Mutation Analysis (MutSig 2CV v3.1)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1RB73SJ
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/C1RB73SJ
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: HNSC-TP

  • Number of patients in set: 510

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:HNSC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 38

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: 38. 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 TP53 tumor protein p53 1890 4 0 5 244 66 46 79 435 359 215 7.8e-16 1e-05 1e-05 1e-16 5.1e-13
2 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 17 0 1 21 60 13 23 117 112 54 1.6e-15 0.00012 1e-05 1e-16 5.1e-13
3 CASP8 caspase 8, apoptosis-related cysteine peptidase 1749 50 0 1 28 16 10 9 63 55 50 1e-16 0.015 1e-05 1e-16 5.1e-13
4 NSD1 nuclear receptor binding SET domain protein 1 8179 7 0 2 29 27 1 22 79 63 78 5.4e-16 0.22 0.0004 1.1e-16 5.1e-13
5 HLA-B major histocompatibility complex, class I, B 1119 25 0 1 11 6 3 6 26 24 21 1e-16 0.22 0.088 4.4e-16 1.6e-12
6 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 16826 1 0 6 31 29 7 22 89 78 86 2e-16 0.33 0.04 5.6e-16 1.7e-12
7 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 1807 24 0 2 16 6 2 1 25 23 16 2.8e-12 1e-05 0.44 1.1e-15 2.9e-12
8 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 13871 9 0 11 32 67 4 40 143 114 132 2.6e-15 0.84 0.033 1e-14 2.4e-11
9 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 7800 9 0 9 52 18 5 21 96 87 93 1.5e-15 0.48 0.4 3.8e-14 7.6e-11
10 JUB jub, ajuba homolog (Xenopus laevis) 1645 65 0 1 6 9 3 18 36 33 34 2.7e-15 0.63 0.95 7.6e-14 1.4e-10
11 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 44 0 2 26 0 0 1 27 26 18 6.3e-10 1e-05 1e-05 2.1e-13 3.6e-10
12 FBXW7 F-box and WD repeat domain containing 7 2580 8 0 4 22 4 1 8 35 33 26 1.3e-12 0.0036 0.32 3.3e-13 5e-10
13 ZNF750 zinc finger protein 750 2176 1 0 1 8 6 0 8 22 19 21 1.6e-11 0.11 0.0099 2.7e-12 3.9e-09
14 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 660 132 0 0 15 0 0 0 15 14 8 1.6e-07 1e-05 0.18 4.4e-11 5.7e-08
15 EPHA2 EPH receptor A2 2995 19 0 2 9 7 4 9 29 24 26 5.1e-12 0.38 0.49 5.9e-11 7.3e-08
16 HLA-A major histocompatibility complex, class I, A 1128 1 0 4 9 7 4 4 24 22 21 3.7e-11 0.14 0.5 1.7e-10 1.9e-07
17 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 659 2 0 0 31 1 0 0 32 29 9 2.2e-06 1e-05 0.00042 5.7e-10 6.1e-07
18 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 5 0 1 93 0 1 2 96 94 35 0.000059 1e-05 6e-05 1.3e-08 0.000013
19 EP300 E1A binding protein p300 7365 0 0 1 29 6 3 1 39 39 32 0.000097 2e-05 0.077 2.1e-08 2e-05
20 RB1 retinoblastoma 1 (including osteosarcoma) 3716 13 0 2 5 5 4 4 18 18 18 6.6e-09 1 0.069 2.5e-08 0.000023
21 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 24 0 0 6 5 1 2 14 14 14 5.4e-08 0.56 0.027 3.6e-08 0.000031
22 RASA1 RAS p21 protein activator (GTPase activating protein) 1 3250 3 0 0 6 5 4 3 18 17 16 2e-07 0.1 0.081 1e-07 0.000085
23 MAPK1 mitogen-activated protein kinase 1 1115 27 0 0 8 1 0 0 9 9 2 0.000046 0.0023 0.025 1.5e-07 0.00012
24 NAP1L2 nucleosome assembly protein 1-like 2 1383 0 0 0 2 0 0 5 7 7 3 0.00014 3e-05 0.45 1.9e-07 0.00015
25 KEAP1 kelch-like ECH-associated protein 1 1895 24 0 3 22 1 0 1 24 22 23 1.6e-07 0.31 0.44 7.3e-07 0.00053
26 KDM6A lysine (K)-specific demethylase 6A 4318 5 0 2 6 5 4 2 17 17 16 9.6e-08 0.41 0.68 8.2e-07 0.00058
27 RHOA ras homolog gene family, member A 918 13 0 1 9 1 0 0 10 10 7 0.000027 0.042 0.13 7.7e-06 0.0052
28 CREBBP CREB binding protein (Rubinstein-Taybi syndrome) 7449 26 0 8 29 6 1 4 40 35 39 0.000032 0.012 0.59 9.1e-06 0.0059
29 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 500 7 0 1 1 0 0 7 8 8 2 0.0074 1e-05 1 0.000013 0.0084
30 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 1360 27 0 0 0 0 0 4 4 4 1 0.0027 0.00021 0.56 0.000021 0.013
31 SMAD4 SMAD family member 4 1699 44 0 1 9 5 0 0 14 13 14 4e-06 1 0.82 0.000054 0.032
32 CUL3 cullin 3 2367 23 0 1 9 3 2 0 14 14 14 0.000034 0.23 0.42 0.000077 0.044
33 TIGD4 tigger transposable element derived 4 1539 2 0 0 5 1 0 1 7 7 6 0.0042 0.039 0.0059 0.000082 0.046
34 MYH9 myosin, heavy chain 9, non-muscle 6043 1 0 9 19 0 1 4 24 22 21 0.67 0.0024 0.0059 0.000087 0.047
35 C3orf59 chromosome 3 open reading frame 59 1480 59 0 1 10 1 0 0 11 11 7 0.022 0.00034 0.71 0.000094 0.049
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CDKN2A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

NSD1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

HLA-B

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

TGFBR2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

FAT1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

NOTCH1

Figure S7.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

NFE2L2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

FBXW7

Figure S9.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

ZNF750

Figure S10.  This figure depicts the distribution of mutations and mutation types across the ZNF750 significant gene.

RAC1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

EPHA2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the EPHA2 significant gene.

HLA-A

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

HRAS

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

PIK3CA

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

EP300

Figure S16.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

RB1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

PTEN

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

RASA1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the RASA1 significant gene.

MAPK1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the MAPK1 significant gene.

NAP1L2

Figure S21.  This figure depicts the distribution of mutations and mutation types across the NAP1L2 significant gene.

KEAP1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

KDM6A

Figure S23.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

RHOA

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

CREBBP

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

NUDT11

Figure S26.  This figure depicts the distribution of mutations and mutation types across the NUDT11 significant gene.

SMAD4

Figure S27.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

CUL3

Figure S28.  This figure depicts the distribution of mutations and mutation types across the CUL3 significant gene.

TIGD4

Figure S29.  This figure depicts the distribution of mutations and mutation types across the TIGD4 significant gene.

MYH9

Figure S30.  This figure depicts the distribution of mutations and mutation types across the MYH9 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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