Mutation Analysis (MutSig 2CV v3.1)
Stomach and Esophageal carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1T72GXK
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1T72GXK
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: STES-TP

  • Number of patients in set: 578

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:STES-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 924

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: 924. 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 0 1 3 236 49 30 62 377 341 174 1e-16 1e-05 1e-05 1e-16 1.8e-13
2 ARID1A AT rich interactive domain 1A (SWI-like) 6934 1 0 1 27 29 6 77 139 114 111 1e-16 1e-05 0.16 1e-16 1.8e-13
3 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 16826 1 0 20 66 14 4 48 132 99 117 4.9e-15 1e-05 0.97 1e-16 1.8e-13
4 RNF43 ring finger protein 43 2384 4 0 5 12 5 0 48 65 47 27 1e-16 1e-05 0.18 1e-16 1.8e-13
5 SMAD4 SMAD family member 4 1699 45 0 2 33 6 0 7 46 41 36 1e-16 0.002 0.55 1e-16 1.8e-13
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 4 0 0 40 0 0 0 40 40 6 3.4e-15 1e-05 0.039 1e-16 1.8e-13
7 XYLT2 xylosyltransferase II 2638 5 0 5 14 0 0 33 47 40 17 1e-16 1e-05 1 1e-16 1.8e-13
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1 0 4 17 6 2 22 47 37 33 3.3e-15 2e-05 1 1e-16 1.8e-13
9 LARP4B La ribonucleoprotein domain family, member 4B 2283 1 0 3 10 3 1 24 38 34 16 1.5e-16 1e-05 0.83 1e-16 1.8e-13
10 FBXW7 F-box and WD repeat domain containing 7 2580 2 1 1 29 7 2 8 46 44 30 3.9e-14 0.0008 0.013 1.1e-16 1.8e-13
11 RHOA ras homolog gene family, member A 918 42 0 0 22 0 0 1 23 22 17 3.1e-13 1e-05 0.47 1.1e-16 1.8e-13
12 B2M beta-2-microglobulin 374 24 0 1 5 2 2 20 29 20 20 8.5e-16 0.0089 0.64 5.6e-16 8.5e-13
13 HLA-B major histocompatibility complex, class I, B 1119 9 0 0 13 5 4 16 38 35 33 5.7e-16 0.59 0.1 6.6e-15 9.2e-12
14 C7orf50 chromosome 7 open reading frame 50 2545 2 0 0 3 0 0 10 13 13 4 1.3e-10 1e-05 0.39 4.5e-14 5.9e-11
15 GNG12 guanine nucleotide binding protein (G protein), gamma 12 227 0 0 2 2 0 0 10 12 12 4 1.9e-11 0.00012 0.32 6.1e-14 7.4e-11
16 PLEKHA6 pleckstrin homology domain containing, family A member 6 3231 3 0 6 11 1 1 22 35 28 22 1.5e-09 1e-05 0.96 4.9e-13 5.4e-10
17 PGM5 phosphoglucomutase 5 1744 12 0 3 38 7 0 1 46 43 12 1.6e-09 1e-05 1 5.3e-13 5.4e-10
18 MLL4 myeloid/lymphoid or mixed-lineage leukemia 2 8293 0 0 17 28 5 2 46 81 53 54 1.6e-09 1e-05 1 5.3e-13 5.4e-10
19 KLF3 Kruppel-like factor 3 (basic) 1058 9 0 4 8 0 3 14 25 22 17 3.3e-11 0.0005 0.94 1.1e-12 1.1e-09
20 ZBTB20 zinc finger and BTB domain containing 20 2238 0 0 12 21 0 0 31 52 42 23 9e-09 1e-05 0.92 2.8e-12 2.5e-09
21 MBD6 methyl-CpG binding domain protein 6 3056 0 0 2 9 1 0 21 31 25 22 2.3e-08 1e-05 0.93 6.8e-12 6e-09
22 MUC6 mucin 6, oligomeric mucus/gel-forming 7450 9 0 15 38 0 0 34 72 59 66 1.7e-10 0.017 0.015 1.9e-11 1.6e-08
23 CBWD1 COBW domain containing 1 1296 101 0 2 3 0 20 0 23 22 4 1.3e-07 1e-05 1e-05 3.6e-11 2.8e-08
24 CTNND1 catenin (cadherin-associated protein), delta 1 2983 5 0 1 14 7 2 12 35 33 32 2.8e-11 0.17 0.12 8.5e-11 6.5e-08
25 APC adenomatous polyposis coli 8592 2 0 12 34 17 2 20 73 62 64 8.8e-10 0.0037 0.96 2.1e-10 1.5e-07
26 LARP7 La ribonucleoprotein domain family, member 7 1797 5 0 1 5 0 2 15 22 22 13 9.3e-07 1e-05 0.02 2.5e-10 1.7e-07
27 DDX17 DEAD (Asp-Glu-Ala-Asp) box polypeptide 17 2245 2 2 2 4 0 0 13 17 17 7 9.5e-07 1e-05 0.99 2.5e-10 1.7e-07
28 CIC capicua homolog (Drosophila) 4905 0 0 6 35 2 0 22 59 54 33 1.6e-06 1e-05 1 4.2e-10 2.6e-07
29 TENC1 tensin like C1 domain containing phosphatase (tensin 2) 4449 1 0 4 11 0 4 13 28 23 23 1.6e-06 1e-05 0.69 4.2e-10 2.6e-07
30 ARID4A AT rich interactive domain 4A (RBP1-like) 3866 2 0 2 8 2 0 15 25 24 17 2.8e-06 1e-05 0.36 7e-10 4.3e-07
31 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 2709 7 0 3 26 1 6 1 34 33 30 4e-06 0.0007 0.0002 1e-09 5.9e-07
32 BCOR BCL6 co-repressor 5324 0 0 6 11 11 2 13 37 31 35 3.8e-10 0.53 0.034 1.2e-09 6.8e-07
33 C14orf43 chromosome 14 open reading frame 43 3178 10 0 5 17 1 0 20 38 32 25 0.000015 1e-05 0.97 3.5e-09 1.9e-06
34 ZBTB7C zinc finger and BTB domain containing 7C 1866 1 0 7 4 0 0 15 19 17 9 0.000018 1e-05 0.0037 4.2e-09 2.3e-06
35 FRMD4A FERM domain containing 4A 3216 1 0 4 11 1 1 16 29 28 16 0.000019 1e-05 0.0028 4.4e-09 2.3e-06
TP53

