Mutation Analysis (MutSigCV v0.9)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1WQ02ZR
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSigCV v0.9). Broad Institute of MIT and Harvard. doi:10.7908/C1WQ02ZR
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: CESC-TP

  • Number of patients in set: 194

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:CESC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 8

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: CESC-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: 8. 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
PIK3CA 504362 129034 114576 58 53 19 0 1 20 0.57 3.3e-15 140 0.16 6e-11
PTEN 188512 45288 50340 17 15 15 0 2 20 1 9.7e-15 78 0.16 6e-11
HLA-A 158960 48076 44852 17 16 14 1 0 20 1.8 9.9e-15 78 0.15 6e-11
FBXW7 376820 103414 69490 20 19 14 1 1 20 0.77 5e-14 72 0.15 2.3e-10
CASP8 282500 66154 61710 9 9 8 1 0 20 0.67 1.4e-08 44 0.15 5e-05
EP300 1110456 311940 189336 26 21 22 1 0 20 1.3 1.2e-07 77 0.15 0.00036
MAPK1 152302 39588 43634 9 9 3 0 0 20 1.4 0.000014 30 0.15 0.037
ZNF750 318366 102432 12400 11 10 11 2 0 20 1.5 0.000032 41 0.15 0.073
NFE2L2 273370 72362 22422 16 12 14 1 0 20 1.4 0.000054 34 0.14 0.11
CTNNBIP1 25790 7166 12786 3 3 2 0 0 20 0.71 0.000069 17 0.13 0.13
IFNGR1 219852 60104 34428 6 6 5 0 0 20 1.1 0.000086 28 0.15 0.14
HFM1 657704 168500 202036 12 11 12 0 0 18 0.4 0.00013 35 0.15 0.19
FLG 1782988 529194 13684 25 20 25 1 0 15 0.25 0.00014 51 0.15 0.19
ARID1A 866646 255316 111428 17 14 17 1 0 2 0.23 0.00018 56 0.16 0.23
NAA15 403788 96964 105424 9 7 9 1 0 20 0.62 0.00024 28 0.14 0.29
LIN9 263864 70034 85876 7 7 6 0 0 20 0.69 0.00033 25 0.14 0.38
RB1 552848 145778 162336 10 9 10 1 2 20 1.1 0.00038 35 0.15 0.39
DPCR1 107054 34274 9160 7 7 7 0 0 20 0.96 0.0004 21 0.14 0.39
BSG 114198 32978 32702 6 5 6 2 0 20 1.1 0.00041 22 0.14 0.39
MUC4 884696 287040 119604 88 37 85 12 0 2 3.8 0.00054 91 0.15 0.5
B2M 55702 15520 20192 3 3 3 0 0 20 1.2 0.00071 16 0.13 0.62
LATS1 517592 143172 54186 11 9 11 2 0 20 0.78 0.00084 31 0.15 0.69
BCL2L11 91022 26008 17564 3 3 3 0 0 20 0.88 0.0011 16 0.14 0.81
UBXN4 232244 63414 70850 5 5 5 0 0 20 0.84 0.0011 22 0.14 0.81
SSX4B 26820 5832 7628 2 2 2 0 0 20 0.52 0.0011 11 0.15 0.81
SMAD4 256904 71598 63540 7 7 7 0 0 20 0.95 0.0013 24 0.14 0.93
HLA-B 143900 44026 32304 12 11 9 0 0 1 1.1 0.0017 49 0.15 1
ZNF829 207670 49880 28744 4 4 4 0 2 14 0.91 0.0019 21 0.14 1
SUMO1 50452 11458 32076 2 2 2 0 2 20 1.1 0.0019 13 0.12 1
STK11 97188 28092 14410 8 5 8 1 0 20 1.6 0.002 19 0.14 1
C2orf73 78224 20796 12534 3 3 3 0 0 20 0.88 0.002 15 0.13 1
SOCS3 65326 21836 3082 6 4 6 2 0 15 0.88 0.0021 16 0.14 1
AMD1 154692 38376 54702 5 5 5 0 0 20 0.7 0.0022 17 0.14 1
WIZ 250642 86704 24774 12 12 12 3 2 20 1.5 0.0025 26 0.14 1
ACVR2A 241432 63656 66252 6 5 6 1 0 10 0.58 0.0027 20 0.14 1
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

PTEN

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

HLA-A

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

FBXW7

Figure S4.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

EP300

Figure S5.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

MAPK1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the MAPK1 significant gene.

ZNF750

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ZNF750 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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