N-acetylgalactosamine-6-sulfatase (GALNS), Similar to Glycodelin, Is a Potential General Biomarker for Multiple Malignancies.

BACKGROUND/AIM: The aim of this study was to evaluate N-acetylgalactosamine-6-sulfatase (GALNS) as a new biomarker candidate for detecting lung cancer. Glycodelin or PAEP, the serum levels of which are known to be elevated in lung and other cancers, served as a benchmark for comparison. PATIENTS AND METHODS: A total of 170 serum samples from healthy controls and patients with pneumonia, lung cancer, breast cancer, colon cancer, liver cancer, and head and neck cancer were analyzed for the levels of GALNS and PAEP by ELISA. RESULTS: The median serum levels of GALNS and PAEP in all cancer types as well as pneumonia patients were significantly higher than those of the healthy controls. CONCLUSION: In addition to previously known cancers, the median serum levels of PAEP were also found to be higher in liver and head and neck cancer patients. GALNS and PAEP are promising general biomarkers for multiple cancers and deserve further evaluation.

Meta-analytical biomarker search of EST expression data reveals three differentially expressed candidates.

BACKGROUND: Researches have been conducted for the identification of differentially expressed genes (DEGs) by generating and mining of cDNA expressed sequence tags (ESTs) for more than a decade. Although the availability of public databases make possible the comprehensive mining of DEGs among the ESTs from multiple tissue types, existing studies usually employed statistics suitable only for two categories. Multi-class test has been developed to enable the finding of tissue specific genes, but subsequent search for cancer genes involves separate two-category test only on the ESTs of the tissue of interest. This constricts the amount of data used. On the other hand, simple pooling of cancer and normal genes from multiple tissue types runs the risk of Simpson's paradox. Here we presented a different approach which searched for multi-cancer DEG candidates by analyzing all pertinent ESTs in all categories and narrowing down the cancer biomarker candidates via integrative analysis with microarray data and selection of secretory and membrane protein genes as well as incorporation of network analysis. Finally, the differential expression patterns of three selected cancer biomarker candidates were confirmed by real-time qPCR analysis. RESULTS: Seven hundred and twenty three primary DEG candidates (p-value < 0.05 and lower bound of confidence interval of odds ratio ≥ 1.65) were selected from a curated EST database with the application of Cochran-Mantel-Haenszel statistic (CMH). GeneGO analysis results indicated this set as neoplasm enriched. Cross-examination with microarray data further narrowed the list down to 235 genes, among which 96 had membrane or secretory annotations. After examined the candidates in protein interaction network, public tissue expression databases, and literatures, we selected three genes for further evaluation by real-time qPCR with eight major normal and cancer tissues. The higher-than-normal tissue expression of COL3A1, DLG3, and RNF43 in some of the cancer tissues is in agreement with our in silico predictions. CONCLUSIONS: Searching digitized transcriptome using CMH enabled us to identify multi-cancer differentially expressed gene candidates. Our methodology demonstrated simultaneously analysis for cancer biomarkers of multiple tissue types with the EST data. With the revived interest in digitizing the transcriptomes by NGS, cancer biomarkers could be more precisely detected from the ESTs. The three candidates identified in this study, COL3A1, DLG3, and RNF43, are valuable targets for further evaluation with a larger sample size of normal and cancer tissue or serum samples.

Automated lipid A structure assignment from hierarchical tandem mass spectrometry data.

Infusion-based electrospray ionization (ESI) coupled to multiple-stage tandem mass spectrometry (MS(n)) is a standard methodology for investigating lipid A structural diversity (Shaffer et al. J. Am. Soc. Mass. Spectrom. 18(6), 1080-1092, 2007). Annotation of these MS(n) spectra, however, has remained a manual, expert-driven process. In order to keep up with the data acquisition rates of modern instruments, we devised a computational method to annotate lipid A MS(n) spectra rapidly and automatically, which we refer to as hierarchical tandem mass spectrometry (HiTMS) algorithm. As a first-pass tool, HiTMS aids expert interpretation of lipid A MS(n ) data by providing the analyst with a set of candidate structures that may then be confirmed or rejected. HiTMS deciphers the signature ions (e.g., A-, Y-, and Z-type ions) and neutral losses of MS(n) spectra using a species-specific library based on general prior structural knowledge of the given lipid A species under investigation. Candidates are selected by calculating the correlation between theoretical and acquired MS(n) spectra. At a false discovery rate of less than 0.01, HiTMS correctly assigned 85% of the structures in a library of 133 manually annotated Francisella tularensis subspecies novicida lipid A structures. Additionally, HiTMS correctly assigned 85% of the structures in a smaller library of lipid A species from Yersinia pestis demonstrating that it may be used across species.

