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GOBO: Gene Expression-Based Outcome for Breast Cancer Online

Author

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  • Markus Ringnér
  • Erik Fredlund
  • Jari Häkkinen
  • Åke Borg
  • Johan Staaf

Abstract

Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo), allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1) rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2) identification of co-expressed genes for creation of potential metagenes, 3) association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Suggested Citation

  • Markus Ringnér & Erik Fredlund & Jari Häkkinen & Åke Borg & Johan Staaf, 2011. "GOBO: Gene Expression-Based Outcome for Breast Cancer Online," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-11, March.
    • Handle: RePEc:plo:pone00:0017911
    DOI: 10.1371/journal.pone.0017911
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    References listed on IDEAS

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    1. Charles M. Perou & Therese Sørlie & Michael B. Eisen & Matt van de Rijn & Stefanie S. Jeffrey & Christian A. Rees & Jonathan R. Pollack & Douglas T. Ross & Hilde Johnsen & Lars A. Akslen & Øystein Flu, 2000. "Molecular portraits of human breast tumours," Nature, Nature, vol. 406(6797), pages 747-752, August.
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    Cited by:

    1. Masoumeh Moslemi & Ehsan Sohrabi & Nemamali Azadi & Ali Zekri & Hamed Afkhami & Mansoor Khaledi & Ehsan Razmara, 2020. "Expression Analysis of EEPD1 and MUS81 Genes in Breast Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 29(4), pages 22556-22564, August.
    2. Raul Aguirre-Gamboa & Hugo Gomez-Rueda & Emmanuel Martínez-Ledesma & Antonio Martínez-Torteya & Rafael Chacolla-Huaringa & Alberto Rodriguez-Barrientos & José G Tamez-Peña & Victor Treviño, 2013. "SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-9, September.
    3. Peng-Zhou Kong & Fan Yang & Lin Li & Xiao-Qing Li & Yu-Mei Feng, 2013. "Decreased FOXF2 mRNA Expression Indicates Early-Onset Metastasis and Poor Prognosis for Breast Cancer Patients with Histological Grade II Tumor," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
    4. Xinhua Liu & Pan Zeng & Qinghua Cui & Yuan Zhou, 2017. "Comparative analysis of genes frequently regulated by drugs based on connectivity map transcriptome data," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.

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