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Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma - PubMed

  • ️Mon Jan 01 2007

Comparative Study

Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma

Rameen Beroukhim et al. Proc Natl Acad Sci U S A. 2007.

Abstract

Comprehensive knowledge of the genomic alterations that underlie cancer is a critical foundation for diagnostics, prognostics, and targeted therapeutics. Systematic efforts to analyze cancer genomes are underway, but the analysis is hampered by the lack of a statistical framework to distinguish meaningful events from random background aberrations. Here we describe a systematic method, called Genomic Identification of Significant Targets in Cancer (GISTIC), designed for analyzing chromosomal aberrations in cancer. We use it to study chromosomal aberrations in 141 gliomas and compare the results with two prior studies. Traditional methods highlight hundreds of altered regions with little concordance between studies. The new approach reveals a highly concordant picture involving approximately 35 significant events, including 16-18 broad events near chromosome-arm size and 16-21 focal events. Approximately half of these events correspond to known cancer-related genes, only some of which have been previously tied to glioma. We also show that superimposed broad and focal events may have different biological consequences. Specifically, gliomas with broad amplification of chromosome 7 have properties different from those with overlapping focalEGFR amplification: the broad events act in part through effects on MET and its ligand HGF and correlate with MET dependence in vitro. Our results support the feasibility and utility of systematic characterization of the cancer genome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.

Overview of the GISTIC method. After identifying the locations and, in the case of copy-number alterations, magnitudes (as log2 signal intensity ratios) of chromosomal aberrations in multiple tumors (Left), GISTIC scores each genomic marker with a G score that is proportional to the total magnitude of aberrations at each location (Upper Center). In addition, by permuting the locations in each tumor, GISTIC determines the frequency with which a given score would be attained if the events were due to chance and therefore randomly distributed (Lower Center). A significance threshold (green line) is determined such that significant scores are unlikely to occur by chance alone. Alterations are deemed significant if they occur in regions that surpass this threshold (Right). For more details see

SI Text

.

Fig. 2.
Fig. 2.

Significant broad and focal copy-number alterations in the glioma genome. (a) Amplifications (red) and deletions (blue), determined by segmentation analysis of normalized signal intensities from 100K SNP arrays (see

SI Text

), are displayed across the genome (chromosome positions, indicated along the y axis, are proportional to marker density) for 141 gliomas (x axis; diagnosis is displayed on top, and gliomas with low purity are segregated to the right). Broad events near the size of a chromosome arm are the most prominent, including amplifications of chr7 and deletions of chr10 observed among >80% of GBMs. (b) GISTIC analysis of copy-number changes in glioma. The statistical significance of the aberrations identified in a are displayed as FDR q values (9) to account for multiple-hypothesis testing. Chromosome positions are indicated along the y axis with centromere positions indicated by dotted lines. Fifteen broad events (indicated by red bars for amplifications and blue bars for deletions) and 16 focal events (indicated by dashes) surpass the significance threshold (green line). The locations of the peak regions and the known cancer-related genes within those peaks are indicated to the right of each panel. Several broad regions, including chr7 and chr10, contain superimposed focal events, leading to needle-shaped peaks superimposed on highly significant plateaus.

Fig. 3.
Fig. 3.

Broad gains of chromosome 7 often activate the MET pathway but not EGFR. (a) Expression levels of EGFR, MET, and its ligand HGF (all located on chr7) in primary GBMs. These data are log2-transformed signal intensities from all concordant probe sets for each gene from Affymetrix U133 arrays, centered and normalized according to the median and median absolute deviation of samples with 7norm. Samples with 7gainEGFRamp but not 7gain overexpress EGFR (highlighted in red) relative to 7norm. Conversely, a subset of tumors with 7gain overexpress MET or its ligand HGF, even in the absence of focal amplification. (b) A subset of glioma cell lines with 7gain also overexpress MET and HGF (MET/HGF+ lines, highlighted in red). We characterized lines as having 7gain if SNP array analysis showed them to be amplified across most of chr7. Cell lines are classified as being MET-dependent based on the results shown in d or previously published results (asterisks) (35). (c) Constitutive phosphorylation of MET in MET/HGF+ lines. Immunoblots to the indicated epitopes were performed on whole-cell lysates prepared after 24-h serum starvation. Decreased MET protein levels in activated lines are a result of HGF-induced degradation (36). MET-dependent gastric cancer cells (MKN-45) were included as positive controls (35). (d) Decreased viability of MET/HGF+ cell lines (red) compared with non-MET/HGF+ lines (black) when treated with the MET inhibitor SU11274. Viability was measured by using Trypan blue exclusion after exposure to inhibitor at the indicated concentrations for 96 h. MKN-45 cells (blue) were included as positive controls.

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