Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Bladder Urothelial Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C18P5XW5
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C18P5XW5
Overview
Introduction

This report serves to describe the mutational landscape and properties of a given individual set, as well as rank genes and genesets according to mutational significance. MutSig v2.0 and MutSigCV v0.9 merged result was used to generate the results found in this report.

  • Working with individual set: BLCA-TP

  • Number of patients in set: 28

Input

The input for this pipeline is a set of individuals with the following files associated for each:

  1. An annotated .maf file describing the mutations called for the respective individual, and their properties.

  2. A .wig file that contains information about the coverage of the sample.

Summary

  • MAF used for this analysis:BLCA-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 1

  • Mutations seen in COSMIC: 35

  • Significantly mutated genes in COSMIC territory: 3

  • Significantly mutated genesets: 20

Mutation Preprocessing

  • Read 28 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 7557

  • After removing 3 mutations outside chr1-24: 7554

  • After removing 166 blacklisted mutations: 7388

  • After removing 126 noncoding mutations: 7262

Mutation Filtering

  • Number of mutations before filtering: 7262

  • After removing 79 mutations outside gene set: 7183

  • After removing 11 mutations outside category set: 7172

Results
Breakdown of Mutations by Type

Table 1.  Get Full Table Table representing breakdown of mutations by type.

type count
Frame_Shift_Del 85
Frame_Shift_Ins 37
In_Frame_Del 20
In_Frame_Ins 4
Missense_Mutation 4662
Nonsense_Mutation 418
Nonstop_Mutation 9
Silent 1814
Splice_Site 115
Translation_Start_Site 8
Total 7172
Breakdown of Mutation Rates by Category Type

Table 2.  Get Full Table A breakdown of mutation rates per category discovered for this individual set.

category n N rate rate_per_mb relative_rate exp_ns_s_ratio
Tp*C->(T/G) 2634 108904258 0.000024 24 3.7 3
Tp*C->A 202 108904258 1.9e-06 1.9 0.28 4
(A/C/G)p*C->mut 1219 308289400 4e-06 4 0.61 3.2
A->mut 615 402887181 1.5e-06 1.5 0.23 3.9
indel+null 677 820080839 8.3e-07 0.83 0.13 NaN
double_null 11 820080839 1.3e-08 0.013 0.0021 NaN
Total 5358 820080839 6.5e-06 6.5 1 3.5
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: BLCA-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5.  Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

Significantly Mutated Genes

Column Descriptions:

  • N = number of sequenced bases in this gene across the individual set

  • n = number of (nonsilent) mutations in this gene across the individual set

  • npat = number of patients (individuals) with at least one nonsilent mutation

  • nsite = number of unique sites having a non-silent mutation

  • nsil = number of silent mutations in this gene across the individual set

  • n1 = number of nonsilent mutations of type: Tp*C->(T/G)

  • n2 = number of nonsilent mutations of type: Tp*C->A

  • n3 = number of nonsilent mutations of type: (A/C/G)p*C->mut

  • n4 = number of nonsilent mutations of type: A->mut

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_cons = p-value for enrichment of mutations at evolutionarily most-conserved sites in gene

  • p_joint = p-value for clustering + conservation

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 1. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).

