed the Warburg effect. Overall, these results demonstrated that NNMT decreases 5-FU sensitivity in human ESCC cells through promoting the Warburg effect, suggesting that NNMT may contribute to predict the treatment effects of the clinical chemotherapy in ESCC.

Application of metabolomics in the diagnosis of breast cancer: a systematic review

Breast cancer (BC) remains the most frequent type of cancer in females worldwide. However, the pathogenesis of BC is still under the cloud, along with the huge challenge of early diagnosis, which is widely acknowledged as the key to a successful therapy. Metabolomics, a newborn innovative technique in recent years, has demonstrated great potential in cancer-related researches. The aim of this review is to look back on clinical and cellular metabolomic studies in the diagnosis of BC over the past decade, and provide a systematic summary of metabolic biomarkers and pathways related to BC diagnosis.

Targeted metabolomics: Liquid chromatography coupled to mass spectrometry method development and validation for the identification and quantitation of modified nucleosides as putative cancer biomarkers

A notable change in the body fluids nucleosides of cancer patients has been actively highlighted in searches for new biomarkers to early cancer detection. For this reason, improvements of bioanalytical methods for these compounds focused on a noninvasive sampling trend are of great importance. Therefore, this work aimed firstly to develop efficient methods for nucleoside analysis in urine and serum by liquid chromatography-tandem mass spectrometry (LC-MS/MS), applying different strategies to quantify nine nucleosides, and further identify other untargeted nucleosides. Sample preparation was based on protein precipitation and affinity-solid phase extraction (SPE), whereas quantification was performed using a triple quadrupole (QqQ) mass analyzer operating in the selected reaction monitoring (SRM) mode. Surrogates matrices were proposed as an alternative to standard addition calibration. Specifically, to quantitate creatinine, a simple LC-MS/MS method was validated and used for normalization of urinary metabolites quantitation. To identify the other nucleosides, LC methods using different MS scans modes were evaluated on a quadrupole-time of flight (Q-TOF) or a hybrid triple quadrupole linear ion trap (Q-trap). Validation was performed for nucleosides quantification using the synthetic matrices of urine and serum, and selectivity, linearity, accuracy, reproducibility, matrix effect, LOD's and LOQ's were accessed, providing trustworthy results for bioanalysis purposes. Both LC-Q-Trap/MS and LC-Q-TOF/MS methods showed proper sensitivity for structural characterization on assays with urine and serum samples from healthy volunteers and could also be used in the identification of untargeted nucleosides. The investigated approaches delivered in-depth results and seem promising for future applications on urine and serum samples analyses aiming to validate nucleosides as cancer biomarkers.

Human acireductone dioxygenase (HsARD), cancer and human health: Black hat, white hat or gray?

Multiple factors involving the methionine salvage pathway (MSP) and polyamine biosynthesis have been found to be involved in cancer cell proliferation, migration, invasion and metastasis. This review summarizes the relationships of the MSP enzyme acireductone dioxygenase (ARD), the ADI1 gene encoding ARD and other gene products (ADI1GP) with carcinomas and carcinogenesis. ARD exhibits structural and functional differences depending upon the metal bound in the active site. In the penultimate step of the MSP, the Fe²⁺ bound form of ARD catalyzes the on-pathway oxidation of acireductone leading to methionine, whereas Ni²⁺ bound ARD catalyzes an off-pathway reaction producing methylthiopropionate and carbon monoxide, a biological signaling molecule and anti-apoptotic. The relationship between ADI1GP, MSP and polyamine synthesis are discussed, along with possible role(s) of metal in modulating the cellular behavior of ADI1GP and its interactions with other cellular components.

