Mutation Analysis (MutSig 2CV v3.1)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C15T3JHC
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/C15T3JHC
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: KIRC-TP

  • Number of patients in set: 515

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:KIRC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 27

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: 27. 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 SETD2 SET domain containing 2 7777 25 3 2 21 20 5 9 55 49 53 2.8e-16 0.0074 0.041 1e-16 1.8e-12
2 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 2254 12 0 1 17 11 7 12 47 45 43 6.6e-16 0.0058 0.5 3.3e-16 3e-12
3 PBRM1 polybromo 1 5418 1 1 4 26 46 14 57 143 139 132 2.4e-16 0.42 0.027 7.8e-16 4.7e-12
4 KDM5C lysine (K)-specific demethylase 5C 4879 10 0 1 11 7 1 9 28 28 28 1e-16 0.47 0.61 2.1e-15 9.6e-12
5 VHL von Hippel-Lindau tumor suppressor 650 0 0 7 108 38 18 73 237 228 137 4e-15 0.99 1 1.4e-13 5e-10
6 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1 0 1 6 5 2 6 19 17 19 3.5e-13 0.11 0.84 1.7e-12 5.1e-09
7 MTOR mechanistic target of rapamycin (serine/threonine kinase) 8871 87 0 4 30 0 0 1 31 30 25 5e-08 1e-05 0.81 1.5e-11 3.8e-08
8 TP53 tumor protein p53 1889 49 0 1 9 2 2 0 13 12 13 2.5e-10 0.35 0.013 1.6e-10 3.6e-07
9 FAM200A family with sequence similarity 200, member A 1726 6 0 0 6 0 0 0 6 5 6 2.5e-07 0.33 0.019 3.6e-07 0.00071
10 NEFH neurofilament, heavy polypeptide 200kDa 3077 3 0 0 1 0 0 5 6 6 5 2.4e-06 0.031 0.14 3.9e-07 0.00071
11 PTCH1 patched homolog 1 (Drosophila) 4640 39 0 3 7 0 0 0 7 7 6 0.037 6e-05 0.26 5.8e-06 0.0096
12 NF2 neurofibromin 2 (merlin) 1894 55 0 0 1 1 3 1 6 6 6 7.4e-06 1 0.046 0.000011 0.017
13 CCDC120 coiled-coil domain containing 120 2042 37 0 0 4 0 0 0 4 4 3 0.0057 0.0001 0.51 0.000014 0.019
14 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 2 0 0 11 1 0 0 12 12 9 0.1 3e-05 0.73 0.000015 0.02
15 ATM ataxia telangiectasia mutated 9438 5 0 1 9 4 0 3 16 13 16 0.0007 0.049 0.0097 0.000017 0.02
16 KIAA1751 KIAA1751 2357 4 0 0 4 2 0 0 6 6 4 0.0027 0.00024 0.98 0.000018 0.02
17 GUSB glucuronidase, beta 2000 19 0 1 6 0 0 0 6 4 4 0.14 1e-05 0.85 2e-05 0.021
18 ARID1A AT rich interactive domain 1A (SWI-like) 6934 1 0 1 4 2 0 5 11 11 11 0.000015 1 0.064 0.000023 0.023
19 GPR50 G protein-coupled receptor 50 1860 3 0 0 0 0 0 3 3 3 2 0.00065 0.0036 0.54 0.000033 0.031
20 PCK1 phosphoenolpyruvate carboxykinase 1 (soluble) 1905 55 0 1 1 0 0 3 4 4 4 0.00064 0.012 0.27 0.000034 0.031
21 DPCR1 diffuse panbronchiolitis critical region 1 4190 18 0 1 4 0 0 2 6 6 5 0.000039 0.057 0.65 0.000036 0.032
22 NFAT5 nuclear factor of activated T-cells 5, tonicity-responsive 4706 2 0 0 6 1 0 0 7 6 6 0.48 2e-05 0.23 0.000063 0.053
23 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 3999 4 0 0 7 0 0 0 7 7 6 0.061 9e-05 0.67 0.000087 0.067
24 TRIM6 tripartite motif-containing 6 1579 46 0 0 3 0 0 2 5 5 5 0.00021 0.026 0.32 0.000088 0.067
25 RBMX RNA binding motif protein, X-linked 1265 0 1 0 1 0 0 3 4 4 3 0.00048 0.015 0.95 0.000093 0.068
26 GPR172B G protein-coupled receptor 172B 1359 32 0 0 2 0 0 2 4 4 3 0.00049 0.016 1 0.000099 0.07
27 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 2642 69 0 1 3 1 0 0 4 4 3 0.0097 0.019 0.02 0.00011 0.071
28 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 4763 2 0 0 1 2 0 0 3 3 2 0.009 0.01 0.052 0.00015 0.1
29 OPTC opticin 1027 81 0 1 3 0 1 0 4 4 4 0.0017 0.012 0.99 0.00025 0.16
30 GOLGA5 golgi autoantigen, golgin subfamily a, 5 2244 75 0 0 4 0 0 1 5 5 4 0.0017 0.016 0.61 0.00033 0.2
31 TRIM16 tripartite motif-containing 16 1715 11 0 1 3 0 0 0 3 3 2 0.0057 0.0067 0.74 0.00046 0.27
32 CUL9 cullin 9 7716 10 0 3 8 0 0 1 9 9 8 0.23 0.00013 0.92 0.00049 0.27
33 LTA4H leukotriene A4 hydrolase 1910 168 0 1 3 0 0 1 4 4 3 0.018 0.013 0.2 0.00049 0.27
34 GPR172A G protein-coupled receptor 172A 2641 12 0 0 1 0 0 2 3 3 2 0.0068 0.0067 1 0.00058 0.31
35 BCL6 B-cell CLL/lymphoma 6 (zinc finger protein 51) 2153 38 0 0 4 1 0 0 5 5 5 0.000054 1 0.94 0.00059 0.31
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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