Set Of Novel Biomarkers Research Articles

Biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach using LC-HRMS/MS and chemometrics

Since its first employment in World War I, chlorine gas has often been used as chemical warfare agent. Unfortunately, after suspected release, it is difficult to prove the use of chlorine as a chemical weapon and unambiguous verification is still challenging. Furthermore, similar evidence can be found for exposure to chlorine gas and other, less harmful chlorinating agents. Therefore, the current study aims to use untargeted high resolution mass spectrometric analysis of chlorinated biomarkers together with machine learning techniques to be able to differentiate between exposure of plants to various chlorinating agents. Green spire (Euonymus japonicus), stinging nettle (Urtica dioica), and feathergrass (Stipa tenuifolia) were exposed to 1000 and 7500 ppm chlorine gas and household bleach, pool bleach, and concentrated sodium hypochlorite. After sample preparation and digestion, the samples were analyzed by liquid chromatography high resolution tandem mass spectrometry (LC-HRMS/MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). More than 150 chlorinated compounds including plant fatty acids, proteins, and DNA adducts were tentatively identified. Principal component analysis (PCA) and linear discriminant analysis (LDA) showed clear discrimination between chlorine gas and bleach exposure and grouping of the samples according to chlorine concentration and type of bleach. The identity of a set of novel biomarkers was confirmed using commercially available or synthetic reference standards. Chlorodopamine, dichlorodopamine, and trichlorodopamine were identified as specific markers for chlorine gas exposure. Fenclonine (Cl-Phe), 3-chlorotyrosine (Cl-Tyr), 3,5-dichlorotyrosine (di-Cl-Tyr), and 5-chlorocytosine (Cl-Cyt) were more abundantly present in plants after chlorine contact. In contrast, the DNA adduct 2-amino-6-chloropurine (Cl-Ade) was identified in both types of samples at a similar level. None of these chlorinated biomarkers were observed in untreated samples. The DNA adducts Cl-Cyt and Cl-Ade could clearly be identified even three months after the actual exposure. This study demonstrates the feasibility of forensic biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach.

Prognostic utility of TME-associated genes in pancreatic cancer.

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Homocysteine and Inflammatory Cytokines in the Clinical Assessment of Infection in Venous Leg Ulcers.

Inflammation and biofilm-associated infection are common in chronic venous leg ulcers (VU), causing deep pain and delayed healing. Albeit important, clinical markers and laboratory parameters for identifying and monitoring persistent VU infections are limited. This study analyzed 101 patients with infected (IVU) and noninfected VUs (NVU). Clinical data were collected in both groups. The serum homocysteine (Hcys) and inflammatory cytokines from the wound fluid were measured. In addition, microbial identification, antibiotic susceptibility, and biofilm production were examined. IVU were 56 (55.4%) while NVU were 45 (44.5%). IVUs showed a significant increase in the wound’s size and depth compared to NVUs. In addition, significantly higher levels of interleukin (IL)-6, IL-10, IL17A, and tumor necrosis factor-alpha (TNF-α) were found in patients with IVUs compared to those with NVUs. Notably, hyperhomocysteinemia (HHcy) was significantly more common in patients with IVUs than NVUs. A total of 89 different pathogens were identified from 56 IVUs. Gram-negative bacteria were 51.7%, while the Gram-positives were 48.3%. At the species level, Staphylococcus aureus was the most common isolate (43.8%), followed by Pseudomonas aeruginosa (18.0%). Multidrug-resistant organisms (MDROs) accounted for 25.8% of the total isolates. Strong biofilm producers (SBPs) (70.8%) were significantly more abundant than weak biofilm producers (WBP) (29.2%) in IVUs. SBPs were present in 97.7% of the IVUs as single or multispecies infections. Specifically, SBPs were 94.9% for S. aureus, 87.5% for P. aeruginosa, and 28.6% for Escherichia coli. In IVU, the tissue microenvironment and biofilm production can support chronic microbial persistence and a most severe clinical outcome even in the presence of an intense immune response, as shown by the high levels of inflammatory molecules. The measurement of local cytokines in combination with systemic homocysteine may offer a novel set of biomarkers for the clinical assessment of IVUs caused by biofilm-producing bacteria.

Single-cell phenotypic profiling to identify a set of immune cell protein biomarkers for relapsed and refractory diffuse large B cell lymphoma: A single-center study.

Diffuse large B-cell lymphoma (DLBCL) is the most common invasive type of non-Hodgkin lymphoma. Cell-of-origin (COO) classification is related to patients' prognoses. Primary drug resistance in treatment for DLBCL has been observed. The specific serum biomarkers in these patients who suffer from relapsed and refractory (R/R)-DLBCL remains unclear. In the current study, using single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF), we determined and verified immune cell biomarkers at the mRNA and protein levels in single-cell resolution from 18 diagnostic PBMC specimens collected from patients with R/R DLBCL. As controls, 5 PBMC specimens from healthy volunteers were obtained. We identified a panel of 35 surface marker genes for the features of R/R DLBCL unique cell cluster by scRNA-seq of 8 R/R DLBCL patient samples and validated its efficiency in an external cohort consisting of 10 R/R DLBCL patients by CyTOF. The cell clustering and dimension reduction were compared among R/R DLBCL samples in CyTOF Space with COO as well as the C-MYC expression designation. Immune cells from each patient occupied unique regions in the 32-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Significant heterogeneity observed in subgroups was mainly attributed to individual differences among samples and not to expression differences in a single, homogeneous immune cell subpopulation. The marker panel showed reliability in labeling R/R DLBCL without any influence from COO stratification and C-MYC expression designation. Furthermore, we compared all the markers between R/R DLBCL and normal samples. A total of 12 biomarkers were significantly overexpressed in R/R DLBCL relative to the normal samples. Therefore, we further optimized the diagnostic biomarker panel of R/R DLBCL comprising CD82, CD55, CD36, CD63, CD59, IKZF1, CD69, CD163, CD14, CD226, CD84, and CD31. In summary, we developed a novel set of biomarkers for the diagnoses of patients with R/R DLBCL. Detections procedures at single-cell resolution provide precise biomarkers, which may substantially overcome intertumoral and intratumoral heterogeneity among primary samples. The findings confirmed that each case was unique and may comprise multiple, genetically distinct subclones.

Proteomic Profiling of Cold Storage Preservation Solution to Identify Signatures of Primary Graft Dysfunction Following Heart Transplantation

Purpose There currently exist no validated biomarkers of donor primary graft dysfunction (PGD) risk. We hypothesized that proteomic profiling of cold-storage preservation solution may identify novel biomarkers of post-transplant allograft dysfunction. Methods 169 samples of HTK preservation solution were obtained between 2016 and 2018 at Duke University and analyzed using LC-MS. After QC, proteins quantified by two or more unique precursors were retained, and protein levels were log-transformed. Univariate logistic regression was performed to identify proteins associated with ISHLT-defined moderate-severe PGD (p<0.05). Significant proteins were included in an iterative Monte Carlo LASSO regression model; proteins retained in at least 50% of the 1000 total iterations were selected as a parsimonious model. We used AUC analysis to assess the predictive performance of the protein model compared to a clinical model including donor age, ischemic time and predicted heart mass. Results Out of 1340 proteins, 213 were nominally associated with PGD in univariate analysis. Sixteen of these proteins were retained in at least 50% of iterations of the LASSO model (Table 1). All of these proteins remained significant in multivariable analysis after adjustment for the aforementioned clinical covariates. AUC of the 16-protein model was 0.90 as compared to the clinical model at 0.68 (p<0.001). Two proteins (FMOD and CSN5) were modestly correlated with ischemic time (R=0.28 and R=-0.15, p<0.05) and four proteins (CMA1, CNDP1, CSN5, and HV323) were modestly correlated with donor predicted heart mass (R=-0.24 - 0.2, p<0.05). Conclusion Using non-targeted proteomic profiling of traditional cold storage preservation solution, we have identified a set of novel biomarkers that are associated with PGD. Key biologic candidates within this set include MYL4, FMOD, ELOC, and CMA1. Future studies are needed to validate these signals and elucidate their role in clinical care. There currently exist no validated biomarkers of donor primary graft dysfunction (PGD) risk. We hypothesized that proteomic profiling of cold-storage preservation solution may identify novel biomarkers of post-transplant allograft dysfunction. 169 samples of HTK preservation solution were obtained between 2016 and 2018 at Duke University and analyzed using LC-MS. After QC, proteins quantified by two or more unique precursors were retained, and protein levels were log-transformed. Univariate logistic regression was performed to identify proteins associated with ISHLT-defined moderate-severe PGD (p<0.05). Significant proteins were included in an iterative Monte Carlo LASSO regression model; proteins retained in at least 50% of the 1000 total iterations were selected as a parsimonious model. We used AUC analysis to assess the predictive performance of the protein model compared to a clinical model including donor age, ischemic time and predicted heart mass. Out of 1340 proteins, 213 were nominally associated with PGD in univariate analysis. Sixteen of these proteins were retained in at least 50% of iterations of the LASSO model (Table 1). All of these proteins remained significant in multivariable analysis after adjustment for the aforementioned clinical covariates. AUC of the 16-protein model was 0.90 as compared to the clinical model at 0.68 (p<0.001). Two proteins (FMOD and CSN5) were modestly correlated with ischemic time (R=0.28 and R=-0.15, p<0.05) and four proteins (CMA1, CNDP1, CSN5, and HV323) were modestly correlated with donor predicted heart mass (R=-0.24 - 0.2, p<0.05). Using non-targeted proteomic profiling of traditional cold storage preservation solution, we have identified a set of novel biomarkers that are associated with PGD. Key biologic candidates within this set include MYL4, FMOD, ELOC, and CMA1. Future studies are needed to validate these signals and elucidate their role in clinical care.

