Detection of Hepatocellular Carcinoma in Hepatitis C Patients: Biomarker Discovery by LC-MS

Hepatocellular carcinoma (HCC) accounts for most cases of liver cancer worldwide; contraction of hepatitis C (HCV) is considered a major risk factor for liver cancer even when individuals have not developed formal cirrhosis. Global, untargeted metabolic profiling methods were applied to serum samples from patients with either HCV alone or HCC (with underlying HCV). The main objective of the study was to identify metabolite based biomarkers associated with cancer risk, with the long term goal of ultimately improving early detection and prognosis. Serum global metabolite profiles from patients with HCC (n=37) and HCV (n=21) were obtained using high performance liquid chromatography-mass spectrometry (HPLC-MS) methods. The selection of statistically significant metabolites for partial least-squares discriminant analysis (PLS-DA) model creation based on biological and statistical significance was contrasted to that of a traditional approach utilizing p-values alone. A PLS-DA model created using the former approach resulted in a model with 92% sensitivity, 95% specificity, and an AUROC of 0.93. A series of PLS-DA models iteratively utilizing three to seven metabolites that were altered significantly (p<0.05) and sufficiently (FC≤0.7 or FC≥1.3) showed the best performance using p-values alone, the PLS-DA model was capable of generating 73% sensitivity, 95% specificity, and an AUROC of 0.92. Metabolic profiles derived from LC-MS readily distinguish patients with HCC and HCV from those with HCV only. Differences in the metabolic profiles between highrisk individuals and HCC indicate the possibility of identifying the early development of liver cancer in at risk patients. The use of biological significance as a selection process prior to PLSDA modeling may offer improved probabilities for translation of newly discovered biomarkers to clinical application

Esophageal Cancer Metabolite Biomarkers Detected by LC-MS and NMR Methods

Background: Esophageal adenocarcinoma (EAC) is a rarely curable disease and is rapidly rising worldwide in incidence. Barret’s esophagus (BE) and high-grade dysplasia (HGD) are considered major risk factors for invasive adenocarcinoma. In the current study, unbiased global metabolic profiling methods were applied to serum samples from patients with EAC, BE and HGD, and healthy individuals, in order to identify metabolite based biomarkers associated with the early stages of EAC with the goal of improving prognostication. Methodology/Principal Findings: Serum metabolite profiles from patients with EAC (n = 67), BE (n = 3), HGD (n = 9) and healthy volunteers (n = 34) were obtained using high performance liquid chromatography-mass spectrometry (LC-MS) methods. Twelve metabolites differed significantly (p,0.05) between EAC patients and healthy controls. A partial leastsquares discriminant analysis (PLS-DA) model had good accuracy with the area under the receiver operative characteristic curve (AUROC) of 0.82. However, when the results of LC-MS were combined with 8 metabolites detected by nuclear magnetic resonance (NMR) in a previous study, the combination of NMR and MS detected metabolites provided a much superior performance, with AUROC = 0.95. Further, mean values of 12 of these metabolites varied consistently from healthy controls to the high-risk individuals (BE and HGD patients) and EAC subjects. Altered metabolic pathways including a number of amino acid pathways and energy metabolism were identified based on altered levels of numerous metabolites

Rapid Screening of Ellagitannins in Natural Sources via Targeted Reporter Ion Triggered Tandem Mass Spectrometry

Complex biomolecules present in their natural sources have been difficult to analyze using traditional analytical approaches. Ultrahigh-performance liquid chromatography (UHPLC-MS/MS) methods have the potential to enhance the discovery of a less well characterized and challenging class of biomolecules in plants, the ellagitannins. We present an approach that allows for the screening of ellagitannins by employing higher energy collision dissociation (HCD) to generate reporter ions for classification and collision-induced dissociation (CID) to generate unique fragmentation spectra for isomeric variants of previously unreported species. Ellagitannin anions efficiently form three characteristic reporter ions after HCD fragmentation that allows for the classification of unknown precursors that we call targeted reporter ion triggering (TRT). We demonstrate how a tandem HCD-CID experiment might be used to screen natural sources using UHPLC-MS/MS by application of 22 method conditions from which an optimized data-dependent acquisition (DDA) emerged. The method was verified not to yield false-positive results in complex plant matrices. We were able to identify 154 non-isomeric ellagitannins from strawberry leaves, which is 17 times higher than previously reported in the same matrix. The systematic inclusion of CID spectra for isomers of each species classified as an ellagitannin has never been possible before the development of this approach

Gas phase analysis of biomolecular ions in a quadrupole ion trap: Protein analysis and instrumentation

Ion/ion reactions were performed in a quadrupole mass spectrometer in order to facilitate top down protein identification, charge reduction, and charge inversion. The first portion of the dissertation is focused on original instrumental development of an electrospray interface optimized to efficiently transmit ions generated from electrospray through the ring electrode. Additionally, emitter voltage manipulation schemes to enable more robust ion/ion reaction capacity from duel emitters on a single source were also developed. The second portion of the dissertation focuses on a series of proton transfer ion/ion reactions that are used for distinctly different applications. A top-down protein identification strategy for complex protein mixtures was derived from post ion/ion mass spectra formed from a series of ion-parking, collision-induced dissociation, and proton transfer reaction steps. Simple proton hydrate clusters were utilized to facilitate proton transfer reactions that successfully charge reduced intact Arixtra molecules by partitioning some portion of the ion/ion reaction exothermicity into the desolvation of the proton hydrates. Finally, a sequential ion/ion reaction scheme was used to generate radical [M-2H]-. protein anions that were charge inverted [M]+. cations via a proton transfer reaction

Fast Additive Noise Steganalysis

This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is created by adding a pseudo-noise to a coverimage. This addition predictably alters the joint histogram of the image. In color images it has been shown that this alteration can be detected using a three-dimensional Fast Fourier Transform (FFT) of the histogram. As the computation of this transform is typically very intensive, a method to reduce the required processing is desirable. By considering the histogram between pairs of channels in RGB images, three separate two-dimensional FFTs are used in place of the original three-dimensional FFT. This method is shown to o#er computational savings of approximately two orders of magnitude while only slightly decreasing classification accuracy

The perceived importance of veal meat attributes in consumer choice decisions

Animal scientists have recently found a way to produce extremely pale grain-fed veal, thus achieving high quality grade, while averting concerns over unethical treatment and medication residues in milk-fed veal production. Consumers, however, may reject pale cuts of veal labeled as “grain-fed.” This article uses questionnaire data from six groceries in the province of Quebec, Canada, to investigate frequency of veal purchases and perceived importance of price, color, and production type as determinants of veal purchases. Consumers do not appear to have clear preferences for milk-fed veal characteristics. Frequency of consumption and importance of veal meat attributes were influenced more by variables of habit formation than by price, income, or education. The veal industry might be advised to encourage consumption of veal as a means to diversify consumers' meat menu. &lsqb;Econ-Lit citations: D120, Q130&rsqb; © 2001 John Wiley & Sons, Inc.

Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer

Breast cancer is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. As an example, only some women will benefit from chemotherapy. Identifying patients who will respond to chemotherapy and thereby improve their long‐term survival has important implications to treatment protocols and outcomes, while identifying non responders may enable these patients to avail themselves of other investigational approaches or other potentially effective treatments. In this study, serum metabolite profiling was performed to identify potential biomarker candidates that can predict response to neoadjuvant chemotherapy for breast cancer. Metabolic profiles of serum from patients with complete (n = 8), partial (n = 14) and no response (n = 6) to chemotherapy were studied using a combination of nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography–mass spectrometry (LC–MS) and statistical analysis methods. The concentrations of four metabolites, three (threonine, isoleucine, glutamine) from NMR and one (linolenic acid) from LC–MS were significantly different when comparing response to chemotherapy. A prediction model developed by combining NMR and MS derived metabolites correctly identified 80% of the patients whose tumors did not show complete response to chemotherapy. These results show promise for larger studies that could result in more personalized treatment protocols for breast cancer patients., ► Metabolomics differentiates response to neoadjuvant breast cancer chemotherapy.► Four serum metabolites are found to correlate with response to chemotherapy.► A 4‐metabolite model identifies 80% of the patients not showing complete response.► Additional studies on larger patient cohorts are needed to validate the findings

Altered metabolism pathways for the most relevant metabolic differences between patients with EAC and control subjects.

<p>Blue boxes indicate metabolites that are up-regulated in EAC patient sera, while red boxes indicate metabolites that are down-regulated. Metabolites in bold showed mean levels that changed progressively from control to high-risk esophagus diseases (BE and HGD) and ultimately EAC.</p

Comparison of sensitivity, specificity and AUROC values from different PLS-DA models using differentiating metabolites detected individually by NMR or MS and their combination.

<p>aTrending markers that progressively change in their levels between EAC, high risk (BE and HGD) and healthy controls (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030181#pone-0030181-g003" target="_blank">Figure 3</a>).</p