Informatik-Spektrum

, Volume 32, Issue 4, pp 332–338

Large-scale antibody profiling of human blood sera: The future of molecular diagnosis

  • Andreas Keller
  • Nicole Ludwig
  • Sabrina Heisel
  • Petra Leidinger
  • Claudia Andres
  • Wolf-Ingo Steudel
  • Hanno Huwer
  • Bernhard Burgeth
  • Matthias Hein
  • Joachim Weickert
  • Eckart Meese
  • Hans-Peter Lenhof
HAUPTBEITRAG LARGE-SCALE ANTIBODY PROFILING

DOI: 10.1007/s00287-009-0354-5

Cite this article as:
Keller, A., Ludwig, N., Heisel, S. et al. Informatik Spektrum (2009) 32: 332. doi:10.1007/s00287-009-0354-5

Abstract

Despite the progress in cancer diagnosis the timely detection of many cancer types is still a grand challenge. For various human cancer types including lung cancer, prostate cancer, and breast cancer, several groups recently demonstrated that autoantibody profiling might be a promising approach towards earlier and more accurate cancer diagnosis.

In this paper, we confirm the ability of autoantibody profiling as a diagnostic test by providing evidence that not only cancer sera can be distinguished well from normal controls, but also from sera of patients with noncancerous diseases. Altogether, we screened blood sera of 191 cancer patients, 60 physiologically unaffected controls, and 177 sera of patients with noncancerous diseases for more than 1800 immunogenic clones. The measured autoantibody fingerprints were evaluated using a novel image analysis pipeline.

For 13 antigens, statistically significant (p<0.05) and at least two-fold elevated immuno-reactivity in cancer sera compared to normal sera could be observed. Nine of these antigens also showed increased reactivity compared to sera of patients with other diseases, including the tumor marker vimentin. Supervised discrimination between cancer and normal sera by using linear Support Vector Machines was possible with an accuracy of 94.04%, a specificity of 83.38%, and a sensitivity of 97.44%. Here, our so-called MIMM (minimally invasive multiple marker) approach showed no significant difference in the classification accuracy between low and higher tumor grades. The classification in healthy and diseased sera showed an even higher accuracy of 96.12% while the discrimination in cancer sera and diseased controls revealed an accuracy of 69.58%.

These results demonstrate that autoantibody profiling offers the possibility of cancer screening for a variety of different cancer types as well as inflammatory diseases at an early disease stage.

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Andreas Keller
    • 1
  • Nicole Ludwig
    • 2
  • Sabrina Heisel
    • 2
  • Petra Leidinger
    • 2
  • Claudia Andres
    • 1
  • Wolf-Ingo Steudel
    • 3
  • Hanno Huwer
    • 5
  • Bernhard Burgeth
    • 4
  • Matthias Hein
    • 6
  • Joachim Weickert
    • 4
  • Eckart Meese
    • 2
  • Hans-Peter Lenhof
    • 1
  1. 1.Center for BioinformaticsSaarland UniversitySaarbrückenGermany
  2. 2.Department of Human Genetics, Medical SchoolSaarland UniversityHomburg/SaarGermany
  3. 3.Department of Neurosurgery, Medical SchoolSaarland UniversityHomburg/SaarGermany
  4. 4.Mathematical Image Analysis GroupSaarland UniversitySaarbrückenGermany
  5. 5.SHG Clinics VölklingenVölklingenGermany
  6. 6.Machine Learning GroupSaarland UniversitySaarbrückenGermany

Personalised recommendations