gms | German Medical Science

27. Deutscher Krebskongress

Deutsche Krebsgesellschaft e. V.

22. - 26.03.2006, Berlin

Microarray based prediction for lymphatic metastasis in colorectal cancer

Meeting Abstract

  • corresponding author presenting/speaker Roland Croner - Department of Surgery, University of Erlangen, Deutschland
  • Bertram Reingruber - Department of Surgery, University of Erlangen
  • Alice Gall - Department of Molecular and Experimental Surgery, University of Erlangen
  • Ludger Klein-Hitpass - Institute of Cell Biology, University of Essen
  • Wolfgang Brückl - Department of Internal Medicine I, University of Erlangen
  • Thomas Papadopoulos - Department of Pathology, University of Erlangen
  • Thomas Brabletz - Department of Pathology, University of Erlangen
  • Thomas Kirchner - Department of Pathology, University of Erlangen
  • Jürgen Behrens - Department of Molecular Medicine II, University of Erlangen
  • Michael Stürzl - Department of Molecular and Experimental Surgery, University of Erlangen
  • Werner Hohenberger - Department of Surgery, University of Erlangen
  • Berthold Lausen - Department of Biometry and Epidemiology, University of Erlangen

27. Deutscher Krebskongress. Berlin, 22.-26.03.2006. Düsseldorf, Köln: German Medical Science; 2006. DocPO420

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Veröffentlicht: 20. März 2006

© 2006 Croner et al.
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Purpose: Lymphatic metastasis strongly determines treatment algorithms in CRC. Currently, postoperative histology is needed to obtain the lymph node status. Reliable preoperative information would be useful to advance treatment strategies. We investigated whether microarray based gene expression analysis of a primary tumor biopsy could be used to predict nodal status in colorectal carcinoma (CRC).

Materials and methods: We analyzed 80 colorectal cancer patients from the Erlangen Registry of Colorectal Cancer (ERCRC). Forty shock-frozen samples of stage UICC I/II CRC, and 40 samples of stage UICC III CRC were manually microdissected, RNA was isolated and GeneChips (HG-U133A, Affymetrix) were hybridized. Prediction rates for lymphatic metastasis were calculated using conventional clinico-pathological parameters, gene expression data and a combination of both. Prediction error, specificity and sensitivity were analyzed using six different statistical classifiers. Marker genes were reevaluated by PCR and immunohistochemistry (IHC).

Results: Analysis of conventional parameters produced a positive prediction rate ranging between 53% and 61%, sensitivity of 42% and a specificity of 72%. Microarray prediction rates were between 62% and 67% for lymphatic metastasis. Specificity was between 76% and 83% and sensitivity was between 38% and 48%, depending on the statistical procedure. The conventional estimates could be improved by 9 to 12% when array data were added. PCR and IHC confirmed microarray data.

Conclusions: Current data show that prediction of lymphatic metastasis can be improved by gene expression profiling of the primary tumor biopsy, alone or in combination with conventional parameters. Gene expression profiling can potentially become increasingly valuable for CRC treatment planning