Pulmonary genetics, genomics, and gene therapy: conference summary.
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Animals↗
Biomedical subjects
Steven M Albelda
Publications and source records attributed to Steven M Albelda.
Detection of SV40 DNA sequences in malignant mesothelioma specimens from the United States, but not from Turkey.
The incidence of malignant mesothelioma (MM) shows a strong epidemiological association with exposure to asbestos fibers. Recently, simian virus 40 (SV40) DNA sequences have been reported in MM tumor specimens from the United States and several European countries, and the SV40 tumor virus has been implicated as a potential co-factor in the etiology of this disease. However, several large studies from the US, Finland, and Turkey did not detect SV40 sequences in MM samples. To address this discrepancy, MM specimens from Turkey and the US were analyzed in the same laboratory under identical conditions to detect the presence of SV40 DNA. We detected SV40 sequences in 4 of 11 specimens from the United States, but in none of the 9 Turkish samples examined. These findings suggest that geographical differences exist with regard to the involvement of SV40 in human tumors.
Blotting, Southern↗
Alterations in cell cycle genes in early stage lung adenocarcinoma identified by expression profiling.
In normal lung epithelial cells, cellular division is an ordered, tightly regulated process involving multiple checkpoints that assess extracellular growth signals, cell size, and DNA integrity. In contrast, neoplastic lung cells develop the ability to bypass several of these checkpoints, particularly at the G1/S and G2/M boundaries. We used genomic profiling to compare gene expression levels in early stage lung adenocarcinomas and non-neoplastic pulmonary tissue in order to comprehensively identify alterations in the process of cell cycling. RNA extracted from node negative, poorly differentiated lung adenocarcinomas (15 patients) and non-neoplastic pulmonary tissue (5 patients) was hybridized to oligonu-cleotide microarray filters containing 44,363 genes. Ontological classification was used to extract genes involved with cell cycle progression. Further analysis discovered a subset of differentially expressed genes for further study. Of the 624 cell cycle genes on the microarray filters, 40 genes were predicted to be differentially expressed in lung adeno-carcinomas. Alterations in several genes (i.e., cyclin B1, cyclin D1, p21, MDM2) are consistent with published data in the literature. We also identified 19 novel genes that have neither been described in non-small cell lung cancer (i.e., cdc2, cullin 4A, ZAC, p57, DP-1, GADD45, PISSLRE, cdc20) nor in any other tumors (i.e., cyclin F, cullin 5, p34). These results identified several potential cell cycle genes altered in lung cancer.
Adenocarcinoma↗
Microarray data simulator for improved selection of differentially expressed genes.
The development of microarray technology has allowed researchers to measure expression levels of thousands of genes simultaneously. Analysis of these data requires the best normalization and statistical approaches to account for the biological and technical variability inherent in the technique. To approach this problem we have developed a publicly available simulator of microarray hybridization experiments that can be used to help assess the accuracy of bioinformatic tools in discovering significant genes. After analyzing microarray hybridization experiments from over 50 samples, an estimate of various degrees of technical and biological variability was obtained. This information was used to develop a simulator of microarray hybridization data which modeled "normal tissue samples" and "diseased tissue samples" with known, defined, changes in gene expression (a "gold standard"). The data derived from the simulator were then used to evaluate the true positive and false negative rates of several normalization procedures and gene selection techniques. We found that the type of normalization approach used was an important aspect of data analysis. Global normalization was the least accurate approach. Evaluation of gene selection techniques showed that "Significance analysis of microarrays" (SAM) and "Patterns of Gene Expression" (PaGE) were more accurate than simple t-test analysis. We provide access to the microarray hybridization simulator as a public resource for biologists to further test new emerging genomic bioinfomatic tools.
Computer Simulation↗
Differentially expressed apoptotic genes in early stage lung adenocarcinoma predicted by expression profiling.
OBJECTIVE: In undiseased lung epithelial cells, apoptosis is an evolutionarily conserved and genetically regulated form of cell suicide which plays an important role in development and in the maintenance of tissue homeostasis. Neoplastic lung cells develop the ability to deregulate growth by alterations in these genes which control apoptosis. Genomic profiling was used to compare gene expression levels in early stage lung adenocarcinomas and nonneoplastic pulmonary tissue in order to comprehensively identify alterations in the process of apoptosis. METHODS: RNA extracted from node negative, poorly differentiated lung adenocarcinomas (15 patients) and nonneoplastic pulmonary tissue (5 patients) was hybridized to oligonucleotide microarray filters containing 44,363 genes. Ontological classification was used to extract genes involved with apoptosis. Further analysis discovered a subset of differentially expressed genes for further study. RESULTS: Of the 308 apoptotic genes on the microarray filters, 24 genes were predicted to be differentially expressed in lung adenocarcinomas. Alterations in several genes (i.e., Akt, BcL-xL, PTEN, FAS) are consistent with the literature. We also identified 10 novel genes that have not been described in nonsmall cell lung cancer (i.e., RIP, Caspase 1, PDK-1). CONCLUSIONS: These results identified several potential apoptotic genes altered in lung cancer.
Adenocarcinoma↗