Discovery Of Potential Biomarkers Research Articles

P2.11-10 Discovery of Potential Biomarkers That Discriminate Early Stage NSCLC from Controls by Non-Targeted Metabolomics Profiling

P2.11-10 Discovery of Potential Biomarkers That Discriminate Early Stage NSCLC from Controls by Non-Targeted Metabolomics Profiling

Database-Assisted Globally Optimized Targeted Mass Spectrometry (dGOT-MS): Broad and Reliable Metabolomics Analysis with Enhanced Identification.

Targeted mass spectrometry (MS) is an important measurement approach in metabolomics with strong analytical performance, given its specificity, sensitivity, and quantitative capacity. However, traditional targeted-MS relies heavily on chemical standards for the development of various detection panels; thus, its metabolite coverage is often limited to those well-known and commercially available compounds. To address this fundamental gap, we previously developed a novel approach [ H. Gu et al. Anal. Chem. 2015 , 87 , 12355 - 12362 ], globally optimized targeted (GOT)-MS, which enables reliable metabolic analysis with broad coverage using a single triple quadrupole instrument. In the present study, we further developed and optimized an innovative targeted MS approach, database-assisted globally optimized targeted (dGOT)-MS, which utilizes the HMDB and METLIN databases to significantly improve both identification and metabolite coverage. As it is well-known, these metabolomics databases have a comprehensive collection of metabolites and their tandem MS spectra; therefore, in this study, multiple reaction monitoring transitions (MRMs) were directly obtained from the databases and, after optimizing MS parameters for those MRMs, 927 metabolites were measured from a plasma aqueous extract sample with high reliability by dGOT-MS. Of these, 310 were confirmed using pure chemical standards while the rest were annotated by identification level using database entries. Furthermore, using breast cancer diagnosis as a proof-of-principle metabolomics application, we showed dGOT-MS to significantly outperform a traditional large-scale targeted MS assay for potential biomarker discovery. In principle, dGOT-MS is able to cover all metabolites (including lipids) that have been characterized in these comprehensive metabolomics databases from various types of biological samples. Therefore, dGOT-MS opens a novel avenue for MS measurements and may play an important role in many future metabolomics studies.

Metabolomics of Aurantio-Obtusin-Induced Hepatotoxicity in Rats for Discovery of Potential Biomarkers.

Aurantio-obtusin is an anthraquinone derived from Cassia obtusifolia (cassiae semen). It is also used as a tool and a detection index for the identification of cassiae semen, as stipulated by the Chinese Pharmacopoeia. Anthraquinones, the main components in cassiae semen, have been reported to show hepatotoxicity. This study investigates the hepatotoxicity of aurantio-obtusin in male Sprague–Dawley rats. We randomly divided the animals into a blank control group and treated three test groups with different doses of aurantio-obtusin: Low dose (4 mg/kg), medium dose (40 mg/kg), and high dose (200 mg/kg). Each group was treated with aurantio-obtusin for 28 days, whereas the control group was administered an equal volume of 0.5% carboxymethyl cellulose sodium salt (CMC-Na) aqueous solution. Subsequently, we conducted biochemical, hematological, and pathological investigations and determined the weight of different organs. We used serum metabolomics to identify possible biomarkers related to hepatotoxicity. The low-dose group showed no significant liver injury, whereas the medium- and high-dose groups manifested obvious liver injury. Compared with the control group, the test groups showed an increase in alanine transaminase, aspartate transaminase, and alkaline phosphatase levels. The liver organ coefficient also significantly increased. Additionally, we found significant changes in the hematological indices. Metabolomics analysis showed that aurantio-obtusin induced 28 endogenous markers related to liver injury. Our data indicate that aurantio-obtusin induces hepatotoxicity in rat liver in a dose-dependent manner and is mediated by pathways involving bile acids, fatty acids, amino acids, and energy metabolism. In particular, changes in bile acid content during treatment with therapeutic agents containing aurantio-obtusin deserve increased attention.

Mass Spectrometry Imaging of N-Glycans from Formalin-Fixed Paraffin-Embedded Tissue Sections Using a Novel Subatmospheric Pressure Ionization Source.

N-linked glycosylation, featuring various glycoforms, is one of the most common and complex protein post-translational modifications (PTMs) controlling protein structures and biological functions. It has been revealed that abnormal changes of protein N-glycosylation patterns are associated with many diseases. Hence, unraveling the disease-related alteration of glycosylation, especially the glycoforms, is crucial and beneficial to improving our understanding about the pathogenic mechanisms of various diseases. In past decades, given the capability of in situ mapping of biomolecules and their region-specific localizations, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been widely applied to the discovery of potential biomarkers for many diseases. In this study, we coupled a novel subatmospheric pressure (SubAP)/MALDI source with a Q Exactive HF hybrid quadrupole-orbitrap mass spectrometer for in situ imaging of N-linked glycans from formalin-fixed paraffin-embedded (FFPE) tissue sections. The utility of this new platform for N-glycan imaging analysis was demonstrated with a variety of FFPE tissue sections. A total of 55 N-glycans were successfully characterized and visualized from a FFPE mouse brain section. Furthermore, 29 N-glycans with different spatial distribution patterns could be identified from a FFPE mouse ovarian cancer tissue section. High-mannose N-glycans exhibited elevated expression levels in the tumor region, indicating the potential association of this type of N-glycans with tumor progression.

Hot Topic: Precision Medicine for Asthma-Has the Time Come?

Asthma is a common inflammatory airway disease, which affects more than 300 million people worldwide. Although conventional drugs are effective for most of the patients with mild-to-moderate asthma, they are less effective for patients with difficult-to-treat or severe asthma. Identification of asthma endotypes and biomarkers will lead to more precise approaches to treat asthma. Asthma subphenotypes and endotypes have been described based on clinical variables and sputum granulocytes. A recent asthma endotype study has been summarized based on the combination of T2 (FeNO) and non-T2 (IL-6) biomarkers. Discovery of potential biomarkers for asthma has been discussed in the context of omics approaches. Current biologic drugs for asthma have been summarized, and the future direction of precise treatment of asthma has been suggested. This review provides a concise overview of the current state of subphenotypes, endotypes, biomarkers, omics approaches, and biologic drugs in asthma.

Could circRNA be a new biomarker for pre-eclampsia?

Pre-eclampsia is a devastating complication of pregnancy which is characterized by hypertension and proteinuria in pregnant women. Pre-eclampsia is important as it is the leading cause of death. Moreover, untreated pre-eclampsia might lead to other lethal complications, for both fetus and mother. Pre-eclampsia can also affect the quality of life in affected women. Despite a large number of risk factors for pre-eclampsia, these risk factors are able to detect just 30% of women who are susceptible to pre-eclampsia. Heterogeneous manifestations of pre-eclampsia necessitate the discovery of potential biomarkers required for its early detection. Circular RNAs (circRNAs) are a type of RNA which are more abundant, specific, and highly organized compared with other types of RNA. Accordingly, circRNAs have been suggested as one of the potential biomarkers for different diseases. Recently, researchers have shown interest in the effects of circRNAs in pre-eclampsia, although the current evidence is limited. The majority of obstetricians are probably not aware of circRNAs as a useful biomarker. Here, we aimed to summarize recent supporting evidence and assess the mechanisms by which circRNAs are involved in pre-eclampsia.

Discovery of potential plasma protein biomarkers for acute myocardial infarction via proteomics.

