Integrated Analysis of TP53 Gene and Pathway Alterations in The Cancer Genome Atlas

Abstract

The TP53 tumor suppressor gene is frequently mutated in human cancers. An analysis of five data platforms in 10,225 patient samples from 32 cancers reported by The Cancer Genome Atlas (TCGA) enables comprehensive assessment of p53 pathway involvement in these cancers. More than 91% of TP53-mutant cancers exhibit second allele loss by mutation, chromosomal deletion, or copy-neutral loss of heterozygosity. TP53 mutations are associated with enhanced chromosomal instability, including increased amplification of oncogenes and deep deletion of tumor suppressor genes. Tumors with TP53 mutations differ from their non-mutated counterparts in RNA, miRNA, and protein expression patterns, with mutant TP53 tumors displaying enhanced expression of cell cycle progression genes and proteins. A mutant TP53 RNA expression signature shows significant correlation with reduced survival in 11 cancer types. Thus, TP53 mutation has profound effects on tumor cell genomic structure, expression, and clinical outlook.

Keywords: PanCanAtlas; TCGA; TP53; TP53 mutation; The Cancer Genome Atlas; chromosomal instability; p53; p53 signaling pathway; p53 signature; p53 targets.

Figure 1.. TP53 mutation profile in the TCGA dataset is similar to that of current TP53 databases.

(A) TP53 mutation frequency varies depending on tumor type. For each cancer type, the relative fraction of non-truncating and truncating mutations are indicated. (B) Distribution of global TP53 mutations in the TCGA dataset are similar to the Sanger sequenced subset of the UMD_TP53 Mutation Database. Major TP53 hotspot mutations are indicated. (C) Exon distribution of TP53 mutations for all variants in the Sanger subset of the UMD_TP53 Mutation Database (top panel) is similar to that observed for TCGA dataset TP53 mutations (middle panel). Previously unreported TP53 single nucleotide variants (SNVs) discovered by TCGA are in bottom panel. (D) Distribution of codon SNV sites along the p53 protein recorded to date. For each codon nine SNVs are possible. Red bars indicate SNVs observed for each codon, while green bars indicate SNVs not yet reported. Unmutated residues at codon 114 and hotspot residues at codon 175, 248, and 273 are shown by asterisks. TAD: transactivation domain; Pro: proline rich domain; OLI: tetramerization domain; I to V: evolutionarily conserved domains. (E) TP53 variants in functional domains of p53. The DNA-binding surface of p53 protein is composed of two large loops (L2 and L3) stabilized by a zinc ion. Sheet S10 and Helix H2, is a component of the LSH (loop Sheet Helix) domain that includes loop L1. These various domains are essential for DNA recognition. Variants are depicted for each structural domain. Sanger: number of TP53 variants found in the Sanger dataset of the UMD_TP53 database; TCGA: number of TP53 variants in the TCGA dataset. Variant frequencies are denoted by bars. The heat map corresponds to loss of function of TP53 variants measured by the functional assays of Kato et al. (1); Kotler et al. (2) and the three functional assays of Giacomelli et al. (3–5). Also see Fig. S1,S2.

Figure 2.. Inactivation of both alleles occurs in most TCGA cancers with TP53 mutations.

