Use of SMART-generated cDNA for gene expression studies in multiple human tumors

We demonstrate here that SMART PCR-amplified cDNAs arrayed on a nylon membrane are suitable for high-throughput tissue expression profiling when starting biological materials are limited. We show that SMART cDNA accurately reflects gene expression patterns found in total RNA by comparing the expression level of several target genes in SMART PCR-amplified cDNAs and their corresponding total RNAs. We also arrayed cDNAs from 68 matched tumor and normal samples on a nylon membrane to determine whether SMART PCR-amplified cDNA could be used for detecting differentially expressed genes in these tissues. These arrays containing normalized tumor and normal cDNAs were hybridized with probes for glutathione peroxidase and gelsolin. The hybridization results revealed cancer-related and patient-specific gene expression differences between tumor and normal tissues for these genes. These studies show that SMART PCR-amplified cDNAs maintain the complexity of the original mRNA population and are thus suitable for high-throughput studies to compare the relative abundance of target genes and to detect differentially expressed genes in a wide variety of tissues simultaneously.     

Cross-species application of cDNA microarrays to profile gene expression using UV-induced melanoma in Monodelphis domestica as the model system

This study established the utility of cross-species application of the cDNA microarray technique for investigating differential gene expression. Using both total RNA and mRNA samples recovered from two opossum cell lines derived from UVB-induced melanoma, we analyzed expression of ca. 4400 genes on the human DermArray DNA microarrays. The signals generated on the DermArrays were clear, strong, and reproducible. A cDNA dot blot consisting of differentially expressed genes representative of different functional clusters was used to validate the DermArray results. We also cloned a Monodelphis gene, keratin 18 (KRT18), and characterized its expression patterns in tumor samples of different progression stages. Up-regulated expression was observed for the KRT18 gene in advanced melanomas, a finding consistent with the DermArray analysis. These results provide evidence that cross-species application of cDNA microarrays is a useful strategy for investigating gene expression patterns in animal models for which species-specific cDNA microarrays are not available.     

A computational approach to measuring coherence of gene expression in pathways

This study uses a computational approach to analyze coherence of expression of genes in pathways. Microarray data were analyzed with respect to coherent gene expression in a group of genes defined as a pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Our hypothesis is that genes in the same pathway are more likely to be coordinately regulated than a randomly selected gene set. A correlation coefficient for each pair of genes in a pathway was estimated based on gene expression in normal or tumor samples, and statistically significant correlation coefficients were identified. The coherence indicator was defined as the ratio of the number of gene pairs in the pathway whose correlation coefficients are significant, divided by the total number of gene pairs in the pathway. We defined all genes that appeared in the KEGG pathways as a reference gene set. Our analysis indicated that the mean coherence indicator of pathways is significantly larger than the mean coherence indicator of random gene sets drawn from the reference gene set. Thus, the result supports our hypothesis. The significance of each individual pathway of n genes was evaluated by comparing its coherence indicator with coherence indicators of 1000 random permutation sets of n genes chosen from the reference gene set. We analyzed three data sets: two Affymetrix microarrays and one cDNA microarray. For each of the three data sets, statistically significant pathways were identified among all KEGG pathways. Seven of 96 pathways had a significant coherence indicator in normal tissue and 14 of 96 pathways had a significant coherence indicator in tumor tissue in all three data sets. The increase in the number of pathways with significant coherence indicators may reflect the fact that tumor cells have a higher rate of metabolism than normal cells. Five pathways involved in oxidative phosphorylation, ATP synthesis, protein synthesis, or RNA synthesis were coherent in both normal and tumor tissue, demonstrating that these are essential genes, a high level of expression of which is required regardless of cell type.     

Differential expression of the L-plastin gene in human colorectal cancer progression and metastasis.

To identify molecular alterations in the progression of colorectal carcinoma, we analyzed gene expression profiles of colon cancer cell lines derived from primary and metastatic tumors from a single patient. Of 2280 cDNAs investigated using our in-house microarray, the expression of 6 genes (tumor-associated antigen L6, L-plastin, the human homologue of yeast ribosomal protein S28, the B-cell translocation gene, mitochondrial aspartate-aminotransferase, and HLA-A) increased, while that of 2 genes (keratin 5 and phosphoglucomutase) decreased in metastatic-tumor-derived cells compared with primary-tumor-derived cells. Of these genes, we assessed the L-plastin gene, an actin-bundling protein, at the protein level using a tissue microarray consisting of 58 clinically stratified colorectal cancer specimens. Consistent with our microarray results, the expression of L-plastin was significantly correlated with the progression of cancer staging. Therefore, our results suggest that the L-plastin gene is a potential metastatic marker. In addition, combining cDNA microarrays and tissue arrays, as shown here, is thought to facilitate the rapid characterization of candidate biomarkers.     

Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse

Background  

cDNA microarrays have the potential to identify the genes involved in invasion and metastasis. However, when used with whole tumor tissue, the results average the expression patterns of different cell types. We have combined chemotaxis-based cell collection of the invasive subpopulation of cells within the primary tumor with array-based gene expression analysis to identify the genes necessary for the process of carcinoma cell invasion.     

Gene expression patterns in human liver cancers

Hepatocellular carcinoma (HCC) is a leading cause of death worldwide. Using cDNA microarrays to characterize patterns of gene expression in HCC, we found consistent differences between the expression patterns in HCC compared with those seen in nontumor liver tissues. The expression patterns in HCC were also readily distinguished from those associated with tumors metastatic to liver. The global gene expression patterns intrinsic to each tumor were sufficiently distinctive that multiple tumor nodules from the same patient could usually be recognized and distinguished from all the others in the large sample set on the basis of their gene expression patterns alone. The distinctive gene expression patterns are characteristic of the tumors and not the patient; the expression programs seen in clonally independent tumor nodules in the same patient were no more similar than those in tumors from different patients. Moreover, clonally related tumor masses that showed distinct expression profiles were also distinguished by genotypic differences. Some features of the gene expression patterns were associated with specific phenotypic and genotypic characteristics of the tumors, including growth rate, vascular invasion, and p53 overexpression.     

A comparison of cDNA, oligonucleotide, and Affymetrix GeneChip gene expression microarray platforms.

We have conducted a study to compare the variability in measured gene expression levels associated with three types of microarray platforms. Total RNA samples were obtained from liver tissue of four male mice, two each from inbred strains A/J and C57BL/6J. The same four samples were assayed on Affymetrix Mouse Genome Expression Set 430 GeneChips (MOE430A and MOE430B), spotted cDNA microarrays, and spotted oligonucleotide microarrays using eight arrays of each type. Variances associated with measurement error were observed to be comparable across all microarray platforms. The MOE430A GeneChips and cDNA arrays had higher precision across technical replicates than the MOE430B GeneChips and oligonucleotide arrays. The Affymetrix platform showed the greatest range in the magnitude of expression levels followed by the oligonucleotide arrays. We observed good concordance in both estimated expression level and statistical significance of common genes between the Affymetrix MOE430A GeneChip and the oligonucleotide arrays. Despite their apparently high precision, cDNA arrays showed poor concordance with other platforms.     

Distinct gene expression signatures during development of distant metastasis

Using cDNA microarrays, we have conducted a systematic characterization of global gene expression in v-raf or v-raf/v-myc transformed rat liver epithelial (RLE) cell lines exhibiting both non-metastatic and metastatic phenotypes. Seven transformed cell lines were compared with the non-transformed parental RLE cell. The hierarchical clustering analysis of gene expression profiles revealed two groups reflecting the in vivo metastatic potential of the cells. Surprisingly, one non-metastatic cell line T1 was co-clustered with metastatic cell lines, suggesting that T1 underwent significant genetic changes. The T1 cell line was further compared against all the metastatic cell lines in order to reveal the critical genes required for metastatic conversion but not expressed in the T1. These data demonstrated that expression of genes involved in apoptosis and immune cell homing were altered in all metastatic cell lines. Survival of both intravasated cells in circulation systems and extravasated cells in a new tissue environment might be critical for the final step in the metastatic process. Our study provides gene expression signatures consistent with two critical events in the metastatic process, namely, the acquisition of early homing capacity and increased survival potential of the tumor cells.     

Identification of genes with correlated patterns of variations in DNA copy number and gene expression level in gastric cancer

To identify DNA copy number changes that had a direct influence on mRNA expression in gastric cancer, cDNA microarray-based comparative genomic hybridization (aCGH) and gene expression profiling were performed using 17 K cDNA microarrays. A set of 158 genes showing Pearson correlation coefficients over 0.6 between DNA copy number changes and mRNA expression level variations was selected. In an independent gene expression profiling of 60 tissue samples, the 158 genes were able to distinguish most of the normal and tumor tissues in an unsupervised hierarchical clustering, suggesting that the differential expression patterns displayed by this specific group of genes are most likely based on the gene copy number changes. Furthermore, 43 statistically significant (P<0.01) genes were selected that correctly distinguished all of the tissue samples. The copy number changes detected by aCGH can be verified by fluorescence in situ hybridization and real-time polymerase chain reaction. The selected genes include those that were previously identified as being tumor suppressors or deleted in various tumors, including GATA binding protein 4 (GATA4), monoamine oxidase A (MAOA), cyclin C (CCNC), and oncogenes including malignant fibrous histiocytoma amplified sequence 1 (MFHAS1/MASL1), high mobility group AT-hook 2 (HMGA2), PPAR binding protein (PPARBP), growth factor receptor-bound protein 7 (GRB7), and TBC1 (tre-2, BUB2, cdc16) domain family, member 1 (TBC1D1).     

Protein microarrays for gene expression and antibody screening.

Proteins translate genomic sequence information into function, enabling biological processes. As a complementary approach to gene expression profiling on cDNA microarrays, we have developed a technique for high-throughput gene expression and antibody screening on chip-size protein microarrays. Using a picking/spotting robot equipped with a new transfer stamp, protein solutions were gridded onto polyvinylidene difluoride filters at high density. Specific purified protein was detected on the filters with high sensitivity (250 amol or 10 pg of a test protein). On a microarray made from bacterial lysates of 92 human cDNA clones expressed in a microtiter plate, putative protein expressors could be reliably identified. The rate of false-positive clones, expressing proteins in incorrect reading frames, was low. Product specificity of selected clones was confirmed on identical microarrays using monoclonal antibodies. Cross-reactivities of some antibodies with unrelated proteins imply the use of protein microarrays for antibody specificity screening against whole libraries of proteins. Because this application would not be restricted to antigen-antibody systems, protein microarrays should provide a general resource for high-throughput screens of gene expression and receptor-ligand interactions.