Mutation Analysis (MutSig 2CV v3.1)
Pheochromocytoma and Paraganglioma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1SF2V7X
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/C1SF2V7X
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: PCPG-TP

  • Number of patients in set: 178

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:PCPG-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 7

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: 7. 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 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 659 104 0 0 18 0 0 0 18 18 3 4e-16 1e-05 0.0005 1e-16 1.8e-12
2 EPAS1 endothelial PAS domain protein 1 2673 78 0 0 8 0 0 0 8 8 4 6.9e-12 1e-05 0.00017 2.7e-15 2.4e-11
3 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 12119 1 0 0 1 3 2 10 16 15 16 1.3e-16 1 0.62 4.9e-15 3e-11
4 RET ret proto-oncogene 3451 95 0 0 7 0 0 0 7 6 4 1.1e-07 0.00051 0.066 8.8e-11 4e-07
5 CSDE1 cold shock domain containing E1, RNA-binding 2611 107 0 0 0 0 2 2 4 4 4 1.7e-07 1 0.24 1.1e-06 0.0039
6 GPR128 G protein-coupled receptor 128 2454 265 0 0 4 0 0 0 4 4 4 6.4e-07 1 0.94 9.8e-06 0.03
7 AMMECR1 Alport syndrome, mental retardation, midface hypoplasia and elliptocytosis chromosomal region, gene 1 1024 496 0 0 0 0 0 3 3 3 2 5e-05 0.019 1 2e-05 0.051
8 SHROOM4 shroom family member 4 4516 117 0 0 0 0 0 3 3 3 1 0.0061 0.001 0.72 0.000079 0.18
9 FAM83D family with sequence similarity 83, member D 1862 110 0 0 2 0 0 1 3 3 3 0.000016 1 0.66 0.00016 0.33
10 TRDN triadin 2352 112 0 0 0 0 0 3 3 3 2 0.00022 NaN NaN 0.00022 0.4
11 SRPX sushi-repeat-containing protein, X-linked 1431 385 0 0 0 0 0 2 2 2 1 0.0032 0.01 0.99 0.00037 0.61
12 LILRB5 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 5 1824 230 0 1 3 0 0 0 3 3 2 0.0005 NaN NaN 0.0005 0.65
13 OSBPL6 oxysterol binding protein-like 6 3013 38 0 0 1 0 1 0 2 2 2 0.00047 1 0.031 0.00052 0.65
14 MAP3K4 mitogen-activated protein kinase kinase kinase 4 4931 4 0 0 3 0 0 0 3 3 2 0.023 0.0021 0.9 0.00053 0.65
15 PRMT1 protein arginine methyltransferase 1 1158 238 0 0 1 0 1 0 2 2 2 0.0021 1 0.019 0.00056 0.65
16 BCOR BCL6 co-repressor 5324 244 0 0 2 0 0 1 3 3 3 0.00012 1 0.32 0.00058 0.65
17 SUSD4 sushi domain containing 4 1658 108 0 0 2 0 0 1 3 2 3 0.0054 0.0089 0.83 0.00061 0.65
18 MUC2 mucin 2, oligomeric mucus/gel-forming 8640 0 0 0 0 0 0 2 2 2 2 0.006 0.01 0.87 0.00064 0.65
19 LAMA4 laminin, alpha 4 5788 46 0 1 2 0 0 0 2 2 1 0.0074 0.01 0.34 0.00077 0.75
20 MGAM maltase-glucoamylase (alpha-glucosidase) 5762 52 0 1 1 1 0 1 3 3 3 0.00026 1 0.37 0.00097 0.89
21 DENND4A DENN/MADD domain containing 4A 5845 131 0 0 2 0 0 1 3 3 3 0.00031 1 0.27 0.0011 0.93
22 CLEC17A C-type lectin domain family 17, member A 916 1000 0 0 0 0 0 2 2 2 1 0.011 0.01 0.69 0.0012 0.96
23 HNRNPM heterogeneous nuclear ribonucleoprotein M 2255 8 0 0 2 0 1 0 3 3 3 0.0021 1 0.035 0.0012 0.97
24 FBF1 Fas (TNFRSF6) binding factor 1 3514 89 0 0 1 0 1 0 2 2 2 0.00075 1 0.16 0.0013 1
25 FAM120C family with sequence similarity 120C 3373 52 0 0 0 0 0 2 2 2 1 0.014 0.01 0.7 0.0014 1
26 SHC1 SHC (Src homology 2 domain containing) transforming protein 1 1850 247 0 0 2 0 0 0 2 2 2 0.0014 1 0.075 0.0017 1
27 FAM47C family with sequence similarity 47, member C 3110 12 0 0 3 0 0 0 3 3 2 0.042 0.0047 0.66 0.002 1
28 CD99L2 CD99 molecule-like 2 829 1000 0 0 0 0 0 2 2 2 1 0.021 0.01 0.49 0.002 1
29 P2RY1 purinergic receptor P2Y, G-protein coupled, 1 1122 512 0 0 1 1 0 0 2 2 2 0.0018 1 0.072 0.0024 1
30 GBA glucosidase, beta; acid (includes glucosylceramidase) 1659 119 0 0 2 0 0 0 2 2 2 0.0013 1 0.1 0.0024 1
31 CACNA1H calcium channel, voltage-dependent, T type, alpha 1H subunit 7198 72 0 0 2 0 0 1 3 3 3 0.00026 1 0.75 0.0024 1
32 TM9SF4 transmembrane 9 superfamily protein member 4 1997 47 0 0 0 1 0 0 1 1 1 0.0024 NaN NaN 0.0024 1
33 ATP6V1G3 ATPase, H+ transporting, lysosomal 13kDa, V1 subunit G3 419 249 0 0 2 0 0 0 2 2 2 0.00091 1 0.24 0.0026 1
34 FGFR1 fibroblast growth factor receptor 1 (fms-related tyrosine kinase 2, Pfeiffer syndrome) 2946 48 0 0 2 0 0 0 2 2 1 0.03 0.01 0.89 0.0027 1
35 FLG filaggrin 12194 13 0 1 5 0 0 0 5 4 5 0.18 0.0026 0.5 0.003 1
HRAS

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

EPAS1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the EPAS1 significant gene.

NF1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

RET

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

CSDE1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CSDE1 significant gene.

GPR128

Figure S6.  This figure depicts the distribution of mutations and mutation types across the GPR128 significant gene.

AMMECR1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the AMMECR1 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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