(A) p53 functional analyses in some TCGA tumors with two TP53 mutations. Heat maps show relative transcriptional activity of TP53 variants compared with wildtype TP53 based on data in Kato et al. (2003). Each column shows a p53 transcriptional target and each row shows a TP53 variant. W - WAF1 (CDKN1A); M – MDM2; B – BAX; 14 – 14-3-3 sigma (SFN); A – AIP (TP53AIP1); G – GADD45A; N – NOXA (PMAIP1); P – p53R2 (RRM2B). Database variant frequency is shown as a blue bar. (B) Individual DNA sequence reads from tumors with two closely linked TP53 mutations show trans (left) and cis (right) mutation configurations. Mutations are at the top. Gray boxes represent individual nucleotides. Gray lines show individual sequence reads with colored segments indicating mutations. (C) Most tumors with two closely linked TP53 mutations have trans mutations and retain diploid copy number (NO LOH), while a minority have cis mutations but show wildtype TP53 allele loss (LOH). (D) Tumors with one TP53 mutation exhibit TP53 copy number loss while tumors with 0 or 2 TP53 mutations are largely diploid. Copy number values at the TP53 locus for tumors with 0 (top panel), 1 (middle panel), or 2–3 (lower panel) TP53 mutations are shown. On the X axis TP53 copy number values are binned in 0.1 value increments where 0 represents diploidy and values of −0.4 to −0.6 are roughly equivalent to a haploid copy number. Significant differences between each category are indicated. ****(p < 1E-50); ***(p < 1E-25). (E,F) Median variant allele fractions (VAF) in tumors with one TP53 mutation approximate 1.0, indicating frequent loss of both wildtype TP53 alleles. Uterine corpus endometrial carcinoma (UCEC) (E) and head and neck squamous cell carcinoma (HNSC) (F) were stratified by mutation number and copy number. A copy number (CN) of 0 is considered diploid and CN of −1 is considered haploid. “Mult Mut” indicates tumors with 2+ TP53 mutations. VAF distributions are shown and median values are indicated by the central bar in the box and whiskers plots. Statistical significance was indicated by t tests. See also Fig. S3.

Figure 3.. TP53 mutation is correlated with increased chromosomal instability.

(A) Genomic profile aggregated from copy number data of all TCGA tumors shows that frequent amplifications and deep deletions occur significantly more in MUT TP53 than in WT TP53 tumors. Fraction of copy number losses (CN < −1) (top panel) and gains (CN > 2) (middle panel) for wildtype (blue line) and mutant (orange line) tumors are shown. Peaks correspond to frequent regions of deep deletion (top panel) and amplification (middle panel) and are labeled with the tumor suppressor gene or oncogene at the epicenter of each peak. Statistical significance in relative frequency of deletion or amplification between WT and MUT TP53 tumors at each gene are indicated in the bottom panel. (B) Mutant TP53 tumor genomes display roughly 2.5 fold higher rates of amplification and deep deletion relative to their wildtype TP53 counterparts. Gene loci with copy number values greater than 2 (amplification) and less than −1 (deep deletion) were totaled for all wildtype and all mutant TP53 tumors and divided by total loci number in each TP53 category. (C) Most cancer types show significantly increased rates of amplification and deep deletion in the MUT TP53 tumors (Mut TP53 Sig Inc) compared to wildtype TP53 tumors (WT TP53 Sig Inc). The fraction of loci with deep deletion or amplification in MUT TP53 tumors was divided by that in WT TP53 tumors to give a ratio. Significance was determined by t test. (D) Of the six most frequent deep deletions, five occur significantly more frequently in the mutant compared to the wildtype TP53 group. (E) Of the six most frequent amplifications, five occur significantly more frequently in the mutant compared to the wildtype TP53 group. (F) Three frequently amplified negative regulators of p53 (MDM2, MDM4, and PPM1D) are significantly more amplified in WT relative to MUT TP53 tumors. (G) Nucleotide level mutation rates are increased in MUT TP53 tumors. Median mutation numbers per tumor for wildtype and mutant TP53 tumors are shown in the box and whiskers plots. An unpaired t test showed that the mutant TP53 tumors have significantly more total mutations per tumor compared to their wildtype counterparts. See also Table S1.

Figure 4.. Comparison of global RNA expression reveals p53-dependent pathways in cancer.

(A) The most significantly upregulated gene RNAs in wildtype TP53 cancers are mostly known p53 target genes and the number of cancer types in which they were upregulated is indicated. Direct p53 target genes are indicated by red bars. See also Table S2 and S3. (B) Pathway analyses based on genes expressed at significantly higher rates in wildtype TP53 cancers shows that p53-related pathways (red bars) are highly enriched. See also Table S4A. (C) The most significantly upregulated RNAs in mutant TP53 cancers are cell division promoters. For each cancer the top 100 and 500 gene RNAs most highly expressed in mutant relative to wildtype TP53 tumors were identified and the top 20 upregulated genes across all mutant TP53 cancers are shown. Roles for cell division, G2/M checkpoint control, E2F target genes, and documented repression by p53 are indicated by blue boxes. Significant upregulation in individual cancer types are indicated by red and pink boxes. Red arrows indicate four genes comprising the mutant p53 signature discussed later (Fig. 7). (D) Pathway GSEA analysis based on mutant TP53 upregulated genes in TCGA cancers confirms importance of cell cycle regulation (blue bars). Also see Table S4B.

Figure 5.. Comparison of global microRNA, and protein expression reveals p53-dependent pathways in cancer.

(A) Tumors with wildtype TP53 show upregulation of a subset of miRNAs relative to tumors with mutant TP53. For each tumor type those miRNAs most significantly upregulated for expression in wildtype relative to mutant TP53 cancers were determined. The top 20 most significantly upregulated miRNAs are shown. Blue rectangles indicate whether each miRNA is a direct p53 transcriptional target or has been shown to exhibit tumor suppressor activity. Pink rectangles indicate the miRNA is significantly upregulated in specific cancers. See also Table S5A. (B) Tumors with mutant TP53 show significant upregulation of a subset of miRNAs relative to tumors with wildtype TP53. For each tumor type, the top 20 miRNAs most significantly upregulated for expression in mutant TP53 cancers are shown. Green rectangles indicate miRNA oncogenic activity and blue rectangles indicate significantly upregulation in specific cancers. Also see Table S5B. (C) Schematic diagram outlining miRNAs significantly upregulated in wildtype TP53 cancers (left) and mutant TP53 cancers (right), their key target genes and proposed pathway impacts. (D) GSEA analysis of RPPA data indicates that proteins most upregulated in TCGA mutant TP53 tumors are enriched for cell cycle progression (green bars) and DNA damage response (blue bars). See Table S6B.

Figure 6.. Genomic alterations mutually exclusive with TP53 mutations.

(A) Schematic overview of Mutex algorithm for determining gene mutual exclusivity (see Methods). (B) Pathway representation of mutually exclusive partners of TP53 across all cancer types. The color code represents the cancer type in which mutual exclusivity is observed. White indicates mutual exclusivity in more than one cancer. Genes are grouped based on their topology in the network. The disconnected gene groups on the right do not have connections to TP53 in the Pathway Commons database. (C) The oncoprint representation of TP53 mutation mutual exclusivity genomic modules. Note the partners in SARC are all amplified on the same samples, which is a chromosomal event at chromosome 12q. The p values represent significance of the observed mutual exclusivity between each gene and TP53 as calculated by a Fisher’s Exact Test. See also Fig. S6.

Figure 7.. Development of a prognostic mutant TP53 signature.

(A) Lower grade glioma (LGG) stratified by mutant p53 expression signature correlates with a number of clinical and molecular parameters. For all LGG, RNA expression of the four genes comprising the mutant p53 signature (CDC20, PLK1, CENPA, and KIF2C) were ranked from low to high expression and combined (“Mut p53 Signature”). The bottom and top signature expression quartiles are demarcated by black vertical lines. Also indicated are tumor grade and mortality. Below the signature is shown TP53 mutation status and copy number and mutation status of a number of cancer driver genes relevant to LGG development. p values to the right indicate the significance of the difference of the low and high signature quartiles for each parameter. (B) p53 mutant signature status is more prognostically predictive than TP53 mutation status for overall survival in LGG. Log rank analysis was performed on the LGG overall survival data based on TP53 mutation status (top panel) or on mutant p53 signature status (bottom panel) in a top versus bottom quartile analysis. (C) Skin cutaneous melanoma (SKCM) stratified by p53 expression signature shows correlates with TP53 mutation and mortality. The heat maps shown here are similar to those described for panel (A), though driver genes relevant to SKCM are shown. (D) p53 mutant signature status is more prognostically predictive than TP53 mutation status for overall survival in SKCM. Overall survival in SKCM is compared based on TP53 mutation status (top panel) or on mutant p53 signature status (bottom panel) as in panel B. See also Fig. S7 and Table S7.