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A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-kappaBeta pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types.

Conflict of interest statement

Competing Interests Statement

The authors declare that they have no competing financial interests.


Figure 1
Figure 1
Identification of significant arm-level and focal SCNAs across cancer. a) Length distribution of SCNAs. b) Length-adjusted Z-scores for gains (x-axis) and losses (y-axis) of indicated chromosome arms. Arms in red, blue, purple, and black exhibit significant gain, loss, both, or neither, respectively. c) GISTIC q-values (x-axis) for deletions (left, blue) and amplifications (right, red) are plotted across the genome (y-axis). Known or putative gene targets within the peak regions (TRB@, indicated by an asterisk, is immediately adjacent) are indicated for the 20 most significant peaks; values in parentheses represent the number of genes in the peak region.
Figure 2
Figure 2
Characteristics of significant focal SCNAs. a) Genes are ranked by the amount of genome occupied. Local gene density is normalized against the genome-wide average. b) Average gene density as a function of copy number. c) GRAIL analysis p-values, plotted for each peak region, reflect the similarity between genes in that region compared to genes in all other regions. Increasing significance is plotted towards the top and reflects greater similarity. Histograms of p-values are displayed for randomly placed regions (“Permuted controls”). d) The literature terms most associated with genes in either deletion or amplification peaks, but not both.
Figure 3
Figure 3
Dependency of cancer cell lines on the amplified BCL2 family members, MCL1 and BCL2L1. a) Enrichment of pro- and anti-apoptotic BCL2 family members deletion and amplification peaks. b) Copy-number profiles among 50 tumors around MCL1 (lineages are across the top; genomic locations are on the left). c) Changes in cell number after MCL1 knockdown relative to controls. d) Proliferation rates in NCI-H2110 cells after siRNA transfection against the listed genes. e) Effect of MCL1 knock-down on growth of NCI-H2110 xenografts. f) Changes in cell number after BCL2L1 knockdown relative to controls. Error bars represent s.e.m. across 3 experiments.
Figure 4
Figure 4
The majority of significant focal SCNA peaks identified in any one tumor type are also identified in the rest of the dataset (its complement). The top Venn diagram represents median results across the 17 tumor types represented by >40 samples. Venn diagrams representing the specific examples of non-small cell lung cancer, esophageal adenocarcinoma, and acute lymphoblastic leukemia are displayed along the bottom. Diagrams are not drawn to scale.

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