Acute myocardial infarction (AMI) is an acute disease with high mortality and seriously threatens human health. The identification of new effective biological markers for AMI is a prerequisite for treatment. Most proteomic studies have focused on atherosclerotic plaques, vascular cells, monocytes and platelets in the blood; however, the concentration of these factors in plasma is low, making it difficult to measure the complexity of plasma components. Moreover, some studies have examined the plasma protein of patients with acute coronary syndrome with histochemistry; however, the results are not consistent. Therefore, it is necessary to further investigate the differential proteins in the plasma of patients with AMI via proteomics to identify new biomarkers of AMI. In this study, immunodepletion of high-abundance plasma proteins followed by an isobaric tagging for relative and absolute quantitation (iTRAQ)-based quantitative proteomic approach was used to analyze plasma samples from 5 control individuals and 10 AMI patients. Four hundred sixty-eight proteins were identified from two samples, and 33 proteins were differentially expressed in AMI patients compared to the controls. Among the 33 proteins, 12 proteins showed a ≥1.5-fold change between AMI and control samples. These proteins included fatty acid binding protein 3 (FABP3, ratio =6.36), creatine kinase-MB (CK-MB ratio =4.89), adenylate kinase1 (AK1 ratio =4.16), pro-platelet basic protein (PPBP ratio =3.29), creatine kinase (CK ratio =2.88), platelet factor 4 (PF4 ratio =2.62), peptidyl prolyl isomerase Cyclophilin A (PPIA ratio =2.05), Cofilin-1 (CFL1 ratio =1.81), coronin1A (CORO1A ratio =1.71), protein kinase M (PKM ratio =1.63), ribonuclease inhibitor (RNH1, ratio =1.67), and triose phosphate isomerase (TPI1 ratio =1.56). By contrast, there was a decrease of 19 proteins, such as adiponectin (ADIPOQ ratio =0.70), insulin-like growth factor binding protein6 (IGFBP6 ratio =0.70), Dickkopf-related protein 3 (DKK3 ratio =0.70) and complement 4B (C4B ratio =0.68). The most over-represented term was regulation of cell proliferation in the cellular component category of Gene Ontology (GO). The top 3 biological process terms were regulation of cell proliferation, response to wounding and wound healing. These proteins included immune proteins, blood coagulation proteins, lipid metabolism proteins, cytoskeleton proteins, energy metabolism proteins, gene regulation proteins, myocutaneous proteins, and myocardial remodeling proteins and were highly connected with each other, which indicates that the functional network of these processes contribute to the pathophysiology of AMI. In conclusion, the present quantitative proteomic study identified novel AMI biomarker candidates and might provide fundamental information for the development of an AMI biomarker.

Proteomic approaches in the discovery of potential urinary biomarkers of mucopolysaccharidosis type II

Mucopolysaccharindosis type II (MPS II) is a rare lysosomal storage disorder caused by deficient or absent activity of the iduronate-2-sulfatase (IDS) enzyme, which leads to pathological accumulation of the glycosaminoglycans(GAGs). The absence of early diagnosis can result in irreversible developmental, neurological, and physiological damage. The lack of clear understanding of the etiology of physiological dysfunction in MPS II has been a major obstacle to the development of new treatment. Therefore, a reliable biomarker for early diagnosis and exploration of pathogenic mechanism are of great importance. Proteomics provides powerful tool for protein expression alterations and study of complicated pathological process. This study was performed to identify the differential protein profile in urine of MPS II patients using two-dimensional gel electrophoresis(2D-PAGE)combining with MALDI-TOF/TOF and a total of 15 differentially expressed proteins were identified. Content of alpha1-antitrypsin, Gm2 activator and lipocalin-type prostaglandin D synthase was measured by ELISA method. The value of urinary α1-AT/Cr in MPS II group was 0.79 ± 0.10 mg/mmol, significantly higher than 0.42 ± 0.05 mg/mmol in healthy control group; whereas the value of GM2A/Cr and L-PGDS/Cr in MPS II group was 1.30 ± 0.12 μg/mmol and 9.86 ± 1.16 ng/mmol respectively, which was significantly lower than 2.19 ± 0.19 μg/mmol and 13.98 ± 1.48 ng/mmol in healthy control group. The proteins can be considered as accessory diagnostic biomarkers for MPS II. This approach helped to discover early diagnostic markers and provided a better understanding of the pathogenic mechanism of MPS II.

Proteomics and Leishmaniasis: Potential Clinical Applications.

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

Branched chain amino acids: Passive biomarkers or the key to the pathogenesis of cardiometabolic diseases?

The metabolomic approach to research on lifestyle diseases has led to the discovery of new potential biomarkers of pathological conditions as well as key metabolic pathways that may become targets of therapeutic intervention. Current evidence supports plasma branched chain amino acids (BCAAs) as potential diagnostic and prognostic biomarkers of cardiometabolic diseases. However, the biological mechanisms of the associations that have been identified are still not completely understood and should be clarified before implementing BCAA-based biomarkers in the clinical setting. The most crucial issue that needs to be solved first is determining whether BCAA plasma profile disturbances are only passive biomarkers or whether they facilitate dysmetabolic processes. In this context, further research is also warranted to investigate the role of dietary BCAAs. Gaining this knowledge would be significant progress in molecular nutrition research, providing perspective for target therapeutic and prophylactic interventions. This paper provides a comprehensive review of the main hypotheses and mechanistic models that consider circulating BCAAs both as passive biomarkers and as contributors to cardiometabolic diseases.

Discovery of potential urine-accessible metabolite biomarkers associated with muscle disease and corticosteroid response in the mdx mouse model for Duchenne.

