Paper Info
Title
Large-scale antibody profiling of human blood sera: The future of molecular diagnosis
Abstract
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.
Year
DOI
Venue
2009
10.1007/s00287-009-0354-5
Informatik Spektrum
DocType
Volume
Issue
Journal
32
4
ISSN
Citations 
PageRank 
1432-122X
0
0.34
References 
Authors
3
12
Name
Order
Citations
PageRank
Andreas Keller117321.19
Nicole Ludwig2133.58
Sabrina Heisel300.34
Petra Leidinger4101.26
Claudia Andres550.76
Wolf-Ingo Steudel611.40
Hanno Huwer700.34
Bernhard Burgeth835826.09
Matthias Hein966362.80
Joachim Weickert105489391.03
Eckart Meese1110814.50
Hans-peter Lenhof1261564.08