Mutation Analysis (MutSigCV v0.9)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C14M93X8
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C14M93X8
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. MutSigCV v0.9 was used to generate the results found in this report.

  • Working with individual set: HNSC-TP

  • Number of patients in set: 511

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): 90

Results
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: HNSC-TP.patients.counts_and_rates.txt

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 3.  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 4.  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 5.  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

  • nflank = number of noncoding mutations from this gene's flanking region, across the individual set

  • 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: 90. 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).

gene Nnon Nsil Nflank nnon npat nsite nsil nflank nnei fMLE p score time q
NOTCH1 2040423 589694 183160 100 90 95 9 0 20 0.78 0 350 0.48 0
CDKN2A 307622 87381 29884 117 112 54 1 0 6 0.78 7.8e-16 630 0.48 6.8e-12
PIK3CA 1328089 339815 190872 97 94 36 1 0 20 1 1.1e-15 260 0.65 6.8e-12
HLA-A 419020 126728 74228 24 22 21 3 0 20 1.5 1.8e-15 110 0.52 8.1e-12
HRAS 236593 68474 41452 34 31 10 0 0 20 0.91 2.3e-15 110 0.7 8.5e-12
FAT1 5433463 1570814 187498 141 112 130 12 0 2 1.3 4.9e-15 480 0.52 1.3e-11
FBXW7 992362 272363 115198 35 33 26 4 0 20 0.71 5.4e-15 140 0.51 1.3e-11
TP53 482895 141036 99292 442 364 220 6 0 4 1.9 5.9e-15 1500 0.51 1.3e-11
CASP8 744016 174251 102666 62 54 49 1 0 20 0.94 8.2e-15 260 0.46 1.7e-11
NSD1 3242806 916734 210152 78 62 75 2 0 20 0.69 1.1e-14 260 0.51 1.9e-11
ZNF750 838551 269808 21208 24 22 23 1 0 20 0.99 2.7e-14 110 0.48 4.4e-11
OR6C65 368942 105266 12050 16 16 7 1 0 20 1.6 1.5e-13 82 0.44 2.3e-10
EPHA2 1090474 323463 137370 29 24 26 2 0 16 1.1 3.2e-13 120 0.5 4.5e-10
PTEN 497714 119574 83868 14 14 14 0 0 20 0.53 1e-12 70 0.51 1.3e-09
TGFBR2 694960 186515 115680 26 24 17 2 0 20 1.4 3.2e-12 94 0.74 3.8e-09
FLG 4695068 1393497 21208 93 74 91 23 0 15 1.1 4e-12 180 0.6 4.6e-09
CSMD3 4545856 1270346 685404 142 106 139 28 2 5 3 6.6e-11 250 0.47 7.1e-08
NFE2L2 719999 190603 39042 28 27 19 2 0 20 1.1 1e-10 80 0.71 1e-07
B2M 146657 40880 30848 9 8 8 0 0 20 0.72 7.7e-10 45 0.46 7.4e-07
RB1 1455328 383761 234252 17 17 17 3 0 20 0.72 2e-09 82 0.48 1.8e-06
CUL3 934619 239659 144118 16 16 16 1 0 20 0.49 2.9e-09 66 0.55 2.5e-06
RAC1 242725 73073 56876 15 14 8 0 1 20 0.79 7.1e-09 47 0.46 5.9e-06
DST 8029854 2072105 3577404 73 59 72 17 0 0 0.6 2.1e-08 160 0.5 0.000017
EP300 2924964 821688 300768 38 38 31 1 0 20 1 5.4e-08 120 0.5 0.000041
C6 1159970 300979 164844 23 22 23 2 0 9 0.77 6.3e-08 81 1.3 0.000046
HLA-B 379162 115997 54948 26 24 21 1 0 1 2.1 1.5e-07 100 0.52 0.0001
COL11A1 2187591 686784 612622 70 49 69 12 1 18 2.4 1.6e-07 140 0.53 0.00011
CTCF 901404 230972 96882 16 15 16 2 0 20 0.71 2.1e-07 61 0.45 0.00014
ZFP36L2 258566 83293 7712 8 8 8 2 0 20 0.87 5e-07 45 0.49 0.00032
FCRL4 622398 187026 116644 18 17 18 3 0 16 0.93 7.2e-07 58 0.49 0.00044
SMAD4 676564 188559 107004 14 13 14 1 1 20 0.68 9.9e-07 52 0.5 0.00058
ADCY8 1364370 403179 170628 28 28 28 8 0 15 1.3 1.6e-06 82 0.49 0.00092
HFM1 1731268 443548 336436 24 21 24 2 0 18 0.57 1.8e-06 67 0.5 0.001
NECAB1 256011 63364 43380 8 7 8 3 0 20 0.96 5.5e-06 35 0.44 0.0029
SI 2258620 586628 434764 59 52 57 11 0 11 3 8.3e-06 140 0.58 0.0043
NOTCH1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

CDKN2A

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

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

HLA-A

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

HRAS

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

FAT1

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

FBXW7

Figure S7.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

TP53

Figure S8.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NSD1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

ZNF750

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

OR6C65

Figure S11.  This figure depicts the distribution of mutations and mutation types across the OR6C65 significant gene.

EPHA2

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

PTEN

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

TGFBR2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

FLG

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

CSMD3

Figure S16.  This figure depicts the distribution of mutations and mutation types across the CSMD3 significant gene.

NFE2L2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

B2M

Figure S18.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

RB1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

CUL3

Figure S20.  This figure depicts the distribution of mutations and mutation types across the CUL3 significant gene.

RAC1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

EP300

Figure S22.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

C6

Figure S23.  This figure depicts the distribution of mutations and mutation types across the C6 significant gene.

HLA-B

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

COL11A1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the COL11A1 significant gene.

CTCF

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

ZFP36L2

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 significant gene.

FCRL4

Figure S28.  This figure depicts the distribution of mutations and mutation types across the FCRL4 significant gene.

SMAD4

Figure S29.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

ADCY8

Figure S30.  This figure depicts the distribution of mutations and mutation types across the ADCY8 significant gene.

HFM1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the HFM1 significant gene.

NECAB1

Figure S32.  This figure depicts the distribution of mutations and mutation types across the NECAB1 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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