Mutation Analysis (MutSig 2CV v3.1)
Colorectal Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
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/C1KW5FDZ
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: COADREAD-TP

  • Number of patients in set: 489

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:COADREAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 1637

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: 1637. 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 APC adenomatous polyposis coli 8592 0 0 194 319 374 29 134 856 403 435 1e-16 1e-05 1 1e-16 3.7e-13
2 TP53 tumor protein p53 1890 0 0 68 339 47 27 33 446 323 226 1e-16 1e-05 1e-05 1e-16 3.7e-13
3 ARID1A AT rich interactive domain 1A (SWI-like) 6934 2 0 19 48 22 5 21 96 83 73 1.3e-16 1e-05 0.042 1e-16 3.7e-13
4 RNF43 ring finger protein 43 2384 5 0 2 16 2 1 37 56 47 28 1e-16 1e-05 0.28 1e-16 3.7e-13
5 CRIPAK cysteine-rich PAK1 inhibitor 1341 19 0 3 13 1 0 17 31 29 17 3.9e-15 1e-05 0.018 1e-16 3.7e-13
6 SOX9 SRY (sex determining region Y)-box 9 (campomelic dysplasia, autosomal sex-reversal) 1538 1 0 0 8 7 1 30 46 41 43 1e-16 0.17 0.5 8.9e-16 2.6e-12
7 FAM123B family with sequence similarity 123B 3412 25 0 7 24 30 0 12 66 60 49 1.2e-15 0.01 0.77 1e-15 2.6e-12
8 ZFP36L2 zinc finger protein 36, C3H type-like 2 1489 23 0 1 1 1 0 15 17 17 14 5.1e-14 0.0073 0.07 5.8e-15 1.3e-11
9 B2M beta-2-microglobulin 374 4 0 1 7 2 5 8 22 17 16 7.9e-15 0.043 0.25 1.4e-14 2.8e-11
10 TXNDC2 thioredoxin domain-containing 2 (spermatozoa) 1672 46 0 2 6 1 0 20 27 24 10 1e-10 1e-05 0.98 3.6e-14 6.6e-11
11 ACVR1B activin A receptor, type IB 1679 9 0 0 23 7 0 3 33 28 27 6.1e-11 0.0003 0.077 6e-13 9.9e-10
12 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 2709 0 0 19 73 10 13 4 100 86 72 2.2e-09 1e-05 0.23 7.1e-13 1.1e-09
13 MLH1 mutL homolog 1, colon cancer, nonpolyposis type 2 (E. coli) 4163 1 0 17 41 3 18 8 70 59 49 7.1e-09 1e-05 0.13 2.2e-12 3.1e-09
14 BCOR BCL6 co-repressor 5324 0 0 5 11 9 2 9 31 30 28 1.3e-11 0.081 0.0069 3.4e-12 4.5e-09
15 SMAD2 SMAD family member 2 1444 40 0 1 15 7 2 0 24 22 18 2.8e-10 0.0038 0.015 1.1e-11 1.4e-08
16 WNT1 wingless-type MMTV integration site family, member 1 1125 1 0 0 0 0 0 7 7 7 1 6.9e-08 1e-05 1e-05 2e-11 2.3e-08
17 FMN2 formin 2 5237 1 0 15 32 1 1 39 73 63 41 8.7e-08 1e-05 1 2.5e-11 2.7e-08
18 GGT1 gamma-glutamyltransferase 1 2332 0 0 1 0 0 1 9 10 10 3 1.3e-07 1e-05 0.032 3.6e-11 3.6e-08
19 STARD3NL STARD3 N-terminal like 737 46 0 2 15 0 0 0 15 15 5 8.6e-07 2e-05 0.00095 2.3e-10 2.2e-07
20 SELPLG selectin P ligand 1217 21 0 2 6 0 0 14 20 19 11 7.4e-08 0.00045 0.59 1.2e-09 1.1e-06
21 OR4D10 olfactory receptor, family 4, subfamily D, member 10 936 91 0 2 17 1 0 0 18 16 11 6.5e-06 1e-05 0.013 1.6e-09 1.4e-06
22 NF2 neurofibromin 2 (merlin) 1894 0 0 27 54 15 12 1 82 67 62 9.6e-06 1e-05 0.41 2.3e-09 1.9e-06
23 MAPK6 mitogen-activated protein kinase 6 2182 8 0 1 17 0 2 0 19 19 14 0.000011 1e-05 0.084 2.6e-09 2e-06
24 RHOA ras homolog gene family, member A 918 5 0 0 7 3 1 2 13 13 9 1.7e-08 0.0049 0.49 3.2e-09 2.5e-06
25 FAM9A family with sequence similarity 9, member A 1035 0 0 1 4 0 0 9 13 12 8 2.4e-06 0.00032 0.072 4e-09 2.9e-06
26 EGR1 early growth response 1 1636 1 0 2 7 2 0 5 14 12 11 0.000023 0.00012 0.081 5.2e-09 3.7e-06
27 PRKDC protein kinase, DNA-activated, catalytic polypeptide 12728 17 0 22 72 6 10 8 96 70 77 0.000027 1e-05 0.75 6.2e-09 4.2e-06
28 RPTN repetin 2363 7 0 2 2 1 0 15 18 18 5 0.000031 1e-05 0.28 7.2e-09 4.6e-06
29 THOC7 THO complex 7 homolog (Drosophila) 643 4 0 0 7 0 4 1 12 11 7 0.000032 1e-05 0.7 7.2e-09 4.6e-06
30 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 12120 0 0 49 102 18 23 2 145 107 105 0.000037 1e-05 0.0057 8.3e-09 5.1e-06
31 FBXW7 F-box and WD repeat domain containing 7 2580 0 2 53 117 26 5 8 156 130 91 0.000043 1e-05 0.00041 9.6e-09 5.7e-06
32 CHUK conserved helix-loop-helix ubiquitous kinase 2320 12 0 2 22 1 3 1 27 24 20 0.000051 1e-05 0.081 1.1e-08 6.5e-06
33 ATXN3L ataxin 3-like 1068 19 0 2 19 1 0 1 21 20 16 9.2e-06 1e-05 0.38 1.2e-08 6.8e-06
34 MGA MAX gene associated 9290 1 0 10 36 5 2 11 54 43 43 0.00013 1e-05 1 2.7e-08 0.000015
35 TPRKB TP53RK binding protein 544 117 0 0 10 0 0 0 10 10 3 0.0002 1e-05 0.00073 4.2e-08 0.000022
APC

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

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

ARID1A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

RNF43

Figure S4.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

CRIPAK

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

SOX9

Figure S6.  This figure depicts the distribution of mutations and mutation types across the SOX9 significant gene.

FAM123B

Figure S7.  This figure depicts the distribution of mutations and mutation types across the FAM123B significant gene.

ZFP36L2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 significant gene.

B2M

Figure S9.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

TXNDC2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the TXNDC2 significant gene.

ACVR1B

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ACVR1B significant gene.

CDH1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

MLH1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the MLH1 significant gene.

BCOR

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

SMAD2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the SMAD2 significant gene.

WNT1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the WNT1 significant gene.

FMN2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the FMN2 significant gene.

STARD3NL

Figure S18.  This figure depicts the distribution of mutations and mutation types across the STARD3NL significant gene.

SELPLG

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

OR4D10

Figure S20.  This figure depicts the distribution of mutations and mutation types across the OR4D10 significant gene.

NF2

Figure S21.  This figure depicts the distribution of mutations and mutation types across the NF2 significant gene.

MAPK6

Figure S22.  This figure depicts the distribution of mutations and mutation types across the MAPK6 significant gene.

RHOA

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

FAM9A

Figure S24.  This figure depicts the distribution of mutations and mutation types across the FAM9A significant gene.

EGR1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the EGR1 significant gene.

PRKDC

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

RPTN

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

THOC7

Figure S28.  This figure depicts the distribution of mutations and mutation types across the THOC7 significant gene.

NF1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

FBXW7

Figure S30.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

CHUK

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

ATXN3L

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ATXN3L significant gene.

MGA

Figure S33.  This figure depicts the distribution of mutations and mutation types across the MGA 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)