title: Molecular classification of unknown primary cancer.
abstract: The diagnosis of unknown primary carcinoma is often the result of the failure of light microscopy and immunohistochemistry to elucidate the origin of adenocarcinoma or poorly differentiated carcinoma. Recent advances in gene expression profiling using either reverse transcription polymerase chain reaction (RT-PCR) or microarray have enabled researchers to develop expression profiles unique to a wide variety of well-characterized primary cancers and to compare these unique signatures with those from unknown primary cancers. As the gene expression profile is frequently conserved when the tumor metastasizes, it is often possible to analyze a biopsy specimen and genomically identify its tissue of origin. In fact, the overall accuracy of genomic cancer classification in patients with known primary cancers is 80% to 90%. This new system of molecular classification might be considered as "genomic taxonomy." The genomic classification is then available to the pathologist and clinician to aid in both the patient's diagnosis and treatment planning. The impact of this new technology on patient outcomes is currently under study.
authors.affiliation: Agendia, Inc, Huntington Beach, CA 92647, USA. richard.bender@agendia.com
authors.forename: Richard A
authors.initials: RA
authors.lastname: Bender
authors.forename: Mark G
authors.initials: MG
authors.lastname: Erlander
mesh_terms: D020869:Gene Expression Profiling; D006801:Humans; D009382:Neoplasms, Unknown Primary / Q000145:classification* / Q000235:genetics*