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Traditional cancer diagnosis relies on a combination of clinical and histo-pathological data. In many cases, however, the morphology of in particular metastatic cancer is not discriminative enough for correct diagnosis. In addition, the morphology of tumor cells do not provide information on aberrant molecular pathways that may be used to specifically target the tumor like the application of Herceptin to breast cancers with amplification in the ERBB2 gene. With the completion of the human genome project, molecular pathology has dramatically increased its arsenal of novel molecular biomarkers that can be used to determine the phenotype of tumors. Gene expression profiling using high-density microarray technology is an extremely powerful tool to comprehensively characterize the tumor phenotype. We have developed TCLASS&#xae; a multi-class tumor classifier that interprets gene expression microarray data and allows the identification of the primary site of Cancers of Unknown Promary site (CUP). The classifier is implemented as a web-based tool and is an extremely simple and straightforward approach for molecular characterization of tumor samples.  We are currently looking for collaborations with clinicians with access to fresh frozen CUP samples to further validate the tool in a clinical context. Alternatively, CEL files of  CUP samples analyzed with Affynetrix 133 Plus 2.0 arrays can also be directly analyzed using TCLASS.&#xd;&#xa

nature precedings

The Molecular In Silico Dissection of Cancer using TCLASS and its Application in the Identification of the Tissue of Origin of *Cancers of Unknown Primary Site*