Mutation Analysis (MutSig 2CV v3.1)
Pancreatic Adenocarcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
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/C14T6H4V
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: PAAD-TP

  • Number of patients in set: 41

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:PAAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 141

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: 141. 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 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 281 0 0 31 0 0 0 31 30 4 6.9e-16 1e-05 0.00057 1e-16 9.1e-13
2 TP53 tumor protein p53 1889 105 0 0 15 4 0 5 24 24 21 1e-16 0.45 0.00044 1e-16 9.1e-13
3 C19orf55 chromosome 19 open reading frame 55 1321 90 0 0 2 0 0 5 7 7 3 3.2e-11 0.00024 0.94 4.1e-13 2.5e-09
4 B4GALT2 UDP-Gal:betaGlcNAc beta 1,4- galactosyltransferase, polypeptide 2 1561 3 0 0 0 0 0 5 5 5 1 9.4e-09 1e-05 1 2.9e-12 1.3e-08
5 COTL1 coactosin-like 1 (Dictyostelium) 441 212 0 0 0 7 0 0 7 7 1 1.4e-12 0.072 1 7.6e-12 2.8e-08
6 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1002 832 0 0 2 4 0 1 7 7 4 3.9e-08 0.00022 1e-05 1.2e-11 3.5e-08
7 NFIL3 nuclear factor, interleukin 3 regulated 1389 642 0 0 1 0 0 5 6 6 2 2.5e-07 1e-05 0.99 6.8e-11 1.8e-07
8 OTOF otoferlin 6503 7 0 0 3 0 0 8 11 9 4 3.5e-07 1e-05 0.98 9.7e-11 2.2e-07
9 IRS1 insulin receptor substrate 1 3735 20 0 1 1 0 0 5 6 6 2 5.5e-07 1e-05 0.94 1.5e-10 3e-07
10 GAS2L2 growth arrest-specific 2 like 2 2665 43 0 0 3 0 0 3 6 6 3 7.1e-07 1e-05 0.47 1.9e-10 3.4e-07
11 RBM10 RNA binding motif protein 10 2882 19 0 0 1 0 0 5 6 6 2 2.8e-06 1e-05 0.48 7.1e-10 1.2e-06
12 APP amyloid beta (A4) precursor protein (peptidase nexin-II, Alzheimer disease) 2381 33 0 0 2 0 0 5 7 6 3 4.1e-06 1e-05 0.85 1e-09 1.6e-06
13 IPP intracisternal A particle-promoted polypeptide 1889 7 0 0 0 1 0 5 6 5 2 0.000011 1e-05 0.96 2.6e-09 3.7e-06
14 MAMLD1 mastermind-like domain containing 1 3467 8 0 2 1 0 0 6 7 7 3 0.000025 1e-05 0.28 5.7e-09 7e-06
15 ARHGAP18 Rho GTPase activating protein 18 2050 35 0 1 0 0 0 4 4 4 1 2.5e-06 0.0001 0.088 5.7e-09 7e-06
16 PHF8 PHD finger protein 8 3433 40 0 0 0 0 0 5 5 5 1 0.000034 1e-05 1 7.7e-09 8.8e-06
17 THBS4 thrombospondin 4 2970 17 0 0 1 0 0 5 6 6 2 0.000043 1e-05 1 9.8e-09 0.000011
18 SMAD4 SMAD family member 4 1699 111 0 0 2 1 0 4 7 7 7 4.3e-09 1 0.069 1.2e-08 0.000013
19 PTPRF protein tyrosine phosphatase, receptor type, F 5852 70 0 3 5 0 0 5 10 7 6 2e-05 2e-05 0.98 1.8e-08 0.000017
20 MED12 mediator complex subunit 12 6710 8 0 0 2 0 0 6 8 6 4 0.000083 1e-05 0.99 1.8e-08 0.000017
21 BMP2K BMP2 inducible kinase 3582 3 0 0 1 0 0 4 5 4 2 0.000024 2e-05 0.96 2.6e-08 0.000023
22 ZMYM5 zinc finger, MYM-type 5 2145 13 0 0 1 0 0 3 4 4 2 0.000011 0.0001 0.56 3.5e-08 0.000029
23 SYT15 synaptotagmin XV 1350 77 0 0 1 0 0 3 4 4 2 0.000017 0.0001 0.96 4.7e-08 0.000037
24 PLAU plasminogen activator, urokinase 1661 61 0 1 1 0 0 3 4 4 2 0.000022 0.0001 0.67 5.5e-08 0.000042
25 MEPCE methylphosphate capping enzyme 2082 20 0 0 0 1 0 3 4 4 2 0.000028 0.0001 1 5.8e-08 0.000043
26 ZMIZ1 zinc finger, MIZ-type containing 1 3288 102 0 1 0 0 0 5 5 5 3 0.000049 5e-05 0.84 7e-08 0.000049
27 SLC39A5 solute carrier family 39 (metal ion transporter), member 5 1856 46 0 0 2 0 0 2 4 4 2 0.000039 0.0001 0.56 8e-08 0.000054
28 GUCY2F guanylate cyclase 2F, retinal 3402 5 0 0 2 0 0 3 5 5 3 0.00047 1e-05 0.82 9.4e-08 0.000062
29 EDC4 enhancer of mRNA decapping 4 4328 1 0 1 1 0 0 4 5 5 3 0.00028 1e-05 0.89 1.1e-07 7e-05
30 SEH1L SEH1-like (S. cerevisiae) 1313 132 0 0 0 1 0 3 4 3 2 0.000067 0.0001 0.89 1.3e-07 0.000081
31 SLC4A3 solute carrier family 4, anion exchanger, member 3 3872 24 0 1 2 0 0 3 5 3 3 0.00013 5e-05 0.76 1.5e-07 0.000088
32 CD99L2 CD99 molecule-like 2 829 362 0 0 0 0 0 4 4 4 2 4e-05 0.00024 0.53 1.9e-07 0.00011
33 SBNO1 strawberry notch homolog 1 (Drosophila) 4302 60 0 2 3 0 0 1 4 4 2 0.000026 0.0005 0.32 2.5e-07 0.00014
34 NPNT nephronectin 1891 27 0 1 0 0 0 3 3 3 1 0.000017 0.001 0.86 3.2e-07 0.00017
35 TMEM175 transmembrane protein 175 1555 138 0 0 4 0 0 3 7 5 5 8.7e-06 0.0017 0.31 3.4e-07 0.00018
KRAS

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

TP53

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

C19orf55

Figure S3.  This figure depicts the distribution of mutations and mutation types across the C19orf55 significant gene.

B4GALT2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the B4GALT2 significant gene.

COTL1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the COTL1 significant gene.

CDKN2A

Figure S6.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

NFIL3

Figure S7.  This figure depicts the distribution of mutations and mutation types across the NFIL3 significant gene.

OTOF

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

IRS1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the IRS1 significant gene.

GAS2L2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the GAS2L2 significant gene.

RBM10

Figure S11.  This figure depicts the distribution of mutations and mutation types across the RBM10 significant gene.

APP

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

IPP

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

MAMLD1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the MAMLD1 significant gene.

ARHGAP18

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ARHGAP18 significant gene.

PHF8

Figure S16.  This figure depicts the distribution of mutations and mutation types across the PHF8 significant gene.

THBS4

Figure S17.  This figure depicts the distribution of mutations and mutation types across the THBS4 significant gene.

SMAD4

Figure S18.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

PTPRF

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

MED12

Figure S20.  This figure depicts the distribution of mutations and mutation types across the MED12 significant gene.

BMP2K

Figure S21.  This figure depicts the distribution of mutations and mutation types across the BMP2K significant gene.

ZMYM5

Figure S22.  This figure depicts the distribution of mutations and mutation types across the ZMYM5 significant gene.

SYT15

Figure S23.  This figure depicts the distribution of mutations and mutation types across the SYT15 significant gene.

PLAU

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

MEPCE

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

ZMIZ1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the ZMIZ1 significant gene.

SLC39A5

Figure S27.  This figure depicts the distribution of mutations and mutation types across the SLC39A5 significant gene.

GUCY2F

Figure S28.  This figure depicts the distribution of mutations and mutation types across the GUCY2F significant gene.

EDC4

Figure S29.  This figure depicts the distribution of mutations and mutation types across the EDC4 significant gene.

SEH1L

Figure S30.  This figure depicts the distribution of mutations and mutation types across the SEH1L significant gene.

SLC4A3

Figure S31.  This figure depicts the distribution of mutations and mutation types across the SLC4A3 significant gene.

CD99L2

Figure S32.  This figure depicts the distribution of mutations and mutation types across the CD99L2 significant gene.

SBNO1

Figure S33.  This figure depicts the distribution of mutations and mutation types across the SBNO1 significant gene.

NPNT

Figure S34.  This figure depicts the distribution of mutations and mutation types across the NPNT 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)