Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Prostate Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1G73CCF
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1G73CCF
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 v2.0 and MutSigCV v0.9 merged result was used to generate the results found in this report.

  • Working with individual set: PRAD-TP

  • Number of patients in set: 261

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:PRAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 10

  • Mutations seen in COSMIC: 93

  • Significantly mutated genes in COSMIC territory: 7

  • Significantly mutated genesets: 27

Mutation Preprocessing

  • Read 261 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 19400

  • After removing 31 mutations outside chr1-24: 19369

  • After removing 1866 blacklisted mutations: 17503

  • After removing 1049 noncoding mutations: 16454

  • After collapsing adjacent/redundant mutations: 14262

Mutation Filtering

  • Number of mutations before filtering: 14262

  • After removing 738 mutations outside gene set: 13524

  • After removing 11 mutations outside category set: 13513

Results
Breakdown of Mutations by Type

Table 1.  Get Full Table Table representing breakdown of mutations by type.

type count
Frame_Shift_Del 651
Frame_Shift_Ins 187
In_Frame_Del 178
In_Frame_Ins 21
Missense_Mutation 8225
Nonsense_Mutation 473
Nonstop_Mutation 12
Silent 3249
Splice_Site 464
Translation_Start_Site 53
Total 13513
Breakdown of Mutation Rates by Category Type

Table 2.  Get Full Table A breakdown of mutation rates per category discovered for this individual set.

category n N rate rate_per_mb relative_rate exp_ns_s_ratio
*CpG->T 3007 433062194 6.9e-06 6.9 5.2 2.1
*Cp(A/C/T)->T 1354 3514370872 3.9e-07 0.39 0.29 1.7
A->G 1174 3778429637 3.1e-07 0.31 0.23 2.3
transver 2740 7725862703 3.5e-07 0.35 0.27 5
indel+null 1979 7725862703 2.6e-07 0.26 0.19 NaN
double_null 10 7725862703 1.3e-09 0.0013 0.00097 NaN
Total 10264 7725862703 1.3e-06 1.3 1 3.5
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom). If the figure is unpopulated, then full coverage is assumed (e.g. MutSig CV doesn't use WIGs and assumes full coverage).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: PRAD-TP.patients.counts_and_rates.txt

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 3.  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 4.  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 5.  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:

  • N = number of sequenced bases in this gene across the individual set

  • n = 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

  • n1 = number of nonsilent mutations of type: *CpG->T

  • n2 = number of nonsilent mutations of type: *Cp(A/C/T)->T

  • n3 = number of nonsilent mutations of type: A->G

  • n4 = number of nonsilent mutations of type: transver

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_cons = p-value for enrichment of mutations at evolutionarily most-conserved sites in gene

