Mutation Analysis (MutSig 2CV v3.1)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C16D5RTT
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: 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): 25

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: 25. 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 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 34 0 0 11 0 0 0 11 11 5 7e-12 4e-05 0.034 2.7e-15 4.9e-11
2 HLA-A major histocompatibility complex, class I, A 1128 86 0 1 4 7 3 3 17 16 14 2.6e-15 0.15 0.67 2.3e-14 2.1e-10
3 FBXW7 F-box and WD repeat domain containing 7 2580 4 0 1 15 5 0 0 20 19 14 1.4e-11 0.0001 0.051 4.4e-14 2.7e-10
4 HLA-B major histocompatibility complex, class I, B 1119 46 0 0 3 5 3 1 12 11 9 2.2e-14 0.16 0.4 2.1e-13 9.8e-10
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 2 2 0 6 6 3 2 17 15 15 1.5e-13 0.33 0.78 1.9e-12 6.8e-09
6 ARID1A AT rich interactive domain 1A (SWI-like) 6934 17 0 1 5 9 0 3 17 14 17 2.1e-12 1 0.31 2.8e-11 8.7e-08
7 MAPK1 mitogen-activated protein kinase 1 1115 79 0 0 9 0 0 0 9 9 3 2.2e-07 0.0001 0.0054 2.9e-10 7.6e-07
8 EP300 E1A binding protein p300 7366 3 0 1 13 11 2 0 26 21 22 3e-08 0.02 0.45 2.3e-08 0.000053
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 2 0 0 58 0 0 0 58 53 19 0.0028 1e-05 4e-05 5.1e-07 0.001
10 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 25 0 1 14 1 0 1 16 12 14 1.5e-06 0.1 0.032 5.6e-07 0.001
11 FAT2 FAT tumor suppressor homolog 2 (Drosophila) 13140 1 0 2 10 5 0 0 15 11 13 0.00012 0.0022 0.96 5.4e-06 0.0091
12 ZNF750 zinc finger protein 750 2176 4 0 2 5 2 0 4 11 10 11 3.3e-06 1 0.28 0.000018 0.028
13 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 2254 10 0 0 0 4 0 0 4 4 3 6.4e-06 0.39 0.99 0.000042 0.057
14 RAB35 RAB35, member RAS oncogene family 626 1 0 0 1 2 0 1 4 4 4 0.000044 NaN NaN 0.000044 0.057
15 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 4266 21 0 1 12 0 0 0 12 11 9 0.00058 0.0066 0.43 0.000049 0.058
16 SMAD4 SMAD family member 4 1700 16 0 0 5 2 0 0 7 7 7 8.6e-06 1 0.4 0.000051 0.058
17 TCTE1 t-complex-associated-testis-expressed 1 1690 22 0 0 3 1 1 0 5 5 5 5e-06 1 0.99 0.000066 0.071
18 NHS Nance-Horan syndrome (congenital cataracts and dental anomalies) 5024 46 0 1 9 3 0 0 12 12 12 0.000017 1 0.25 0.000077 0.077
19 LIN9 lin-9 homolog (C. elegans) 1733 19 0 0 5 2 0 0 7 7 6 0.000089 0.071 0.42 0.000087 0.077
20 C12orf43 chromosome 12 open reading frame 43 811 219 0 0 4 0 0 0 4 4 2 0.0064 0.00093 0.047 0.000091 0.077
21 MED1 mediator complex subunit 1 4810 7 0 0 10 2 1 1 14 11 14 7.2e-06 1 0.59 0.000093 0.077
22 USP28 ubiquitin specific peptidase 28 3332 6 0 0 1 2 1 0 4 4 4 0.000048 1 0.1 0.000093 0.077
23 IDS iduronate 2-sulfatase (Hunter syndrome) 1715 3 0 0 7 0 1 0 8 7 8 0.000027 1 0.18 0.00011 0.085
24 TRIM9 tripartite motif-containing 9 2217 18 0 1 7 1 0 0 8 8 8 9.3e-06 1 1 0.00012 0.087
25 SEMA4B sema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 4B 2566 22 0 0 6 1 0 0 7 7 7 9.4e-06 1 0.84 0.00012 0.087
26 ARHGAP4 Rho GTPase activating protein 4 3051 5 0 0 3 2 1 0 6 6 6 0.000022 1 0.27 0.00016 0.11
27 POU2F1 POU class 2 homeobox 1 2292 5 0 0 1 1 1 0 3 3 2 0.00017 NaN NaN 0.00017 0.11
28 IFNGR1 interferon gamma receptor 1 1495 150 0 0 2 3 0 1 6 6 5 0.00049 0.095 0.14 0.00018 0.11
29 IGFN1 immunoglobulin-like and fibronectin type III domain containing 1 11219 50 0 2 13 0 0 0 13 11 13 0.000015 1 0.92 0.00018 0.11
30 RPGR retinitis pigmentosa GTPase regulator 4072 18 0 2 8 2 0 1 11 9 11 0.000016 1 0.39 0.00019 0.11
31 CASP8 caspase 8, apoptosis-related cysteine peptidase 1750 2 0 1 4 5 0 0 9 9 8 0.00011 0.37 0.18 0.00024 0.14
32 GAS6 growth arrest-specific 6 2093 13 0 0 2 1 1 0 4 4 4 0.000059 1 0.32 0.00026 0.15
33 ABCD1 ATP-binding cassette, sub-family D (ALD), member 1 2274 16 0 1 7 0 0 0 7 7 6 0.0011 0.062 0.18 0.00028 0.16
34 RPAP1 RNA polymerase II associated protein 1 4278 11 0 1 3 1 0 0 4 4 3 0.016 0.0097 0.04 0.00033 0.18
35 HIST1H4E histone cluster 1, H4e 314 53 0 0 4 0 0 0 4 4 4 0.000085 1 0.27 0.00034 0.18
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)