Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library.

MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies.

Based on theoretically calculated comprehensive lipid libraries, in lipidomics as many as 1000 multiple reaction monitoring (MRM) transitions can be monitored for each single run. On the other hand, lipid analysis from each MRM chromatogram requires tremendous manual efforts to identify and quantify lipid species. Isotopic peaks differing by up to a few atomic masses further complicate analysis.

MRMPROBS suite for metabolomics using large-scale MRM assays.

Unlabelled: We developed new software environment for the metabolome analysis of large-scale multiple reaction monitoring (MRM) assays. It supports the data format of four major mass spectrometer vendors and mzML common data format. This program provides a process pipeline from the raw-format import to high-dimensional statistical analyses.

A computational drug metabolite detection using the stable isotopic mass-shift filtering with high resolution mass spectrometry in pioglitazone and flurbiprofen.

The identification of metabolites in drug discovery is important. At present, radioisotopes and mass spectrometry are both widely used. However, rapid and comprehensive identification is still laborious and difficult.

MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics.

We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work.

Nested case control study of proteomic biomarkers for interstitial lung disease in Japanese patients with non-small-cell lung cancer treated with erlotinib: a multicenter phase IV study (JO21661).

Background: Interstitial lung disease (ILD) is a serious adverse drug reaction associated with epidermal growth factor receptor tyrosine-kinase inhibitors (EGFR TKIs). Its risk factors are yet to be fully elucidated. We sought to identify proteomic biomarkers associated with ILD development in erlotinib-treated Japanese patients with non-small-cell lung cancer (NSCLC) to build predictive models.

Identification by differential tissue proteome analysis of talin-1 as a novel molecular marker of progression of hepatocellular carcinoma.

Objective: Hepatocellular carcinoma (HCC) is characterized by a multistage process of tumor progression. This study addressed its molecular features to identify novel protein candidates involved in HCC progression.

Methods: Using liquid chromatography-tandem mass spectrometry, proteomes of 4 early HCCs and 4 non-HCC tissues derived from 2 cases of liver transplant surgery were compared with respect to the separation profiles of their tryptic peptides.

Proteomic biomarkers for acute interstitial lung disease in gefitinib-treated Japanese lung cancer patients.

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan.

i-RUBY: a novel software for quantitative analysis of highly accurate shotgun-proteomics liquid chromatography/tandem mass spectrometry data obtained without stable-isotope labeling of proteins.

We developed a novel software named i-RUBY (identification-Related qUantification-Based strategY algorithm for liquid chromatography/tandem mass spectrometry (LC/MS/MS) data) that enables us to perform fully automatic ion current-based spectral feature analysis of highly accurate data obtained by LC/MS/MS. At the 1st step, this software utilizes accurate peptide/protein identification information for peak detection and peak matching among measurements. Then, at the 2nd step, it picks yet unidentified peaks and matches them to the peaks identified at the 1st step by a linear interpolation algorithm.

Synuclein-gamma is closely involved in perineural invasion and distant metastasis in mouse models and is a novel prognostic factor in pancreatic cancer.

Purpose: Perineural invasion is associated with the high incidence of local recurrence and a dismal prognosis in pancreatic cancer. We previously reported a novel perineural invasion model and distinguished high- and low-perineural invasion groups in pancreatic cancer cell lines. This study aimed to elucidate the molecular mechanism of perineural invasion.

Personalized medicine and proteomics: lessons from non-small cell lung cancer.

Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches.

De novo peptide sequencing using ion peak intensity and amino acid cleavage intensity ratio.

Motivation: Peptide-sequencing methods by mass spectrum use the following two approaches: database searching and de novo sequencing. The database-searching approach is convenient; however, in cases wherein the corresponding sequences are not included in the databases, the exact identification is difficult. On the other hand, in the case of de novo sequencing, no preliminary information is necessary; however, continuous amino acid sequence peaks and the differentiation of these peaks are required.

Disease proteomics toward bedside reality.

The human genome has been sequenced, and investigation of its products has become possible in a sequence-based framework. More than 200,000 protein species are expressed in the body from approximately 30000 human genes. The term proteome, coined as a linguistic equivalent to the concept of genome, is used to describe the complete set of proteins that is expressed, and modified following expression, by the entire genome in a cell at any one time.