Mutation Analysis (MutSig 2CV v3.1)
Bladder Urothelial Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1X63M3F
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1X63M3F
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 2CV v3.1 was used to generate the results found in this report.

  • Working with individual set: BLCA-TP

  • Number of patients in set: 395

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

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 63

Results
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 1.  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 2.  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 3.  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:

  • nnon = 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

  • p = p-value (overall)

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

Table 1.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 63. 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 longname codelen nnei nncd nsil nmis nstp nspl nind nnon npat nsite pCV pCL pFN p q
1 TP53 tumor protein p53 1890 0 0 7 157 41 7 23 228 196 120 1e-16 1e-05 1e-05 1e-16 5.1e-13
2 RB1 retinoblastoma 1 (including osteosarcoma) 3719 10 0 1 8 36 15 20 79 70 70 1e-16 0.61 0.00063 1e-16 5.1e-13
3 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 1148 9 0 0 35 3 1 21 60 46 50 1e-16 0.14 0.036 1.1e-16 5.1e-13
4 TSC1 tuberous sclerosis 1 3579 3 0 4 10 13 5 6 34 33 30 1e-16 0.021 0.2 1.1e-16 5.1e-13
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 24 0 4 93 0 1 0 94 86 35 5.6e-13 1e-05 1e-05 2.2e-16 6.8e-13
6 RHOB ras homolog gene family, member B 591 99 0 0 30 0 0 0 30 26 18 8e-15 0.00054 0.11 2.2e-16 6.8e-13
7 KDM6A lysine (K)-specific demethylase 6A 4318 2 0 6 22 37 11 43 113 103 97 1.7e-16 0.071 0.1 3.3e-16 8.7e-13
8 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 6 0 0 17 4 2 7 30 26 22 2.8e-12 0.025 1e-05 1.1e-15 2.5e-12
9 ARID1A AT rich interactive domain 1A (SWI-like) 6934 36 0 8 41 48 6 30 125 97 110 1e-16 0.37 0.46 1.9e-15 3.8e-12
10 STAG2 stromal antigen 2 3939 5 0 8 17 25 3 16 61 56 54 1e-16 0.47 0.78 2.6e-15 4.7e-12
11 ZFP36L1 zinc finger protein 36, C3H type-like 1 1197 14 0 1 8 4 0 20 32 25 31 5.4e-16 0.52 0.88 1.4e-14 2.4e-11
12 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 503 89 0 1 8 6 0 29 43 35 33 2.3e-15 0.1 0.75 1.5e-14 2.4e-11
13 EP300 E1A binding protein p300 7365 24 0 7 48 21 1 8 78 61 74 3.3e-15 0.36 0.2 2.7e-14 3.8e-11
14 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 16826 1 0 14 56 57 12 30 155 114 149 1.6e-15 1 0.53 5.6e-14 7.3e-11
15 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 2642 8 1 5 61 1 0 2 64 56 18 3.5e-10 1e-05 0.0075 1.2e-13 1.5e-10
16 ERCC2 excision repair cross-complementing rodent repair deficiency, complementation group 2 (xeroderma pigmentosum D) 2430 43 1 3 38 0 0 0 38 38 22 3e-09 1e-05 0.017 9.6e-13 1.1e-09
17 CREBBP CREB binding protein (Rubinstein-Taybi syndrome) 7449 11 0 8 26 17 3 5 51 48 48 5e-12 0.035 0.71 1.1e-11 1.2e-08
18 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 659 25 0 1 15 1 0 0 16 16 10 1.6e-06 1e-05 0.14 4.1e-10 4.2e-07
19 FOXA1 forkhead box A1 1423 7 0 2 5 0 0 9 14 14 13 9.6e-11 0.42 0.73 1.3e-09 1.2e-06
20 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 127 1 0 13 0 0 0 13 13 5 7.1e-06 2e-05 0.24 1.7e-09 1.6e-06
21 RHOA ras homolog gene family, member A 918 94 0 1 19 0 0 0 19 18 15 1.9e-08 0.066 0.14 3e-08 0.000026
22 KIAA1267 KIAA1267 3372 0 0 1 12 5 4 4 25 24 24 4.3e-09 0.53 0.6 5.7e-08 0.000048
23 MLL myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila) 12052 6 0 10 29 17 3 5 54 44 53 5.2e-09 0.71 0.95 1e-07 0.000083
24 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 13871 1 0 8 30 14 0 13 57 50 56 2.2e-08 0.59 0.13 1.5e-07 0.00012
25 KLF5 Kruppel-like factor 5 (intestinal) 1386 4 0 3 17 1 0 6 24 23 21 9.4e-07 0.017 0.12 2.9e-07 0.0002
26 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 5 0 0 8 6 1 1 16 14 15 1.6e-08 0.77 0.66 3e-07 0.0002
27 C3orf70 chromosome 3 open reading frame 70 757 29 0 0 15 2 0 0 17 17 10 7.8e-07 0.0086 0.92 3e-07 0.0002
28 PSIP1 PC4 and SFRS1 interacting protein 1 1678 13 0 1 8 5 4 4 21 20 20 1.6e-08 0.61 0.75 3e-07 0.0002
29 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 14968 1 0 12 55 22 7 14 98 74 96 1.6e-08 0.6 0.6 3.1e-07 0.0002
30 ASXL2 additional sex combs like 2 (Drosophila) 4352 11 0 4 35 8 1 1 45 36 40 0.000097 0.078 0.00017 4.2e-07 0.00025
31 ZBTB7B zinc finger and BTB domain containing 7B 1628 5 0 1 10 1 0 1 12 11 8 0.0079 1e-05 0.0034 1.4e-06 0.00081
32 RXRA retinoid X receptor, alpha 1425 2 0 5 21 2 0 2 25 24 12 0.00078 8e-05 0.0044 1.6e-06 0.00092
33 FBXW7 F-box and WD repeat domain containing 7 2580 0 6 1 22 10 0 3 35 30 25 0.000032 0.005 0.033 1.7e-06 0.00096
34 RBM10 RNA binding motif protein 10 2881 0 0 4 9 8 1 4 22 22 22 2.1e-07 1 0.38 2.2e-06 0.0012
35 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 2 0 0 24 0 0 1 25 24 16 0.021 1e-05 0.0058 3.4e-06 0.0018
TP53

