Mutation Analysis (MutSig 2CV v3.1)
Breast Invasive Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C17943V9
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/C17943V9
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: BRCA-TP

  • Number of patients in set: 978

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:BRCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 62

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: 62. 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 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 13 0 6 338 0 6 7 351 316 53 1e-16 1e-05 1e-05 1e-16 4.6e-13
2 TP53 tumor protein p53 1890 0 0 4 173 45 23 59 300 297 161 1e-16 1e-05 1e-05 1e-16 4.6e-13
3 GATA3 GATA binding protein 3 1351 20 0 2 9 2 1 89 101 97 56 1.6e-15 1e-05 0.36 1e-16 4.6e-13
4 MAP3K1 mitogen-activated protein kinase kinase kinase 1 4615 7 0 1 16 14 4 64 98 71 88 1e-16 2e-05 0.93 1e-16 4.6e-13
5 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 2709 6 0 1 16 29 12 52 109 107 90 1.2e-15 0.00053 0.68 2.2e-16 8.1e-13
6 CBFB core-binding factor, beta subunit 615 15 0 1 10 3 2 7 22 22 20 1e-16 0.52 0.07 6.7e-16 2e-12
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 145 0 0 13 7 1 15 36 35 33 3.9e-15 0.023 0.72 9.3e-15 2.4e-11
8 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 1520 4 0 2 11 2 1 16 30 29 23 4.4e-11 0.0043 0.00031 1.6e-14 3.7e-11
9 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 14968 1 0 6 28 23 2 30 83 70 82 2.5e-15 0.64 0.16 2.4e-14 4.8e-11
10 CDKN1B cyclin-dependent kinase inhibitor 1B (p27, Kip1) 605 3 0 1 0 5 0 7 12 10 11 5.4e-14 0.51 0.59 1.1e-12 2e-09
11 MAP2K4 mitogen-activated protein kinase kinase 4 1242 2 0 0 12 5 3 12 32 32 28 2.9e-12 0.016 0.46 3.9e-12 6.5e-09
12 ARID1A AT rich interactive domain 1A (SWI-like) 6934 37 0 3 10 9 2 7 28 27 26 2e-11 0.044 0.62 3.5e-11 5.3e-08
13 FOXA1 forkhead box A1 1423 13 0 0 19 0 0 5 24 23 16 1.4e-08 6e-05 0.17 1e-10 1.4e-07
14 GPS2 G protein pathway suppressor 2 1788 2 0 1 0 1 2 7 10 10 10 3.4e-11 1 0.09 2.6e-10 3.3e-07
15 TBX3 T-box 3 (ulnar mammary syndrome) 2260 50 0 1 8 1 1 17 27 27 26 4.8e-11 0.7 0.97 1.2e-09 1.5e-06
16 RB1 retinoblastoma 1 (including osteosarcoma) 3716 70 0 3 5 10 1 6 22 19 21 1.3e-10 0.45 0.46 1.8e-09 2e-06
17 CTCF CCCTC-binding factor (zinc finger protein) 2224 27 0 3 9 4 1 2 16 16 14 0.000016 0.00077 0.00011 3.7e-09 4e-06
18 RBMX RNA binding motif protein, X-linked 1265 450 0 1 3 0 0 10 13 13 5 0.000028 1e-05 0.43 6.5e-09 6.6e-06
19 HRNR hornerin 8561 20 0 9 27 2 0 5 34 31 28 0.0016 1e-05 0.98 3.1e-07 0.0003
20 ZMYM3 zinc finger, MYM-type 3 4227 3 0 1 6 1 1 7 15 15 13 2e-06 0.0078 0.94 3.7e-07 0.00033
21 NCOR1 nuclear receptor co-repressor 1 7666 0 0 2 19 11 3 8 41 40 39 1.1e-07 0.14 0.23 4e-07 0.00035
22 GPRIN2 G protein regulated inducer of neurite outgrowth 2 1381 128 0 2 9 0 0 2 11 11 7 0.000054 0.00024 0.58 5.6e-07 0.00047
23 SPEN spen homolog, transcriptional regulator (Drosophila) 11051 24 0 12 18 7 1 15 41 32 39 8.9e-07 0.067 0.59 1.5e-06 0.0012
24 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 12120 4 0 2 10 8 3 9 30 28 29 4.9e-07 0.26 0.68 2.6e-06 0.002
25 TCP11 t-complex 11 homolog (mouse) 1639 2 0 0 2 0 0 4 6 6 3 0.0004 0.00017 0.99 2.7e-06 0.002
26 SF3B1 splicing factor 3b, subunit 1, 155kDa 4035 20 0 2 15 1 0 0 16 16 9 0.025 1e-05 0.047 4.1e-06 0.0029
27 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 3896 22 0 2 21 0 0 0 21 20 14 0.027 1e-05 0.00076 4.3e-06 0.0029
28 RAB42 RAB42, member RAS oncogene family 318 195 0 0 1 0 0 3 4 4 2 0.0072 0.00076 0.047 0.000011 0.0071
29 CDC42EP1 CDC42 effector protein (Rho GTPase binding) 1 1180 12 0 2 2 0 0 3 5 5 3 0.00053 0.0012 1 0.000013 0.0082
30 KDM6A lysine (K)-specific demethylase 6A 4318 9 0 1 7 0 2 7 16 15 15 5.7e-06 0.13 0.29 0.000014 0.0085
31 AQP12A aquaporin 12A 902 49 0 0 6 0 0 0 6 6 4 0.0018 0.015 0.0019 0.000016 0.0093
32 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 275 0 0 6 0 0 0 6 6 3 0.014 9e-05 0.099 0.000019 0.011
33 NBPF9 neuroblastoma breakpoint family, member 9 2909 5 1 0 2 0 0 3 5 5 3 0.042 4e-05 0.26 3e-05 0.017
34 MYB v-myb myeloblastosis viral oncogene homolog (avian) 2346 15 0 0 4 1 1 6 12 12 12 0.000017 1 0.037 0.000032 0.017
35 ZNF362 zinc finger protein 362 1295 57 0 0 2 0 0 3 5 5 3 0.029 0.00038 0.053 0.000036 0.019
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

GATA3

Figure S3.  This figure depicts the distribution of mutations and mutation types across the GATA3 significant gene.

MAP3K1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the MAP3K1 significant gene.

CDH1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

CBFB

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

PTEN

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

RUNX1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the RUNX1 significant gene.

CDKN1B

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CDKN1B significant gene.

MAP2K4

Figure S10.  This figure depicts the distribution of mutations and mutation types across the MAP2K4 significant gene.

ARID1A

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

FOXA1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

GPS2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the GPS2 significant gene.

TBX3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the TBX3 significant gene.

RB1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

CTCF

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

HRNR

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

ZMYM3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ZMYM3 significant gene.

NCOR1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the NCOR1 significant gene.

GPRIN2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the GPRIN2 significant gene.

SPEN

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

NF1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

TCP11

Figure S23.  This figure depicts the distribution of mutations and mutation types across the TCP11 significant gene.

SF3B1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the SF3B1 significant gene.

ERBB2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ERBB2 significant gene.

RAB42

Figure S26.  This figure depicts the distribution of mutations and mutation types across the RAB42 significant gene.

CDC42EP1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CDC42EP1 significant gene.

KDM6A

Figure S28.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

AQP12A

Figure S29.  This figure depicts the distribution of mutations and mutation types across the AQP12A significant gene.

KRAS

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

MYB

Figure S31.  This figure depicts the distribution of mutations and mutation types across the MYB 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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