rank gene description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_clust p_cons p_joint p_cv p q
1 TP53 tumor protein p53 34506 14 11 13 1 2 0 8 1 3 0 0.000023 0.0031 0.000022 0.0023 8.9e-07 0.016
2 FBXW7 F-box and WD repeat domain containing 7 68665 6 5 5 0 2 0 2 0 2 0 0.003 0.071 0.0034 0.0058 0.00023 1
3 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 50092 4 4 4 0 1 0 1 2 0 0 0.27 0.0095 0.016 0.048 0.0061 1
4 CRYBB1 crystallin, beta B1 21812 2 1 2 1 0 1 0 0 1 0 0.0091 0.083 0.015 0.11 0.012 1
5 RFTN2 raftlin family member 2 40281 3 3 3 0 1 0 0 0 2 0 0.32 0.51 0.5 0.0051 0.018 1
6 H1FX H1 histone family, member X 6847 2 1 2 0 2 0 0 0 0 0 0.073 0.18 0.038 0.07 0.019 1
7 TBCC tubulin folding cofactor C 28768 3 1 3 0 3 0 0 0 0 0 0.16 0.0041 0.0056 0.51 0.02 1
8 C17orf81 chromosome 17 open reading frame 81 29954 3 2 3 1 2 0 1 0 0 0 0.0087 0.081 0.0065 0.44 0.02 1
9 PYGO1 pygopus homolog 1 (Drosophila) 35616 3 3 3 0 0 0 1 1 1 0 0.088 0.62 0.21 0.016 0.022 1
10 GPS2 G protein pathway suppressor 2 26706 3 3 3 0 0 1 0 0 1 1 0.4 0.37 0.55 0.0061 0.023 1
11 AZI1 5-azacytidine induced 1 72929 3 2 3 2 3 0 0 0 0 0 0.011 0.012 0.004 0.86 0.023 1
12 RPL31 ribosomal protein L31 12690 3 1 3 0 3 0 0 0 0 0 0.0046 0.16 0.0065 0.58 0.025 1
13 NXPH2 neurexophilin 2 20944 2 1 2 0 0 0 1 1 0 0 0.01 0.8 0.018 0.22 0.026 1
14 C8orf42 chromosome 8 open reading frame 42 10958 2 1 2 0 1 0 0 0 1 0 0.13 0.058 0.066 0.06 0.026 1
15 AMACR alpha-methylacyl-CoA racemase 37197 2 2 2 0 1 0 0 0 1 0 0.04 0.22 0.063 0.066 0.027 1
16 KLF5 Kruppel-like factor 5 (intestinal) 31500 2 2 2 1 0 0 0 0 2 0 0.1 0.4 0.4 0.01 0.027 1
17 ZNF263 zinc finger protein 263 58087 3 3 3 0 1 0 0 0 2 0 0.056 0.64 0.23 0.019 0.028 1
18 NUDT14 nudix (nucleoside diphosphate linked moiety X)-type motif 14 16739 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.03 0.03 1
19 MGA MAX gene associated 241266 2 2 2 0 1 0 0 0 1 0 0.79 0.0046 0.0052 0.98 0.032 1
20 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 32054 3 3 3 0 0 0 1 0 2 0 0.44 0.48 0.7 0.0075 0.033 1
21 LCE1F late cornified envelope 1F 10079 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.033 0.033 1
22 ADSS adenylosuccinate synthase 37589 1 1 1 0 1 0 0 0 0 0 NaN NaN NaN 0.035 0.035 1
23 CDH8 cadherin 8, type 2 68247 3 2 3 0 0 2 0 0 1 0 0.0044 0.13 0.0065 0.88 0.035 1
24 FEZ2 fasciculation and elongation protein zeta 2 (zygin II) 22624 2 2 2 0 1 0 0 0 1 0 0.065 0.59 0.32 0.018 0.036 1
25 GINS1 GINS complex subunit 1 (Psf1 homolog) 17292 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.036 0.036 1
26 C11orf85 chromosome 11 open reading frame 85 19112 2 2 2 0 0 0 0 1 1 0 0.2 0.9 0.22 0.029 0.038 1
27 MGP matrix Gla protein 8863 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.042 0.042 1
28 OR11H12 olfactory receptor, family 11, subfamily H, member 12 25197 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.042 0.042 1
29 HLA-A major histocompatibility complex, class I, A 29882 3 3 3 0 0 0 1 0 2 0 1 0.67 0.93 0.0076 0.042 1
30 TP53I13 tumor protein p53 inducible protein 13 26129 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.042 0.042 1
31 TNFSF4 tumor necrosis factor (ligand) superfamily, member 4 (tax-transcriptionally activated glycoprotein 1, 34kDa) 15764 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.043 0.043 1
32 INPP4B inositol polyphosphate-4-phosphatase, type II, 105kDa 78653 2 1 2 0 0 0 1 0 1 0 0.0097 0.03 0.02 0.38 0.044 1
33 NME4 non-metastatic cells 4, protein expressed in 13692 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.045 0.045 1
34 DOT1L DOT1-like, histone H3 methyltransferase (S. cerevisiae) 113039 5 2 5 4 3 0 0 0 2 0 0.013 0.029 0.0078 1 0.046 1
35 OR13G1 olfactory receptor, family 13, subfamily G, member 1 25970 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.046 0.046 1
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

COSMIC analyses

In this analysis, COSMIC is used as a filter to increase power by restricting the territory of each gene. Cosmic version: v48.