  • p_joint = p-value for clustering + conservation

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 10. 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 description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_clust p_cons p_joint p_cv p q
1 KIDINS220 kinase D-interacting substrate, 220kDa 1414413 3 3 3 1 0 0 0 2 1 0 0.15 0 0 0.62 0 0
2 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 625585 9 9 7 0 0 1 3 5 0 0 8e-07 0.05 0 0.00046 0 0
3 SPOP speckle-type POZ protein 302876 27 26 11 0 1 0 5 20 1 0 0 0.52 0 6.7e-16 0 0
4 TP53 tumor protein p53 323081 24 23 19 0 9 1 4 5 5 0 7e-06 0.0002 6e-06 9.2e-11 2e-14 9e-11
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 300965 13 13 13 0 0 0 1 2 10 0 0.21 0.91 0.34 5.7e-15 6.7e-14 2.4e-10
6 FOXA1 forkhead box A1 281369 12 12 10 2 1 1 2 4 3 1 0.000013 0.036 7e-06 5.4e-09 1.2e-12 3.6e-09
7 LMOD2 leiomodin 2 (cardiac) 273015 3 3 1 0 0 0 0 0 3 0 0.00016 0.3 0.00072 0.0012 0.000013 0.035
8 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 329944 4 4 2 0 3 0 0 1 0 0 0.000032 0.73 7e-05 0.038 0.000037 0.083
9 NKX3-1 NK3 homeobox 1 143901 5 5 5 0 0 0 2 2 1 0 0.11 0.0055 0.017 0.00017 0.000041 0.083
10 CDKN1B cyclin-dependent kinase inhibitor 1B (p27, Kip1) 157763 4 4 4 0 0 0 0 0 4 0 0.31 0.37 0.4 7.7e-06 0.000042 0.083
11 BRAF v-raf murine sarcoma viral oncogene homolog B1 581618 6 6 5 0 0 0 1 4 1 0 0.059 0.017 0.014 0.0017 0.00027 0.44
12 SLC10A2 solute carrier family 10 (sodium/bile acid cotransporter family), member 2 278276 5 5 5 0 1 0 0 3 1 0 0.5 0.71 0.7 4e-05 0.00032 0.49
13 LARP1 La ribonucleoprotein domain family, member 1 818445 3 3 3 0 0 0 0 2 1 0 0.014 0.0014 0.00017 0.25 0.00046 0.64
14 ITGA2B integrin, alpha 2b (platelet glycoprotein IIb of IIb/IIIa complex, antigen CD41) 723351 3 3 3 1 1 0 0 1 1 0 0.12 0.000088 0.00032 0.32 0.001 1
15 ZCCHC10 zinc finger, CCHC domain containing 10 137019 2 2 2 0 0 0 0 0 2 0 NaN NaN NaN 0.0015 0.0015 1
16 ETV3 ets variant gene 3 115212 3 3 3 0 0 0 1 0 2 0 0.019 0.53 0.039 0.005 0.0018 1
17 SMG7 Smg-7 homolog, nonsense mediated mRNA decay factor (C. elegans) 903944 4 4 3 0 0 0 1 1 2 0 0.059 0.0039 0.0028 0.069 0.0018 1
18 HDGFL1 hepatoma derived growth factor-like 1 79350 2 2 1 0 0 0 0 0 2 0 0.02 0.96 0.19 0.0011 0.0019 1
19 SETD5 SET domain containing 5 1056712 4 1 4 1 0 3 0 1 0 0 0.0002 0.52 0.0005 0.84 0.0037 1
20 LCE1F late cornified envelope 1F 93960 3 2 3 0 1 1 0 1 0 0 0.01 0.63 0.032 0.013 0.0038 1
21 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 853498 10 9 10 2 2 2 2 4 0 0 0.16 0.12 0.1 0.0044 0.0039 1
22 CDK12 cyclin-dependent kinase 12 1160249 9 7 9 0 1 2 1 1 3 1 0.36 0.89 0.56 0.00085 0.0041 1
23 LHX3 LIM homeobox 3 232893 3 3 3 0 0 1 0 1 1 0 0.4 0.17 0.16 0.0032 0.0045 1
24 MED12 mediator complex subunit 12 1461980 4 4 3 1 0 2 0 2 0 0 0.00038 0.21 0.00065 0.86 0.0047 1
25 OR52D1 olfactory receptor, family 52, subfamily D, member 1 250766 3 3 3 1 0 1 0 1 1 0 0.012 0.61 0.044 0.013 0.0048 1
26 PBX4 pre-B-cell leukemia homeobox 4 247922 4 4 4 0 2 0 0 0 2 0 0.71 0.77 1 0.00059 0.005 1
27 OSCAR osteoclast associated, immunoglobulin-like receptor 119268 2 2 2 0 1 0 0 0 1 0 0.78 0.028 0.049 0.013 0.0054 1
28 RBPMS2 RNA binding protein with multiple splicing 2 135158 2 2 2 0 1 0 0 0 1 0 0.05 0.82 0.05 0.013 0.0055 1
29 MYO15A myosin XVA 2373636 7 7 7 0 6 1 0 0 0 0 0.0016 0.54 0.0029 0.25 0.0061 1
30 RPTN repetin 616724 6 6 5 0 2 1 0 0 3 0 0.11 0.54 0.21 0.0039 0.0067 1
31 KCNA3 potassium voltage-gated channel, shaker-related subfamily, member 3 404411 4 4 4 2 1 0 0 1 2 0 0.65 0.26 0.42 0.0022 0.0073 1
32 SLC16A6 solute carrier family 16, member 6 (monocarboxylic acid transporter 7) 403383 3 3 3 1 1 1 0 0 1 0 0.48 0.031 0.066 0.014 0.0075 1
33 ZMYM3 zinc finger, MYM-type 3 823102 7 6 7 0 0 0 0 3 4 0 0.52 0.39 0.63 0.0015 0.0075 1
34 SMARCA1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 1 818642 5 5 5 0 0 0 0 2 3 0 0.042 0.27 0.067 0.015 0.0081 1
35 MED15 mediator complex subunit 15 617103 5 5 5 0 1 1 0 1 2 0 0.21 0.35 0.23 0.0045 0.0083 1
KIDINS220

Figure S1.  This figure depicts the distribution of mutations and mutation types across the KIDINS220 significant gene.