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

ARID1A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

RNF43

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

SMAD4

Figure S4.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

KRAS

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

XYLT2

Figure S6.  This figure depicts the distribution of mutations and mutation types across the XYLT2 significant gene.

PTEN

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

LARP4B

Figure S8.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

FBXW7

Figure S9.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

RHOA

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

B2M

Figure S11.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

HLA-B

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

C7orf50

Figure S13.  This figure depicts the distribution of mutations and mutation types across the C7orf50 significant gene.

GNG12

Figure S14.  This figure depicts the distribution of mutations and mutation types across the GNG12 significant gene.

PLEKHA6

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PLEKHA6 significant gene.

PGM5

Figure S16.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

KLF3

Figure S17.  This figure depicts the distribution of mutations and mutation types across the KLF3 significant gene.

ZBTB20

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

MBD6

Figure S19.  This figure depicts the distribution of mutations and mutation types across the MBD6 significant gene.

MUC6

Figure S20.  This figure depicts the distribution of mutations and mutation types across the MUC6 significant gene.

CBWD1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the CBWD1 significant gene.

CTNND1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the CTNND1 significant gene.

APC

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

LARP7

Figure S24.  This figure depicts the distribution of mutations and mutation types across the LARP7 significant gene.

DDX17

Figure S25.  This figure depicts the distribution of mutations and mutation types across the DDX17 significant gene.

CIC

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

TENC1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the TENC1 significant gene.

ARID4A

Figure S28.  This figure depicts the distribution of mutations and mutation types across the ARID4A significant gene.

CDH1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

BCOR

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

ZBTB7C

Figure S31.  This figure depicts the distribution of mutations and mutation types across the ZBTB7C significant gene.

Methods & Data
Methods

MutSig and its evolving algorithms have existed since the youth of clinical sequencing, with early versions used in multiple publications. [1][2][3]

"Three significance metrics [are] calculated for each gene, using the […] methods MutSigCV [4], MutSigCL, and MutSigFN [5]. These measure the significance of mutation burden, clustering, and functional impact, respectively […]. MutSigCV determines the P value for observing the given quantity of non-silent mutations in the gene, given the background model determined by silent (and noncoding) mutations in the same gene and the neighbouring genes of covariate space that form its 'bagel'. […] MutSigCL and MutSigFN measure the significance of the positional clustering of the mutations observed, as well as the significance of the tendency for mutations to occur at positions that are highly evolutionarily conserved (using conservation as a proxy for probably functional impact). MutSigCL and MutSigFN are permutation-based methods and their P values are calculated as follows: The observed nonsilent coding mutations in the gene are permuted T times (to simulate the null hypothesis, T = 108 for the most significant genes), randomly reassigning their positions, but preserving their mutational 'category', as determined by local sequence context. We [use] the following context categories: transitions at CpG dinucleotides, transitions at other C-G base pairs, transversions at C-G base pairs, mutations at A-T base pairs, and indels. Indels are unconstrained in terms of where they can move to in the permutations. For each of the random permutations, two scores are calculated: SCL and SFN, measuring the amount of clustering and function impact (measured by conservation) respectively. SCL is defined to be the fraction of mutations occurring in hotspots. A hotspot is defined as a 3-base-pair region of the gene containing many mutations: at least 2, and at least 2% of the total mutations. SFN is defined to be the mean of the base-pair-level conservation values for the position of each non-silent mutation […]. To determine a PCL, the P value for the observed degree of positional clustering, the observed value of SCL (computed for the mutations actually observed), [is] compared to the distribution of SCL obtained from the random permutations, and the P value [is] defined to be the fraction of random permutations in which SCL [is] at least as large as the observed SCL. The P value for the conservation of the mutated positions, PFN, [is] computed analogously." [6]

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] Getz G, Höfling H, Mesirov JP, Golub TR, Meyerson M, Tibshirani R, Lander ES, Comment on "The Consensus Coding Sequences of Human Breast and Colorectal Cancers", Science 317(5844):1500b (2007)
[3] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474(7353):609-615 (2011)
[4] Lawrence MS, et al., Mutational heterogeneity in cancer and the search for new cancer-associated genes, Nature 499(7457):214-218 (2013)
[6] Lawrence MS, et al., Discovery and saturation analysis of cancer genes across 21 tumour types, Nature 505(7484):495-501 (2014)
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