Mutation Analysis (MutSig 2CV v3.1)
Skin Cutaneous Melanoma (Metastatic)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1J38RVD
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/C1J38RVD
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: SKCM-TM

  • Number of patients in set: 290

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:SKCM-TM.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 61

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: 61. 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 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 941 2 0 1 88 1 1 0 90 87 10 1.7e-14 1e-05 1e-05 1e-16 6.1e-13
2 TP53 tumor protein p53 1890 12 0 2 33 10 6 5 54 48 43 7.9e-16 0.0006 1e-05 1e-16 6.1e-13
3 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 0 0 6 15 15 6 6 42 41 21 1e-16 9e-05 1e-05 1e-16 6.1e-13
4 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 12120 2 0 9 19 22 8 4 53 38 48 2.3e-11 0.0018 0.95 2.7e-12 1.2e-08
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 6 0 0 10 6 2 7 25 25 23 5.3e-12 0.35 0.48 6.9e-11 2.5e-07
6 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 660 23 0 1 20 0 0 0 20 20 9 2.3e-09 0.0015 0.85 1.5e-10 4.6e-07
7 ARID2 AT rich interactive domain 2 (ARID, RFX-like) 5588 3 0 7 21 22 3 5 51 37 40 8.3e-08 6e-05 0.2 2e-10 5.2e-07
8 C15orf23 chromosome 15 open reading frame 23 1024 3 0 4 21 0 0 0 21 19 8 0.000011 1e-05 1 2.6e-09 6e-06
9 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 500 1 0 0 0 0 0 8 8 8 1 0.00012 1e-05 1 2.7e-08 0.000054
10 ZFX zinc finger protein, X-linked 2505 0 0 1 8 5 0 3 16 15 15 1.5e-06 0.22 0.02 4.8e-07 0.00087
11 SLC38A4 solute carrier family 38, member 4 1700 8 0 4 35 0 2 0 37 33 31 6.5e-07 0.042 0.9 7.7e-07 0.0013
12 FAM58A family with sequence similarity 58, member A 762 3 0 0 1 1 2 2 6 6 5 3.5e-06 0.14 0.047 1.7e-06 0.0026
13 PPP6C protein phosphatase 6, catalytic subunit 1057 8 1 2 16 2 2 1 21 20 15 3.7e-06 0.016 0.79 1.8e-06 0.0026
14 C7orf58 chromosome 7 open reading frame 58 3209 1 0 10 38 2 6 0 46 37 38 0.017 0.00051 0.0081 2.9e-06 0.0038
15 COL3A1 collagen, type III, alpha 1 (Ehlers-Danlos syndrome type IV, autosomal dominant) 4601 13 0 14 71 6 11 0 88 59 80 9.9e-06 0.021 1 6.1e-06 0.0071
16 CDK4 cyclin-dependent kinase 4 940 17 0 1 8 0 0 0 8 8 4 0.039 1e-05 0.04 6.2e-06 0.0071
17 DSG3 desmoglein 3 (pemphigus vulgaris antigen) 3060 1 0 12 65 0 3 0 68 48 56 0.066 1e-05 0.73 1e-05 0.011
18 MLL myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila) 12052 0 0 9 40 7 1 1 49 40 46 0.0014 0.00032 0.78 0.000016 0.016
19 DDX3X DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked 2053 18 0 3 11 4 0 5 20 20 18 0.000034 0.051 0.34 0.000016 0.016
20 HSD11B1 hydroxysteroid (11-beta) dehydrogenase 1 905 7 0 0 14 0 0 0 14 14 13 1.3e-06 0.65 0.6 0.000019 0.017
21 ALPK2 alpha-kinase 2 6561 6 0 16 71 1 0 0 72 47 64 0.13 1e-05 0.74 0.000019 0.017
22 ATP5F1 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit B1 1201 7 0 0 7 0 0 0 7 6 5 0.018 9e-05 0.052 0.000026 0.021
23 RPTN repetin 2363 8 0 8 51 0 1 0 52 42 45 0.000013 0.11 0.86 3e-05 0.022
24 KRTAP5-10 keratin associated protein 5-10 611 14 0 2 11 0 0 0 11 10 7 0.011 4e-05 0.76 0.000031 0.022
25 GML glycosylphosphatidylinositol anchored molecule like protein 489 24 0 1 11 0 1 0 12 11 11 0.000011 0.26 0.2 0.000031 0.022
26 MAP2K1 mitogen-activated protein kinase kinase 1 1224 0 0 3 16 2 0 0 18 16 9 0.28 1e-05 0.75 0.000039 0.026
27 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 1277 5 0 3 14 0 1 0 15 15 5 0.041 1e-05 0.98 4e-05 0.026
28 KEL Kell blood group, metallo-endopeptidase 2271 0 0 22 35 3 5 1 44 36 35 0.3 1e-05 0.81 0.000041 0.026
29 RQCD1 RCD1 required for cell differentiation1 homolog (S. pombe) 927 13 0 1 9 0 0 0 9 9 4 0.0028 0.0011 0.13 5e-05 0.031
30 NGF nerve growth factor (beta polypeptide) 730 7 0 4 8 1 0 0 9 9 5 0.038 8e-05 0.37 0.000052 0.031
31 DMC1 DMC1 dosage suppressor of mck1 homolog, meiosis-specific homologous recombination (yeast) 1075 4 0 2 7 2 3 0 12 11 9 0.00036 0.006 1 0.000053 0.031
32 TRERF1 transcriptional regulating factor 1 3655 3 0 13 32 2 1 3 38 26 32 0.052 1e-05 0.36 0.000056 0.032
33 CYP3A5 cytochrome P450, family 3, subfamily A, polypeptide 5 1559 14 0 2 10 1 4 0 15 13 15 0.000014 0.3 0.82 0.000067 0.037
34 BRAF v-raf murine sarcoma viral oncogene homolog B1 2371 1 0 5 165 1 2 1 169 145 19 0.66 1e-05 1e-05 0.000086 0.045
35 NBPF1 neuroblastoma breakpoint family, member 1 3519 0 0 7 27 3 1 0 31 27 27 0.11 1e-05 0.85 0.000087 0.045
NRAS

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

TP53

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

CDKN2A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

NF1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

PTEN

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

RAC1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

ARID2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ARID2 significant gene.

ZFX

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

SLC38A4

Figure S9.  This figure depicts the distribution of mutations and mutation types across the SLC38A4 significant gene.

FAM58A

Figure S10.  This figure depicts the distribution of mutations and mutation types across the FAM58A significant gene.

PPP6C

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PPP6C significant gene.

COL3A1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the COL3A1 significant gene.

CDK4

Figure S13.  This figure depicts the distribution of mutations and mutation types across the CDK4 significant gene.

DSG3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the DSG3 significant gene.

DDX3X

Figure S15.  This figure depicts the distribution of mutations and mutation types across the DDX3X significant gene.

HSD11B1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the HSD11B1 significant gene.

ALPK2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the ALPK2 significant gene.

ATP5F1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ATP5F1 significant gene.

RPTN

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

KRTAP5-10

Figure S20.  This figure depicts the distribution of mutations and mutation types across the KRTAP5-10 significant gene.

GML

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

MAP2K1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the MAP2K1 significant gene.

IDH1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

KEL

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

RQCD1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the RQCD1 significant gene.

NGF

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

DMC1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the DMC1 significant gene.

TRERF1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the TRERF1 significant gene.

CYP3A5

Figure S29.  This figure depicts the distribution of mutations and mutation types across the CYP3A5 significant gene.

BRAF

Figure S30.  This figure depicts the distribution of mutations and mutation types across the BRAF 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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