Urine is increasingly being considered as a source of biomarker development in Duchenne Muscular Dystrophy (DMD), a severe, life-limiting disorder that affects approximately 1 in 4500 boys. In this study, we considered the mdx mice—a murine model of DMD—to discover biomarkers of disease, as well as pharmacodynamic biomarkers responsive to prednisolone, a corticosteroid commonly used to treat DMD. Longitudinal urine samples were analyzed from male age-matched mdx and wild-type mice randomized to prednisolone or vehicle control via liquid chromatography tandem mass spectrometry. A large number of metabolites (869 out of 6,334) were found to be significantly different between mdx and wild-type mice at baseline (Bonferroni-adjusted p-value < 0.05), thus being associated with disease status. These included a metabolite with m/z = 357 and creatine, which were also reported in a previous human study looking at serum. Novel observations in this study included peaks identified as biliverdin and hypusine. These four metabolites were significantly higher at baseline in the urine of mdx mice compared to wild-type, and significantly changed their levels over time after baseline. Creatine and biliverdin levels were also different between treated and control groups, but for creatine this may have been driven by an imbalance at baseline. In conclusion, our study reports a number of biomarkers, both known and novel, which may be related to either the mechanisms of muscle injury in DMD or prednisolone treatment.

Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics.

Semen abnormality (SA) male infertility has become a worldwide reproductive health problem. The invasive tests (e.g., testicular biopsy) and labor-intensive methods of semen collection severely inhibit diagnosis of male infertility. In addition, the pathogenesis and biological interpretation of male infertility are still obscure. In this report, a total of 84 semen abnormality (SA) patients, diagnosed as teratozoospermia (TE, n = 21), asthenozoospermia (AS, n = 23), oligozoospermia (OL, n = 20), azoospermia (AZ, n = 20), and age-matched healthy controls (HC, n = 29) were analyzed by GC-MS for discrimination analysis and discovery of potential biomarkers. Twenty-three biomarkers were obtained by multivariate statistical method (partial least squares-discriminant analysis, PLS-DA) and univariate statistical method (analysis of variance, ANOVA) with comparisons of TE versus HC, AS versus HC, OL versus HC and AZ versus HC. Based on those biomarkers, the most relevant pathways were mainly associated with the metabolism of carbohydrates, amino acids, and lipids. The principal metabolic alternations in SA male infertility included increased levels of energy-related metabolisms, such as tricarboxylic acid cycle, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, glycine, serine, threonine metabolism and saturated fatty acid metabolism. Furthermore, increased levels of glutathione metabolism were related to oxidative stress. Finally, decreased levels of arginine and proline metabolism and inositol phosphate metabolism were observed. In conclusion, blood plasma metabolomics is powerful for characterizing metabolic disturbances in SA male infertility. From metabolic pathway analysis, energy production, oxidation stress and the released enzyme during spermatogenesis take the primary responsibilities for SA male infertility.

The Peripheral Nervous System in Amyotrophic Lateral Sclerosis: Opportunities for Translational Research.

Although amyotrophic lateral sclerosis (ALS) has been considered as a disorder of the motor neuron (MN) cell body, recent evidences show the non-cell-autonomous pathogenic nature of the disease. Axonal degeneration, loss of peripheral axons and destruction of nerve terminals are early events in the disease pathogenic cascade, anticipating MN degeneration, and the onset of clinical symptoms. Therefore, although ALS and peripheral axonal neuropathies should be differentiated in clinical practice, they also share damage to common molecular pathways, including axonal transport, RNA metabolism and proteostasis. Thus, an extensive evaluation of the molecular events occurring in the peripheral nervous system (PNS) could be fundamental to understand the pathogenic mechanisms of ALS, favoring the discovery of potential disease biomarkers, and new therapeutic targets.

Proteomics Approaches for Biomarker and Drug Target Discovery in ALS and FTD.

Neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are increasing in prevalence but lack targeted therapeutics. Although the pathological mechanisms behind these diseases remain unclear, both ALS and FTD are characterized pathologically by aberrant protein aggregation and inclusion formation within neurons, which correlates with neurodegeneration. Notably, aggregation of several key proteins, including TAR DNA binding protein of 43 kDa (TDP-43), superoxide dismutase 1 (SOD1), and tau, have been implicated in these diseases. Proteomics methods are being increasingly applied to better understand disease-related mechanisms and to identify biomarkers of disease, using model systems as well as human samples. Proteomics-based approaches offer unbiased, high-throughput, and quantitative results with numerous applications for investigating proteins of interest. Here, we review recent advances in the understanding of ALS and FTD pathophysiology obtained using proteomics approaches, and we assess technical and experimental limitations. We compare findings from various mass spectrometry (MS) approaches including quantitative proteomics methods such as stable isotope labeling by amino acids in cell culture (SILAC) and tandem mass tagging (TMT) to approaches such as label-free quantitation (LFQ) and sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) in studies of ALS and FTD. Similarly, we describe disease-related protein-protein interaction (PPI) studies using approaches including immunoprecipitation mass spectrometry (IP-MS) and proximity-dependent biotin identification (BioID) and discuss future application of new techniques including proximity-dependent ascorbic acid peroxidase labeling (APEX), and biotinylation by antibody recognition (BAR). Furthermore, we explore the use of MS to detect post-translational modifications (PTMs), such as ubiquitination and phosphorylation, of disease-relevant proteins in ALS and FTD. We also discuss upstream technologies that enable enrichment of proteins of interest, highlighting the contributions of new techniques to isolate disease-relevant protein inclusions including flow cytometric analysis of inclusions and trafficking (FloIT). These recently developed approaches, as well as related advances yet to be applied to studies of these neurodegenerative diseases, offer numerous opportunities for discovery of potential therapeutic targets and biomarkers for ALS and FTD.

Correlation of HERVK with efficacy on anti-PD-1/PD-L1 therapy in a pilot metagenomics study on Chinese advanced lung cancer patients.

e14046 Background: Patient selection for PD-1 inhibitors in NSCLC is still based on imperfect screening biomarkers, including PD-L1 expression and tumor mutational burden(TMB).There are several reports show certain bacteria or virus infections are correlated with efficacy and prognosis on PD-1 inhibitors treatment. In order to explore more potential biomarkers for anti-PD-1 therapy, we investigate whether we can discover microorganisms in Chinese lung cancer patients and whether certain microorganism are correlated with efficacy or prognosis on anti-PD-1 therapy using metagenomics technology. Methods: In this study, 30 advanced lung cancer patient were enrolled, including 15 cases of adenocarcinoma, 12 cases of squamous carcinoma, 2 cases of Small cell lung cancer. 10 patients received PD-1/PD-L1 inhibitors as first-line therapy and other patients as second-line therapy. Among these 30 patients, 15 PR,1 CR, 10 PD, 4 SD according to RECIST 1.1. Plasma cell-free DNA (cfDNA) were collected from these patients prior to anti-PD-1 treatment and whole-genome sequencing of cfDNA at average coverage 5X was performed on Illumina NovaSeq in 2 ×150bp length model. A bioinformatics pipeline composed of 4 tools: BWA/Sambama/Kraken2/Bracken, was constructed to analyze the sequencing data. Non-human derived reads were extracted by sambama from the bam file that generated by BWA. Bacteria/Virus abundance in each sample was estimated through Bracken, followed by bac/vir database alignment in Kraken2. Results: In our pilot study, 4 patients were selected for metagenomics sequencing(1CR, 1PR, 2PD). Interestingly, over 100 different microbial sequence were detected in every patient. Compare microorganism in CR+PR patients to PD patients, Human endogenous retrovirus K (HERVK) were quite abundant in CR/PR patients but not in PD patients: 5.6 times more abundant in CR/PR patients comparing to PD patients. (HERVK abundance: CR:PR:PD = 1.20% : 0.32% : (0.17%, 0.10%)). HERVK is a family of human endogenous retroviruses associated with certain malignant tumors, studies have indicated that HERVK may trigger an antigen specific immune response for certain cancer patients. Conclusions: Metagenomics sequencing on plasma cfDNA could be a potential biomarker discovery approach to identify prognostic biomarkers for anti-PD-1 therapy. HERVK are correlated with efficacy on anti-PD-1 treatment in our pilot study, however more thorough investigation need to be conducted to confirm whether HERVK can be served as efficacy biomarkers for anti-PD-1.

