Global proteomics and metabolomics in cancer biomarker discovery

Integrative proteomics and m6A microarray analyses of the signatures induced by METTL3 reveals prognostically significant in gastric cancer by affecting cellular metabolism

METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification that participates in tumor initiation and progression via governing the expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly characterized. In this study, m6A microarray and quantitative proteomics were employed to explore the potential effect and mechanism of METTL3 on the metabolism in GC cells. Our results showed that METTL3 induced significant alterations in the protein and m6A modification profile in GC cells. Gene Ontology (GO) enrichment indicated that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS). Moreover, the protein-protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. A prognostic model was subsequently constructed based on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the high-risk group exhibited a worse prognosis in GC patients. Meanwhile, Gene Set Enrichment Analysis (GSEA) demonstrated significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the molecules of OXPHOS. Besides, there were significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to the consensus clustering algorithm. Finally, highly expressed and highly methylated molecules regulated by METTL3 were analyzed and three (AVEN, DAZAP2, DNAJB1) genes were identified to be significantly associated with poor prognosis in GC patients. These results signified that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be implicated in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 is involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

Metabolic response to radiation therapy in cancer

Tumor metabolism has emerged as a hallmark of cancer and is involved in carcinogenesis and tumor growth. Reprogramming of tumor metabolism is necessary for cancer cells to sustain high proliferation rates and enhanced demands for nutrients. Recent studies suggest that metabolic plasticity in cancer cells can decrease the efficacy of anticancer therapies by enhancing antioxidant defenses and DNA repair mechanisms. Studying radiation-induced metabolic changes will lead to a better understanding of radiation response mechanisms as well as the identification of new therapeutic targets, but there are few robust studies characterizing the metabolic changes induced by radiation therapy in cancer. In this review, we will highlight studies that provide information on the metabolic changes induced by radiation and oxidative stress in cancer cells and the associated underlying mechanisms.

Urinary free metanephrines measurement in dogs with adrenal gland diseases using a new simple liquid chromatography tandem mass spectrometry method

Measurement of urinary metanephrines in spot samples is used for the diagnosis of canine pheochromocytoma (PC). We describe a simple analytical method based on liquid chromatography tandem mass spectrometry (LC-MS/MS) for measuring free metanephrine (MN) and normetanephrine (NMN) in spot urine samples. Using the developed method, we evaluated the stability of urinary free-MN and free-NMN at various storing conditions. In addition, we assessed the feasibility of urinary free-MN and -NMN measurement for diagnosing PC. Urine samples were mixed with stable isotope internal standards and thereafter purified by ultrafiltration. The purified samples were analyzed by LC-MS/MS in the multiple reaction monitoring mode after separation on a multimode octa decyl silyl column. The coefficient of variation of free-MN and -NMN measurement was 7.6% and 5.5%, respectively. The linearity range was 0.5–10 µg/l for both analytes. Degradation was less than 10% for both analytes under any of the storage conditions. The median free-NMN ratio to creatinine of 9 PC dogs (595, range 144–47,961) was significantly higher (P<0.05) than that of 13 dogs with hypercortisolism (125, range 52–224) or 15 healthy dogs (85, range 50–117). The developed method is simple and may not require acidification of spot urine. The results of this preliminary retrospective study suggest that the measurement of urinary free metanephrines is a promising tool for diagnosing canine PC.

Identification of metabolites in plasma for predicting survival in glioblastoma

Circulating metabolomics profiling holds prognostic potential. However, such efforts have not been extensively carried out in glioblastoma. In this study, two-step (training and testing) metabolomics profiling was conducted from the plasma samples of 159 glioblastoma patients. Metabolomics profiling was tested for correlation with 2-year overall and disease-free survivals. Arginine, methionine, and kynurenate levels were significantly associated with 2-year overall survival in both the training and testing sets. In the combined sets, elevated levels of arginine and methionine were associated with a 34% and 37% increased probability whereas kynurenate was associated with a 55% decreased probability of 2-year overall survival. These three metabolites were also significantly associated with 2-year disease-free survival. Risk scores were generated using the linear combination of levels of these significant metabolites. Glioblastoma patients with a high-risk score exhibited a 2.41-fold decreased probability of 2-year overall survival (hazard ratio (HR) = 2.41; 95% Confidence Interval (CI) = 1.20-4.93) and a 3.17-fold decreased probability of 2-year disease free survival (HR = 3.17, 95%CI = 1.42-7.54) relative to those with a low-risk score. In conclusion, we identified a unique plasma metabolite profile that is predictive of glioblastoma prognosis.

Investigation of the protective effect of Paeonia lactiflora on Semen Strychni-induced neurotoxicity based on monitoring nine potential neurotoxicity biomarkers in rat serum and brain tissue

Semen Strychni has been widely used as a traditional Chinese herb medicine, but its clinical use was limited for its potential neurotoxicity and nephrotoxicity. This study aimed to investigate S. Strychni-induced neurotoxicity and the neuro-protective effect of Paeonia lactiflora based on monitoring nine potential neurotoxicity biomarkers in rat serum and brain tissue. A sensitive liquid chromatography-tandem mass spectrometry method was developed and validated to monitor serotonin, tryptophan, dopamine, tyrosine and glutamate in serum and five brain regions (prefrontal cortex, hippocampus, striatum, cerebellum and hypothalamus). Analytes were separated on a CAPCELL CORE PC column (150 mm × 2 mm, 2.7 μm) with a gradient program of acetonitrile-water (0.2 % formic acid) and a total runtime of 7.5 min. In addition, enzyme-linked immunosorbent assay was conducted to determine four kinds of protein (tryptophan hydroxylase, tyrosine hydroxylase, endogenous brain-derived neurotrophic factor and nerve growth factor). Results demonstrated that the administration of S. Strychni could cause certain endogenous substances disorder. These analytes were found significantly changed (p < 0.05) in serum (except glutamate) and in certain tested brain regions in S. Strychni extract group. Pretreatment of P. lactiflora could significantly reverse the S. Strychni-induced neurotoxicity and normalize the levels of such endogenous substances. The study could be further used in predicting and monitoring neurotoxicity caused by other reasons, and it was expected to be useful for improving clinical use of S. Strychni through pretreatment with P. lactiflora.

Metabolites involved in glycolysis and amino acid metabolism are altered in short children born small for gestational age

BACKGROUND

Later life metabolic dysfunction is a well-recognized consequence of being born small for gestational age (SGA). This study has applied metabolomics to identify whether there are changes in these pathways in prepubertal short SGA children and aimed to compare the intracellular and extracellular metabolome in fibroblasts derived from healthy children and SGA children with postnatal growth impairment.

METHODS

Skin fibroblast cell lines were established from eight SGA children (age 1.8-10.3 y) with failure of catch-up growth and from three healthy control children. Confluent cells were incubated in serum-free media and the spent growth medium (metabolic footprint), and intracellular metabolome (metabolic fingerprint) were analyzed by gas-chromatography mass spectrometry.

RESULTS

Nineteen metabolites were significantly altered between SGA and control cell lines. The greatest fold difference (FD) was seen for alanine (fingerprint FD, SGA: control 0.3, P = 0.01 and footprint FD = 0.19, P = 0.01), aspartic acid (fingerprint FD = 5.21, P = 0.01), and cystine (footprint FD = 1.66, P = 0.02). Network analysis of the differentially expressed metabolites predicted inhibition of insulin as well as growth (ERK) signaling in SGA cells.

CONCLUSION

This study indicates that changes in cellular metabolism associated with both growth failure and insulin insensitivity are present in prepubertal short children born SGA.

Utility of mass spectrometry for the diagnosis of the unstable coronary plaque

Mass spectrometry is a powerful technique that is used to identify unknown compounds, to quantify known materials, and to elucidate the structure and chemical properties of molecules. Recent advances in the accuracy and speed of the technology have allowed data acquisition for the global analysis of lipids from complex samples such as blood plasma or serum. Here, mass spectrometry as a tool is described, its limitations explained and its application to biomarker discovery in coronary artery disease is considered. In particular an application of mass spectrometry for the discovery of lipid biomarkers that may indicate plaque morphology that could lead to myocardial infarction is elucidated.

The role of protein and peptide separation before mass spectrometry analysis in clinical proteomics

The purpose of clinical proteomics is to characterise protein profiles of a plethora of diseases with the aim of finding specific biomarkers. These are particularly valuable for early diagnosis, and represent key molecules suitable to elucidate pathogenic mechanisms. Samples deriving from patients (i.e. blood, urine, cerebrospinal fluid, biopsies) are the sources for clinical proteomics. Due to the complexity of the extracted samples their direct analysis is unachievable. Any analytical clinical proteomics study should start with the choice of the optimal combination of strategies with respect to both sample preparations and MS approaches. Protein or peptide fractionation (off-line or on-line) is essential to reduce complexity of biological samples and to achieve the most complete and reproducible analysis. The aim of this review is to introduce the readers to a functional range of strategies to help scientists in their proteomics set up. In particular, the separation approaches of proteins or peptides (both gel-based and gel-free) are reviewed with special attention paid to their advantages and limitations, and to the different liquid chromatography techniques used to peptide fractionation after protein enzymatic digestion and before their detection. Finally, the role of mass spectrometry (MS) for protein identification and quantification is discussed including emerging MS data acquisition strategies.

MICROFLUIDIC DEVICES FOR LABEL-FREE AND NON-INSTRUMENTED QUANTITATION OF UNAMPLIFIED NUCLEIC ACIDS BY FLOW DISTANCE MEASUREMENT

Timely biomarker quantitation has potential to improve human health but current methods have disadvantages either in terms of cost and complexity for benchtop instruments, or reduced performance in quantitation and/or multiplexing for point-of-care systems. We previously developed microfluidic devices wherein visually observed flow distances correlated with a model analyte's concentration.1 Here, we significantly expand over this prior result to demonstrate the measurement of unamplified DNA analogues of microRNAs (miRNAs), biomarkers whose levels can be altered in disease states. We have developed a method for covalently attaching nucleic acid receptors on poly(dimethylsiloxane) microchannel surfaces by silane and cross-linker treatments. We found a flow distance dependence on target concentrations from 10 μg/mL to 10 pg/mL for DNA in both buffer and synthetic urine. Moreover, flow time in addition to flow distance is correlated with target concentration. We also observed longer flow distances for single-base mismatches compared to the target sequence at the same concentration, indicating that our approach can be used to detect point mutations. Finally, experiments with DNA analogues of miRNA biomarkers for kidney disease (mir-200c-3p) and prostate cancer (mir-107) in synthetic urine showed the ability to detect these analytes near clinically relevant levels. Our results demonstrate that these novel microfluidic assays offer a simple route to sensitive, amplification-free nucleic acid quantitation, with strong potential for point-of-care application.

Metabolomic studies of human gastric cancer: Review

Metabolomics is a field of study in systems biology that involves the identification and quantification of metabolites present in a biological system. Analyzing metabolic differences between unperturbed and perturbed networks, such as cancerous and non-cancerous samples, can provide insight into underlying disease pathology, disease prognosis and diagnosis. Despite the large number of review articles concerning metabolomics and its application in cancer research, biomarker and drug discovery, these reviews do not focus on a specific type of cancer. Metabolomics may provide biomarkers useful for identification of early stage gastric cancer, potentially addressing an important clinical need. Here, we present a short review on metabolomics as a tool for biomarker discovery in human gastric cancer, with a primary focus on its use as a predictor of anticancer drug chemosensitivity, diagnosis, prognosis, and metastasis.

Application of two-dimensional gel-based mass spectrometry to functionally dissect resistance to targeted cancer therapy

PURPOSE

The majority of gastric cancers are diagnosed at advanced stages, characterized by robust therapy resistance. The oncoprotein hypoxia-inducible factor 1 (HIF-1) is associated with therapy resistance, partly via activation of the DNA damage response. We have noted a robust ability of gastric cancer cells to functionally compensate the loss of HIF-1 in vitro. The purpose of this study was to identify molecular pathways that underlie this compensation.

EXPERIMENTAL DESIGN

We performed 2DE to compare the nuclear proteome of wild-type and HIF-1-deficient gastric cancer cells. Differently expressed protein spots were identified via MS). After bioinformatic evaluation, functional validation of selected identified pathways was performed.

RESULTS

2DE displayed a total of 2523 protein spots, from which 87 were identified as regulated by HIF-1. Seventy of the identified spots were different proteins and 17 were isoforms. Bioinformatic analyses revealed that a significant amount of the identified proteins were related to cellular survival pathways. Specifically, members of the proteasome pathway were found upregulated upon loss of HIF-1. Combined inhibition of HIF-1 and the proteasome inflicted significant DNA damage, supporting the hypothesis that the proteasome is of functional importance to compensate the loss of HIF-1.

CONCLUSIONS AND CLINICAL RELEVANCE

Our data show robust and functional changes of the nuclear proteome upon inactivation of the HIF-1 oncoprotein in gastric cancer cells. We propose that 2DE-MS represents a useful tool to functionally dissect resistance mechanisms to targeted therapy and to identify novel targets for antiproliferative combination therapy.

Determination of 12 potential nephrotoxicity biomarkers in rat serum and urine by liquid chromatography with mass spectrometry and its application to renal failure induced by Semen Strychni

In previous nephrotoxicity metabonomic studies, several potential biomarkers were found and evaluated. To investigate the relationship between the nephrotoxicity biomarkers and the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni-induced renal failure, 12 typical biomarkers are selected and a simple LC-MS method has been developed and validated. Citric acid, guanidinosuccinic acid, taurine, guanidinoacetic acid, uric acid, creatinine, hippuric acid, xanthurenic acid, kynurenic acid, 3-indoxyl sulfate, indole-3-acetic acid, and phenaceturic acid were separated by a Phenomenex Luna C18 column and a methanol/water (5 mM ammonium acetate) gradient program with a runtime of 20 min. The prepared calibration curves showed good linearity with regression coefficients all above 0.9913. The absolute recoveries of analytes from serum and urine were all more than 70.4%. With the developed method, analytes were successfully determined in serum and urine samples within 52 days. Results showed that guanidinosuccinic acid, guanidinoacetic acid, 3-indoxyl sulfate, and indole-3-acetic acid (only in urine) were more sensitive than the conventional renal function markers in evaluating the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni-induced renal failure. The method could be further used in predicting and monitoring renal failure cause by other reasons in the following researches.

Review: toxicometabolomics

Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context.

Metabolomic signatures of aggressive prostate cancer

BACKGROUND

Current diagnostic techniques have increased the detection of prostate cancer; however, these tools inadequately stratify patients to minimize mortality. Recent studies have identified a biochemical signature of prostate cancer metastasis, including increased sarcosine abundance. This study examined the association of tissue metabolites with other clinically significant findings.

METHODS

A state of the art metabolomics platform analyzed prostatectomy tissues (331 prostate tumor, 178 cancer-free prostate tissues) from two independent sites. Biochemicals were analyzed by gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-tandem mass spectrometry. Statistical analyses identified metabolites associated with cancer aggressiveness: Gleason score, extracapsular extension, and seminal vesicle and lymph node involvement.