Structural and biochemical characterization of Rv0187, an O-methyltransferase from Mycobacterium tuberculosis

Catechol O-methyltransferase (COMT) is widely distributed in nature and installs a methyl group onto one of the vicinal hydroxyl groups of a catechol derivative. Enzymes belonging to this family require two cofactors for methyl transfer: S-adenosyl-l-methionine as a methyl donor and a divalent metal cation for regiospecific binding and activation of a substrate. We have determined two high-resolution crystal structures of Rv0187, one of three COMT paralogs from Mycobacterium tuberculosis, in the presence and absence of cofactors. The cofactor-bound structure clearly locates strontium ions and S-adenosyl-l-homocysteine in the active site, and together with the complementary structure of the ligand-free form, it suggests conformational dynamics induced by the binding of cofactors. Examination of in vitro activities revealed promiscuous substrate specificity and relaxed regioselectivity against various catechol-like compounds. Unexpectedly, mutation of the proposed catalytic lysine residue did not abolish activity but altered the overall landscape of regiospecific methylation.

Unraveling altered RNA metabolism in pancreatic cancer cells by liquid-chromatography coupling to ion mobility mass spectrometry

Ion mobility coupling to mass spectrometry facilitates enhanced identification certitude. Further coupling to liquid chromatography results in multi-dimensional analytical methods, especially suitable for complex matrices with structurally similar compounds. Modified nucleosides represent a large group of very similar members linked to aberrant proliferation. Besides basal production under physiological conditions, they are increasingly excreted by transformed cells and subsequently discussed as putative biomarkers for various cancer types. Here, we report a method for modified nucleosides covering 37 species. We determined collisional cross-sections with high reproducibility from pure analytical standards. For sample purification, we applied an optimized phenylboronic acid solid-phase extraction on media obtained from four different pancreatic cancer cell lines. Our analysis could discriminate different subtypes of pancreatic cancer cell lines. Importantly, they could clearly be separated from a pancreatic control cell line as well as blank medium. m1A, m27G, and Asm were the most important features discriminating cancer cell lines derived from well-differentiated and poorly differentiated cancers. Eventually, we suggest the analytical method reported here for future tumor-marker identification studies. Graphical abstract.

Activation of polymeric nanoparticle intracellular targeting overcomes chemodrug resistance in human primary patient breast cancer cells

Background

Successfully overcoming obstacles due to anticancer drugs’ toxicity and achieving effective treatment using unique nanotechnology is challenging. The complex nature of breast tumors is mainly due to chemoresistance. Successful docetaxel (DTX) delivery by nanoparticles (NPs) through inhibition of multidrug resistance (MDR) can be a bridge to enhance intracellular dose and achieve higher cytotoxicity for cancer cells.

Purpose

This study tested primary patient breast cancer cells in vitro with traditional free DTX in comparison with polymeric nanocarriers based on poly lactic co-glycolic acid (PLGA) NPs.

Materials and methods

Establishment of primary cell line from breast malignant tumor depends on enzymatic digestion. Designed DTX-loaded PLGA NPs were prepared with a solvent evaporation method; one design was supported by the use of folic acid (FA) conjugated to PLGA. The physical properties of NPs were characterized as size, charge potential, surface morphology, DTX loading, and encapsulation efficiency. In vitro cellular uptake of fluorescent NPs was examined visually with confocal fluorescence microscopy and quantitatively with flow cytometry. In vitro cytotoxicity of all DTX designed NPs against cancer cells was investigated with MTT assay. RT-PCR measurements were done to examine the expression of chemoresistant and apoptotic genes of the tested DTX NPs.

Results

Cellular uptake of DTX was time dependent and reached the maximum after loading on PLGA NPs and with FA incorporation, which activated the endocytosis mechanism. MTT assay revealed significant higher cytotoxicity of DTX-loaded FA/PLGA NPs with higher reduction of IC50 (8.29 nM). In addition, PLGA NPs, especially FA incorporated, limited DTX efflux by reducing expression of ABCG2 (3.2-fold) and MDR1 (2.86-fold), which were highly activated by free DTX. DTX-loaded FA/PLGA NPs showed the highest apoptotic effect through the activation of Caspase-9, Caspase-3, and TP53 genes by 2.8-, 1.6-, and 1.86-fold, respectively.

Conclusion

FA/PLGA NPs could be a hopeful drug delivery system for DTX in breast cancer treatment.

Metabolic Phenotyping of Anks3 Depletion in mIMCD-3 cells - a Putative Nephronophthisis Candidate

Nephronophthisis (NPH) is an autosomal recessive form of cystic kidney disease and the leading cause of hereditary kidney failure in children and young adults. Like other NPH proteins, the NPHP16/Anks6-interacting protein Anks3 has been identified to cause laterality defects in humans. However, the cellular functions of Anks3 remain enigmatic. We investigated the metabolic impact of Anks3 depletion in cultured murine inner medullary collecting duct cells via GC-MS profiling and LC-MS/MS analysis. Combined metabolomics successfully identified 155 metabolites; 48 metabolites were identified to be significantly altered by decreasing Anks3 levels. Especially, amino acid and purine/pyrimidine metabolism were affected by loss of Anks3. Branched-chain amino acids were identified to be significantly downregulated suggesting disrupted nutrient signalling. Tryptophan and 1-ribosyl-imidazolenicotinamide accumulated whereas NAD⁺ and NADP⁺ concentrations were diminished indicating disturbances within the tryptophan-niacin pathway. Most strikingly, nucleosides were reduced upon Anks3 depletion, while 5-methyluridine and 6-methyladenosine accumulated over time. Hence, elevated PARP1 and cleaved PARP1 levels could be detected. Furthermore, living cell number and viability was significantly declined. In combination, these results suggest that Anks3 may be involved in DNA damage responses by balancing the intracellular nucleoside pool.

The three-legged stool of understanding metabolism: integrating metabolomics with biochemical genetics and computational modeling

Traditional biochemical research has resulted in a good understanding of many aspects of metabolism. However, this reductionist approach is time consuming and requires substantial resources, thus raising the question whether modern metabolomics and genomics should take over and replace the targeted experiments of old. We proffer that such a replacement is neither feasible not desirable and propose instead the tight integration of modern, system-wide omics with traditional experimental bench science and dedicated computational approaches. This integration is an important prerequisite toward the optimal acquisition of knowledge regarding metabolism and physiology in health and disease. The commentary describes advantages and drawbacks of current approaches to assessing metabolism and highlights the challenges to be overcome as we strive to achieve a deeper level of metabolic understanding in the future.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

Current Challenges toward In Vitro Cellular Validation of Inorganic Nanoparticles

An impressive development has been achieved toward the production of well-defined "smart" inorganic nanoparticles, in which the physicochemical properties can be controlled and predicted to a high degree of accuracy. Nanoparticle design is indeed highly advanced, multimodal and multitargeting being the norm, yet we do not fully understand the obstacles that nanoparticles face when used in vivo. Increased cooperation between chemists and biochemists, immunologists and physicists, has allowed us to think outside the box, and we are slowly starting to understand the interactions that nanoparticles undergo under more realistic situations. Importantly, such an understanding involves awareness about the limitations when assessing the influence of such inorganic nanoparticles on biological entities and vice versa, as well as the development of new validation strategies.

The Impact of Soy Isoflavones on MCF-7 and MDA-MB-231 Breast Cancer Cells Using a Global Metabolomic Approach

Despite substantial research, the understanding of the chemopreventive mechanisms of soy isoflavones remains challenging. Promising tools, such as metabolomics, can provide now a deeper insight into their biochemical mechanisms. The purpose of this study was to offer a comprehensive assessment of the metabolic alterations induced by genistein, daidzein and a soy seed extract on estrogen responsive (MCF-7) and estrogen non-responsive breast cancer cells (MDA-MB-231), using a global metabolomic approach. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay showed that all test compounds induced a biphasic effect on MCF-7 cells and only a dose-dependent inhibitory effect on MDA-MB-231 cells. Proton nuclear magnetic resonance (¹H-NMR) profiling of extracellular metabolites and gas chromatography-mass spectrometry (GC-MS) profiling of intracellular metabolites confirmed that all test compounds shared similar metabolic mechanisms. Exposing MCF-7 cells to stimulatory concentrations of isoflavones led to increased intracellular levels of 6-phosphogluconate and ribose 5-phosphate, suggesting a possible upregulation of the pentose phosphate pathway. After exposure to inhibitory doses of isoflavones, a significant decrease in glucose uptake was observed, especially for MCF-7 cells. In MDA-MB-231 cells, the glutamine uptake was significantly restricted, leading to alterations in protein biosynthesis. Understanding the metabolomic alterations of isoflavones represents a step forward in considering soy and soy derivates as functional foods in breast cancer chemoprevention.

