Clustering of tumor gene expression data and identification of tumor-specific molecular markers. Hierarchical clustering (a) and a 5 X 5 self-organizing map (SOM) (b) were used to cluster 144 tumors spanning 14 tumor classes according to their gene expression patterns. (c) Gene expression values for class-specific OVA markers, as determined using the S2N metric, are shown. Columns represent 190 primary human tumor samples ordered by class. Rows represent 10 genes most highly correlated with each OVA distinction. Red indicates high relative level of expression, and blue represents low relative level of expression. The known cancer markers prostate-specific antigen (PSA), carcinoembryonic antigen (CEA), and estrogen receptor (ER) are identified. BR, breast adenocarcinoma; PR, prostate adenocarcinoma; LU, lung adenocarcinoma; CR, colorectal adenocarcinoma; LY, lymphoma; BL, bladder transitional cell carcinoma; ML, melanoma; UT,uterine adenocarcinoma; LE, leukemia; RE, renal cell carcinoma; PA, pancreatic adenocarcinoma; OV, ovarian adenocarcinoma; ME, pleural mesothelioma; CNS, central nervous system.
Ramaswamy, S. et al. Multiclass cancer diagnosis using tumor gene expression signatures. Proc Natl Acad Sci USA 98, 15149-15154 (December 18, 2001) ©2001 National Academy of Sciences, U.S.A.