Immunoprofiling of active and inactive systemic juvenile idiopathic arthritis reveals distinct biomarkers: a single-center study

BackgroundThis study aimed to perform an immunoprofiling of systemic juvenile idiopathic arthritis (sJIA) in order to define biomarkers of clinical use as well as reveal new immune mechanisms.MethodsImmunoprofiling of plasma samples from a clinically well-described cohort consisting of 21 sJIA patients as well as 60 age and sex matched healthy controls, was performed by a highly sensitive proteomic immunoassay. Based on the biomarkers being significantly up- or down-regulated in cross-sectional and paired analysis, related canonical pathways and cellular functions were explored by Ingenuity Pathway Analysis (IPA).ResultsThe well-studied sJIA biomarkers, IL6, IL18 and S100A12, were confirmed to be increased during active sJIA as compared to healthy controls. IL18 was the only factor found to be increased during inactive sJIA as compared to healthy controls. Novel factors, including CASP8, CCL23, CD6, CXCL1, CXCL11, CXCL5, EIF4EBP1, KITLG, MMP1, OSM, SIRT2, SULT1A1 and TNFSF11, were found to be differentially expressed in active and/or inactive sJIA and healthy controls. No significant pathway activation could be predicted based on the limited factor input to the IPA. High Mobility Group Box 1 (HMGB1), a damage associated molecular pattern being involved in a series of inflammatory diseases, was determined to be higher in active sJIA than inactive sJIA.ConclusionsWe could identify a novel set of biomarkers distinguishing active sJIA from inactive sJIA or healthy controls. Our findings enable a better understanding of the immune mechanisms active in sJIA and aid the development of future diagnostic and therapeutic strategies.

Intensification of functional neural control on heartbeat dynamics in subclinical depression

Subclinical depression (dysphoria) is a common condition that may increase the risk of major depression and leads to impaired quality of life and severe comorbid somatic diseases. Despite its prevalence, specific biological markers are unknown; consequently, the identification of dysphoria currently relies exclusively on subjective clinical scores and structured interviews. Based on recent neurocardiology studies that link brain and cardiovascular disorders, it was hypothesized that multi-system biomarkers of brain–body interplay may effectively characterize dysphoria. Thus, an ad hoc computational technique was developed to quantify the functional bidirectional brain–heart interplay. Accordingly, 32-channel electroencephalographic and heart rate variability series were obtained from 24 young dysphoric adults and 36 healthy controls. All participants were females of a similar age, and results were obtained during a 5-min resting state. The experimental results suggest that a specific feature of dysphoria is linked to an augmented functional central-autonomic control to the heart, which originates from central, frontopolar, and occipital oscillations and acts through cardiovascular sympathovagal activity. These results enable further development of a large set of novel biomarkers for mood disorders based on comprehensive brain–body measurements.

Identification of Tumor Microenvironment-Related Prognostic Biomarkers in Luminal Breast Cancer.

