Transcript and protein expression profiles of the NCI-60 cancer cell panel: an integromic microarray study.

To evaluate the utility of transcript profiling for prediction of protein expression levels, we compared profiles across the NCI-60 cancer cell panel, which represents nine tissues of origin. For that analysis, we present here two new NCI-60 transcript profile data sets (A based on Affymetrix HG-U95 and HG-U133A chips; Affymetrix, Santa Clara, CA) and one new protein profile data set (based on reverse-phase protein lysate arrays). The data sets are available online at http://discover.nci.nih.gov in the CellMiner program package. Using the new transcript data in combination with our previously published cDNA array and Affymetrix HU6800 data sets, we first developed a "consensus set" of transcript profiles based on the four different microarray platforms. Using that set, we found that 65% of the genes showed statistically significant transcript-protein correlation, and the correlations were generally higher than those reported previously for panels of mammalian cells. Using the predictive analysis of microarray nearest shrunken centroid algorithm for functional prediction of tissue of origin, we then found that (a) the consensus mRNA set did better than did data from any of the individual mRNA platforms and (b) the protein data seemed to do somewhat better (P = 0.027) on a gene-for-gene basis in this particular study than did the consensus mRNA data, but both did well. Analysis based on the Gene Ontology showed protein levels of structure-related genes to be well predicted by mRNA levels (mean r = 0.71). Because the transcript-based technologies are more mature and are currently able to assess larger numbers of genes at one time, they continue to be useful, even when the ultimate aim is information about proteins.

Clusters of adjacent and similarly expressed genes across normal human tissues complicate comparative transcriptomic discovery.

Transcriptomic techniques are valuable tools with which to validate genetic and biological hypotheses and are now widely available for research. However, with the exception of tumor biology, comparative genomics analyses have been difficult to use as discovery engines to describe biologically relevant expression changes. We propose that physical proximity of human genes correlates with similar mRNA expression, so that increased expression might include a disease-relevant gene and many other genes in the adjacent region. To increase the efficiency of combining susceptibility gene mapping and interpretation of transcriptomics, we developed a method to identify clusters of adjacent and similarly expressed genes. Gene expression profiles for 28,945 genes across 101 normal human tissues were obtained from the Gene Logic BioExpress system. The expression similarity for genes in sliding-windows was measured using average pair-wise Pearson correlation coefficients. We identified 187 clusters (p < 10e-4) of co-regulated genes, including 2648 genes, or 9.1% of all genes considered and termed these "clusters of adjacent and similarly expressed genes" (CASEGs). Genes in 15 (8.2%) of these clusters demonstrate a significant co-expression enrichment (p < 10e-10). This study demonstrates the coordinate expression of neighboring genes and provides a comprehensive view of expression-based compartmentalization of the human genome, which can be overlaid on genetic susceptibility gene maps.

Expression of SSX genes in the neoplastic cells of Hodgkin's lymphoma.

The cancer/testis antigen (CTA) group of tumor-associated proteins have been reported to be expressed in various cancers and in adult testis but they are essentially not found in any other normal adult nonneoplastic tissues. Prompted by the frequent detection of SSX1 in a previous comprehensive expression profile of the Hodgkin's lymphoma (HL) cell line L428, we analyzed SSX expression by nonnested reverse-transcription polymerase chain reaction (RT-PCR) in 4 HL cell lines (L428, L540, HD-MY-Z, and KM-H2) and 32 tumor samples of HL. The cellular localization of SSX expression in the tumor samples was further analyzed by in situ hybridization (ISH). All 4 HL cell lines were positive by RT-PCR using SSX consensus primers. Using primers specific to individual SSX genes, all 4 cell lines expressed multiple SSX family members. Five tumor samples (15.6%) were positive by RT-PCR using SSX consensus primers and direct sequencing of the RT-PCR products showed that 4 of 5 expressed more than 1 SSX family member. ISH confirmed that SSX expression originated in HL cells in all 5 RT-PCR-positive tumor samples. Furthermore, ISH demonstrated SSX-positive HL cells in 6 of 11 cases (55%) that were negative by RT-PCR. Our results suggest that members of the SSX family of CTA are expressed in most HL. This subset of HL may be a candidate for immunotherapy approaches directed at SSX proteins.