Mutation Analysis (MutSig 2CV v3.1)
Adrenocortical Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1FF3R6H
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/C1FF3R6H
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: ACC-TP

  • Number of patients in set: 62

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:ACC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 113

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: 113. 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 ZFPM1 zinc finger protein, multitype 1 3059 40 0 0 4 0 0 35 39 24 6 1e-16 1e-05 1 1e-16 3e-13
2 LACTB lactamase, beta 1668 100 0 0 18 0 0 1 19 19 2 3.9e-15 1e-05 1 1e-16 3e-13
3 CCDC102A coiled-coil domain containing 102A 1681 177 0 0 17 0 0 0 17 17 1 1.1e-16 1e-05 0.81 1e-16 3e-13
4 ZNF517 zinc finger protein 517 1495 326 0 0 14 0 0 0 14 13 2 2.5e-14 1e-05 0.99 1e-16 3e-13
5 MAL2 mal, T-cell differentiation protein 2 546 2 0 1 1 0 0 11 12 11 2 1.4e-15 1e-05 0.22 1e-16 3e-13
6 CLDN23 claudin 23 879 402 0 0 10 0 0 0 10 10 1 1.3e-14 1e-05 0.99 1e-16 3e-13
7 TOR3A torsin family 3, member A 1214 169 0 0 12 0 0 0 12 12 1 8.8e-12 1e-05 1 3.3e-15 8.7e-12
8 USP42 ubiquitin specific peptidase 42 2985 269 0 1 16 0 0 0 16 15 3 1e-12 NaN NaN 1e-12 2.4e-09
9 TP53 tumor protein p53 1889 49 0 1 5 3 2 4 14 12 14 2.7e-13 0.53 0.079 1.2e-12 2.4e-09
10 APOE apolipoprotein E 969 129 0 0 8 0 0 0 8 7 2 1.4e-07 1e-05 0.85 3.9e-11 7.2e-08
11 ZAR1 zygote arrest 1 1378 5 0 0 11 0 0 0 11 11 2 3.2e-07 1e-05 1 8.7e-11 1.5e-07
12 ASPDH aspartate dehydrogenase domain containing 913 40 0 0 8 0 0 0 8 8 2 2.1e-08 0.00025 1 1.7e-10 2.6e-07
13 KCNK17 potassium channel, subfamily K, member 17 1296 191 0 0 9 0 0 0 9 9 2 2e-07 1e-05 0.97 2.6e-10 3.6e-07
14 LZTR1 leucine-zipper-like transcription regulator 1 2621 12 0 0 0 0 0 6 6 6 1 2.3e-06 1e-05 6e-05 5.9e-10 7.7e-07
15 ERCC2 excision repair cross-complementing rodent repair deficiency, complementation group 2 (xeroderma pigmentosum D) 2430 33 0 0 10 0 0 0 10 10 1 3.3e-06 1e-05 0.0021 8.2e-10 9.4e-07
16 RINL Ras and Rab interactor-like 1569 72 0 0 8 0 0 0 8 8 1 3.3e-06 1e-05 0.45 8.2e-10 9.4e-07
17 SYT8 synaptotagmin VIII 1240 76 0 0 8 0 0 0 8 8 3 1.3e-08 0.0076 0.08 1.8e-09 2e-06
18 LRIG1 leucine-rich repeats and immunoglobulin-like domains 1 3356 33 0 0 26 0 0 0 26 16 2 0.000013 1e-05 0.94 3.1e-09 3e-06
19 C1orf106 chromosome 1 open reading frame 106 2030 27 0 0 9 0 0 0 9 9 2 3.4e-07 0.00021 1 3.1e-09 3e-06
20 GPRIN2 G protein regulated inducer of neurite outgrowth 2 1381 174 0 1 8 0 0 0 8 8 1 9.7e-08 0.0004 0.61 3.6e-09 3.3e-06
21 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 2406 53 0 0 6 0 0 1 7 7 4 0.000019 1e-05 0.68 4.4e-09 3.9e-06
22 C16orf3 chromosome 16 open reading frame 3 549 33 0 0 5 0 0 0 5 5 2 1.5e-07 0.0041 0.7 5e-09 4.2e-06
23 CCDC105 coiled-coil domain containing 105 1526 111 0 0 6 0 0 0 6 6 1 0.000027 1e-05 1 6.3e-09 5e-06
24 RGS9BP regulator of G protein signaling 9 binding protein 708 37 0 0 8 0 0 0 8 8 1 2.9e-06 5e-05 0.79 6.7e-09 5.1e-06
25 HHIPL1 HHIP-like 1 2482 84 0 0 6 0 0 0 6 6 1 0.000031 1e-05 1 7.1e-09 5.2e-06
26 C10orf95 chromosome 10 open reading frame 95 780 48 0 0 6 0 0 0 6 6 1 1.6e-06 0.00011 0.81 1.3e-08 9.5e-06
27 TSC22D2 TSC22 domain family, member 2 2355 54 0 0 7 1 0 0 8 8 3 0.000014 1e-05 1 3.1e-08 0.000021
28 NOXA1 NADPH oxidase activator 1 1508 147 0 0 5 0 0 0 5 5 1 0.00017 1e-05 0.99 3.7e-08 0.000024
29 THEM4 thioesterase superfamily member 4 743 89 0 0 5 0 0 0 5 5 1 0.000042 1e-05 0.94 4.4e-08 0.000028
30 ATXN1 ataxin 1 2452 14 0 1 5 0 0 6 11 10 8 3e-05 2e-05 1 5.1e-08 0.000031
31 PLIN5 perilipin 5 1424 51 0 0 5 0 0 0 5 5 1 0.00029 0.00035 1e-05 6.1e-08 0.000036
32 OPRD1 opioid receptor, delta 1 1127 2 0 1 12 0 0 0 12 12 1 0.00036 1e-05 1 7.3e-08 0.000042
33 KRTAP4-5 keratin associated protein 4-5 548 71 0 0 4 0 0 3 7 5 4 0.000047 1e-05 1 7.7e-08 0.000042
34 C19orf10 chromosome 19 open reading frame 10 544 53 0 0 7 0 0 0 7 7 1 5.4e-07 0.0027 1 9.5e-08 0.000051
35 AATK apoptosis-associated tyrosine kinase 4179 111 0 1 7 0 0 0 7 6 2 0.00015 1e-05 0.76 1.2e-07 0.000062
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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