Background: The tumor microenvironment (TME) has been reported to have significant value in the diagnosis and prognosis of cancers. This study aimed to identify key biomarkers in the TME of luminal breast cancer (BC).Methods: We obtained immune scores (ISs) and stromal scores (SSs) for The Cancer Genome Atlas (TCGA) luminal BC cohort from the online ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) portal. The relationships between ISs and SSs and the overall survival of luminal BC patients were assessed by the Kaplan-Meier method. The differentially expressed messenger RNAs (DEmRNAs) related to the ISs and SSs were subjected to functional enrichment analysis. Additionally, a competing endogenous RNA (ceRNA) network was constructed with differentially expressed microRNAs (DEmiRNAs) and long noncoding RNAs (DElncRNAs). Furthermore, a protein–protein interaction (PPI) network was established to analyze the DEmRNAs in the ceRNA network. Then, survival analysis of biomarkers involved in the ceRNA network was carried out to explore their prognostic value. Finally, these biomarkers were validated using the luminal BC dataset from the Gene Expression Omnibus (GEO) database.Results: The results showed that ISs were significantly associated with longer survival times of luminal BC patients. Functional enrichment analysis showed that the DEmRNAs were mainly associated with immune response, antigen binding, and the extracellular region. In the PPI network, the top 10 DEmRNAs were identified as hub genes that affected the TME of luminal BC. Finally, two DEmiRNAs, two DElncRNAs, and 17 DEmRNAs of the ceRNA network associated with the TME were shown to have prognostic value. Subsequently, the expression of 15 prognostic biomarkers was validated in one additional dataset (GSE81002). In particular, one lncRNA (GVINP1) and five mRNAs (CCDC69, DOCK2, IKZF1, JCHAIN, and NCKAP1L) were novel biomarkers.Conclusions: Our studies demonstrated that ISs were associated with the survival of luminal BC patients, and a set of novel biomarkers that might play a prognostic role in the TME of luminal BC was identified.

Identification of three miRNAs signature as a prognostic biomarker in breast cancer using bioinformatics analysis.

BackgroundAccumulating evidences indicated that some miRNAs are dysregulated in breast cancer and involved in cell growth, migration and invasion, differentiation, cell cycle arrest, apoptosis, and autophagy. Our study aims to identify a novel set of biomarkers for predicting the prognosis of breast cancer patients.MethodsWe downloaded clinical information and raw sequencing data from The Cancer Genome Atlas (TCGA) database. We selected samples with miRNA sequencing data and relevant clinical prognostic data for subsequent analysis. The association between miRNA and prognosis function was analyzed by Cox regression analysis. The potential biofunctions of target miRNAs were investigated through bioinformatic analysis.ResultsWe identified 84 differentially expressed miRNAs (DEmiRNAs), among them, 17 were downregulated and 67 were upregulated. We used Kaplan-Meier survival analysis to evaluate the prognostic value of three miRNAs (mir-105-1, mir-301b and mir-1258). We also found that the three-miRNA signature is independent prognostic factors for breast cancer by using Cox regression analysis. It might be participated in different signaling pathways associated with cancer by using functional enrichment analysis, including adherens junction, autophagy, and TGF-beta signaling pathway, ErbB signaling pathway, FoxO signaling pathway.ConclusionsTaken together, three-miRNA signature might be used as a potential predicting prognostic biomarker in breast cancer.

The transcriptome of circulating cells indicates potential biomarkers and therapeutic targets in the course of hypertension-related myocardial infarction

Hypertension (HT) is the most common public-health challenge and shows a high incidence around the world. Cardiovascular diseases are the leading cause of mortality and morbidity among the elderly (age > 65 years) in the United States. Now, there is widespread acceptance of the causal link between HT and acute myocardial infarction (MI). This is the first data-mining study to identify co-expressed differentially expressed genes (co-DEGs) between HT and MI (relative to normal control) and to uncover potential biomarkers and therapeutic targets of HT-related MI. In this manuscript, HT-specific DEGs and MI-specific DEGs and differentially expressed microRNAs (DE-miRNAs) were identified in Gene Expression Omnibus (GEO) datasets GSE24752, GSE60993, GSE62646, and GSE24548 after data consolidation and batch correction. Subsequently, enrichment in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways as well as protein–protein interaction networks were identified, and single-gene gene set enrichment analysis was performed to determine the affected biological categories and networks. Cross-matching of the results on co-DE-miRNAs and predicted miRNAs targeting the co-DEGs was conducted and discussed as well. We found that MYC and HIST1H2BO may be associated with HT, whereas FCGR1A, FYN, KLRD1, KLRB1, and FOLR3 may be implicated in MI. Moreover, co-DEGs FOLR3 and NFE2 with predicted miRNAs and DE-miRNAs, especially miR-7 and miR-548, may be significantly associated and show huge potential as a new set of novel biomarkers and important molecular targets in the course of HT-related MI.