RESULTS

Prostate tumors had significantly altered metabolite profiles compared to cancer-free prostate tissues, including biochemicals associated with cell growth, energetics, stress, and loss of prostate-specific biochemistry. Many metabolites were further associated with clinical findings of aggressive disease. Aggressiveness-associated metabolites stratified prostate tumor tissues with high abundances of compounds associated with normal prostate function (e.g., citrate and polyamines) from more clinically advanced prostate tumors. These aggressive prostate tumors were further subdivided by abundance profiles of metabolites including NAD+ and kynurenine. When added to multiparametric nomograms, metabolites improved prediction of organ confinement (AUROC from 0.53 to 0.62) and 5-year recurrence (AUROC from 0.53 to 0.64).

CONCLUSIONS

These findings support and extend earlier metabolomic studies in prostate cancer and studies where metabolic enzymes have been associated with carcinogenesis and/or outcome. Furthermore, these data suggest that panels of analytes may be valuable to translate metabolomic findings to clinically useful diagnostic tests.

Application of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry technology for the diagnosis of colorectal adenoma

The aim of the present study was to identify a specific biological marker for the diagnosis of colorectal adenomas through the analysis of variations in serum protein profiling in colorectal adenoma patients. The study was conducted at the Renmin Hospital of Wuhan University (Wuhan, China) between September 2011 and May 2012. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was performed to compare the serum protein profiles of 50 patients with colorectal adenoma and 50 healthy individuals. The obtained protein profiles were analyzed using Biomarker Wizard software. Twenty protein peaks were identified to exhibit differences in average intensity between colorectal adenomas compared with normal controls, including peaks 8,565.84, 8,694.51 and 5,910.50 Da, in which the intensity between the patients and control individuals was significantly different. Two peaks, 8,565.84 and 8,694.51 Da, were observed to be highly expressed in the colorectal adenomas, however, expression was low in the control samples. By contrast, 5,910.50 Da expression was low in the colorectal adenomas and high in the controls. The results of the current study indicate that the three protein peaks may represent specific biomarkers for colorectal adenomas.

Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery

Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (<±1%), and mass accuracy (<±1 ppm). Based on normalised data (against creatinine levels, osmolality or MS total useful signals/MSTUS) coupled with supervised multivariate analysis using Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA), we were able to discriminate urine samples from men with or without prostate cancer with R2Y(cum) >0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05) between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

Gas chromatography-mass spectrometry metabolite profiling of worker honey bee (Apis mellifera L.) hemolymph for the study of Nosema ceranae infection

Here, we are presenting a gas chromatography-mass spectrometry (GC/MS) approach for the study of infection of the worker honey bee (Apis mellifera L.) by the newly emerged obligate intracellular parasite Nosema ceranae based on metabolite profiling of hemolymph. Because of the severity of the disease, early detection is crucial for its efficient control. Results revealed that the parasite causes a general disturbance of the physiology of the honey bee affecting the mechanisms controlling the mobilization of energy reserves in infected individuals. The imposed nutritional and energetic stress to the host was depicted mainly in the decreased levels of the majority of carbohydrates and amino acids, including metabolites such as fructose, l-proline, and the cryoprotectants sorbitol and glycerol, which are implicated in various biochemical pathways. Interestingly, the level of glucose was detected at significantly higher levels in infected honey bees. Metabolomics analyses were in agreement with those of multiplex quantitative PCR analyses, indicating that it can be used as a complementary tool for the detection and the study of the physiology of the disease.

Profiling eicosanoids and phospholipids using LC-MS/MS: principles and recent applications

Eicosanoids are potent lipid mediators involved in numerous physiological and pathophysiological processes. Precursors are polyunsaturated fatty acids liberated from membrane phospholipids. Thus, profiling and quantification of these molecules has gained a lot of attention during last years. Eicosanoids and phospholipids are commonly profiled by LC-MS/MSbecause this technique allows accurate quantification within acceptable run-times. This article therefore focuses on liquid chromatography and the ESI-MS/MS analysis of proinflammatory lipid mediators, particularly arachidonic acid (C20:4) derived eicosanoids and their precursors phospholipids. Recent analytical developments for quantification of these compounds are highlighted and analytical challenges are discussed. Furthermore, applications such as the use of these molecules as biomarkers are presented.

Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.