Transcription Factors to Classify Tumor Types and Subtypes
Poster Dec 12, 2014
Benjamin Otto 1,2, Kristin Klätschke 2, Thomas Streichert 3, Christoph Wagener 2, Genrich Tolstonog 4
Awareness of the role in tumor biology of epigenetics and transcription regulatory mechanisms, such as miRNAs, is increasing. We assume that transcription factors play a crucial role in that context, such that they might be capable of discriminating different tumor classes and yet unknown subgroups. Our approach aims at unsupervised identification of a) sample subsets within a dataset and b) the TFs associated with these subsets. The results show, that an unsupervised selection of TFs can clearly distinguish between the classic breast cancer subtypes and different tumor types such as breast, colon, kidney or prostata cancer. Therefore we assume that the method might help in future to identify new markers suitable for diagnosis of specific treatment related phenotypes or detection of tissues of origin.
Despite the developments in conventional PCR, the complexity of multiplex Real Time PCR is still limited due to the lack of sufficient detection channels. To achieve high-end multiplexing capacity on standard Real Time PCR machines, Anapa Biotech has developed the MeltPlex® technology (see box on right).READ MORE