Table 4.  Get Full Table Significantly mutated genes (COSMIC territory only). To access the database please go to: COSMIC. Number of significant genes found: 3. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 14 356 14 9968 2964 0 0
2 FBXW7 F-box and WD repeat domain containing 7 6 91 4 2548 102 3.2e-09 7.1e-06
3 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 2 62 2 1736 216 0.000064 0.096
4 DPYSL4 dihydropyrimidinase-like 4 1 1 1 28 2 0.00018 0.17
5 TBC1D8B TBC1 domain family, member 8B (with GRAM domain) 2 1 1 28 1 0.00018 0.17
6 BMX BMX non-receptor tyrosine kinase 2 2 1 56 2 0.00037 0.24
7 GABRA6 gamma-aminobutyric acid (GABA) A receptor, alpha 6 2 2 1 56 1 0.00037 0.24
8 BAZ1A bromodomain adjacent to zinc finger domain, 1A 1 4 1 112 1 0.00073 0.36
9 PHIP pleckstrin homology domain interacting protein 3 4 1 112 1 0.00073 0.36
10 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3 220 2 6160 375 0.00079 0.36

Note:

n - number of (nonsilent) mutations in this gene across the individual set.

cos = number of unique mutated sites in this gene in COSMIC

n_cos = overlap between n and cos.

N_cos = number of individuals times cos.

cos_ev = total evidence: number of reports in COSMIC for mutations seen in this gene.

p = p-value for seeing the observed amount of overlap in this gene)

q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Geneset Analyses

Table 5.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 20. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 IFNGR2(1), JAK2(1), RB1(2), RELA(1), TNFRSF1B(1), TP53(14), USH1C(1) 754587 21 15 19 1 5 1 9 1 4 1 0.023 1.8e-08 0.000011
2 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(5), DAXX(1), PML(3), RARA(2), RB1(2), SP100(1), TNFRSF1B(1), TP53(14) 792662 29 17 27 2 7 0 13 1 7 1 0.012 5.3e-08 0.000016
3 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 DNAJC3(1), RELA(1), TP53(14) 408205 16 12 15 1 4 0 8 1 3 0 0.085 2.9e-07 0.000059
4 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 SP3(2), TP53(14) 292760 16 12 15 2 4 0 8 1 3 0 0.19 8.3e-07 0.00013
5 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 8 CUL1(4), FBXW7(6), RB1(2) 343289 12 9 9 0 5 0 3 0 3 1 0.06 5.7e-06 0.0007
6 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(3), RB1(2), TP53(14), WEE1(1) 734757 20 16 18 3 3 0 9 2 5 1 0.3 0.000022 0.0022
7 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(3), ATR(3), TP53(14) 670310 20 13 19 2 6 0 9 2 3 0 0.18 0.000065 0.0058
8 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 CCND1(1), CDKN1A(2), E2F2(1), TP53(14) 345627 18 12 17 3 4 0 9 2 3 0 0.22 0.00015 0.012
9 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(1), PIK3CA(3), PIK3R1(1), RB1(2), TP53(14) 838723 21 13 19 3 5 1 9 1 4 1 0.16 0.00025 0.017
10 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ABL1(1), ATM(3), ATR(3), CCND1(1), CDK6(1), CDKN1A(2), RB1(2), TP53(14) 1250337 27 17 25 3 10 0 10 2 4 1 0.079 0.00028 0.017
Methods & Data
Methods

In brief, we tabulate the number of mutations and the number of covered bases for each gene. The counts are broken down by mutation context category: four context categories that are discovered by MutSig, and one for indel and 'null' mutations, which include indels, nonsense mutations, splice-site mutations, and non-stop (read-through) mutations. For each gene, we calculate the probability of seeing the observed constellation of mutations, i.e. the product P1 x P2 x ... x Pm, or a more extreme one, given the background mutation rates calculated across the dataset. [1]

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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