NCI Data Base for Cancer Cell Lines

The NCI has published a pare in Cancer Research. The paper states:

The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. This panel has generated the most extensive cancer pharmacology database worldwide. In addition, these cell lines have been intensely investigated, providing a unique platform for hypothesis-driven research focused on enhancing our understanding of tumor biology. Here, we report a comprehensive analysis of coding variants in the NCI-60 panel of cell lines identified by whole exome sequencing, providing a list of possible cancer specific variants for the community. 

Furthermore, we identify pharmacogenomic correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin showing one of many ways the data could be used to validate and generate novel hypotheses for further investigation. As new cancer genes are identified through large-scale sequencing studies, the data presented here for the NCI-60 will be an invaluable resource for identifying cell lines with mutations in such genes for hypothesis-driven research. To enhance the utility of the data for the greater research community, the genomic variants are freely available in different formats and from multiple sources including the CellMiner and Ingenuity websites. 

On the NCI web site they state:

 NCI scientists have developed a comprehensive list of genetic variants for each of the types of cells that comprise what is known as the NCI-60 cell line collection. This new list adds depth to the most frequently studied human tumor cell lines in cancer research, molecular pharmacology, and drug discovery. The NCI-60 cancer cell panel represents nine different types of cancer: breast, ovary, prostate, colon, lung, kidney, brain, leukemia, and melanoma. In this study, the investigators sequenced the whole exomes, or DNA coding regions, of each of NCI-60 cell lines, to define novel cancer variants and aberrant patterns of gene expression in tumor cells and to relate such patterns and variants to those that occur during the development of cancer. They also found correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and the activity of anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin.

 NIH introduced the tools such as CellMiner a year ago and it was in the following release:

Genomic sequencing and analysis have become increasingly important in biomedicine, but they are yielding data sets so vast that researchers may find it difficult to access and compare them.  As new technologies emerge and more data are generated, tools to facilitate the comparative study of genes and potentially promising drugs will be of even greater importance.  With the new tools, available at http://discover.nci.nih.gov/cellminer, researchers can compare patterns of drug activity and gene expression, not only to each other but also to other patterns of interest.  CellMiner allows the input of large quantities of genomic and drug data, calculates correlations between genes and drug activity profiles, and identifies correlations that are statistically significant. Its data integration capacities are easier, faster, and more flexible than other available methods, and these tools can be adapted for use with other collections of data.  

CellMiner is accessible at NCI.