Mutation Analysis (MutSig 2CV v3.1)
Uterine Carcinosarcoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1HQ3Z6C
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/C1HQ3Z6C
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: UCS-TP

  • Number of patients in set: 57

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:UCS-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 10

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: 10. 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 386 0 0 42 4 5 5 56 51 44 1e-16 0.00035 1e-05 1e-16 9.1e-13
2 FBXW7 F-box and WD repeat domain containing 7 2580 102 0 0 22 2 0 0 24 22 15 1e-16 4e-05 0.0077 1e-16 9.1e-13
3 PPP2R1A protein phosphatase 2 (formerly 2A), regulatory subunit A , alpha isoform 1826 280 0 0 17 0 0 0 17 16 10 2.8e-10 1e-05 0.033 9.7e-14 5.9e-10
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 122 0 0 7 0 0 0 7 7 2 3.8e-09 1e-05 0.079 1.2e-12 5.4e-09
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 34 0 0 9 4 1 2 16 11 15 6.8e-14 0.54 0.85 1.5e-12 5.4e-09
6 RB1 retinoblastoma 1 (including osteosarcoma) 3705 84 0 0 1 4 1 1 7 6 7 2.4e-10 1 0.76 5.5e-09 0.000017
7 ZBTB7B zinc finger and BTB domain containing 7B 1628 86 0 0 4 1 0 2 7 6 7 5.2e-08 1 0.089 1.5e-07 0.0004
8 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 2361 231 0 0 1 0 0 7 8 6 8 2.5e-07 1 0.52 4.1e-06 0.0093
9 ARHGAP35 glucocorticoid receptor DNA binding factor 1 4520 23 0 0 1 1 0 4 6 6 6 9.2e-07 1 0.74 0.000014 0.028
10 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 2 0 0 22 0 0 0 22 20 13 0.18 1e-05 0.0072 0.000025 0.046
11 MAMLD1 mastermind-like domain containing 1 3467 30 0 0 3 0 0 1 4 4 3 0.00091 0.0098 0.66 0.0001 0.17
12 U2AF1 U2 small nuclear RNA auxiliary factor 1 824 60 0 0 2 0 0 0 2 2 1 0.0017 0.014 0.02 0.00021 0.31
13 BCL2L11 BCL2-like 11 (apoptosis facilitator) 738 375 0 0 0 0 0 2 2 2 1 0.0019 0.01 0.11 0.00022 0.32
14 NET1 neuroepithelial cell transforming gene 1 1930 171 0 0 2 0 0 1 3 3 3 0.00027 1 0.12 0.00038 0.48
15 LZTFL1 leucine zipper transcription factor-like 1 936 34 0 0 0 0 2 0 2 2 2 0.000035 1 0.83 0.00039 0.48
16 RFC1 replication factor C (activator 1) 1, 145kDa 3540 17 0 0 1 1 0 1 3 3 3 0.00017 1 0.23 0.00045 0.52
17 YSK4 yeast Sps1/Ste20-related kinase 4 (S. cerevisiae) 4025 19 0 0 1 2 0 0 3 3 3 0.000062 1 0.91 0.00067 0.72
18 TBXAS1 thromboxane A synthase 1 (platelet, cytochrome P450, family 5, subfamily A) 1799 54 0 0 0 1 0 1 2 2 2 0.00076 1 0.072 0.00075 0.77
19 SPOP speckle-type POZ protein 1161 205 0 0 5 0 0 0 5 4 5 0.000083 1 0.13 0.00087 0.83
20 ZC3H18 zinc finger CCCH-type containing 18 2930 133 0 0 1 2 0 0 3 3 3 0.000094 1 0.97 0.00096 0.85
21 ARID1A AT rich interactive domain 1A (SWI-like) 6934 5 0 0 4 3 0 2 9 7 9 0.000095 1 0.89 0.00098 0.85
22 MYOZ1 myozenin 1 920 138 0 0 0 0 0 2 2 2 2 0.011 0.01 0.91 0.0011 0.94
23 MUC17 mucin 17, cell surface associated 13532 28 0 2 8 0 0 0 8 7 8 0.024 0.0063 0.55 0.0016 1
24 FAM92B family with sequence similarity 92, member B 943 1000 0 0 2 0 1 0 3 3 3 0.004 1 0.023 0.0017 1
25 LZTR1 leucine-zipper-like transcription regulator 1 2623 187 0 0 2 0 0 0 2 2 1 0.02 0.01 0.91 0.0019 1
26 FER fer (fps/fes related) tyrosine kinase 2543 143 0 0 0 2 0 0 2 2 1 0.017 0.015 0.29 0.0024 1
27 TMUB2 transmembrane and ubiquitin-like domain containing 2 982 123 0 0 3 0 0 0 3 3 3 0.0023 1 0.06 0.0029 1
28 TTF1 transcription termination factor, RNA polymerase I 2758 4 0 0 0 1 0 1 2 2 2 0.0005 1 0.66 0.0033 1
29 SAMD4B sterile alpha motif domain containing 4B 2129 120 0 1 2 0 0 0 2 2 1 0.017 0.023 0.97 0.0035 1
30 MGAM maltase-glucoamylase (alpha-glucosidase) 5762 134 0 1 6 1 0 0 7 6 7 0.00041 1 0.59 0.0036 1
31 CTCF CCCTC-binding factor (zinc finger protein) 2224 15 0 0 1 1 0 1 3 3 3 0.0009 1 0.46 0.0036 1
32 SLC10A6 solute carrier family 10 (sodium/bile acid cotransporter family), member 6 1154 336 0 0 2 0 0 1 3 2 3 0.016 1 0.0094 0.004 1
33 PLXNB2 plexin B2 5657 22 0 0 2 0 0 1 3 3 3 0.0079 1 0.028 0.0041 1
34 DAB1 disabled homolog 1 (Drosophila) 1720 12 0 0 0 0 0 2 2 2 2 0.0016 1 0.19 0.0049 1
35 CHD4 chromodomain helicase DNA binding protein 4 5895 3 0 0 9 2 1 0 12 10 12 0.0058 1 0.053 0.0051 1
TP53

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

FBXW7

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PPP2R1A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PPP2R1A significant gene.

KRAS

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

PTEN

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

RB1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ZBTB7B

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ZBTB7B significant gene.

PIK3R1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

PIK3CA

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PIK3CA 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle