Talks and Poster Presentations (with Proceedings-Entry):

J. Luna-Coronell, K. Sergelen, R. Kulovics, A. Gsur, F. Längle, A. Weinhäusel:
"ldentification of Autoantibody Biomarkers for Colon Cancer Screening using Protein Microarrays";
Poster: 5 th Life Science Meeting Innsbruck, ÖGMBT Jahrestagung 2013, Innsbruck; 09-24-2013 - 09-27-2013; in: "5 th Life Science Meeting Innsbruck, ÖGMBT Jahrestagung 2013", (2013), 78.

English abstract:
lntroduction and Objectives Cancer has become a serious health problem. Early diagnosis can improve survival, thus, there is great need and anticipation to identify novel biomarkers for cancer diagnostics at the earliest stage as possible. The aim of this project is to identify tumor autoantibodies (TAA) and to
develop a test which enables early identification of colon cancer patients. Materials and Methods We have produced a protein-array from 16,000 human cDNA expression clones. On these 16k protein arrays we have performed a candidate marker screening for identifying autoantibody profiles suitable for distinction of 4 groups, namely carcinoma patients, patients with polyps (low risk and high risk groups) and healthy controls. Biomarker screening was performed with isolated lgG from serum samples trom a test-set of 134 samples derived trom 99 serum patients between the 4 defined groups. Biostatistical microarray data was performed. A literature review was also made to check the reported colon TAAs Results Class prediction between carcinoma vs. control samples gave a mean percent of cor(ect classification of 89% of the samples, and cross-validation receiver operating characteristic (ROC) area under the curve of 0.938. Correct class prediction classification between controls vs. low risk samples resulted in 89%; low risk vs. high risk samples in 86%; and high
risk vs. carcinoma samples 68%. A literature review was also made from published TAAs, and the classifier proteins which were found in the 16k human cDNA expression clones were added to the resulting clone list. Conclusion Biostatistics results showed that the samples, could be differentiated between the defined groups. In the end, a total of 729 candidate markers were selected and will be used to generate targeted micro-arrays. Validation of these previous
results will take place using a validation-set of serum samples from 100 individuals per group and tumor entity (n=400).

Created from the Publication Database of the AIT Austrian Institute of Technology.