Analysis of urinary nucleosides as potential cancer markers determined using LC–MS technique

Structure-Assisted Boronic Acid Implanted Mesoporous Metal-Organic Frameworks for Specific Extraction of cis-Diol Molecules

cis-Diol-containing molecules, an essential type of compounds in living organisms, have attracted intensive research interest from various fields. The analysis of cis-diol-containing molecules is still suffering from some drawbacks, including low abundance and abundant interference. Metal-organic frameworks (MOFs) have proven to be an ideal sorbent for sample preparation. However, most of the reported MOFs are mainly restricted to a microporous regime (pore size <2 nm), which greatly limits the application. Herein, a facile strategy is established to construction of boronate affinity MOFs via the postsynthetic ligand-exchange process. Owing to the fact that the ligand-exchange process was assisted by the structural integrity of the primitive metal-organic framework and the great compatibility of click chemistry, the obtained EPBA-PCN-333(Fe) is able to realize the maximum maintaining the porosity and crystallinity of the parent material. Several intriguing features of EPBA-PCN-333(Fe) (e.g., excellent selectivity, efficient diffusion, good accessibility, and size exclusion effect) are experimentally demonstrated via a series of cis-diol-containing molecules with different molecular sizes (small molecules, glycopeptides, and glycoproteins). The binding performance of EPBA-PCN-333(Fe) is evaluated by employing catechol as the test molecule (binding capacity: 0.25 mmol/g, LOD: 200 ng/mL). Finally, the real-world applications of EPBA-PCN-333(Fe) were demonstrated by the detection of nucleosides of human urine samples.

An on-line SPE-LC-MS/MS method for quantification of nucleobases and nucleosides present in biological fluids

Solid phase extraction (SPE) and liquid chromatographic (LC) separation of nucleobases and nucleosides are challenging due to the high hydrophilicity of these compounds. Herein we report a novel on-line SPE-LC-MS/MS method for their quantification after pre-column derivatization with chloroacetaldehyde (CAA). The method proposed is selective and sensitive with limits of detection at the nano-molar level. Analysis of urine and saliva samples by using this method is demonstrated. Adenine, guanine, cytosine, adenosine, guanosine, and cytidine were found in the range from 0.19 (guanosine) to 1.83 μM (cytidine) in urine and from 0.015 (guanosine) to 0.79 μM (adenine) in saliva. Interestingly, methylation of cytidine was found to be significantly different in urine from that in saliva. While 5-hydroxymethylcytidine was detected at a very low level (<0.05 μM) in saliva, it was found to be the most prominent methylated cytidine in urine at a high level of 3.33 μM. Since on-line SPE is deployed, the proposed LC-MS/MS quantitative assay is convenient to carry out and offers good assay accuracy and repeatability.

Targeted quantitative metabolomics with a linear mixed-effect model for analysis of urinary nucleosides and deoxynucleosides from bladder cancer patients before and after tumor resection

In the present study, we developed and validated a fast, simple, and sensitive quantitative method for the simultaneous determination of eleven nucleosides and deoxynucleosides from urine samples. The analyses were performed with the use of liquid chromatography coupled with triple quadrupole mass spectrometry. The sample pretreatment procedure was limited to centrifugation, vortex mixing of urine samples with a methanol/water solution (1:1, v/v), evaporation and dissolution steps. The analysis lasted 20 min and was performed in dynamic multiple reaction monitoring mode (dMRM) in positive polarity. Process validation was conducted to determine the linearity, precision, accuracy, limit of quantification, stability, recovery and matrix effect. All validation procedures were carried out in accordance with current FDA and EMA regulations. The validated method was applied for the analysis of 133 urine samples derived from bladder cancer patients before tumor resection and 24 h, 2 weeks, and 3, 6, 9, and 12 months after the surgery. The obtained data sets were analyzed using a linear mixed-effect model. The analysis revealed that concentration level of 2-methylthioadenosine was decreased, while for inosine, it was increased 24 h after tumor resection in comparison to the preoperative state. The presented quantitative longitudinal study of urine nucleosides and deoxynucleosides before and up to 12 months after bladder tumor resection brings additional prospective insight into the metabolite excretion pattern in bladder cancer disease. Moreover, incurred sample reanalysis was performed proving the robustness and repeatability of the developed targeted method.

Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer

Cis-diol metabolic reprogramming evolves during primary liver cancer (PLC) initiation and progression. However, owing to the low concentrations and highly structural heterogeneity of cis-diols in vivo, severe interference from complex biofluids and limited profiling coverage of existing methods, in-depth profiling of cis-diol metabolites and linking their specific changes with PLC remain challenging. Besides, due to the low specificity of widely used protein biomarkers, accurate classification of PLC from hepatitis still represents an unmet need in clinical diagnostics. Herein, to high-coverage profile cis-diols and explore the translational potential of them as biomarkers, a machine learning-empowered boronate affinity extraction-solvent evaporation assisted enrichment-mass spectrometry (MLE-BESE-MS) was developed. A single analytical platform integrated with multiple complementary functions, including pH-controlled boronate affinity extraction, solvent evaporation-assisted enrichment and nanoelectrospray ionization-based cis-diol identification, was constructed, which significantly improved the metabolite coverage. Meanwhile, by virtue of machine learning (principal components analysis, orthogonal partial least-squares discrimination analysis and random forest), collected cis-diols were statistically screened to extract efficient features for precise PLC diagnosis, and the results outperform the routinely used protein biomarker-based methods both in sensitivity (87.5% vs. less than 70%) and specificity (85.7% vs. ca. 80%). This machine learning-empowered integrated MS platform advanced the targeted metabolic analysis for early cancer diagnosis, rendering great promise for clinical translation.

Integrated LC-MS and network pharmacology methods to screen quantitative indicators in the Hippocampus histrix Kaup and method transfer

Hippocampus histrix Kaup is a popular marine medicine with high medicinal and healthcare values. In this study, liquid chromatography-mass spectrometry (LC-MS) analysis combined with network pharmacological method was used to screen for suitable quantitative indicators for the quality control of H. histrix Kaup. Firstly, an LC-MS analytical method for the simultaneous determination of 12 nucleosides in extracts of H. histrix Kaup was established. And then, a network pharmacological method incorporated target prediction, protein-protein interaction network, components-targets network, and targets-pathways network was performed to screen for quantitative indicators. Finally, the developed LC-MS method was transferred to liquid chromatographs to improve the generalizability of the method. All 12 nucleotides were authenticated in extracts of H. histrix Kaup by comparing with the standards. The optimal chromatographic separation conditions are as follows: the chromatographic separation was achieved on an Acquire BEH-C18 column (2.1 mm * 100 mm, 1.7 µm) and gradient elution was performed using methanol solution and buffer (0.30% formic acid and 10 mmol/L ammonium acetate) as mobile phase at a flow rate of 0.15 mL/min and an acquisition wavelength of 260 nm. Network pharmacology results showed that adenosine, and uridine show excellent pharmacological activity. Integration the content, correlation, chromatographic separation, and pharmacological activity of each compound in H. histrix Kaup, uridine and adenosine were tentatively determined as quantitative indicators for quality control in H. histrix Kaup. The established LC-MS method was successfully transferred to liquid chromatographs, and the method is stable and reliable for the quality control of H. histrix Kaup. This developed integrated strategy was successfully used to screen quantitative indicators in the H. histrix Kaup.

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.

Pre- and Post-Resection Urine Metabolic Profiles of Bladder Cancer Patients: Results of Preliminary Studies on Time Series Metabolomics Analysis

Simple Summary

Bladder cancer is one of the most frequently diagnosed cancers worldwide and due to non-specific symptoms, it is often detected at a late stage. For this reason, possible diagnostic alternatives that could be used for non-invasive screening are still being sought. In recent years, metabolomics approach has been frequently used for this type of research, using urine or blood collected from two groups: patients with a given disease and healthy volunteers. Usually, to minimize the impact of between-subject differences, participants of the study are matched in terms of age, gender, or BMI. Another way to rule out the impact of this variability is to analyze samples taken at intervals from the same patient. Therefore, the aim of our study was to validate results obtained using the traditional approach on a small group of patients, from whom samples were taken before and after resection of the bladder tumor, in a given time frame.

