Global Proteome Analysis of the NCI-60 Cell Line Panel

Abstract

The NCI-60 cell line collection is a very widely used panel for the study of cellular mechanisms of cancer in general and in vitro drug action in particular. It is a model system for the tissue types and genetic diversity of human cancers and has been extensively molecularly characterized. Here, we present a quantitative proteome and kinome profile of the NCI-60 panel covering, in total, 10,350 proteins (including 375 protein kinases) and including a core cancer proteome of 5,578 proteins that were consistently quantified across all tissue types. Bioinformatic analysis revealed strong cell line clusters according to tissue type and disclosed hundreds of differentially regulated proteins representing potential biomarkers for numerous tumor properties. Integration with public transcriptome data showed considerable similarity between mRNA and protein expression. Modeling of proteome and drug-response profiles for 108 FDA-approved drugs identified known and potential protein markers for drug sensitivity and resistance. To enable community access to this unique resource, we incorporated it into a public database for comparative and integrative analysis (http://wzw.tum.de/proteomics/nci60).

Characterizing the Covalent Targets of a Small Molecule Inhibitor of the Lysine Acetyltransferase P300

“…18 Whole proteome surveys indicate tubulins, heat shock proteins, and elongation factors are among the most abundant proteins in the cell. 19 The three strongly enriched proteins that lack an identified hyperreactive cysteine (TUBA8, TUBB2A, TUBB4A) are all tubulin proteins, implying C646 reactivity may possess a degree of recognition toward this protein class. While we cannot rule out that lower abundance proteins outside the scope of our detection method are also modified, these studies suggest that the major targets of C646-yne reactivity are abundant cellular proteins containing reactive cysteine residues.…”

Shotgun Lipidomic Profiling of the NCI60 Cell Line Panel Using Rapid Evaporative Ionization Mass Spectrometry

“…Taken together, these results confirm that REIMS profiles are strongly associated with the biological identity of cancer cell lines. Gene and protein expression patterns of the NCI-60 panel were found to correlate with tissue type of origin to some extent, 12,32 whereas metabolic signatures did not differentiate well between tissue origins. 14 Clustering of the cell lines based on their REIMS lipid profile showed extensive heterogeneity within most tissue types, except for melanoma samples (Figure 3, light blue colored cell lines).…”

“…Data available for these cell lines includes drug sensitivity patterns for more than 100,000 compounds and natural products, global protein and gene expression data and common mutations associated with cancer. [11][12][13][14] However, the associated metabolomics and lipidomics data is comparatively sparse. Although many publications are available investigating the lipid composition of certain types of cell lines using both chromatographybased 15, 16 and shotgun mass spectrometry methods, 4,[17][18][19][20] to our knowledge there is no work available characterizing the lipidome of the NCI60 cell line panel as a whole using a single set of conditions.…”

A biocomputational platform for the automated construction of large-scale mathematical models of miRNA-transcription factor networks for studies on gene dosage compensation

“…We considered input data including high resolution Copy Number Variation data (DNA) of the NCI-60 Cancer Cell lines from 4 different platforms [9], the Gene Transcript (RNA) Average Intensities of 5 Platforms [10], and the protein levels (Protein) of a global proteome analysis of the NCI-60 cell line panel [11]. Figure 1A left shows the relative variation of these absolute DNA, RNA and Protein levels.…”

“…The primary sources were from experiments on the NCI60 panel: gene copy number [17], RNA gene expression [18] and protein expression [11]. MicroRNA related data was downloaded from Mirtarbase [19] and MiRBase [20].…”