Mutation Analysis (MutSig 2CV v3.1)
Pan-kidney cohort (KICH+KIRC+KIRP) (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1DJ5DVC
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/C1DJ5DVC
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: KIPAN-TP

  • Number of patients in set: 703

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:KIPAN-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 34

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: 34. 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 FAM18B2 family with sequence similarity 18, member B2 1003 101 0 0 35 0 1 0 36 35 2 1e-16 1e-05 0.83 1e-16 6.8e-13
2 TP53 tumor protein p53 1889 126 0 1 27 8 8 2 45 35 38 6.4e-16 0.055 6e-05 1e-16 6.8e-13
3 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1 0 1 9 6 2 14 31 26 31 1e-16 0.0064 0.9 1.1e-16 6.8e-13
4 KDM5C lysine (K)-specific demethylase 5C 4879 10 0 2 12 7 1 9 29 29 29 1e-16 0.47 0.63 2.2e-15 1e-11
5 SETD2 SET domain containing 2 7777 24 0 3 17 19 7 18 61 57 59 3.5e-16 0.49 0.063 5.2e-15 1.9e-11
6 PBRM1 polybromo 1 5418 110 0 3 28 45 15 53 141 138 130 1.7e-15 0.79 0.024 1.3e-14 4e-11
7 NEFH neurofilament, heavy polypeptide 200kDa 3077 36 0 2 10 0 0 10 20 16 11 1.9e-10 1e-05 0.83 6.5e-14 1.7e-10
8 VHL von Hippel-Lindau tumor suppressor 650 0 0 2 104 38 19 72 233 225 139 3.6e-15 0.98 0.99 1.2e-13 2.8e-10
9 MET met proto-oncogene (hepatocyte growth factor receptor) 4307 101 0 3 19 0 0 1 20 19 17 1.7e-06 0.00025 0.0062 4.4e-10 8.9e-07
10 HNRNPM heterogeneous nuclear ribonucleoprotein M 2255 13 0 0 3 0 9 0 12 12 4 2.1e-06 1e-05 0.036 5.3e-10 9.7e-07
11 NF2 neurofibromin 2 (merlin) 1894 12 0 1 2 3 6 5 16 16 15 6.7e-10 0.42 0.63 8.2e-09 0.000014
12 TDG thymine-DNA glycosylase 1269 4 0 2 1 0 4 0 5 5 3 8.4e-07 0.0035 0.23 6.1e-08 0.000093
13 MUC5B mucin 5B, oligomeric mucus/gel-forming 17492 16 0 7 25 0 1 7 33 32 27 0.00035 1e-05 0.48 7.2e-08 0.0001
14 ZNF814 zinc finger protein 814 2576 5 0 2 17 0 0 4 21 13 10 0.0042 1e-05 0.94 7.6e-07 0.00099
15 CSGALNACT2 chondroitin sulfate N-acetylgalactosaminyltransferase 2 1653 26 0 1 7 1 0 1 9 8 5 0.0006 0.00014 0.98 1.7e-06 0.0021
16 GPR50 G protein-coupled receptor 50 1860 3 0 0 2 0 0 3 5 5 4 0.018 4e-05 0.25 3e-06 0.0035
17 STAG2 stromal antigen 2 3939 8 0 2 5 4 0 5 14 14 14 3.9e-07 1 0.76 6.2e-06 0.0067
18 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 2 0 0 9 1 0 0 10 10 8 0.066 3e-05 0.008 1e-05 0.01
19 KDELR3 KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 718 19 0 0 3 1 0 3 7 6 7 3e-05 0.095 0.096 0.000013 0.012
20 ATM ataxia telangiectasia mutated 9438 1 0 1 10 4 2 3 19 16 18 0.0054 0.004 0.0043 0.000013 0.012
21 MTOR mechanistic target of rapamycin (serine/threonine kinase) 8871 8 0 6 33 0 1 1 35 34 28 0.13 1e-05 0.76 0.000019 0.016
22 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 0.073 1e-05 0.78 0.000021 0.017
23 SLC6A14 solute carrier family 6 (amino acid transporter), member 14 1981 0 0 0 2 0 0 4 6 5 5 0.0092 0.00017 0.83 0.000034 0.027
24 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 2 0 0 11 1 0 0 12 12 8 0.14 1e-05 0.73 0.000037 0.028
25 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 1360 45 1 0 0 0 0 4 4 4 2 0.0059 0.00053 0.71 0.000043 0.031
26 RIMBP3 RIMS binding protein 3 4920 24 0 0 0 0 0 5 5 5 4 0.33 0.059 2e-05 0.000046 0.032
27 RAI1 retinoic acid induced 1 5737 8 0 0 3 0 1 3 7 7 7 4.1e-06 1 0.89 0.000055 0.037
28 FAM160B2 family with sequence similarity 160, member B2 2097 8 0 0 0 0 1 4 5 4 5 0.00046 0.041 0.14 0.000059 0.039
29 ZNF598 zinc finger protein 598 2763 0 0 3 10 0 0 1 11 11 2 0.63 1e-05 1 0.000082 0.052
30 KDM6A lysine (K)-specific demethylase 6A 4318 10 0 1 1 3 1 6 11 10 11 8.9e-06 1 0.75 0.00011 0.067
31 DPCR1 diffuse panbronchiolitis critical region 1 4190 105 0 1 6 0 0 2 8 8 7 0.000063 0.13 0.84 0.00011 0.067
32 CYP4F11 cytochrome P450, family 4, subfamily F, polypeptide 11 1622 41 0 0 4 0 2 0 6 5 6 0.011 0.029 0.0086 0.00012 0.07
33 STAM signal transducing adaptor molecule (SH3 domain and ITAM motif) 1 1675 1 0 0 3 0 0 3 6 6 5 0.00021 0.036 0.91 0.00013 0.071
34 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 500 92 0 0 1 0 0 4 5 5 2 0.0052 0.0011 0.96 0.00013 0.071
35 PARD6B par-6 partitioning defective 6 homolog beta (C. elegans) 1127 15 0 1 4 1 0 2 7 7 6 0.00024 0.065 0.66 0.0002 0.1
TP53

