Comprehensive genomic characterization defines human glioblastoma genes and core pathways

Abstract

Human cancer cells typically harbour multiple chromosomal aberrations, nucleotide substitutions and epigenetic modifications that drive malignant transformation. The Cancer Genome Atlas (TCGA) pilot project aims to assess the value of large-scale multi-dimensional analysis of these molecular characteristics in human cancer and to provide the data rapidly to the research community. Here we report the interim integrative analysis of DNA copy number, gene expression and DNA methylation aberrations in 206 glioblastomas--the most common type of adult brain cancer--and nucleotide sequence aberrations in 91 of the 206 glioblastomas. This analysis provides new insights into the roles of ERBB2, NF1 and TP53, uncovers frequent mutations of the phosphatidylinositol-3-OH kinase regulatory subunit gene PIK3R1, and provides a network view of the pathways altered in the development of glioblastoma. Furthermore, integration of mutation, DNA methylation and clinical treatment data reveals a link between MGMT promoter methylation and a hypermutator phenotype consequent to mismatch repair deficiency in treated glioblastomas, an observation with potential clinical implications. Together, these findings establish the feasibility and power of TCGA, demonstrating that it can rapidly expand knowledge of the molecular basis of cancer.

Figure 1. Significant copy number aberrations and pattern of somatic mutations

(a) Frequency and significance of focal high-level copy-number alterations. Known and putative target genes are listed for each significant CNA, with “Number of Genes” denoting the total number of genes within each focal CNA boundary. (b–c) Distribution of the number of (b) silent and (c) non-silent mutations across the 91 GBM samples separated according to their treatment status, showing hypermutation in 7 out of the 19 treated samples. (d) Significantly mutated genes in 91 glioblastomas. The eight genes attaining a false discovery rate <0.1 are displayed here. Somatic mutations occurring in untreated samples are in dark blue; those found in statistically non-hypermutated and hypermutated samples among the treated cohort are in respectively lighter shades of blue.

Figure 2. Mutations in NF1 tumor suppressor gene and EGFR family members

(a) NF1 somatic mutations in 91 glioblastoma tumors. Both missense mutations and truncating nonsense, frameshift, and splice site mutations were observed. Splice positions are given in number of bases to the closest exon (e#) numbered according to the NF1 reference transcript in the Human Gene Mutation Database; positive = 3′ of exon, negative = 5′ of exon. *: stop codon. fs: frameshift. (b) Correlation of copy number and mutation status at the NF1 locus with level of expression (Y axis). Mutation events predicted to result in fewer expressed copies (including deletion, nonsense, splice site, and frameshift mutations) generally have lower observed expression. HomoDel = homozygous deletion; HemiDel = single-copy loss; Neutral = no change in copy number (presumed diploid); Amp = increased copy number. Copy number status of the NF1 locus in each sample was determined as described in the Supplementary Information. (c). DNA Copy number and mRNA expression profiles for TCGA samples TCGA-08–0356 (red), TCGA-02–0064 (blue), and TCGA-02–0529 (green) at the EGFR locus. The upper panel shows the segmented DNA copy number (based on Affymetrix SNP6.0 data) versus genomic coordinates on chromosome 7. The lower panel shows relative exon expression levels across the known EGFR exons from the Affymetrix Exon array ordered by genomic position, where relative expression is the median-centered difference in exon intensity and gene intensity. The EGFR gene model lies between the two plots. Black lines map the genomic positions of exons 2 through 7 and 26 through 28. Note that structural deletions cause the relatively lower expression of exons 2–7 in the green and blue samples and exons 26–28 in the red sample. (d) ERBB2 somatic mutations in 91 glioblastoma tumors. Mutations cluster in the extracellular domain in both genes. Splice site mutation position is given in number of bases to the closest exon (e#); positive = 3′ of exon.

Figure 3. PIK3R1 and PIK3CA mutations in GBM

(a). Diamonds above the backbone indicate the locations of mutations found in TCGA tumors. ABD: adaptor binding domain; RDB: Ras binding domain; C2: membrane-binding domain; iSH2: intervening domain. (b). Four mutations found in the interaction interface of the p110α; C2 domain with iSH2 of p85 α. Two residues of p85 α, D560 and N564, are within hydrogen-bonding distance of the C2 residue of p110 α, N345.

Figure 4. Pattern of somatic mutations, MGMT DNA methylation, and MMR gene mutations in treated GBMs

(a). The mean number of validated somatic nucleotide substitutions per tumor for key sample groups is indicated on the Y-axis and denoted by the height of the bar histograms. Samples are grouped along the X-axis according to treatment status of the patient (− = untreated; + = treated), DNA methylation status of MGMT (meth = DNA methylated; − = not methylated), and genetic status of MMR genes − = no genes mutated and mut = one or more of the MLH1, MSH2, MSH6, or PMS2 genes mutated); the number below each bar indicates the number of samples in the group. Bars are color-coded for types of nucleotide substitutions including G-to-A transitions at non-CpG sites (orange), G-to-A transitions at CpG sites (blue), and other mutation types (green). (b). Bar histogram for mutation spectrum in the MMR genes as a function of treatment status, and methylation status of MGMT. The color code for substitution types is the same as in (a).

Figure 5. Frequent genetic alterations in three critical signaling pathways

Primary sequence alterations and significant copy number changes for components of the (a) RTK/RAS/PI-3K, (b) p53, and (c) RB signaling pathways are shown. Red indicates activating genetic alterations, with frequently altered genes showing deeper shades of red. Conversely, blue indicates inactivating alterations, with darker shades corresponding to a higher percentage of alteration. For each altered component of a particular pathway, the nature of the alteration and the percentage of affected tumors affected are indicated. Blue boxes contain the final percentages of glioblastomas with alterations in at least one known component gene of the designated pathway.