Identification of potential biomarkers of vaccine inflammation in mice.

Systems vaccinology approaches have been used successfully to define early signatures of the vaccine-induced immune response. However, the possibility that transcriptomics can also identify a correlate or surrogate for vaccine inflammation has not been fully explored. We have compared four licensed vaccines with known safety profiles, as well as three agonists of Toll-like receptors (TLRs) with known inflammatory potential, to elucidate the transcriptomic profile of an acceptable response to vaccination versus that of an inflammatory reaction. In mice, we looked at the transcriptomic changes in muscle at the injection site, the lymph node that drained the muscle, and the peripheral blood mononuclear cells (PBMCs)isolated from the circulating blood from 4 hr after injection and over the next week. A detailed examination and comparative analysis of these transcriptomes revealed a set of novel biomarkers that are reflective of inflammation after vaccination. These biomarkers are readily measurable in the peripheral blood, providing useful surrogates of inflammation, and provide a way to select candidates with acceptable safety profiles.

IDO Pathway Analysis for Identifying Novel Biomarkers in Multiple Myeloma

Background: Indoleamine 2,3-dioxygenase (IDO) is an intracellular enzyme that catalyzes the initial rate-limiting step in Tryptophan (Trp) degradation along the Kynurenine pathway. Trp can be catabolized by tryptophan hydroxylase into serotonin (Ser) or alternatively, by IDO and tryptophan-2,3-dioxygenase (TDO) into Kynurenine (Kyn). A variety of human tumors have been shown to express an active IDO which leads to the induction of immune tolerance and malignant cell survival (Mellor et al, 1999). Elevated IDO activity within tumor microenvironment impairs the function of antigen specific T cells and suppresses the anti-tumor immune response, while in tumor-draining lymph nodes an active IDO inhibits the antigen presentation reducing the population of antigen-specific T cells and stimulates regulatory T cells (Treg) activation (Curti et al. 2009). IDO overexpression has been correlated with poor prognosis in a number of human solid tumors including ovarian, endometrial and colon carcinoma (Okamoto et al. 2005, Ino et al. 2006, Brandacher et al. 2006). In hematological malignancies, such as AML and DLBCL, IDO expression has also shown significant prognostic value (Folgiero et al. 2014, Ninomiya et al. 2011). Currently, our understanding of the role of IDO in multiple myeloma (MM) is limited to a few existing studies correlating the abundance of selected IDO pathway metabolites with the disease (Bonanno et al. 2012, Zdzisinska et al. 2010). We hypothesize that IDO activity correlates with the disease onset and progression in MM patients.Methods: We quantified the levels of Trp, Kyn, and Ser in human serum by mass spectrometry using the Biocrates AbsoluteIDQ p180 kit. Analysis was performed using MetaboAnalyst 3.0 and Graphpad prism software. The serum samples derived from healthy donors and MM patients were obtained commercially.Results: We found significantly reduced levels of Trp (n=13, p<0.001) and elevated levels of Kyn (n=13, p<0.05) in serum samples from MM patients compared to matching (sex and age paired) healthy donor samples, while Ser levels did not differ significantly. Similarly, samples obtained from Newly Diagnosed (ND) MM patients showed a significant reduction in Trp (n=16, p<0.01) and a trend towards increased Kyn. The overall results in Relapsed/Refractory (R/R) MM patients were similar to the ND setting, although we only detected a trend towards Trp reduction, and observed a significant increase in Kyn levels (n=26, p<0.01) when compared to healthy donors. These results were confirmed when analyzing the data using the widely employed Kyn/Trp ratio, a potential marker for assessing IDO activity. A significantly elevated Kyn/Trp ratio was observed in all of the MM malignant populations (paired: n=13, p<0.001; ND: n=16, p<0.01; R/R: n=26, p<0.01) as compared to healthy individuals.Conclusions: Our study suggests that increased activity of IDO, and/or the production of downstream metabolites is one of the features of MM, and could potentially define a valuable set of novel biomarkers. Here we show a consistent pattern of increased Kyn and decreased Trp levels as well as an elevated Kyn/Trp ratio, all of which are hallmarks of high IDO activity in MM subjects when compared to healthy individuals. We did not detect any significant differences in Ser levels between any of the groups which may suggest that the catabolic pathway is not dependent on tryptophan hydroxylase. Additional studies are being initiated to further investigate the role of IDO/Trp pathway in MM pathogenesis as well as better understand its potential prognostic and predictive impact in currently used MM therapies. DisclosuresNo relevant conflicts of interest to declare.

