PathWave: Discovering patterns of differentially regulated enzymes in metabolic pathways

25Citations
Citations of this article
90Readers
Mendeley users who have this article in their library.

Abstract

Motivation: Gene expression profiling by microarrays or transcript sequencing enables observing the pathogenic function of tumors on a mesoscopic level. Results: We investigated neuroblastoma tumors that clinically exhibit a very heterogeneous course ranging from rapid growth with fatal outcome to spontaneous regression and detected regulatory oncogenetic shifts in their metabolic networks. In contrast to common enrichment tests, we took network topology into account by applying adjusted wavelet transforms on an elaborated and new 2D grid representation of curated pathway maps from the Kyoto Enzyclopedia of Genes and Genomes. The aggressive form of the tumors showed regulatory shifts for purine and pyrimidine biosynthesis as well as folate-mediated metabolism of the onecarbon pool in respect to increased nucleotide production. We spotted an oncogentic regulatory switch in glutamate metabolism for which we provided experimental validation, being the first steps towards new possible drug therapy. The pattern recognition method we used complements normal enrichment tests to detect such functionally related regulation patterns. Availability and Implementation: PathWave is implemented in a package for R (www.r-project.org) version 2.6.0 or higher. It is freely available from http://www.ichip.de/software/pathwave.html. Contact: r.koenig@dkfz.de; r.eils@dkfz.de. Supplementary information: Supplementary data are available at Bioinformatics online. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org.

Cite

CITATION STYLE

APA

Schramm, G., Wiesberg, S., Diessl, N., Kranz, A. L., Sagulenko, V., Oswald, M., … König, R. (2010). PathWave: Discovering patterns of differentially regulated enzymes in metabolic pathways. Bioinformatics, 26(9), 1225–1231. https://doi.org/10.1093/bioinformatics/btq113

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free