Metabolomics Analysis of Opiate Abusers from Golestan Cohort Study (GCS)

Illicit use of opiate is a major public health threat across the world, and is associated with numerous potential adverse health outcomes such as cancers, infectious diseases and psychological disorders. Opium and their derivatives can modulate gene expression through epigenetic and possibly RNA modifications, ultimately impacts intracellular signaling cascades, and creates long‐lasting changes in the metabolome. Furthermore opiate can modify the output of urinary metabolites through many integrated neural and hormonal mechanisms within the periphery and central nervous system and kidneys.Metabolomics is a powerful technique that has been used in clinical and laboratory medicine for the discovery of potential diagnostic, prognostic and therapeutic biomarkers. The result of this study could lead to identification of significant altered biomarkers and can improve our knowledge of underling etiology and molecular pathways of opiate addiction and inform nutrition intervention.We performed 1H‐NMR metabolomics and liquid chromatography mass spectrometry (UPLC‐Q Exactive HF‐X MS) to analyze the urine metabolite profiling of 535 individuals from Golestan Cohort Study (GCS). The GCS is conducted in northeast of Iran to assess risk factors for upper gastrointestinal cancers for more than 50,000 volunteers who also were analyzed for opiate use and their complications.The metabolomics profiles of urine specimens from 443 (285 daily and 158 non‐daily) opiate users, stratified by route of use (oral and smoking) and tobacco use, have been compared with profiles obtained for 92 nonuser controls. After sample preparation, data was collected using a Bruker Avance III 700 MHz NMR Spectrometer. TopSpin and ACD Spectrus Processor softwares were used to data processing and NMR binning. Metabolites were identified by using Chenomx NMR Suite 8.3 Professional software.Metabolomics analysis revealed perturbations in level of hydroxyisovalerate, alanine, choline, citrate, creatinine, glucose, lactate, malonate, methylhydantoin, phenylalanine, phosphocholine, sucrose, tyrosine, acetylsalicylate and inositol in opiate abuser versus control groups.Metabolites are intrinsically involved in multiple metabolic pathways in vivo, so relative quantification of metabolites in body fluids such as urine can provide a profile of the metabolic state of an organism. Over the past decade, a large number of prospective and retrospective epidemiological studies have investigated the potential carcinogenic effect of opiate in humans. While data in favor of opiate's carcinogenicity is mounting, the potential mechanisms are largely unclear. The present study will explore opiate addiction and cancer risk using metabolomics, including exploring opiate effects on metabolic pathways and identification of potential markers of long term opiate abuse.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Robust Markers of Coffee Consumption Identified Among the Volatile Organic Compounds in Human Urine.

The human volatilome has gained high interest for the discovery of potential biomarkers of diseases. However, knowledge about the diet as a crucial factor affecting the volatilome is scarce. Therefore, the search for disease biomarkers, as well as the potential use of volatiles as dietary markers is so far limited. The aim of this study is to investigate the association of the diet with the urinary volatilome with the special task to find potential markers of coffee consumption in 24 h urine samples from the Karlsruhe Metabolomics and Nutrition (KarMeN) study. Acidified urine samples are analyzed using an approach combining headspace solid phase microextraction (HS-SPME) sampling with untargeted GC×GC-MS. Overall, 138 reliably occurring volatiles are detected. To account for the unequally concentrated urine samples, results of six different commonly used normalization methods are compared. Statistical analysis evidences six potential markers of coffee consumption, the most promising being 3,4-dimethyl-2,5-furandione. A correlation analysis between the 24 h dietary recall data and the urinary volatilome reveals further promising associations. The human urinary volatilome is highly affected by the diet, enabling access to a high level of information about potential diet-related biomarkers. Therefore, it is a very promising source for further investigations on dietary markers.

