Gene expression profiles of poorly differentiated, undifferentiated and metastatic cancers

The tissue of origin form metastatic tumors is sometimes difficult to identify from clinical and histologic information. Gene expression signatures are one potential method for identifying the tissue of origin. In the development of algorithms to identify tissue of origin, a collection of human tumor metastatic specimens with known primary sites or primary tumors with poor differentiation are very useful in identifying gene expressions signatures that can classify unknown specimens as to the tissue of origin. Here we describe a series of 276 such tumor specimens used for this purpose. The specimens are poorly differentiated, undifferentiated and metastatic specimens from tumors of the following types/tissues of origin: breast, liver, non-Hodgkin's lymphoma, non-small cell lung cancer, ovary, testicular germ cell, thyroid, kidney, pancreas, colorectal cancer, soft tissue sarcoma, bladder, gastric cancer, prostate and melanoma. This data combined with other series (GSE2109) was used to validate a proprietary tumor classification algorithm of Pathwork Diagnostics. The results of this validation set (N = 545 CEL files) showed that the algorithm correctly identified the tissue of origin for 89.4% of the specimens.

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Monzon FA, Lyons-Weiler M, Buturovic LJ, Rigl CT, Henner WD, Sciulli C, Dumur CI, Medeiros F, Anderson GG