Tumor expression profiling

Examining fhe fwo adjacenf fumor samples (5A and 5B), 149 genes were differentially expressed in common (r = 0.987). However, based upon the level of variation in duplicates, some of fhe observed expression could be attributed to experimental noise. Couple this with a sample-to-sample variance (r = 0.915) reported larger than the observed chip variance (for tumor 5A, 50 genes from hybridization replicates and 100 genes differentially expressed between sample replicates), it would be difficult to believe that the tumor expression profiles were the same or different. 

Watanabe N, Ando K, Yoshida S, et al. Gene expression profile analysis of rheumatoid synovial fibroblast cultures revealing the overexpression of genes responsible for tumor-like growth of rheumatoid synovium. Biochem Biophys Res Commun 2002 294(5) 1121-1129. 

Elek J et al. Microarray-based expression profiling in prostate tumors. In vivo 2000 14 173-182. 

Tumor classification — Drug treatment regimes often depend upon tumor type. The origins of metastatic tumor cells can be difficult to determine by conventional histopathology. Gene expression profiling may complement the more traditional methodologies where tumors are difficult to classify. 

Microarray analyses of breast cancer have identified unique gene expression profiles associated with patient survival. Sorlie et al. (23) found the expression profiles to distinguish ER-i- from ER- tumors with distinct outcomes in a cohort with locally advanced breast cancer treated with primary chemotherapy. Van t Veer et al. (18) established a 70-gene signature to predict metastatic potential in an untreated, node-negative cohort. Sotiriou et al. (24) showed the concordance with these previous analyses in node-positive and node-negative patients with the majority receiving adjuvant treatment. 

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