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

PTEN

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

KDM5C

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

SETD2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the SETD2 significant gene.

PBRM1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

NEFH

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

VHL

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

MET

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

HNRNPM

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

NF2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the NF2 significant gene.

TDG

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

MUC5B

Figure S12.  This figure depicts the distribution of mutations and mutation types across the MUC5B significant gene.

ZNF814

Figure S13.  This figure depicts the distribution of mutations and mutation types across the ZNF814 significant gene.

CSGALNACT2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the CSGALNACT2 significant gene.

GPR50

Figure S15.  This figure depicts the distribution of mutations and mutation types across the GPR50 significant gene.

STAG2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

NFE2L2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

KDELR3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the KDELR3 significant gene.

ATM

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

MTOR

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

EGFR

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

SLC6A14

Figure S22.  This figure depicts the distribution of mutations and mutation types across the SLC6A14 significant gene.

PIK3CA

Figure S23.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

EMG1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the EMG1 significant gene.

RIMBP3

Figure S25.  This figure depicts the distribution of mutations and mutation types across the RIMBP3 significant gene.

RAI1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the RAI1 significant gene.

FAM160B2

Figure S27.  This figure depicts the distribution of mutations and mutation types across the FAM160B2 significant gene.

ZNF598

Figure S28.  This figure depicts the distribution of mutations and mutation types across the ZNF598 significant gene.

KDM6A

Figure S29.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

DPCR1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the DPCR1 significant gene.

STAM

Figure S31.  This figure depicts the distribution of mutations and mutation types across the STAM significant gene.

NUDT11

Figure S32.  This figure depicts the distribution of mutations and mutation types across the NUDT11 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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