Mutation Analysis (MutSig 2CV v3.1)
Lung Squamous Cell Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1KP817T
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/C1KP817T
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: LUSC-TP

  • Number of patients in set: 178

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:LUSC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 14

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: 14. 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 1314 0 0 7 100 20 10 17 147 141 98 4.4e-16 1e-05 1e-05 1e-16 1.8e-12
2 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1834 18 0 0 27 0 0 1 28 27 15 1.8e-12 1e-05 1e-05 7.8e-16 6.8e-12
3 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 1 0 1 14 8 0 4 26 26 23 3e-12 0.25 1e-05 1.1e-15 6.8e-12
4 KEAP1 kelch-like ECH-associated protein 1 1895 30 0 0 22 1 0 1 24 22 21 9.3e-12 0.079 0.18 3.2e-11 1.4e-07
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 1244 34 0 0 8 6 0 2 16 14 15 3.8e-11 0.08 0.49 1.4e-10 5.2e-07
6 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3287 16 0 1 29 0 0 0 29 27 16 0.000046 1e-05 0.0032 1e-08 0.000031
7 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 16826 1 0 5 23 12 3 3 41 35 41 9.5e-10 1 0.32 1.3e-08 0.000034
8 RB1 retinoblastoma 1 (including osteosarcoma) 2891 14 0 0 4 2 3 3 12 12 12 1e-07 1 0.66 1.7e-06 0.0039
9 IBTK inhibitor of Bruton agammaglobulinemia tyrosine kinase 4170 3 0 0 4 1 2 0 7 5 7 0.016 9e-05 0.35 7.6e-06 0.015
10 CYP11B1 cytochrome P450, family 11, subfamily B, polypeptide 1 1546 24 0 0 15 0 0 0 15 15 15 8.1e-07 1 0.94 0.000012 0.022
11 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 7800 16 0 3 11 5 1 1 18 14 18 0.00035 0.18 0.0029 0.000016 0.027
12 SLC28A1 solute carrier family 28 (sodium-coupled nucleoside transporter), member 1 2087 29 0 1 7 1 2 0 10 9 10 0.00022 0.1 0.011 0.000022 0.034
13 ASB5 ankyrin repeat and SOCS box-containing 5 1016 14 0 0 9 0 0 0 9 9 9 0.00018 1 0.0042 0.000032 0.045
14 CPS1 carbamoyl-phosphate synthetase 1, mitochondrial 4675 23 0 3 28 0 2 0 30 25 29 0.000058 0.052 0.82 0.000054 0.071
15 EP300 E1A binding protein p300 7365 7 0 2 8 0 1 0 9 8 8 0.17 0.00015 0.18 0.000087 0.11
16 ARID1A AT rich interactive domain 1A (SWI-like) 6934 37 0 3 8 1 1 4 14 12 14 0.00026 0.042 0.84 0.00017 0.2
17 FBXW7 F-box and WD repeat domain containing 7 2580 8 0 3 7 3 0 0 10 10 8 0.0031 0.016 0.16 0.00021 0.22
18 HLA-A major histocompatibility complex, class I, A 1128 217 0 0 1 4 2 0 7 6 7 0.003 1 0.0037 0.00031 0.3
19 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 3999 1 0 1 6 0 1 0 7 6 6 0.28 0.011 0.0039 0.00032 0.3
20 PDZD7 PDZ domain containing 7 1586 18 0 0 3 0 1 0 4 4 3 0.0015 0.018 0.13 0.00032 0.3
21 POLR2B polymerase (RNA) II (DNA directed) polypeptide B, 140kDa 3625 26 0 0 4 1 1 0 6 6 6 3e-05 1 0.97 0.00034 0.3
22 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 659 572 0 0 5 0 0 0 5 5 4 0.061 0.0016 0.04 0.00039 0.33
23 LAMA4 laminin, alpha 4 5788 33 0 4 15 2 0 0 17 16 16 0.0047 0.0097 0.98 0.00068 0.53
24 ZNF567 zinc finger protein 567 1863 8 0 3 3 1 0 0 4 3 4 0.68 0.017 0.0001 0.00072 0.53
25 DUSP9 dual specificity phosphatase 9 1167 3 0 0 0 2 0 0 2 2 1 0.0026 0.071 0.33 0.00073 0.53
26 CLSTN2 calsyntenin 2 2932 29 0 2 11 4 1 0 16 15 16 0.0042 0.18 0.01 0.00083 0.58
27 CCDC121 coiled-coil domain containing 121 1327 107 0 0 4 0 0 0 4 4 3 0.044 0.025 0.016 0.00094 0.64
28 TYK2 tyrosine kinase 2 3656 12 0 1 7 0 1 0 8 8 8 0.00039 1 0.15 0.00099 0.64
29 SLC46A1 solute carrier family 46 (folate transporter), member 1 1399 1 0 0 2 1 0 0 3 2 3 0.1 0.0065 0.044 0.0011 0.67
30 HGF hepatocyte growth factor (hepapoietin A; scatter factor) 2271 25 0 2 8 1 0 1 10 10 10 0.0015 0.065 0.59 0.0011 0.68
31 KIRREL2 kin of IRRE like 2 (Drosophila) 2227 98 0 1 10 1 0 0 11 11 11 0.00065 1 0.063 0.0012 0.69
32 MUC5B mucin 5B, oligomeric mucus/gel-forming 17492 41 0 9 33 3 1 1 38 32 38 0.00013 1 0.56 0.0012 0.7
33 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 8807 4 0 3 15 5 2 0 22 21 22 0.00013 1 1 0.0013 0.7
34 KDM6A lysine (K)-specific demethylase 6A 4318 7 0 0 2 2 3 0 7 7 7 0.0019 0.15 0.22 0.0014 0.7
35 PI16 peptidase inhibitor 16 1416 88 0 1 6 1 0 0 7 7 7 0.00088 1 0.051 0.0014 0.7
TP53

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

NFE2L2

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

CDKN2A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

KEAP1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

PTEN

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

PIK3CA

Figure S6.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

MLL2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

RB1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

IBTK

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

CYP11B1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CYP11B1 significant gene.

NOTCH1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

SLC28A1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the SLC28A1 significant gene.

ASB5

Figure S13.  This figure depicts the distribution of mutations and mutation types across the ASB5 significant gene.

CPS1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the CPS1 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)
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