Concordance of gene expression and functional correlation patterns across the NCI-60 cell lines and the Cancer Genome Atlas glioblastoma samples - PubMed (original) (raw)

Concordance of gene expression and functional correlation patterns across the NCI-60 cell lines and the Cancer Genome Atlas glioblastoma samples

Barry R Zeeberg et al. PLoS One. 2012.

Abstract

Background: The NCI-60 is a panel of 60 diverse human cancer cell lines used by the U.S. National Cancer Institute to screen compounds for anticancer activity. We recently clustered genes based on correlation of expression profiles across the NCI-60. Many of the resulting clusters were characterized by cancer-associated biological functions. The set of curated glioblastoma (GBM) gene expression data from the Cancer Genome Atlas (TCGA) initiative has recently become available. Thus, we are now able to determine which of the processes are robustly shared by both the immortalized cell lines and clinical cancers.

Results: Our central observation is that some sets of highly correlated genes in the NCI-60 expression data are also highly correlated in the GBM expression data. Furthermore, a "double fishing" strategy identified many sets of genes that show Pearson correlation ≥0.60 in both the NCI-60 and the GBM data sets relative to a given "bait" gene. The number of such gene sets far exceeds the number expected by chance.

Conclusion: Many of the gene-gene correlations found in the NCI-60 do not reflect just the conditions of cell lines in culture; rather, they reflect processes and gene networks that also function in vivo. A number of gene network correlations co-occur in the NCI-60 and GBM data sets, but there are others that occur only in NCI-60 or only in GBM. In sum, this analysis provides an additional perspective on both the utility and the limitations of the NCI-60 in furthering our understanding of cancers in vivo.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: One author, Dr. Ari Kahn, is affiliated with a commercial company SRA International Inc. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials.

Figures

Figure 1

Figure 1. Thumbnails of gene correlation clustering for Cluster 52 genes across (A) NCI-60 cell lines and (B) TCGA GBM samples.

The full size figures are available as Figures S1 and S2. The numbers appended after the gene name refer to the NCI-60 cluster in which that gene appeared.

Figure 2

Figure 2. Thumbnails of gene correlation clustering for Cluster 68 genes across (A) the NCI-60 cell lines and GBM samples (B).

The full size figures are available as Figures S3 and S4. The numbers appended after the gene name refer to the NCI-60 cluster in which that gene appeared.

Figure 3

Figure 3. Thumbnail of GO category versus gene list CIM for sets of genes with correlation ≥0.60 across both the NCI-60 and GBM samples.

The full size CIM is available as Figure S5. The gene name given as the column header is the representative of a list of genes. The full list of genes is available in the HTGM Download S1.

Similar articles

Cited by

References

    1. Weinstein JN (2006) Spotlight on molecular profiling: “Integromic” analysis of the NCI-60 cancer cell lines. Mol Cancer Ther 5: 2601–2605. - PubMed
    1. Zeeberg BR, Reinhold W, Snajder R, Thallinger GG, Weinstein JN, et al. (2012) Functional Categories Associated with Clusters of Genes That Are Co-Expressed across the NCI-60 Cancer Cell Lines. PLoS ONE 7: e30317. - PMC - PubMed
    1. Ross DT, Perou CM (2001) A comparison of gene expression signatures from breast tumors and breast tissue derived cell lines. Disease Markers 17: 99–109. - PMC - PubMed
    1. Cancer Genome Atlas Research Network (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455: 1061–1068. - PMC - PubMed
    1. Verhaak RG, Hoadley KA, Purdom E, Wang V, Qi Y, et al. (2010) Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17: 98–110. - PMC - PubMed

Publication types

MeSH terms

LinkOut - more resources