Mutation Analysis (MutSig 2CV v3.1)
Breast Invasive Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1J9653T
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1J9653T
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: 977

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): 94

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: 94. 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 6 345 0 0 7 352 316 53 1e-16 1e-05 1e-05 1e-16 3.1e-13
2 TP53 tumor protein p53 1902 0 0 5 176 45 19 59 299 296 160 1e-16 1e-05 1e-05 1e-16 3.1e-13
3 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 2709 35 0 3 19 30 7 52 108 105 89 5.9e-16 9e-05 0.64 1e-16 3.1e-13
4 GATA3 GATA binding protein 3 1351 20 0 2 9 2 1 89 101 97 56 2.3e-16 1e-05 0.36 1e-16 3.1e-13
5 MAP3K1 mitogen-activated protein kinase kinase kinase 1 4615 16 0 3 17 14 1 64 96 70 86 1e-16 2e-05 0.92 1e-16 3.1e-13
6 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 1520 4 0 2 11 2 1 16 30 29 23 1e-16 0.0042 0.00025 1e-16 3.1e-13
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 61 0 0 15 6 1 15 37 35 34 1e-16 0.028 0.68 3.3e-16 8.7e-13
8 ARID1A AT rich interactive domain 1A (SWI-like) 6934 20 0 2 10 12 0 7 29 27 27 3.6e-16 0.055 0.56 6.7e-16 1.5e-12
9 CBFB core-binding factor, beta subunit 615 13 0 1 13 3 1 7 24 23 22 1.2e-16 0.6 0.044 1.1e-15 2.3e-12
10 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 14968 3 0 6 29 23 1 30 83 69 82 1e-16 0.66 0.19 1.7e-15 3.1e-12
11 FOXA1 forkhead box A1 1423 23 0 0 19 0 0 5 24 23 16 1.6e-09 5e-05 0.16 7.2e-12 1.2e-08
12 MAP2K4 mitogen-activated protein kinase kinase 4 1242 0 0 0 12 5 3 12 32 32 28 1.1e-11 0.014 0.46 1e-11 1.5e-08
13 RBMX RNA binding motif protein, X-linked 1265 17 0 0 4 0 0 10 14 14 6 4.6e-08 1e-05 0.58 1.3e-11 1.9e-08
14 TBX3 T-box 3 (ulnar mammary syndrome) 2260 50 0 1 8 1 1 17 27 27 26 3.4e-12 0.7 0.97 9.3e-11 1.2e-07
15 THEM5 thioesterase superfamily member 5 765 15 0 1 4 0 0 7 11 11 8 1.8e-10 1 0.072 5.8e-10 7.1e-07
16 RB1 retinoblastoma 1 (including osteosarcoma) 3716 6 0 3 5 10 1 6 22 19 21 5.2e-11 0.48 0.48 8.4e-10 9.6e-07
17 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 12127 3 0 2 9 8 3 9 29 27 28 6e-10 0.26 0.7 4.7e-09 5e-06
18 ACTL6B actin-like 6B 1333 44 0 0 3 1 0 6 10 10 6 1e-06 0.00052 0.99 1.4e-08 0.000014
19 SPEN spen homolog, transcriptional regulator (Drosophila) 11051 24 0 12 19 7 0 15 41 32 39 1.8e-08 0.044 0.53 2.3e-08 0.000023
20 CDKN1B cyclin-dependent kinase inhibitor 1B (p27, Kip1) 606 89 0 1 0 5 0 7 12 10 11 3.9e-09 0.48 0.6 5.1e-08 0.000046
21 NCOR1 nuclear receptor co-repressor 1 7666 0 0 1 21 11 3 8 43 41 41 2.8e-08 0.15 0.28 1.2e-07 0.00011
22 SF3B1 splicing factor 3b, subunit 1, 155kDa 4035 17 0 2 15 1 0 0 16 16 9 0.0016 1e-05 0.048 3.1e-07 0.00026
23 ZFP36L1 zinc finger protein 36, C3H type-like 1 1208 31 0 0 3 1 0 5 9 9 9 3.4e-07 0.092 0.65 6.1e-07 0.00048
24 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 258 0 0 6 0 0 0 6 6 3 0.0082 5e-05 0.1 1.4e-06 0.0011
25 TCP11 t-complex 11 homolog (mouse) 1639 2 0 0 2 0 0 4 6 6 3 0.00025 0.00014 0.99 1.5e-06 0.0011
26 AQP12A aquaporin 12A 902 50 0 0 6 0 0 0 6 6 4 0.0012 0.014 0.0016 1.9e-06 0.0013
27 DLG1 discs, large homolog 1 (Drosophila) 2919 44 0 1 9 2 0 2 13 13 13 1e-06 0.13 0.52 2.3e-06 0.0016
28 MYB v-myb myeloblastosis viral oncogene homolog (avian) 2346 10 0 0 5 1 0 6 12 12 12 1.2e-06 1 0.041 2.6e-06 0.0017
29 RPGR retinitis pigmentosa GTPase regulator 4072 1 0 1 14 0 1 6 21 19 19 8.4e-06 0.063 0.068 2.9e-06 0.0018
30 TBL1XR1 transducin (beta)-like 1 X-linked receptor 1 1601 44 0 0 3 2 1 6 12 10 10 7.6e-06 0.022 0.9 3.6e-06 0.0022
31 KDM6A lysine (K)-specific demethylase 6A 4318 3 0 0 8 0 2 7 17 16 16 1.5e-06 0.16 0.42 4.8e-06 0.0028
32 MYH9 myosin, heavy chain 9, non-muscle 6043 21 0 5 12 3 1 5 21 18 20 0.000022 0.016 0.72 7.5e-06 0.0043
33 HLA-C major histocompatibility complex, class I, C 1131 21 0 0 6 2 1 0 9 9 9 7.1e-07 1 0.74 0.000011 0.006
34 RAB42 RAB42, member RAS oncogene family 318 67 0 0 1 0 0 3 4 4 2 0.0023 0.00056 0.05 0.000011 0.0061
35 FGFR2 fibroblast growth factor receptor 2 (bacteria-expressed kinase, keratinocyte growth factor receptor, craniofacial dysostosis 1, Crouzon syndrome, Pfeiffer syndrome, Jackson-Weiss syndrome) 2782 38 0 2 12 0 0 0 12 11 9 0.0049 8e-05 0.99 0.000012 0.0062
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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle