Mutation Analysis (MutSig 2CV v3.1)
Liver Hepatocellular Carcinoma (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/C128070B
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: LIHC-TP

  • Number of patients in set: 373

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:LIHC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 69

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: 69. 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 9 1 1 67 12 14 24 117 114 85 1e-16 1e-05 1e-05 1e-16 9.1e-13
2 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 2406 37 0 3 99 0 0 4 103 97 27 1e-16 1e-05 0.0023 1e-16 9.1e-13
3 AXIN1 axin 1 2629 12 0 1 4 8 4 9 25 24 24 1e-16 0.62 0.027 3.3e-16 2e-12
4 RB1 retinoblastoma 1 (including osteosarcoma) 3711 1 0 0 5 1 6 13 25 21 24 1e-16 0.076 0.49 4.4e-16 2e-12
5 ARID1A AT rich interactive domain 1A (SWI-like) 6934 0 0 2 8 6 2 18 34 32 32 5.8e-16 0.055 0.8 1.7e-15 6.1e-12
6 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 2254 44 1 1 5 5 1 9 20 19 20 2.5e-13 0.46 0.031 4.8e-13 1.5e-09
7 CDC27 cell division cycle 27 homolog (S. cerevisiae) 2565 77 0 1 5 0 1 9 15 15 8 3e-08 1e-05 0.58 8.9e-12 2.3e-08
8 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 280 0 0 6 0 2 3 11 11 11 8.9e-07 0.33 1e-05 2.3e-10 5.4e-07
9 KRT2 keratin 2 (epidermal ichthyosis bullosa of Siemens) 1954 11 0 2 2 1 1 8 12 12 11 4.9e-08 0.00012 0.54 2.7e-10 5.5e-07
10 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 92 0 0 13 0 0 2 15 13 12 0.000027 1e-05 0.0014 6.3e-09 0.000011
11 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 1 0 1 3 1 2 5 11 11 11 4.4e-10 1 0.79 9.8e-09 0.000016
12 ARID2 AT rich interactive domain 2 (ARID, RFX-like) 5588 10 0 2 7 6 3 9 25 22 25 1.1e-08 0.26 0.79 7.3e-08 0.0001
13 RBM10 RNA binding motif protein 10 2882 25 0 0 6 0 0 3 9 8 7 0.00036 1e-05 1 7.4e-08 0.0001
14 ZNF512B zinc finger protein 512B 2743 6 0 0 5 0 0 3 8 8 6 0.00019 0.00088 0.0084 1.5e-07 0.00019
15 KCNN3 potassium intermediate/small conductance calcium-activated channel, subfamily N, member 3 2244 20 0 0 9 0 0 3 12 12 9 0.000043 0.00014 1 1.5e-07 0.00019
16 KRT10 keratin 10 (epidermolytic hyperkeratosis; keratosis palmaris et plantaris) 1789 134 0 1 10 1 0 0 11 9 4 0.0011 1e-05 0.24 2.2e-07 0.00025
17 APOB apolipoprotein B (including Ag(x) antigen) 13804 0 0 4 22 3 1 18 44 39 42 1e-06 0.017 0.36 3.4e-07 0.00036
18 MLL4 myeloid/lymphoid or mixed-lineage leukemia 2 8293 23 0 3 11 4 3 3 21 19 21 4e-08 1 0.42 7.2e-07 0.00073
19 ALB albumin 1888 2 1 3 12 0 3 35 50 42 42 0.00026 4e-05 0.59 8.3e-07 0.0008
20 TSC2 tuberous sclerosis 2 5590 4 0 0 3 5 0 4 12 12 11 5.1e-07 0.12 0.33 1.2e-06 0.0011
21 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 2817 4 0 1 4 1 0 7 12 12 12 7.3e-07 0.084 0.44 1.5e-06 0.0013
22 C19orf55 chromosome 19 open reading frame 55 1320 23 0 0 2 0 5 0 7 6 4 1.3e-06 0.047 0.53 1.7e-06 0.0014
23 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 32 0 1 13 0 0 0 13 13 8 0.011 1e-05 0.026 2e-06 0.0015
24 CELA1 chymotrypsin-like elastase family, member 1 807 81 0 0 2 0 0 4 6 6 3 0.00011 0.0015 0.94 4.7e-06 0.0035
25 RPS6KA3 ribosomal protein S6 kinase, 90kDa, polypeptide 3 2307 16 0 0 8 4 2 1 15 14 14 1.2e-06 0.23 0.68 5.7e-06 0.0041
26 NRD1 nardilysin (N-arginine dibasic convertase) 3790 104 2 1 14 0 0 0 14 13 7 0.011 1e-05 1 6.9e-06 0.0047
27 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 1417 37 0 0 9 0 0 0 9 9 7 0.00025 0.0085 0.16 7e-06 0.0047
28 TCHH trichohyalin 5836 14 0 3 19 1 0 1 21 17 15 0.069 1e-05 1 1e-05 0.0068
29 COG2 component of oligomeric golgi complex 2 2285 2 0 0 0 0 0 4 4 4 1 0.0075 0.0001 0.078 0.000011 0.0071
30 ATXN1 ataxin 1 2452 8 0 0 6 0 0 5 11 10 8 0.011 3e-05 1 0.000012 0.0073
31 KCTD20 potassium channel tetramerisation domain containing 20 1288 40 0 0 2 0 2 2 6 5 5 0.00015 0.045 0.073 0.000016 0.0096
32 GPR110 G protein-coupled receptor 110 2837 34 0 1 4 0 3 0 7 6 6 0.14 0.00045 0.037 2e-05 0.012
33 CEP164 centrosomal protein 164kDa 4507 16 0 1 8 0 0 1 9 9 5 0.17 1e-05 0.019 0.000025 0.014
34 TCEAL6 transcription elongation factor A (SII)-like 6 556 246 0 0 9 0 0 0 9 4 4 0.2 1e-05 0.11 0.000029 0.015
35 DNAJC28 DnaJ (Hsp40) homolog, subfamily C, member 28 1171 140 0 0 4 1 0 0 5 4 3 0.038 0.00018 0.063 0.000032 0.017
TP53