Alterations of the exo- and endometabolite profiles in breast cancer cell lines: A mass spectrometry-based metabolomics approach

In recent years, knowledge about metabolite changes which are characteristic for the physiologic state of cancer cells has been acquired by liquid chromatography coupled to mass spectrometry. Distinct molecularly characterized breast cancer cell lines provide an unbiased and standardized in vitro tumor model reflecting the heterogeneity of the disease. Tandem mass spectrometry is a widely applied analytical platform and highly sensitive technique for analysis of complex biological samples. Endo- and exometabolite analysis of the breast cancer cell lines MDA-MB-231, -453 and BT-474 as well as the breast epithelial cell line MCF-10A has been performed using two different analytical platforms: UPLC-ESI-Q-TOF based on a scheduled precursor list has been applied for highlighting of significant differences between cell lines and HPLC-ESI-QqQ using multiple reaction monitoring has been utilized for a targeted approach focusing on RNA metabolism and interconnected pathways, respectively. Statistical analysis enabled a clear discrimination of the breast epithelial from the breast cancer cell lines. As an effect of oxidative stress, a decreased GSH/GSSG ratio has been detected in breast cancer cell lines. The triple negative breast cancer cell line MDA-MB-231 showed an elevation in nicotinamide, 1-ribosyl-nicotinamide and NAD+ reflecting the increased energy demand in triple negative breast cancer, which has a more aggressive clinical course than other forms of breast cancer. Obtained distinct metabolite pattern could be correlated with distinct molecular characteristics of breast cancer cells. Results and methodology of this preliminary in vitro study could be transferred to in vivo studies with breast cancer patients.

Interaction between APC and Fen1 during breast carcinogenesis

Aberrant DNA base excision repair (BER) contributes to malignant transformation. However, inter-individual variations in DNA repair capacity plays a key role in modifying breast cancer risk. We review here emerging evidence that two proteins involved in BER - adenomatous polyposis coli (APC) and flap endonuclease 1 (Fen1) - promote the development of breast cancer through novel mechanisms. APC and Fen1 expression and interaction is increased in breast tumors versus normal cells, APC interacts with and blocks Fen1 activity in Pol-β-directed LP-BER, and abrogation of LP-BER is linked with cigarette smoke condensate-induced transformation of normal breast epithelial cells. Carcinogens increase expression of APC and Fen1 in spontaneously immortalized human breast epithelial cells, human colon cancer cells, and mouse embryonic fibroblasts. Since APC and Fen1 are tumor suppressors, an increase in their levels could protect against carcinogenesis; however, this does not seem to be the case. Elevated Fen1 levels in breast and lung cancer cells may reflect the enhanced proliferation of cancer cells or increased DNA damage in cancer cells compared to normal cells. Inactivation of the tumor suppressor functions of APC and Fen1 is due to their interaction, which may act as a susceptibility factor for breast cancer. The increased interaction of APC and Fen1 may occur due to polypmorphic and/or mutational variation in these genes. Screening of APC and Fen1 polymorphic and/or mutational variations and APC/Fen1 interaction may permit assessment of individual DNA repair capability and the risk for breast cancer development. Such individuals might lower their breast cancer risk by reducing exposure to carcinogens. Stratifying individuals according to susceptibility would greatly assist epidemiologic studies of the impact of suspected environmental carcinogens. Additionally, a mechanistic understanding of the interaction of APC and Fen1 may provide the basis for developing new and effective targeted chemopreventive and chemotherapeutic agents.