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

RB1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

TSC1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TSC1 significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

RHOB

Figure S5.  This figure depicts the distribution of mutations and mutation types across the RHOB significant gene.

KDM6A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

CDKN2A

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

ARID1A

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

STAG2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

ZFP36L1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the ZFP36L1 significant gene.

CDKN1A

Figure S11.  This figure depicts the distribution of mutations and mutation types across the CDKN1A significant gene.

EP300

Figure S12.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

FGFR3

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FGFR3 significant gene.

ERCC2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ERCC2 significant gene.

CREBBP

Figure S15.  This figure depicts the distribution of mutations and mutation types across the CREBBP significant gene.

HRAS

Figure S16.  This figure depicts the distribution of mutations and mutation types across the HRAS significant gene.

FOXA1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

KRAS

Figure S18.  This figure depicts the distribution of mutations and mutation types across the KRAS significant gene.

RHOA

Figure S19.  This figure depicts the distribution of mutations and mutation types across the RHOA significant gene.

FAT1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

KLF5

Figure S21.  This figure depicts the distribution of mutations and mutation types across the KLF5 significant gene.

PTEN

Figure S22.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

C3orf70

Figure S23.  This figure depicts the distribution of mutations and mutation types across the C3orf70 significant gene.

PSIP1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PSIP1 significant gene.

ASXL2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ASXL2 significant gene.

ZBTB7B

Figure S26.  This figure depicts the distribution of mutations and mutation types across the ZBTB7B significant gene.

RXRA

Figure S27.  This figure depicts the distribution of mutations and mutation types across the RXRA significant gene.

FBXW7

Figure S28.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

RBM10

Figure S29.  This figure depicts the distribution of mutations and mutation types across the RBM10 significant gene.

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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