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

CTNNB1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

RB1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ARID1A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

BAP1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

CDC27

Figure S6.  This figure depicts the distribution of mutations and mutation types across the CDC27 significant gene.

CDKN2A

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

KRT2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the KRT2 significant gene.

NFE2L2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

PTEN

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

ARID2

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ARID2 significant gene.

RBM10

Figure S12.  This figure depicts the distribution of mutations and mutation types across the RBM10 significant gene.

ZNF512B

Figure S13.  This figure depicts the distribution of mutations and mutation types across the ZNF512B significant gene.

KCNN3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the KCNN3 significant gene.

KRT10

Figure S15.  This figure depicts the distribution of mutations and mutation types across the KRT10 significant gene.

APOB

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

ALB

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

TSC2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the TSC2 significant gene.

IL6ST

Figure S19.  This figure depicts the distribution of mutations and mutation types across the IL6ST significant gene.

PIK3CA

Figure S20.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CELA1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the CELA1 significant gene.

RPS6KA3

Figure S22.  This figure depicts the distribution of mutations and mutation types across the RPS6KA3 significant gene.

NRD1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the NRD1 significant gene.

EEF1A1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the EEF1A1 significant gene.

TCHH

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

COG2

Figure S26.  This figure depicts the distribution of mutations and mutation types across the COG2 significant gene.

ATXN1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ATXN1 significant gene.

KCTD20

Figure S28.  This figure depicts the distribution of mutations and mutation types across the KCTD20 significant gene.

GPR110

Figure S29.  This figure depicts the distribution of mutations and mutation types across the GPR110 significant gene.

CEP164

Figure S30.  This figure depicts the distribution of mutations and mutation types across the CEP164 significant gene.

TCEAL6

Figure S31.  This figure depicts the distribution of mutations and mutation types across the TCEAL6 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)