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Biomedical subjects

Sharon Diskin

Publications and source records attributed to Sharon Diskin.

3 recordsLinked to original sources

Integrative genomics identifies distinct molecular classes of neuroblastoma and shows that multiple genes are targeted by regional alterations in DNA copy number.

Neuroblastoma is remarkable for its clinical heterogeneity and is characterized by genomic alterations that are strongly correlated with tumor behavior. The specific genes that influence neuroblastoma biology and are targeted by genomic alterations remain largely unknown. We quantified mRNA expression in a highly annotated series of 101 prospectively collected diagnostic neuroblastoma primary tumors using an oligonucleotide-based microarray. Genomic copy number status at the prognostically relevant loci 1p36, 2p24 (MYCN), 11q23, and 17q23 was determined by PCR and was aberrant in 26, 20, 40, and 38 cases, respectively. In addition, 72 diagnostic neuroblastoma primary tumors assayed in a different laboratory were used as an independent validation set. Unsupervised hierarchical clustering showed that gene expression was highly correlated with genomic alterations and clinical markers of tumor behavior. The vast majority of samples with MYCN amplification and 1p36 loss of heterozygosity (LOH) clustered together on a terminal node of the sample dendrogram, whereas the majority of samples with 11q deletion clustered separately and both of these were largely distinct from the copy number neutral group of tumors. Genes involved in neurodevelopment were broadly overrepresented in the more benign tumors, whereas genes involved in RNA processing and cellular proliferation were highly represented in the most malignant cases. By combining transcriptomic and genomic data, we showed that LOH at 1p and 11q was associated with significantly decreased expression of 122 (61%) and 88 (27%) of the genes mapping to 1p35-36 and all of 11q, respectively, suggesting that multiple genes may be targeted by LOH events. A total of 71 of the 1p35-36 genes were also differentially expressed in the independent validation data set, providing a prioritized list of candidate neuroblastoma suppressor genes. Taken together, these data are consistent with the hypotheses that the neuroblastoma transcriptome is a sensitive marker of underlying tumor biology and that chromosomal deletion events in this cancer likely target multiple genes through alteration in mRNA dosage. Lead positional candidates for neuroblastoma suppressor genes can be inferred from these data, but the potential multiplicity of transcripts involved has significant implications for ongoing gene discovery strategies.

Chromosome Aberrations↗

1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis.

Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, widespread utilization of a CGH has been limited by the lack of well characterized, high-resolution clone sets optimized for consistent performance in aCGH assays and specifically designed analytic software. We have assembled a set of approximately 4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at approximately 1-Mb resolution across the genome, which includes direct coverage of approximately 400 known cancer genes. This aCGH-optimized clone set was compiled from five existing sets, experimentally refined, and supplemented for higher resolution and enhancing mapping capabilities. This clone set is associated with a public online resource containing detailed clone mapping data, protocols for the construction and use of arrays, and a suite of analytical software tools designed specifically for aCGH analysis. These resources should greatly facilitate the use of aCGH in gene discovery.

Cell Line, Tumor↗

Predicting gene ontology functions from ProDom and CDD protein domains.

A heuristic algorithm for associating Gene Ontology (GO) defined molecular functions to protein domains as listed in the ProDom and CDD databases is described. The algorithm generates rules for function-domain associations based on the intersection of functions assigned to gene products by the GO consortium that contain ProDom and/or CDD domains at varying levels of sequence similarity. The hierarchical nature of GO molecular functions is incorporated into rule generation. Manual review of a subset of the rules generated indicates an accuracy rate of 87% for ProDom rules and 84% for CDD rules. The utility of these associations is that novel sequences can be assigned a putative function if sufficient similarity exists to a ProDom or CDD domain for which one or more GO functions has been associated. Although functional assignments are increasingly being made for gene products from model organisms, it is likely that the needs of investigators will continue to outpace the efforts of curators, particularly for nonmodel organisms. A comparison with other methods in terms of coverage and agreement was performed, indicating the utility of the approach. The domain-function associations and function assignments are available from our website http://www.cbil.upenn.edu/GO.

Algorithms↗