Andrew E Teschendorff

Summary

Affiliation: University College London
Country: UK

Publications

  1. Teschendorff A, Menon U, Gentry Maharaj A, Ramus S, Gayther S, Apostolidou S, et al. An epigenetic signature in peripheral blood predicts active ovarian cancer. PLoS ONE. 2009;4:e8274 pubmed publisher
    ..Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role. ..
  2. Teschendorff A, Severini S. Increased entropy of signal transduction in the cancer metastasis phenotype. BMC Syst Biol. 2010;4:104 pubmed publisher
    ..Further exploration of the statistical properties of such integrated cancer expression and protein interaction networks will be a fruitful endeavour. ..
  3. Teschendorff A, Zhuang J, Widschwendter M. Independent surrogate variable analysis to deconvolve confounding factors in large-scale microarray profiling studies. Bioinformatics. 2011;27:1496-505 pubmed publisher
    ..Thus, ISVA should be useful as a feature selection tool in studies that are subject to confounding. An R-package isva is available from www.cran.r-project.org. ..
  4. Teschendorff A, Jones A, Fiegl H, Sargent A, Zhuang J, Kitchener H, et al. Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation. Genome Med. 2012;4:24 pubmed
    ..The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821. ..
  5. Teschendorff A, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29:189-96 pubmed publisher
    ..BMIQ is freely available from http://code.google.com/p/bmiq/. a.teschendorff@ucl.ac.uk Supplementary data are available at Bioinformatics online. ..
  6. Teschendorff A, Jones A, Widschwendter M. Stochastic epigenetic outliers can define field defects in cancer. BMC Bioinformatics. 2016;17:178 pubmed publisher
    ..Given that cancer studies aiming to find epigenetic field defects are likely to be limited by sample size, adopting the novel feature selection paradigm advocated here will be critical to increase assay sensitivity. ..
  7. Teschendorff A, Gomez S, Arenas A, El Ashry D, Schmidt M, Gehrmann M, et al. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules. BMC Cancer. 2010;10:604 pubmed publisher
    ..Specifically, our results suggest that simultaneous modulation of T-helper differentiation and TGF-beta pathways may improve clinical outcome of hormone insensitive breast cancers over treatments that target only one of these pathways. ..
  8. Teschendorff A, Breeze C, Zheng S, Beck S. A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies. BMC Bioinformatics. 2017;18:105 pubmed publisher
    ..Finally, we demonstrate the added value of EpiDISH in an EWAS of smoking. Estimating cell-type fractions and subsequent inference in EWAS may benefit from the use of non-constrained reference-based cell-type deconvolution methods. ..
  9. Zhuang J, Widschwendter M, Teschendorff A. A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform. BMC Bioinformatics. 2012;13:59 pubmed publisher
    ..The insights presented here will be useful to any study embarking on large-scale DNA methylation profiling using Illumina Infinium beadarrays. ..

Detail Information

Publications9

  1. Teschendorff A, Menon U, Gentry Maharaj A, Ramus S, Gayther S, Apostolidou S, et al. An epigenetic signature in peripheral blood predicts active ovarian cancer. PLoS ONE. 2009;4:e8274 pubmed publisher
    ..Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role. ..
  2. Teschendorff A, Severini S. Increased entropy of signal transduction in the cancer metastasis phenotype. BMC Syst Biol. 2010;4:104 pubmed publisher
    ..Further exploration of the statistical properties of such integrated cancer expression and protein interaction networks will be a fruitful endeavour. ..
  3. Teschendorff A, Zhuang J, Widschwendter M. Independent surrogate variable analysis to deconvolve confounding factors in large-scale microarray profiling studies. Bioinformatics. 2011;27:1496-505 pubmed publisher
    ..Thus, ISVA should be useful as a feature selection tool in studies that are subject to confounding. An R-package isva is available from www.cran.r-project.org. ..
  4. Teschendorff A, Jones A, Fiegl H, Sargent A, Zhuang J, Kitchener H, et al. Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation. Genome Med. 2012;4:24 pubmed
    ..The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821. ..
  5. Teschendorff A, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013;29:189-96 pubmed publisher
    ..BMIQ is freely available from http://code.google.com/p/bmiq/. a.teschendorff@ucl.ac.uk Supplementary data are available at Bioinformatics online. ..
  6. Teschendorff A, Jones A, Widschwendter M. Stochastic epigenetic outliers can define field defects in cancer. BMC Bioinformatics. 2016;17:178 pubmed publisher
    ..Given that cancer studies aiming to find epigenetic field defects are likely to be limited by sample size, adopting the novel feature selection paradigm advocated here will be critical to increase assay sensitivity. ..
  7. Teschendorff A, Gomez S, Arenas A, El Ashry D, Schmidt M, Gehrmann M, et al. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules. BMC Cancer. 2010;10:604 pubmed publisher
    ..Specifically, our results suggest that simultaneous modulation of T-helper differentiation and TGF-beta pathways may improve clinical outcome of hormone insensitive breast cancers over treatments that target only one of these pathways. ..
  8. Teschendorff A, Breeze C, Zheng S, Beck S. A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies. BMC Bioinformatics. 2017;18:105 pubmed publisher
    ..Finally, we demonstrate the added value of EpiDISH in an EWAS of smoking. Estimating cell-type fractions and subsequent inference in EWAS may benefit from the use of non-constrained reference-based cell-type deconvolution methods. ..
  9. Zhuang J, Widschwendter M, Teschendorff A. A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform. BMC Bioinformatics. 2012;13:59 pubmed publisher
    ..The insights presented here will be useful to any study embarking on large-scale DNA methylation profiling using Illumina Infinium beadarrays. ..