Abstract: A metabolic profiling approach for identifying biomarkers that provide highly sensitive and specific colorectal cancer (CRC) detection and monitoring using serum samples. The methods can be used for distinguishing CRC patients from both healthy controls and polyp patients, as well as to monitor disease progression or response to therapy. Receiver operator characteristic curves generated based on these models showed high sensitivities for differentiating CRC patients from healthy controls or polyp patients, good specificities, low false discovery rates, and excellent areas under the curve were obtained. Monte Carlo cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Abstract: Methods for the detection and screening of hepatocellular carcinoma (HCC) patients and for the monitoring of HCC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions, such as HCV infections, to HCC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of HCC, and can also be used to classify HCV infections that are regarded as precursors of HCC.

Abstract: Methods for detecting and measuring metabolic changes useful in the detection of cancer, and in differentiating between ovarian cancer and benign ovarian tumor are described, as well as the unexpected and valuable combination of detecting both lipidomic and aqueous metabolites. Two independent LC-MS-based metabolomics platforms, including a global lipidomics approach, were used to screen for differentially abundant plasma metabolites between cases with serous ovarian carcinoma and controls with benign serous ovarian tumor. The identified biomarkers can be used to distinguish between ovarian cancer and benign tumors. Standards and kits for use with the methods for detecting cancer are also provided.

Abstract: The present disclosure relates to a panel of a plurality of metabolite species that is useful for the identification or detection of subjects having pancreatic cancer, including methods for identifying such metabolic biomarkers within biological samples. The disclosure also includes a statistical model for predicting the presence of pancreatic cancer in a subject's biofluid by quantifying and comparing positive and negative fold changes in metabolite species' concentration; comparing the subject's metabolite species' concentrations to a predetermined value.

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HGD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HGD), which are widely regarded as precursors of EAC.

Abstract: A metabolic profiling approach for identifying biomarkers that provide highly sensitive and specific colorectal cancer (CRC) detection and monitoring using serum samples. The methods can be used for distinguishing CRC patients from both healthy controls and polyp patients, as well as to monitor disease progression or response to therapy. Receiver operator characteristic curves generated based on these models showed high sensitivities for differentiating CRC patients from healthy controls or polyp patients, good specificities, low false discovery rates, and excellent areas under the curve were obtained. Monte Carlo cross validation (MCCV) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Abstract: Globally Optimized Targeted (GOT)-MS, combines many of the advantages of targeted detection and global profiling in metabolomics analysis, including the capability to detect unknowns, broad metabolite coverage, and excellent quantitation. A global search of precursor and product ions using a single triple quadrupole (QQQ) mass spectrometer includes SIM incremental scanning or incremental MS scanning performed in the mass range of 40-2000 Da, followed by tandem MS/MS scanning with incremental collision energy for precursor ions to profile product ions.

Abstract: Methods for the detection and screening of hepatocellular carcinoma (HCC) patients and for the monitoring of HCC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions, such as HCV infections, to HCC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of HCC, and can also be used to classify HCV infections that are regarded as precursors of HCC.

Abstract: The present disclosure relates to a panel of a plurality of metabolite species that is useful for the identification or detection of subjects having pancreatic cancer, including methods for identifying such metabolic biomarkers within biological samples. The disclosure also includes a statistical model for predicting the presence of pancreatic cancer in a subject's biofluid by quantifying and comparing positive and negative fold changes in metabolite species' concentration; comparing the subject's metabolite species' concentrations to a predetermined value.

Abstract: The present disclosure relates to a panel of metabolite species that is useful for forecasting the outcome of preoperative chemotherapy for the treatment of breast cancer, including methods for identifying and using such metabolite species that can be measured in biological samples taken before treatment. In preferred embodiments, a method of forecasting a treatment outcome before subjecting a breast cancer patient to preoperative chemotherapy is disclosed that includes measuring the concentration of at least one metabolite species in a sample of a biofluid taken from the breast cancer patient before preoperative chemotherapy treatment.

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HGD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HGD), which are widely regarded as precursors of EAC.

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HGD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HGD), which are widely regarded as precursors of EAC.

Abstract: A method for differentiating complex biological samples, each sample having one or more metabolite species. The method comprises producing a mass spectrum by subjecting the sample to a mass spectrometry analysis, the mass spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting the individual spectral peaks of the mass spectrum to a statistical pattern recognition analysis; identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass spectrum; and assigning the sample into a defined sample class.

Abstract: A method for differentiating complex mixtures each having one or more chemical species is provided. The method comprises producing a sample NMR spectrum by subjecting a mixture to a selective spectroscopy process, wherein the NMR spectrum has individual spectral peaks representative of the one or more chemical species within the mixture. The one or more chemical species within the mixture are identified by analyzing the individual spectral peaks, and the individual spectral peaks are then subjected to a multivariate statistical analysis.

Abstract: Methods for the detection and screening of esophageal adenocarcinoma (EAC) patients and for the monitoring of EAC treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. In other aspects, methods for detection and screening for the progression of high-risk conditions (BE and HOD) to EAC and to monitoring treatment using a panel or panels of small molecule metabolite biomarkers are disclosed. The biomarkers are sensitive and specific for the detection of EAC, and can also be used to classify Barrett's esophagus (BE) and high-grade dysplasia (HOD), which are widely regarded as precursors of EAC.

Abstract: Results of studies of nucleosides in biofluid specimens from patients with esophageal adenocarcinoma and related disorders have identified five biomarkers of the conditions: 1-methyladenosine, N2,N2-dimethylguanosine, N2-methylguanosine, cytidine and uridine. In certain embodiments, methods of measuring these biomarkers and kits for measuring these biomarkers are provided.

Abstract: A method for differentiating complex mixtures each having one or more chemical species is provided. The method comprises producing a sample NMR spectrum by subjecting a mixture to a selective spectroscopy process, wherein the NMR spectrum has individual spectral peaks representative of the one or more chemical species within the mixture. The one or more chemical species within the mixture are identified by analyzing the individual spectral peaks, and the individual spectral peaks are then subjected to a multivariate statistical analysis.

Abstract: A method is provided for the parallel identification of one or more metabolite species within a biological sample. The method comprises analyzing the sample to produce a spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting each of the individual spectral peaks to a statistical pattern recognition analysis to identify the one or more metabolite species contained within the sample; and identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the spectra.

Abstract: A method for differentiating complex biological samples, each sample having one or more metabolite species. The method comprises producing a mass spectrum by subjecting the sample to a mass spectrometry analysis, the mass spectrum containing individual spectral peaks representative of the one or more metabolite species contained within the sample; subjecting the individual spectral peaks of the mass spectrum to a statistical pattern recognition analysis; identifying the one or more metabolite species contained within the sample by analyzing the individual spectral peaks of the mass spectrum; and assigning the sample into a defined sample class.

Abstract: A method for differentiating complex mixtures each having one or more chemical species is provided. The method comprises producing a sample NMR spectrum by subjecting a mixture to a selective spectroscopy process, wherein the NMR spectrum has individual spectral peaks representative of the one or more chemical species within the mixture. The one or more chemical species within the mixture are identified by analyzing the individual spectral peaks, and the individual spectral peaks are then subjected to a multivariate statistical analysis.