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Results for “pathway analysis”

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PubMed1991

[Effects of stimulation of arcuate nucleus on intragastric pressure and peripheral pathway analysis in rats].

The effect of electrical stimulation of arcuate nucleus (ARC) on intragastric pressure (IGP) was examined on 68 Wistar rats anaesthetized with urethan. The results were as follows: (1) Stimulation of ARC could induce an obvious decrease of IGP. (2) This effect was not blocked by atropine but partially by vagotomy. (3) Extirpation of celiac neural plexus or intramuscular injection of phentolamine could obviously reduce the suppression of IGP induced by ARC stimulation, but intramuscular injection of propranolol had no such effect. (4) After vagotomy plus extirpation of celiac neural plexus, IGP could still be made a decrease by stimulating ARC. In view of the present investigation, it is suggested that (1) Both sympathetic nerve and vagus are involved in the reduction of IGP induced by ARC stimulation, the former and the latter routes being respectively mediated by alpha-adrenoceptor and non-cholinergic, non-adrenergic fibres. (2) Humoral factors may be also involved in this effect of ARC stimulation.

Animals↗
PubMed1987

The role of protein structure in the mitochondrial import pathway. Analysis of the soluble F1-ATPase beta-subunit precursor.

A series of proteins containing defined internal and presequence deletions in the F1-ATPase beta-subunit precursor have been synthesized in vitro using a linked transcription-translation system. These different forms of the protein have been analyzed by the combination of gel filtration and in vitro mitochondrial import studies. These studies reveal that the soluble F1 beta-subunit precursor (55 kDa) forms a homooligomeric assembly of apparent molecular weight 230,000 on gel filtration analysis. The formation of this tetrameric beta-protein was dependent on the sequence between residues 122 and 144 of the precursor and was independent of the presence of a mitochondrial presequence within the first 19 residues of the precursor. When the tetrameric F1 beta-precursor was partially purified from the translation reaction it was incompetent for import into mitochondria. However, import of the partially purified beta-subunit could be restored by addition of reticulocyte lysate protein. In the absence of the tetramer-forming sequence, the protein behaved as an aggregate complex approximately 400 kDa in size. Formation of the high molecular weight aggregate and import into mitochondria was dependent upon a functional presequence at the amino terminus of the precursor. These studies are discussed in terms of the maintenance of an import competent structure for mitochondrial precursors and role of soluble factors in this process.

Amino Acid Sequence↗
PubMed2006

A new tumor suppressor DnaJ-like heat shock protein, HLJ1, and survival of patients with non-small-cell lung carcinoma.

BACKGROUND: We previously identified DnaJ-like heat shock protein (HLJ1) as a gene associated with tumor invasion. Here, we investigated the clinical significance of HLJ1 expression in non-small-cell lung cancer (NSCLC) patients and its role in cancer progression. METHODS: We induced HLJ1 overexpression or knockdown in human lung adenocarcinoma CL1-5 cells and analyzed cell proliferation, anchorage-independent growth, in vivo tumorigenesis, cell motility, invasion, and cell cycle progression. Expression of genes that act downstream of HLJ1 was examined by DNA microarray analysis, pathway analysis, and western blotting. We measured HLJ1 expression in tumors and adjacent normal tissues of 71 NSCLC patients by quantitative reverse transcription-polymerase chain reaction. Associations between HLJ1 expression and disease-free and overall survival were determined using the log-rank test and multivariable Cox proportional hazards regression analysis. Validation was performed in an independent cohort of 56 NSCLC patients. Loss of heterozygosity (LOH) mapping of the HLJ1 locus was analyzed in 48 paired microdissected NSCLC tumors. All statistical tests were two-sided. RESULTS: HLJ1 expression inhibited lung cancer cell proliferation, anchorage-independent growth, tumorigenesis, cell motility, and invasion, and slowed cell cycle progression through a novel STAT1/P21(WAF1) pathway that is independent of P53 and interferon. HLJ1 expression was lower in tumors than in adjacent normal tissue in 55 of 71 patients studied. NSCLC patients with high HLJI expressing tumors had reduced cancer recurrence (hazard ratio [HR] = 0.47; 95% confidence interval [CI] = 0.23 to 0.93; P = .03) and longer overall survival (HR = 0.38; 95% CI = 0.16 to 0.89; P = .03) than those with low-expressing tumors. Validation in the independent patient cohort confirmed the association between HLJ1 expression and patient outcome. LOH mapping revealed high frequencies (66.7% and 70.8%) of allelic loss and microsatellite instability (87.5% and 95.2%) of the HLJ1 locus at chromosome 1p31.1. CONCLUSIONS: HLJ1 is a novel tumor suppressor in NSCLC, and high HLJ1 expression is associated with reduced cancer recurrence and prolonged survival of NSCLC patients.

