Mutation Analysis (MutSig 2CV v3.1)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1M044NB
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/C1M044NB
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: 476

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): 15

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: 15. 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 24 0 1 15 17 6 10 48 44 46 1e-16 0.28 0.022 1.1e-16 2e-12
2 PBRM1 polybromo 1 5418 110 0 2 25 43 14 52 134 131 123 1.8e-16 0.77 0.017 1.8e-15 1.1e-11
3 KDM5C lysine (K)-specific demethylase 5C 4879 10 0 1 9 7 1 9 26 26 26 1e-16 0.41 0.59 1.9e-15 1.1e-11
4 VHL von Hippel-Lindau tumor suppressor 650 0 0 2 102 38 19 71 230 222 137 3.6e-15 0.98 0.99 1.2e-13 5.6e-10
5 MTOR mechanistic target of rapamycin (serine/threonine kinase) 8871 87 0 4 30 0 0 1 31 30 25 8.6e-08 1e-05 0.81 2.5e-11 9e-08
6 TP53 tumor protein p53 1889 49 0 1 7 1 2 0 10 9 10 2.4e-08 0.21 0.0051 3.9e-09 0.000012
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1 0 1 5 4 2 6 17 15 17 1.8e-09 0.082 0.89 5.1e-09 0.000013
8 NEFH neurofilament, heavy polypeptide 200kDa 3077 3 0 0 1 0 0 5 6 6 5 4.7e-06 0.034 0.14 1.4e-06 0.0031
9 NF2 neurofibromin 2 (merlin) 1894 55 0 0 1 1 3 1 6 6 6 3.1e-06 1 0.05 4.7e-06 0.0095
10 ATM ataxia telangiectasia mutated 9438 5 0 1 7 4 1 3 15 12 15 0.00021 0.042 0.021 7.6e-06 0.014
11 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 500 95 0 0 0 0 0 4 4 4 1 0.002 0.00017 0.97 0.000014 0.023
12 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 2 0 0 9 1 0 0 10 10 7 0.14 1e-05 0.78 2e-05 0.03
13 GPR50 G protein-coupled receptor 50 1860 3 0 0 0 0 0 3 3 3 2 0.00065 0.0052 0.53 0.000035 0.05
14 TFDP2 transcription factor Dp-2 (E2F dimerization partner 2) 1498 97 0 0 3 0 1 1 5 5 5 3.9e-06 1 0.88 0.000053 0.069
15 FAM200A family with sequence similarity 200, member A 1726 6 0 0 5 0 0 0 5 4 5 0.00021 0.2 0.02 0.000057 0.07
16 DPCR1 diffuse panbronchiolitis critical region 1 4190 18 0 1 4 0 0 2 6 6 5 0.000086 0.07 0.66 0.000088 0.1
17 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 3999 4 0 0 6 0 0 0 6 6 5 0.15 5e-05 0.77 0.00013 0.14
18 SH3KBP1 SH3-domain kinase binding protein 1 2133 4 0 0 1 0 0 2 3 3 2 0.0017 0.0057 0.92 0.00015 0.15
19 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 1360 803 0 0 0 0 0 4 4 4 2 0.018 0.0008 0.7 0.00019 0.19
20 ARID1A AT rich interactive domain 1A (SWI-like) 6934 31 0 1 3 2 0 5 10 10 10 0.00012 1 0.12 0.00021 0.19
21 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 4763 2 0 0 1 2 0 0 3 3 2 0.009 0.0088 0.051 0.00021 0.19
22 SLC16A9 solute carrier family 16, member 9 (monocarboxylic acid transporter 9) 1550 40 0 1 2 0 0 2 4 4 3 0.0029 0.012 0.22 0.00024 0.2
23 PCK1 phosphoenolpyruvate carboxykinase 1 (soluble) 1905 55 0 1 1 0 0 3 4 4 4 0.0018 0.012 0.26 0.00026 0.2
24 CUL9 cullin 9 7716 10 0 2 6 0 1 0 7 7 6 0.44 4e-05 0.89 0.00026 0.2
25 ZDHHC1 zinc finger, DHHC-type containing 1 1498 30 0 0 2 2 0 0 4 4 3 0.00029 0.071 0.73 0.00029 0.21
26 NPNT nephronectin 1891 28 0 0 5 0 0 1 6 6 6 0.00014 1 0.11 0.00032 0.23
27 BCL6 B-cell CLL/lymphoma 6 (zinc finger protein 51) 2153 77 0 0 4 1 0 0 5 5 5 0.000036 1 0.94 0.00041 0.28
28 RALGAPA1 Ral GTPase activating protein, alpha subunit 1 (catalytic) 6422 7 0 0 3 2 0 3 8 8 8 0.0052 0.026 0.13 0.00042 0.28
29 CYP4F11 cytochrome P450, family 4, subfamily F, polypeptide 11 1622 62 0 0 3 0 2 0 5 4 5 0.026 0.027 0.044 0.00054 0.34
30 GPR172A G protein-coupled receptor 172A 2641 19 0 0 0 0 1 2 3 3 2 0.0055 0.01 1 0.00064 0.39
31 OPTC opticin 1027 81 0 1 2 0 1 0 3 3 3 0.012 0.0054 0.99 0.00069 0.39
32 TAF1C TATA box binding protein (TBP)-associated factor, RNA polymerase I, C, 110kDa 2662 79 0 1 3 0 1 0 4 4 4 0.00022 1 0.26 0.00069 0.39
33 ZP3 zona pellucida glycoprotein 3 (sperm receptor) 1860 53 0 0 0 0 0 2 2 2 1 0.0071 0.01 0.28 0.00075 0.41
34 SERPINB13 serpin peptidase inhibitor, clade B (ovalbumin), member 13 1204 245 0 0 2 2 0 1 5 5 4 0.001 0.074 0.78 0.0009 0.47
35 SLC25A5 solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 5 909 15 0 1 2 0 0 0 2 2 1 0.0089 0.01 0.54 0.00092 0.47
SETD2

Figure S1.  This figure depicts the distribution of mutations and mutation types across the SETD2 significant gene.

PBRM1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

KDM5C

Figure S3.  This figure depicts the distribution of mutations and mutation types across the KDM5C significant gene.

VHL

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

MTOR

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

TP53

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PTEN

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

NEFH

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

NF2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NF2 significant gene.

ATM

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

PIK3CA

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

GPR50

Figure S12.  This figure depicts the distribution of mutations and mutation types across the GPR50 significant gene.

TFDP2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the TFDP2 significant gene.

FAM200A

Figure S14.  This figure depicts the distribution of mutations and mutation types across the FAM200A 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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