Exploring Exercise- and Context-Induced Peptide Changes in Mice by Quantitative Mass Spectrometry.

Recent research suggests that exercise may help facilitate abstinence from cocaine addiction, though the mechanisms are not well understood. In mice, wheel running accelerates the extinction of conditioned place preference (CPP) for cocaine, providing an animal model for evaluating potential neurological mechanisms. The objective of this study was to quantify dynamic changes in endogenous peptides in the amygdala and dentate gyrus of the hippocampus in mice exposed to a context paired with the effects of cocaine, and in response to exercise. Male C57BL/6J mice conditioned to cocaine were housed with or without running wheels for 30 days. Following a CPP test and final exposure to either a cocaine- or saline-associated context, peptides were measured in brain tissue extracts using label-free matrix-assisted laser desorption/ionization mass spectrometry (MS) and stable isotopic labeling with liquid chromatography and electrospray ionization MS. CPP in mice was significantly reduced with running, which correlated to decreased myelin basic protein derivatives in the dentate gyrus extracts, possibly reflecting increased unmyelinated granule neuron density. Exposure to a cocaine-paired context increased hemoglobin-derived peptides in runners and decreased an actin-derived peptide in sedentary animals. These results allowed us to characterize a novel set of biomarkers that are responsive to exercise in the hippocampus and in a cocaine-paired context in the amygdala.

The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications

BackgroundTranslating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study.MethodsWe defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers.ResultsThe most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more.ConclusionIt is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.

Nuevos biomarcadores en la terapia de resincronización cardiaca. El factor de crecimiento hepatocitario es un predictor de los resultados clínicos

Introduction and objectivesCardiac resynchronization therapy (CRT) is beneficial for selected heart failure (HF) patients, although nonresponse to therapy is still prevalent. We investigated a set of novel biomarkers associated with various pathophysiological pathways of HF. Our purpose was to assess their ability to predict clinical outcomes after CRT. MethodsWe studied 136 chronic HF patients undergoing CRT. We measured the plasma levels of fractalkine, pentraxin-3, hepatocyte growth factor (HGF), carbohydrate antigen-125, and matrix metalloproteinase-9 before and 6 months after CRT. The primary endpoint of the study was 5-year all-cause mortality, and we considered the absence of 6-month reverse remodelling (defined as at least a 15% decrease in end-systolic volume) as a secondary endpoint. ResultsFifty-eight patients died during the 5-year follow-up period and 66 patients were categorized as nonresponders. In multivariable models, only an increased HGF was an independent predictor of both mortality (HR, 1.35; 95%CI, 1.11-1.64; P=.003; per 1 standard deviation increase) and the absence of reverse remodelling (OR, 1.83; 95%CI, 1.10-3.04; P=.01; per 1 standard deviation increase). Applying HGF to the basic multivariable model of both mortality (net reclassification improvement=0.69; 95%CI, 0.39-0.99; P<.0001; integrated discrimination improvement=0.06; 95%CI, 0.02-0.11) and reverse remodelling (net reclassification improvement=0.39; 95%CI, 0.07-0.71; P=.01; integrated discrimination improvement=0.03; 95%CI, 0.00-0.06) resulted in a statistically significant reclassification and discrimination improvement. ConclusionsOf the investigated biomarkers, only HGF predicted clinical outcomes following CRT independently of other parameters. Reclassification analyses showed that HGF measurements could be useful in refining patient selection.Full English text available from: www.revespcardiol.org/en

Novel Biomarkers in Cardiac Resynchronization Therapy: Hepatocyte Growth Factor Is an Independent Predictor of Clinical Outcome

Introduction and objectivesCardiac resynchronization therapy (CRT) is beneficial for selected heart failure (HF) patients, although nonresponse to therapy is still prevalent. We investigated a set of novel biomarkers associated with various pathophysiological pathways of HF. Our purpose was to assess their ability to predict clinical outcomes after CRT. MethodsWe studied 136 chronic HF patients undergoing CRT. We measured the plasma levels of fractalkine, pentraxin-3, hepatocyte growth factor (HGF), carbohydrate antigen-125, and matrix metalloproteinase-9 before and 6 months after CRT. The primary endpoint of the study was 5-year all-cause mortality, and we considered the absence of 6-month reverse remodelling (defined as at least a 15% decrease in end-systolic volume) as a secondary endpoint. ResultsFifty-eight patients died during the 5-year follow-up period and 66 patients were categorized as nonresponders. In multivariable models, only an increased HGF was an independent predictor of both mortality (HR, 1.35; 95%CI, 1.11-1.64; P=.003; per 1 standard deviation increase) and the absence of reverse remodelling (OR, 1.83; 95%CI, 1.10-3.04; P=.01; per 1 standard deviation increase). Applying HGF to the basic multivariable model of both mortality (net reclassification improvement=0.69; 95%CI, 0.39-0.99; P<.0001; integrated discrimination improvement=0.06; 95%CI, 0.02-0.11) and reverse remodelling (net reclassification improvement=0.39; 95%CI, 0.07-0.71; P=.01; integrated discrimination improvement=0.03; 95%CI, 0.00-0.06) resulted in a statistically significant reclassification and discrimination improvement. ConclusionsOf the investigated biomarkers, only HGF predicted clinical outcomes following CRT independently of other parameters. Reclassification analyses showed that HGF measurements could be useful in refining patient selection.

Gene and Protein Expression Profiles in a Mouse Model of Collagen-Induced Arthritis.

The risk of rheumatoid arthritis (RA), an autoimmune disease, in the elderly population increases along with that of atherosclerosis, cardiovascular disease, type 2 diabetes, and Alzheimer's disease. Identifying specific biomarkers for RA can clarify the underlying molecular mechanisms and can aid diagnosis and patient care. To this end, the present study investigated the genes and proteins that are differentially expressed in RA using a mouse collagen-induced arthritis (CIA) model. We performed gene microarray and proteome array analyses using blood samples from the mice and found that 50 genes and 24 proteins were upregulated and 48 genes were downregulated by more than 2-fold in the CIA model relative to the control. The gene microarray and proteome array results were validated by evaluating the expression levels of select genes and proteins by real-time PCR and western blotting, respectively. We found that the level of integrin α2, which has not been previously reported as a biomarker of RA, was significantly increased in CIA mice as compared to controls. These findings provide a set of novel biomarkers that can be useful for diagnosing and evaluating the progression of RA.

Response of Rhizobium to Cd exposure: A volatile perspective

The volatile metabolome of Rhizobium sp. strain E20-8 exposed to three concentrations of cadmium (2.5, 5.0 and 7.5 μM) was screened using comprehensive two-dimensional gas chromatography coupled to time of flight mass spectrometry (GC × GC–ToFMS), combined with headspace solid phase microextraction (HS-SPME). Cd exposure induced a global increase in the concentration of volatile organic compounds (VOCs) both intra and extracellularly. Peak areas of several linear alkanes, ketones, aldehydes, alcohols, terpenic and volatile sulfur compounds, and one ester (ethyl acetate), were especially increased when compared with the control condition (no Cd). These compounds might originate from the metabolization of toxic membrane peroxidation products, the proteolysis of oxidized proteins or the alteration of metabolic pathways, resulting from the oxidative stress imposed by Cd. Several VOCs are related to oxidative damage, but the production of VOCs involved in antioxidant response (menthol, α-pinene, dimethyl sulfide, disulfide and trisulfide, 1-butanol and 2-butanone) and in cell aggregation (2,3-butanedione, 3-methyl-1-butanol and 2-butanone) is also observed. These results bring new information that highlights the role of VOCs on bacteria response to Cd stress, identify a novel set of biomarkers related with metal stress and provide information to be applied in biotechnological and remediation contexts.