Biomarkers, Tumor↗
PubMed2003

An overview of data models for the analysis of biochemical pathways.

Biochemical pathways such as metabolic, regulatory or signal transduction pathways can be viewed as interconnected processes forming an intricate network of functional and physical interactions between molecular species in the cell. The amount of information available on such pathways for different organisms is increasing very rapidly. This is offering the possibility of performing various analyses on the structure of the full network of pathways for one organism as well as across different organisms, and has therefore generated interest in developing databases for storing and managing this information. Analysing these networks remains far from straightforward owing to the nature of the databases, which are often heterogeneous, incomplete or inconsistent. Pathway analysis is hence a challenging problem in systems biology and in bioinformatics. Various forms of data models have been devised for the analysis of biochemical pathways. This paper presents an overview of the types of models used for this purpose, concentrating on those concerned with the structural aspects of biochemical networks. In particular, the different types of data models found in the literature are classified using a unified framework. In addition, how these models have been used in the analysis of biochemical networks is described. This enables us to underline the strengths and weaknesses of the different approaches, as well as to highlight relevant future research directions.

Cell Physiological Phenomena↗
PubMed1999

Proteome Analysis: A Pathway to the Functional Analysis of Proteins.

The protein equivalent of genomes, proteomes are quantitative protein patterns of an organism, a cell, or a body fluid, and are determined by the development state and environmental parameters. Changes in protein expression and their consequences can be investigated at the molecular level and provide biologically relevant information not obtainable from experiments with mRNA.

Journal Article↗
PubMed2004

Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia.

BACKGROUND: Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). METHODS: Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. RESULTS: The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. CONCLUSIONS: The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity.

Acute Disease↗
PubMed2002

PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways.

MOTIVATION: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. RESULTS: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named Patika (Pathway Analysis Tool for Integration and Knowledge Acquisition). Patika is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that Patika will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development. AVAILABILITY: A prototype of Patika is available upon request from the authors.

Cell Physiological Phenomena↗
PubMed2004

An ontology for collaborative construction and analysis of cellular pathways.

MOTIVATION: As the scientific curiosity in genome studies shifts toward identification of functions of the genomes in large scale, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. In this regard, it is essential to be able to store, integrate, access and analyze this data effectively with the help of software tools. Clearly this requires a strong ontology that is intuitive, comprehensive and uncomplicated. RESULTS: We define an ontology for an intuitive, comprehensive and uncomplicated representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information via collaboration, and supports manipulation of the stored data. In addition, it facilitates concurrent modifications to the data while maintaining its validity and consistency. Furthermore, novel structures for representation of multiple levels of abstraction for pathways and homologies is provided. Lastly, our ontology supports efficient querying of large amounts of data. We have also developed a software tool named pathway analysis tool for integration and knowledge acquisition (PATIKA) providing an integrated, multi-user environment for visualizing and manipulating network of cellular events. PATIKA implements the basics of our ontology.

Biopolymers↗
PubMed2004

Web-based information retrieval system for the prediction of metabolic pathways.

Analysis of metabolic pathways is a central topic in understanding the relationship between genotype and phenotype. The rapid accumulation of biological data provides the possibility of studying metabolic pathways both at the genomic and metabolic levels. Our motivation is to develop a conceptual framework and computational system that will allow retrieval of metabolic information and prediction of metabolic pathways. In this paper, we introduce a metabolic pathway prediction framework that extracts metabolic information from biological databases via the Internet, and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites, etc. It provides an easy-to-use interface to retrieve, display, and manipulate metabolic information. The system has been implemented into PathAligner, available at http://bibiserv.techfak.uni-bielefeld. de/pathaligner/.

Computer Simulation↗
PubMedDate not supplied

Questions to ask: implementing a system for clinical pathway variance analysis.

Although it is agreed that there is a need for clinical pathway variance analysis, methods for creating a system are less well defined. To help others down this path, we have developed a list of questions around four core issues: data collection, data entry and analysis, data reporting, and organizational support. Our goal is to identify key questions related to variance management and provide a framework for clinical pathway variance analysis.

Analysis of Variance↗
PubMed1998

Outcomes assessment of total hip and total knee arthroplasty: critical pathways, variance analysis, and continuous quality improvement.

