Mutation Analysis (MutSig 2CV v3.1)
Prostate Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1Z037D5
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/C1Z037D5
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: PRAD-TP

  • Number of patients in set: 332

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:PRAD-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 SPOP speckle-type POZ protein 1161 713 0 0 36 0 0 2 38 37 14 3.9e-15 1e-05 0.19 1e-16 1.8e-12
2 TP53 tumor protein p53 1314 498 0 0 13 0 3 7 23 23 21 6.9e-15 0.18 0.00044 2.2e-16 2e-12
3 FOXA1 forkhead box A1 1423 1000 0 0 7 1 0 6 14 13 11 1.2e-08 0.00046 0.014 2.7e-11 1.7e-07
4 BRAF v-raf murine sarcoma viral oncogene homolog B1 2371 98 0 0 6 0 1 1 8 8 8 1.1e-08 1 0.048 2.1e-08 0.000094
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1000 0 0 3 1 1 4 9 9 9 5.4e-09 1 0.82 1.1e-07 0.0004
6 ATM ataxia telangiectasia mutated 9419 43 0 2 11 0 0 2 13 13 13 2.2e-07 1 0.028 2.5e-07 0.00076
7 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 2406 76 0 0 8 0 0 0 8 8 7 3.1e-06 0.039 0.1 3e-07 0.00077
8 MED12 mediator complex subunit 12 6710 29 0 0 6 0 0 0 6 6 3 0.0057 1e-05 0.18 1e-06 0.0023
9 KDM6A lysine (K)-specific demethylase 6A 4318 6 0 1 1 1 1 3 6 6 6 1.3e-06 1 0.11 2.9e-06 0.0058
10 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 16826 6 0 1 3 3 0 5 11 11 11 1.1e-06 1 0.55 0.000016 0.028
11 AKT1 v-akt murine thymoma viral oncogene homolog 1 1495 51 0 0 3 0 0 0 3 3 2 0.0011 0.013 0.01 0.000017 0.028
12 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 659 1000 0 0 4 0 0 0 4 4 2 0.0056 0.00048 0.47 0.000037 0.056
13 XPO5 exportin 5 3739 26 0 0 3 0 0 0 3 3 2 0.0031 0.0097 0.0032 0.000061 0.086
14 KLHL2 kelch-like 2, Mayven (Drosophila) 1878 126 0 0 2 0 2 0 4 4 4 5e-06 1 0.93 0.000066 0.086
15 ZMYM3 zinc finger, MYM-type 3 4227 32 0 0 2 1 1 2 6 6 6 6.3e-06 1 0.87 0.000082 0.1
16 AMFR autocrine motility factor receptor 1984 129 0 0 2 1 0 0 3 3 3 0.0007 0.015 0.87 0.00013 0.14
17 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 2817 1 0 0 0 0 1 2 3 3 3 0.000066 1 0.13 0.00013 0.14
18 CDK12 cyclin-dependent kinase 12 4525 41 0 3 4 1 0 2 7 6 7 0.000027 1 0.5 0.0002 0.2
19 NKX3-1 NK3 homeobox 1 711 335 0 0 4 0 0 0 4 4 4 0.00033 1 0.009 0.00021 0.2
20 IRF4 interferon regulatory factor 4 1388 37 0 1 2 0 0 2 4 4 4 0.000018 1 0.54 0.00022 0.2
21 ASH1L ash1 (absent, small, or homeotic)-like (Drosophila) 9003 24 0 1 3 2 0 2 7 7 7 0.000019 1 0.93 0.00022 0.2
22 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 14968 21 0 2 6 4 1 4 15 13 14 0.002 0.036 0.16 0.00025 0.21
23 RNF17 ring finger protein 17 5014 48 0 1 1 0 2 0 3 3 2 0.016 0.0054 0.24 0.00031 0.25
24 AMPD1 adenosine monophosphate deaminase 1 (isoform M) 2407 31 0 0 2 0 1 0 3 3 3 0.00017 1 0.098 0.00033 0.25
25 EHHADH enoyl-Coenzyme A, hydratase/3-hydroxyacyl Coenzyme A dehydrogenase 2198 51 0 0 3 1 0 1 5 4 5 0.000042 1 0.98 0.00046 0.34
26 MBD1 methyl-CpG binding domain protein 1 2074 114 0 1 0 0 0 2 2 2 2 0.0048 0.01 0.32 0.00052 0.37
27 ZNF770 zinc finger protein 770 2080 26 0 0 4 0 0 0 4 4 4 0.00028 1 0.16 0.0007 0.47
28 SF1 splicing factor 1 2481 101 0 0 2 0 0 1 3 3 3 0.015 0.0098 0.87 0.0014 0.89
29 USP28 ubiquitin specific peptidase 28 3332 6 0 0 1 1 0 1 3 3 3 0.0007 1 0.18 0.0015 0.89
30 PCDH18 protocadherin 18 3420 228 0 1 7 1 0 0 8 8 8 0.0049 1 0.0055 0.0015 0.89
31 CBX4 chromobox homolog 4 (Pc class homolog, Drosophila) 1699 21 0 1 1 1 0 0 2 2 2 0.00052 1 0.12 0.0015 0.89
32 ROCK1 Rho-associated, coiled-coil containing protein kinase 1 4193 3 0 0 3 0 0 1 4 4 3 0.13 0.0062 0.27 0.0019 1
33 OR1A1 olfactory receptor, family 1, subfamily A, member 1 928 18 0 0 0 1 0 0 1 1 1 0.0021 NaN NaN 0.0021 1
34 FAM171A1 family with sequence similarity 171, member A1 2703 28 0 1 1 1 0 1 3 3 3 0.00069 1 0.33 0.0022 1
35 COL6A3 collagen, type VI, alpha 3 9753 0 0 1 3 0 2 0 5 4 4 0.087 0.014 0.068 0.0023 1
SPOP

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

TP53

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

FOXA1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

BRAF

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

PTEN

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

ATM

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

CTNNB1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

MED12

Figure S8.  This figure depicts the distribution of mutations and mutation types across the MED12 significant gene.

KDM6A

Figure S9.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

AKT1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the AKT1 significant gene.

HRAS

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

XPO5

Figure S12.  This figure depicts the distribution of mutations and mutation types across the XPO5 significant gene.

KLHL2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the KLHL2 significant gene.

ZMYM3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ZMYM3 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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