Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for ~3-5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics.
Previous studies have paved the way for gene expression-based tumor type classification. In this study, researchers from Canhelp Genomics and Fudan University, China have established a comprehensive database integrating microarray- and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, they identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, the researchers tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, they have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. This gene panel may hold a promise to be a useful additional tool for the determination of the tumor origin.
Flow diagram of gene expression signature identification and performance evaluation.