Using critical pathways, with variance analysis and continuous quality improvement techniques to refine the pathways, the efficiency of total hip and total knee surgeries in one academic health center was maximized. Using a retrospective cohort study design, complications, readmissions, morbidity/mortality, and function scores were examined in two groups of patients attended by the same surgeon for the year before and the year after the implementation of an outcomes management program. The length of stay was reduced by 57% for knee patients and by 46% for hip patients. Hospital costs were reduced 11% for all knees and 38% for hips. Complications were also significantly reduced. There was no statistically significant difference between pre- or postoperative knee or hip outcome scores. The program resulted in significant savings without adversely affecting overall outcome.

Aged↗
PubMed2006

Topology-based cancer classification and related pathway mining using microarray data.

Cancer classification is the critical basis for patient-tailored therapy, while pathway analysis is a promising method to discover the underlying molecular mechanisms related to cancer development by using microarray data. However, linking the molecular classification and pathway analysis with gene network approach has not been discussed yet. In this study, we developed a novel framework based on cancer class-specific gene networks for classification and pathway analysis. This framework involves a novel gene network construction, named ordering network, which exhibits the power-law node-degree distribution as seen in correlation networks. The results obtained from five public cancer datasets showed that the gene networks with ordering relationship are better than those with correlation relationship in terms of accuracy and stability of the classification performance. Furthermore, we integrated the ordering networks, classification information and pathway database to develop the topology-based pathway analysis for identifying cancer class-specific pathways, which might be essential in the biological significance of cancer. Our results suggest that the topology-based classification technology can precisely distinguish cancer subclasses and the topology-based pathway analysis can characterize the correspondent biochemical pathways even if there are subtle, but consistent, changes in gene expression, which may provide new insights into the underlying molecular mechanisms of tumorigenesis.

Gene Expression Profiling↗
PubMed2026

PPRC1 is a prognostic biomarker and key regulator of mitochondrial oxidative phosphorylation in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains an incurable haematological malignancy, underscoring the need for novel prognostic biomarkers and therapeutic targets. This study aimed to investigate the clinical and biological significance of peroxisome proliferator-activated receptor gamma coactivator-related protein 1 (PPRC1) in MM. METHODS: Expression and clinical data were obtained from public databases and an independent local cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Differential expression analysis, pathway enrichment analysis and single-cell RNA-seq data analysis were used to explore biological functions. PPRC1 was silenced in MM cell lines using siRNA to assess its effects on cell survival and oxidative phosphorylation. RESULTS: PPRC1 was significantly upregulated in MM and was associated with advanced disease stage and poor overall survival. Multivariate Cox analysis identified PPRC1 as an independent prognostic factor. A nomogram incorporating PPRC1 and revised-ISS improved survival prediction. Functional analyses revealed that PPRC1 was positively correlated with oxidative phosphorylation and oncogenic signalling pathways. A potential connection between PPRC1 expression and immune cell infiltration was observed. PPRC1 knockdown inhibited cell proliferation, induced cell cycle arrest and apoptosis and impaired oxidative phosphorylation in MM. CONCLUSIONS: PPRC1 acts as a prognostic biomarker and metabolic regulator in MM by sustaining mitochondrial oxidative phosphorylation. These findings highlight PPRC1 as a potential therapeutic target in MM.

Humans↗
PubMed2006

High-density oligonucleotide microarrays and functional network analysis reveal extended lung carcinogenesis pathway maps and multiple interacting genes in NNK [4-(methylnitrosamino)-1-(3-pyridyle)-1-butanone] induced CD1 mouse lung tumor.

PURPOSE: NNK [4-(methylnitrosamino)-1-(3-pyridyle)-1-butanone] is a nicotine-derived nitrosaminoketone contained in tobacco smoke used as a powerful chemical carcinogen for rodent experimental models of pulmonary carcinogenesis. To clarify its carcinogenetic mechanisms, we examined the expression status of 22,625 mouse genes. METHODS: The affymetrix GeneChip mouse expression 430 A arrays have been used in CD1-induced mouse lung tumor. The affected genes were analyzed by Ingenuity pathway analysis to investigate functional network and gene ontology. RESULTS: A total of 876 genes were found to be differentially expressed at least twofold between NNK-induced tumors and normal lung tissues, 390 up-regulated and 486 down-regulated in these lesions. The functions with the highest P values were related to cellular growth and proliferation (P = 1.71 x 10(-4) to 4.10 x 10(-2)). In addition, we identified canonical pathways for Wnt/beta-catenin signaling (P = 0.0338). CONCLUSIONS: These results suggest that application of gene expression profiling may provide an improved strategy for therapeutic targeting of tobacco smoking-induced lung cancer.

Animals↗