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 does 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 of 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.Here we present TCLASS a molecular multi-class tumor classifier that uses gene expression microaray data for the molecular in silico dissection of diseased tissues and in particular cancer tissues.Our gene expression microarray-based method provides among others information on the level of infiltrating immune or stromal cells but it also provides scores for proliferative capacity, carbohydrate consumption and many relevant targets useful to clinicians for the determination of a personalized targeted (antibody-based) treatment or a tailored chemotherapeutic regimen for the individual patient.