Genetic characterization of thymoma

Thymoma represents the most common anterior mediastinal compartment neoplasm, originating from the epithelial cell population in the thymus. Various histological types of thymoma feature different clinical characteristics. Furthermore, thymoma is frequently associated with autoimmune disorders, esp. myasthenia gravis (MG). However, the underlying molecular tumourigenesis of thymoma remains largely unknown. The goal of our current study is to demonstrate the underlying genetic abberations in thymoma, so as to understand the possible cause of MG in thymoma patients. By using CapitalBio mRNA microarray analysis, we analyzed 31 cases of thymoma including 5 cases of type AB thymoma, 6 B1-type cases, 12 B2-type cases, 5 B2B3-type cases and 3 type-B3 cases. 6 cases of thymoma were not associated with myasthenia gravis, while 25 cases were with myasthenia gravis. By comparisons between thymoma and the paratumoral tissues, differentially expressed genes were identified preliminarily. Among them, 292 genes increased more than 2-fold, 2 genes more than 5-fold. On the other hand, 596 genes were decreased more than 2-fold, 6 genes more than 20-fold. Interestingly, among these genes upregulated more than 2-fold, 6 driver genes (FANCI, NCAPD3, NCAPG, OXCT1, EPHA1 and MCM2) were formerly reported as driver oncogenes. This microarray results were further confirmed through real-time PCR. 8 most dysregulated genes were verified: E2F2, EPHA1, CCL25 and MCM2 were upregulated; and IL6, FABP4, CD36 and MYOC were downregulated. Supervised clustering heat map analysis of 2-fold upregulated and 2-fold downregulated genes revealed 6 distinct clusters. Strikingly, we found that cluster 1 was composed of two type-B2 thymoma; and cluster 6 was three type-B2/B3 thymoma. KEGG database analysis revealed possible genetic mechanisms of thymoma and functional process. We further compared gene expression pattern between thymoma with and without MG, and found 5 genes were upregulated more than 2-fold, more than 30 genes were downregulated more than 2-fold. KEGG analysis revealed 2 important signaling pathways with more than 2-fold upregulated genes (TGF- beta signaling pathway and HTLV-I signaling pathway) as differially functioning between MG positive and negative thymomas. Real-time PCR analysis confirmed that CCL25 was upregulated; and MYC, GADD45B, TNFRSF12 downregulated in thymoma with MG. Our study thus provided important genetic information on thymoma. It shed light on the molecular bases for analyzing the functional process of thymoma and finding potential biomarkers for pathological categorizing and treatment. Our work may provide important clues in understanding possible causes of MG in thymoma patients.

Discovery of potential biomarkers for osteoporosis using LC-MS/MS metabolomic methods.

Our study aimed to evaluate the association of metabolites with bone, trying to find new metabolic markers that are distinguishing for low bone mineral density (BMD). Our study recruited 320 participants, including 138 males and 182 postmenopausal females from the Shanghai area. Bone turnover markers (BTMs), including osteocalcin, PINP and β-CTX, and other biochemical traits were tested. BMD values of the lumber spine (L1-4), femoral neck and total hip were determined using dual-energy X-ray absorptiometry and the serum metabolome profiles including 221 metabolites from five groups (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids and hexose) were assessed by mass spectrometry. No visual separation in the metabolic profiles between different BMD groups was observed in principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) models. We compared metabolites in three groups with different BMD levels in males and postmenopausal females separately and further filtering these metabolites via random forest-based feature selection, a commonly applied machine learning algorithm which could select the features with the greatest impact on osteoporosis, then metabolites with the highest importance (≥ 5%) (5 in males and 9 in postmenopausal females) were selected to construct better models for osteoporosis classification. After adding these selected metabolites to the model, the area under the curve (AUC) of receiver operating characteristic (ROC) curves increased significantly (BTMs: AUC 0.729, 95% CI 0.647-0.802, p < 0.0001, model 1: AUC = 0.828, 95% CI 0.754-0.888, p < 0.0001; model 1 versus model of BTMs: p = 0.0158) compared to the AUC of the BTM-only model in males. Similar results were also observed in postmenopausal females (BTMs: AUC = 0.638, 95% CI 0.562-0.708, p = 0.0025; model 2: AUC = 0.741, 95% CI 0.669-0.803, p < 0.0001; model 1 versus model of BTMs: p = 0.0182). Metabolites combined with traditional BTMs tend to better markers for distinguishing osteoporosis in both males and postmenopausal females than BTMs alone.

Sézary Syndrome, recent biomarkers and new drugs.

Sezary syndrome (SS) is a primary cutaneous T-cell lymphoma (CTCL) characterized by erythroderma, lymphadenopathy and leukemic involvement of the peripheral blood. The high relapse rates and a poor prognosis complicate its clinical course and treatment. The phenotypic characterization and genomic/transcriptomic approaches revealed high heterogeneity of Sezary cells, identifying a wide spectrum of biomarkers implicated in the development of this lymphoma. In this context, we discuss the major malignancy-related biomarkers reported in the literature for the diagnosis, prognosis and staging of SS. The hope for a single reliable diagnostic marker appears increasingly unrealistic, but the discovery of multiple potential biomarkers, with pathogenetic implications, paves the road to promising personalized therapies in SS.