gms | German Medical Science

123. Kongress der Deutschen Gesellschaft für Chirurgie

Deutsche Gesellschaft für Chirurgie

02. bis 05.05.2006, Berlin

Effectiveness of SELDI-TOF mass spectrometry for detection of serum markers for colorectal cancer

Meeting Abstract

  • corresponding author J.K. Habermann - Klinik für Chirurgie, UKSH, Campus Lübeck, Deutschland
  • U.J. Roblick - Klinik für Chirurgie, UKSH, Campus Lübeck, Deutschland
  • B. Luke - NCI Frederick, Frederick, MD, USA
  • D. Prieto - NCI Frederick, Frederick, MD, USA
  • E. Oevermann - Klinik für Chirurgie, UKSH, Campus Lübeck, Deutschland
  • T. Veenstra - NCI Frederick, Frederick, MD, USA
  • H.-P. Bruch - Klinik für Chirurgie, UKSH, Campus Lübeck, Deutschland
  • G. Auer - Cancer Center Karolinksa, Karolinska Institutet, Stockholm, Schweden
  • T. Ried - Genetics Branch, NCI, NIH, Bethesda, MD, USA

Deutsche Gesellschaft für Chirurgie. 123. Kongress der Deutschen Gesellschaft für Chirurgie. Berlin, 02.-05.05.2006. Düsseldorf, Köln: German Medical Science; 2006. Doc06dgch4759

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Veröffentlicht: 2. Mai 2006

© 2006 Habermann et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



Einleitung: Colorectal carcinomas are the third most common malignancies in the Western World. Despite screening programs about 70% of tumors are detected at advanced stages (UICC III/IV). A late diagnosis results in a significant reduction of average survival times. Therefore, alternative tools for early detection are needed.

Material und Methoden: We explored whether detection of malignant disease would be possible through identification of cancer specific protein signatures in serum samples. Sera from patients with colorectal malignancy (n=52) and control individuals (n=32) were analyzed using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry. Class comparison and custom developed algorithms identified a set of 13 serum features (m/z values) that distinguished the malignant samples and the healthy controls of the training set independent from age and tumor stage. These features were validated by class prediction using an independently collected, blinded validation set of 55 sera. The predictions utilized a combination of 16 classifiers based on K-Nearest Neighbors. This deterministic classification procedure has no adjustable parameters and is independent of the order of the training samples. We chose this conservative approach because of the controversy associated with previously published reports on SELDI analyses. Only samples that revealed identical results with all 16 models were considered for further classification into the malignant or control group.

Ergebnisse: Applying this criterion, 48 of 55 samples were classifiable. Of those 48 samples, a total of 98% were classified correctly. None of the normal samples was assigned to the malignant group. The only misclassified sample represented an inoperable tumor whose characteristics were underrepresented for classifier training. Our SELDI based protein profiling with KNN class prediction based on 13 features permitted the discrimination of colorectal cancer-associated sera - including those with early stage disease - from healthy controls in an independent, blinded validation with 96.7% sensitivity, 100% specificity, 100% positive predictive value, and 94.4% negative predictive value. Any other diagnostic approach either alone or in combination reaches only lower diagnostic efficiencies.

Schlussfolgerung: Large scale prospective multicenter studies are now warranted to establish the clinical value of the identified discerning features for colorectal cancer screening.