138P - Detection of microsatellite instability (MSI) in colorectal cancer samples with the automated Idylla MSI Test

Background: Detection of microsatellite instability (MSI) is recommended for all colorectal cancer (CRC) patients. Current clinical reference methods to detect MSI stain for mismatch repair proteins or analyze frequently mutated DNA repeat regions. The Idylla MSI Test is being developed using a unique set of novel biomarkers (Zhao et al. 2014; eLife) capable of faster detection with greater specificity and selectivity compared to current methods. Methods: To assess the suitability of the novel marker set to detect MSI status in CRC, we profiled 8 or more markers in 870 CRC samples. Several clinical sites and different ethnic groups (Afro American, Caucasian, East-Asian, Hispanic and Indian) were included to assess robustness of marker selection. Repeat length was determined on FFPE DNA by PCR followed by melting curve analysis. Two-hundred and one samples were additionally screened with a reference methodology for MSI detection (Promega MSI analysis system). Results: Hundred fifty-three samples (17.6%) were classified as MSI-H and 693 samples (79.7%) as MSS with the novel set of biomarkers, while 24 samples (2.8%) could not be classified. Concordance analysis was performed on 201 samples. The overall percent agreement with results available for both methods (173/201) was 93.6%. 11/173 (6.4%) were scored MSI-H for Idylla and MSS for the reference method; conversely no MSI-H cases for the reference method and MSS for Idylla were detected. 24/201 (11.9%) samples failed with the reference method, even after repeat testing, while only 8/201 (4.0%) samples failed with the Idylla methodology. Conclusions: This study on a diverse set of CRC samples successfully demonstrated the validity of the novel MSI biomarkers to discriminate between MSI-H and MSS status. The Idylla MSI Test is currently under development on the most performant markers. Compatibility with the fully integrated Idylla platform will allow providing accurate and reliable results, with actionable results generated within 150 minutes from just one tumor FFPE slice (no reference sample required). Legal entity responsible for the study: Biocartis NV Funding: None Disclosure: G. Maertens, B. De Craene, E. Rondelez, K. Peeters, L. Vandenbroeck, L. Van Puymbroeck, G. Vandercruyssen, E. Sablon: Biocartis Employee.

Physical activity initiated by employer induces improvements in a novel set of biomarkers of inflammation: an 8-week follow-up study

PurposeWe investigated the level of pro- and anti-inflammatory biomarkers before and after 8 weeks of unsupervised physical activity (PA) initiated by employer.MethodsDuring autumn 2014, background data, blood samples and self-reported exercise level were collected from 76 men and 41 women in a Norwegian road maintenance company. Monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), leptin, adiponectin, p-selectin and CD40 ligand (CD40L) were analyzed. {dot V}{{rm{O}}_{{rm{2max}}}} was measured in a subgroup of 50 subjects.ResultsWith reference point of exercise ≤1 time/week, we found that participants who exercised 2–3 times/week had higher {dot V}{{rm{O}}_{{rm{2max}}}} values (5.6 mL kg−1 min−1; 95% CI [1.3, 9.9]). MCP-1 was lower in those who exercised ≥ 4 times/week (−81.98 pg/ml [−142.9, −21.0]). IL-6 and p-selectin levels were lower in females who exercised ≥4 times/week (−1.04 pg/ml [−2.04, −0.03] and −13.75 ng/ml [−24.03, −3.48]). Leptin was lower in participants who exercised 2–3 times/week (−0.39 µg/ml ln [−0.68, −0.09]) and ≥4 times/week (−0.69 µg/ml ln [−1.10, −0.28]). During follow-up, {dot V}{{rm{O}}_{{rm{2max}}}} increased (2.9 mL kg−1 min−1 [1.5, 4.3]), while p-selectin and CD40L decreased (−2.33 ng/ml [−3.78, −0.87] and 718.14 ng/ml [−1368, −68]). MCP-1 levels decreased among men (−32.70 pg/ml [−51.21, −14.19]). A joint analysis of all biomarkers (inversed adiponectin) showed that those who exercised ≥4 times/week at baseline had lower total levels of biomarkers and that total biomarker levels decreased during follow-up.ConclusionsExercising several times a week was associated with less inflammation compared to exercising once a week or less. During the 8-week follow-up, total levels of biomarkers of inflammation improved.