Abstract

The incidence of bladder cancer (BCa) has remained high for many years. Nevertheless, its pathomechanism has not yet been fully understood and is still being studied. Therefore, multiplatform untargeted urinary metabolomics analysis has been performed in order to study differences in the metabolic profiles of urine samples collected at three time points: before transurethral resection of bladder tumor (TURBT), the day after the procedure and two weeks after TURBT. Collected samples were analyzed with the use of high-performance liquid chromatography hyphenated with time-of-flight mass spectrometry detection (HPLC-TOF/MS) and gas chromatography coupled with triple quadrupole mass spectrometry detection (GC-QqQ/MS, in a scan mode). Levels of metabolites selected in our previous study were assessed in order to confirm their potential to differentiate the healthy and diseased samples, regardless of the risk factors and individual characteristics. Hippuric acid, pentanedioic acid and uridine confirmed their potential for sample differentiation. Based on the results of statistical analysis for the paired samples (comparison of metabolic profiles of samples collected before TURBT and two weeks after), a set of metabolites belonging to nucleotide metabolism and methylation processes was also selected. Longitudinal studies proved to be useful for the evaluation of metabolic changes in bladder cancer.

Metabolomic Changes after Coffee Consumption: New Paths on the Block

SCOPE

Several studies suggest that regular coffee consumption may help preventing chronic diseases, but the impact of daily intake and the contribution of coffee metabolites in disease prevention are still unclear. The present study aims at evaluating whether and how different patterns of coffee intake (one cup of espresso coffee/day, three cups of espresso coffee/day, and one cup of espresso coffee/day and two cocoa-based products containing coffee two times per day) may impact endogenous molecular pathways.

METHODS AND RESULTS

A three-arm, randomized, crossover trial is performed in 21 healthy volunteers who consumed each treatment for one month. Urine samples are collected to perform untargeted metabolomics based on UHPLC-IMS-HRMS. A total of 153 discriminant metabolites are identified. Several molecular features are associated with coffee consumption, while others are linked with different metabolic pathways, such as phenylalanine, tyrosine, energy metabolism, steroid hormone biosynthesis, and arginine biosynthesis and metabolism.

CONCLUSION

This information has provided new insights into the metabolic routes by which coffee and coffee-related metabolites may exert effects on human health.

Study on Urinary Candidate Metabolome for the Early Detection of Breast Cancer

A metabolomic study for determination of certain urinary metabolomes, 1-methyladenosine (1-MA), 1-methylguanosine (1-MG), and 8-hydroxy-2' deoxyguanosine (8-OHdG) in urine specimens of breast cancer patients. The accuracy of these metabolites and their combined score with cancer antigen 15-3 (CA15-3) was developed to improve the early detection of breast cancer. This study recruited 52 healthy individuals, 47 benign breast tumors, and 167 malignant breast tumor patients. Urine samples were handled to adjust the creatinine concentrations to 8 mg/dL (0.7 mmol/L) and analyzed using GC-MS to detect and quantify the selected urinary metabolomes in urine samples of all participants. The accuracy of individual urinary metabolomes and their combination with CA15-3 were evaluated using multivariate statistical analysis. The cutoff value of CA15-3 was 32.5 U/mL. Cutoff values of 1-MA, 1-MG, and 8-OHdG were 2.19, 2.1, and 7.3 µmol/mmol creatinine, respectively. The concentrations of 1-MA, 1-MG, and 8-OHdG were significantly higher in breast cancer patients, especially in the early-stage. The combination of three urinary metabolomes with CA15-3 improves the diagnostic sensitivity of breast cancer. For the combined score, the area under the curve (AUC) value of combined score ranged from 0.820 to 0.950, with high accuracy, ranged from 77.0 to 95.5%. The most significant AUC (0.973), sensitivity (90.1%), selectivity (94.0%) was recorded at comparing the healthy control with the early-stage of malignant breast cancer. In conclusion, the combination of three urinary metabolomes with serum CA15-3 improves the diagnostic sensitivity of breast cancer.

Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score

INTRODUCTION

The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.

OBJECTIVE

To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).

METHODS

Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined.

RESULTS

The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)].