Interrogation of alternative splicing events in duplicated genes during evolution.

BACKGROUND: Gene duplication provides resources for developing novel genes and new functions while retaining the original functions. In addition, alternative splicing could increase the complexity of expression at the transcriptome and proteome level without increasing the number of gene copy in the genome. Duplication and alternative splicing are thought to work together to provide the diverse functions or expression patterns for eukaryotes. Previously, it was believed that duplication and alternative splicing were negatively correlated and probably interchangeable. RESULTS: We look into the relationship between occurrence of alternative splicing and duplication at different time after duplication events. We found duplication and alternative splicing were indeed inversely correlated if only recently duplicated genes were considered, but they became positively correlated when we took those ancient duplications into account. Specifically, for slightly or moderately duplicated genes with gene families containing 2 - 7 paralogs, genes were more likely to evolve alternative splicing and had on average a greater number of alternative splicing isoforms after long-term evolution compared to singleton genes. On the other hand, those large gene families (contain at least 8 paralogs) had a lower proportion of alternative splicing, and fewer alternative splicing isoforms on average even when ancient duplicated genes were taken into consideration. We also found these duplicated genes having alternative splicing were under tighter evolutionary constraints compared to those having no alternative splicing, and had an enrichment of genes that participate in molecular transducer activities. CONCLUSIONS: We studied the association between occurrences of alternative splicing and gene duplication. Our results implicate that there are key differences in functions and evolutionary constraints among singleton genes or duplicated genes with or without alternative splicing incidences. It implies that the gene duplication and alternative splicing may have different functional significance in the evolution of speciation diversity.

DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection.

BACKGROUND: Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired. RESULTS: An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases. CONCLUSIONS: DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from http://140.109.42.19:16080/dodo_web/home.htm.

Nucleotide-binding domain of phosphoglycerate kinase 1 reduces tumor growth by suppressing COX-2 expression.

Phosphoglycerate kinase 1 (PGK-1) is a multifunctional protein that is involved in the glycolytic pathway and the generation of the angiogenesis inhibitor angiostatin. In a previous study, we showed that the overexpression of full-length PGK-1 in Lewis lung carcinoma (LLC-1) can reduce tumor growth in vivo by downregulation of COX-2 expression. Phosphoglycerate kinase 1 has two functional domains: a catalytic domain (CD); and a nucleotide-binding domain (NBD). To identify the functional domain of PGK-1 responsible for its antitumor effects, we evaluated the tumorigenicity of LLC-1 cells overexpressing full-length PGK-1 (LLC-1/PGK), CD (LLC-1/CD), and NBD (LLC-1/NBD). Although no difference in tumor cell growth was observed in vitro, the tumor invasiveness was reduced in the LLC-1/PGK, LLC-1/CD, and LLC-1/NBD cells compared to parental LLC-1 cells in vivo. In addition, in vivo tumor growth retardation by LLC-1/CD and LLC-1/NBD cells was observed, similar to that by LLC-1/PGK cells. However, the reduced stability of COX-2 mRNA and downregulation of the COX-2 protein and its metabolite, prostaglandin E2, was only found in LLC-1/PGK and LLC-1/NBD cells. Low levels of COX-2 were also observed in the tumor mass formed by the modified cells when injected into mice. The results indicate that COX-2 suppression by PGK-1 is independent of its catalytic activity. COX-2 targeting by PGK-1 can be attributed to its NBD and is probably a result of the destabilization of COX-2 gene transcripts brought about by the mRNA-binding property of PGK-1.

Proteomic analysis of an extreme halophilic archaeon, Halobacterium sp. NRC-1.

Halobacterium sp. NRC-1 insoluble membrane and soluble cytoplasmic proteins were isolated by ultracentrifugation of whole cell lysate. Using an ion trap mass spectrometer equipped with a C18 trap electrospray ionization emitter/micro-liquid chromatography column, a number of trypsin-generated peptide tags from 426 unique proteins were identified. This represents approximately one-fifth of the theoretical proteome of Halobacterium. Of these, 232 proteins were found only in the soluble fraction, 165 were only in the insoluble membrane fraction, and 29 were in both fractions. There were 72 and 61% previously annotated proteins identified in the soluble and membrane protein fractions, respectively. Interestingly, 57 of previously unannotated proteins found only in Halobacterium NRC-1 were identified. Such proteins could be interesting targets for understanding unique physiology of Halobacterium NRC-1. A group of proteins involved in various metabolic pathways were identified among the expressed proteins, suggesting these pathways were active at the time the cells were collected. This data containing a list of expressed proteins, their cellular locations, and biological functions could be used in future studies to investigate the interaction of the genes and proteins in relation to genetic or environmental perturbations.