Mutation Analysis (MutSig 2CV v3.1)
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C14J0CXG
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/C14J0CXG
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: UCEC-TP

  • Number of patients in set: 248

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:UCEC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 114

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: 114. 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 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 2 0 5 103 51 12 89 255 161 149 1e-16 1e-05 0.81 1e-16 3.7e-13
2 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 2361 26 0 2 22 17 2 77 118 83 89 1e-16 1e-05 0.47 1e-16 3.7e-13
3 TP53 tumor protein p53 1314 21 0 2 57 7 1 9 74 69 50 2.1e-15 1e-05 1e-05 1e-16 3.7e-13
4 CTCF CCCTC-binding factor (zinc finger protein) 2224 5 0 1 19 20 2 10 51 44 40 1e-16 0.0012 0.35 1e-16 3.7e-13
5 FBXW7 F-box and WD repeat domain containing 7 2580 20 0 1 37 8 0 2 47 39 31 1e-16 0.003 0.059 1e-16 3.7e-13
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 2 0 2 53 0 0 0 53 53 11 1.5e-11 1e-05 0.0011 5.4e-15 1.6e-11
7 ARHGAP35 glucocorticoid receptor DNA binding factor 1 4520 17 0 9 25 18 0 9 52 36 43 2.8e-16 0.58 0.26 6.2e-15 1.6e-11
8 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 8 0 3 163 0 1 8 172 132 76 4e-11 1e-05 1e-05 1.5e-14 3.3e-11
9 ARID1A AT rich interactive domain 1A (SWI-like) 6934 3 0 5 15 55 2 35 107 83 87 7.4e-16 0.77 0.74 2.7e-14 5.4e-11
10 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 2406 7 0 7 80 0 0 0 80 74 25 3.5e-10 1e-05 1e-05 1.2e-13 2.2e-10
11 FGFR2 fibroblast growth factor receptor 2 (bacteria-expressed kinase, keratinocyte growth factor receptor, craniofacial dysostosis 1, Crouzon syndrome, Pfeiffer syndrome, Jackson-Weiss syndrome) 2782 37 0 3 30 2 0 3 35 31 20 2.2e-08 1e-05 0.36 6.8e-12 1.1e-08
12 ZFHX3 zinc finger homeobox 3 11148 2 0 13 57 10 0 12 79 44 71 9.6e-10 0.00025 0.48 1.5e-11 2.4e-08
13 TCP11L2 t-complex 11 (mouse)-like 2 1596 5 0 0 11 4 3 0 18 14 18 1.2e-10 1 0.26 1.3e-09 1.9e-06
14 SPOP speckle-type POZ protein 1161 3 0 0 19 3 0 1 23 21 18 2.1e-07 0.0015 0.084 8.9e-09 0.000012
15 RBMX RNA binding motif protein, X-linked 1265 8 0 0 7 1 0 6 14 13 8 0.0011 2e-05 0.34 2.2e-07 0.00027
16 SOX17 SRY (sex determining region Y)-box 17 1249 79 0 0 6 0 0 1 7 7 3 0.0029 3e-05 0.099 5.4e-07 0.00061
17 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 9 0 0 13 1 1 0 15 15 12 0.000082 0.00066 0.039 6.8e-07 0.00073
18 CCND1 cyclin D1 904 89 0 1 11 1 0 2 14 14 12 4.3e-07 0.086 0.18 8.5e-07 0.00086
19 GNPTAB N-acetylglucosamine-1-phosphate transferase, alpha and beta subunits 3851 42 0 4 21 6 0 0 27 20 22 0.00012 0.00017 0.81 9e-07 0.00087
20 ARID5B AT rich interactive domain 5B (MRF1-like) 3603 16 0 8 20 5 1 9 35 29 34 3e-07 0.14 0.97 9.9e-07 0.0009
21 DNER delta/notch-like EGF repeat containing 2262 8 0 0 18 1 2 0 21 18 20 3.1e-06 0.41 0.0066 1.2e-06 0.001
22 EP300 E1A binding protein p300 7365 9 0 5 21 7 2 2 32 21 31 3.6e-07 0.47 0.099 1.2e-06 0.001
23 MAX MYC associated factor X 837 19 0 0 11 0 1 0 12 11 8 0.00016 0.00029 0.047 1.8e-06 0.0014
24 SGK1 serum/glucocorticoid regulated kinase 1 1997 58 0 3 9 1 0 6 16 15 14 0.00013 0.018 0.014 1.9e-06 0.0015
25 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 590 5 0 2 8 1 0 0 9 9 6 0.016 0.0001 0.013 2.7e-06 0.0019
26 KLHL8 kelch-like 8 (Drosophila) 1895 3 0 1 11 8 0 0 19 12 16 0.000051 0.0035 0.19 3.2e-06 0.0022
27 MORC4 MORC family CW-type zinc finger 4 2878 5 0 2 17 8 1 2 28 20 26 1.5e-06 0.25 0.29 4.2e-06 0.0028
28 ZNF781 zinc finger protein 781 984 4 0 1 9 4 0 0 13 10 6 0.037 1e-05 0.17 5.8e-06 0.0038
29 MKI67 antigen identified by monoclonal antibody Ki-67 9827 12 0 21 45 11 0 6 62 29 58 0.00073 0.0009 0.19 7.2e-06 0.0045
30 ING1 inhibitor of growth family, member 1 1417 30 0 2 6 7 0 0 13 13 10 0.000016 0.059 0.061 8.9e-06 0.0054
31 INTS7 integrator complex subunit 7 2965 2 0 2 9 3 0 0 12 8 8 0.062 8e-05 0.0082 9.5e-06 0.0056
32 CCDC6 coiled-coil domain containing 6 1457 2 0 1 2 2 0 2 6 6 4 0.0013 0.00038 0.99 0.000012 0.0066
33 EIF2S2 eukaryotic translation initiation factor 2, subunit 2 beta, 38kDa 1034 50 0 0 6 1 2 0 9 9 7 0.00013 0.0054 0.89 0.000015 0.0081
34 RBBP6 retinoblastoma binding protein 6 5499 0 0 5 20 11 3 4 38 22 36 3e-06 0.28 0.97 0.000015 0.0081
35 SOS1 son of sevenless homolog 1 (Drosophila) 4092 5 0 1 12 1 0 0 13 12 10 0.11 2e-05 0.036 0.000016 0.0081
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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