CONCLUSIONS

This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

A combination of α-fetoprotein, midkine, thioredoxin and a metabolite for predicting hepatocellular carcinoma

INTRODUCTION AND OBJECTIVES

The heterogenous nature of hepatocellular carcinoma (HCC) motivated this attempt at developing and validating a model based on combined biomarkers for improving early HCC detection.

PATIENTS/MATERIALS AND METHODS

This study examined 196 patients for an estimation study (104 patients with HCC, 52 with liver cirrhosis and 40 with liver fibrosis) and 122 patients for the validation study (80 patients with HCC, 42 with liver cirrhosis). All patients were positive for hepatitis C virus. Four markers were measured: Midkine and thioredoxin using ELISA, 1-methyladenosine and 1-methylguanosine using a gas chromatography-mass spectrometry (GC-MS). The results were compared with alpha-fetoprotein (AFP). The performance of the model was estimated in BCLC, CLIP and Okuda staging systems of HCC.

RESULTS

The model yielded high performance with an area under ROC (AUC) of 0.94 for predicting HCC in patients with liver cirrhosis, compared with AUC of 0.69 for AFP. This model had AUCs of 0.93, 0.94 and 0.94 in patients who had only one single nodule, absent macrovascular invasion and tumor size <2cm, respectively, compared with AUCs of 0.71, 0.6 and 0.59 for AFP. The model produced AUCs of 0.91 for BCLC (0-A), 0.92 for CLIP (0-1) and 0.94 for Okuda (stage I) compared with AUCs of 0.56, 0.58 and 0.64 for AFP. No significant difference was found between AUC in the estimation and the validation groups.

CONCLUSION

This model may enhance early-stage HCC detection and help to overcome insufficient sensitivity of AFP.

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.

Development of a gas chromatography-mass spectrometry method for breast cancer diagnosis based on nucleoside metabolomes 1-methyl adenosine, 1-methylguanosine and 8-hydroxy-2'-deoxyguanosine

Metabolomes are small molecule metabolites (<1000 Da) produced by cellular processes. Metabolomes are close counterparts to the genome, transcriptome and proteome. The aim of this study was to develop a method to detect and quantify candidate nucleoside metabolomes 1-methyl adenosine (1-MA), 1-methylguanosine (1-MG) and 8-hydroxy-2'-deoxyguanosine (8-OHdG) in the urine of patients with breast cancer using gas chromatography-mass spectrometry (GC-MS). The method was applied to urine specimens from patients with breast cancer (n = 56) and benign breast tumors (n = 22), as well as from healthy females (n = 20). The relative standard deviations of precision and repeatability analysis were <10%, and recoveries ranged from 88.5 to 105.6%. Limits of detection were 0.014, 0.012, and 0.018 mg/L for 1-MA, 1-MG and 8-OHdG, respectively. The lower limits of quantitation were 0.056, 0.048 and 0.072 mg/L, respectively. There were significant differences in concentrations of candidate metabolomes between patients with cancer and the healthy individuals, especially for those in the early stages of the disease (p < 0.001). No significant differences were observed between the benign and healthy groups. In conclusion, a reliable GC-MS method for the detection and quantification of 1-MA, 1-MG, and 8-OHdG metabolomes in urine has been developed.

Reduced levels of modified nucleosides in the urine of autistic children. Preliminary studies

The aim of this study was to investigate and compare the levels of concentration of modified nucleosides in the urine of autistic and healthy children. The compounds have never been analyzed before. The levels of nucleosides in the urine of both groups were determined by validated high performance liquid chromatography coupled to mass spectrometry (LC-MS/MS) method using multiple reaction monitoring (MRM) mode. Chromatographic separation was achieved with HILIC column and tubercidin was used as the internal standard for the quantification of urinary nucleosides. The within run accuracy and precision ranged from 89 to 106% and from 0.8% to 4.9%, respectively. Lower levels of O-methylguanosine, 7-methylguanosine, 1-methyladenosine, 1-methylguanine, 7-methylguanine and 3-methyladenine in the urine of 22 children with autism, aged 3 to 16 were observed. The differences were not observed in 20 healthy volunteers, in a similar age group. These findings show that modified nucleosides there are metabolic disturbances and nutritional deficiencies in autistic children.

Current Trends in Cancer Biomarker Discovery Using Urinary Metabolomics: Achievements and New Challenges

BACKGROUND

The development of effective screening methods for early cancer detection is one of the foremost challenges facing modern cancer research. Urinary metabolomics has recently emerged as a potentially transformative approach to cancer biomarker discovery owing to its noninvasive sampling characteristics and robust analytical feasibility.

OBJECTIVE

To provide an overview of new developments in urinary metabolomics, cover the most promising aspects of hyphenated techniques in untargeted and targeted metabolomics, and to discuss technical and clinical limitations in addition to the emerging challenges in the field of urinary metabolomics and its application to cancer biomarker discovery.

METHODS

A systematic review of research conducted in the past five years on the application of urinary metabolomics to cancer biomarker discovery was performed. Given the breadth of this topic, our review focused on the five most widely studied cancers employing urinary metabolomics approaches, including lung, breast, bladder, prostate, and ovarian cancers.

RESULTS

As an extension of conventional metabolomics, urinary metabolomics has benefitted from recent technological developments in nuclear magnetic resonance, mass spectrometry, gas and liquid chromatography, and capillary electrophoresis that have improved urine metabolome coverage and analytical reproducibility. Extensive metabolic profiling in urine has revealed a significant number of altered metabolic pathways and putative biomarkers, including pteridines, modified nucleosides, and acylcarnitines, that have been associated with cancer development and progression.

CONCLUSION

Urinary metabolomics presents a transformative new approach toward cancer biomarker discovery with high translational capacity to early cancer screening.

Urinary Nucleosides and Deoxynucleosides

Urinary nucleosides and deoxynucleosides are mainly known as metabolites of RNA turnover and oxidative damage of DNA. For several decades these metabolites have been examined for their potential use in disease states including cancer and oxidative stress. Subsequent improvements in analytical sensitivity and specificity have provided a reliable means to measure these unique molecules to better assess their relationship to physiologic and pathophysiologic conditions. In fact, some are currently used as antiviral and antitumor agents. In this review we provide insight into their molecular characteristics, highlight current separation techniques and detection methods, and explore potential clinical usefulness.

Polydopamine assisted functionalization of boronic acid on magnetic nanoparticles for the selective extraction of ribosylated metabolites from urine

A novel strategy for the rapid and selective extraction of ribosylated metabolites by dopamine assisted functionalization of boronic acid on magnetic (Fe₃O₄@PDA-FPBA) nanoparticles has been demonstrated under optimized conditions.

Statistical-based approach in potential diagnostic application of urinary nucleosides in urogenital tract cancer

Aim: We aimed at evaluation the potential diagnostic role of urinary nucleosides in urogenital tract cancer. Materials & methods: Concentrations of 12 nucleosides determined by LC-MS/MS were subjected to correlation, association and interaction analyses. Results: We identified six pairs of nucleosides differently correlated in the group of patients and controls (p < 0.05). N-2-methylguanosine (odds ratio: 4.82; 95% CI: 1.78–12.93; p = 0.002) and N,N-dimethylguanosine (odds ratio: 5.45; 95% CI: 1.78–16.44; p = 0.003), were significantly associated with the disease risk (p-corrected = 0.004). Interaction between N-2-methylguanosine and adenosine (p-interaction = 0.019) suggested their multiplicative effect on the outcome. Conclusion: Urinary nucleosides, namely N,N-dimethylguanosine and N-2-methylguanosine may have the potential to serve as prognostic biomarkers. Gender-specific differences in urogenital tract cancer are likely to occur.

The Chemical Constituents and Pharmacological Actions of Cordyceps sinensis

Cordyceps sinensis, also called DongChongXiaCao (winter worm, summer grass) in Chinese, is becoming increasingly popular and important in the public and scientific communities. This study summarizes the chemical constituents and their corresponding pharmacological actions of Cordyceps sinensis. Many bioactive components of Cordyceps sinensis have been extracted including nucleoside, polysaccharide, sterol, protein, amino acid, and polypeptide. In addition, these constituents' corresponding pharmacological actions were also shown in the study such as anti-inflammatory, antioxidant, antitumour, antiapoptosis, and immunomodulatory actions. Therefore can use different effects of C. sinensis against different diseases and provide reference for the study of Cordyceps sinensis in the future.

Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.