CTNNB1

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

SPOP

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

TP53

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PTEN

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

FOXA1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

LMOD2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the LMOD2 significant gene.

IDH1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

NKX3-1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NKX3-1 significant gene.

CDKN1B

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CDKN1B significant gene.

COSMIC analyses

In this analysis, COSMIC is used as a filter to increase power by restricting the territory of each gene. Cosmic version: v48.

Table 4.  Get Full Table Significantly mutated genes (COSMIC territory only). To access the database please go to: COSMIC. Number of significant genes found: 7. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 4 5 4 1305 5968 4.4e-13 2e-09
2 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 9 138 8 36018 3282 1.6e-12 3.6e-09
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 10 220 10 57420 2607 2.5e-12 3.8e-09
4 TP53 tumor protein p53 24 356 23 92916 7433 3.8e-12 4.4e-09
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 13 767 13 200187 188 7.2e-12 6.5e-09
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 6 89 4 23229 210 3.7e-08 0.000028
7 SMAD4 SMAD family member 4 4 159 4 41499 19 3.7e-07 0.00024
8 ACSM2B acyl-CoA synthetase medium-chain family member 2B 2 1 1 261 1 0.00035 0.12
9 ATAD1 ATPase family, AAA domain containing 1 1 1 1 261 1 0.00035 0.12
10 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 2 1 1 261 1 0.00035 0.12

Note:

n - number of (nonsilent) mutations in this gene across the individual set.

cos = number of unique mutated sites in this gene in COSMIC

n_cos = overlap between n and cos.

N_cos = number of individuals times cos.

cos_ev = total evidence: number of reports in COSMIC for mutations seen in this gene.

p = p-value for seeing the observed amount of overlap in this gene)

q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Geneset Analyses

Table 5.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 27. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 ABCB1(4), AKT1(1), ATM(12), CDKN1A(2), CPB2(1), HIC1(3), MDM2(1), NQO1(1), TP53(24) 8123773 49 42 44 1 16 8 6 10 9 0 0.000013 3.2e-15 1.2e-12
2 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 CDKN1A(2), CDKN1B(4), CDKN2A(1), CFL1(1), MDM2(1), TP53(24) 3325946 33 30 28 1 11 1 4 5 12 0 0.0038 3.9e-15 1.2e-12
3 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 SP1(1), SP3(2), TP53(24) 2757815 27 25 22 1 9 2 4 6 6 0 0.0027 1.4e-14 2.9e-12
4 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(12), TP53(24), YWHAH(1) 6218154 37 32 32 1 9 7 5 10 6 0 0.0013 2e-14 3.2e-12
5 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(12), CDC25A(1), CDC25B(2), MYT1(1), RB1(2), TP53(24), YWHAH(1) 6837884 43 37 38 2 12 7 6 11 6 1 0.00059 2.8e-14 3.5e-12
6 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(1), ATM(12), CDKN1A(2), MDM2(1), RB1(2), TP53(24) 7058768 42 36 37 2 11 7 6 10 7 1 0.00059 2.1e-13 2.2e-11
7 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(4), CDKN2A(1), MDM2(1), PIK3CA(10), PIK3R1(1), POLR1B(1), POLR1C(1), RAC1(1), RB1(2), TP53(24) 7933159 46 38 41 3 13 3 9 11 9 1 0.0013 5.7e-11 5e-09
8 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 RELA(2), TP53(24) 3827662 26 23 21 0 9 2 5 5 5 0 0.00086 6.4e-11 5e-09
9 CHEMICALPATHWAY DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 20 AKT1(1), APAF1(1), ATM(12), PRKCA(2), PTK2(2), PXN(1), STAT1(1), TLN1(2), TP53(24) 10707759 46 40 41 0 12 9 5 13 7 0 2.1e-06 1.4e-10 1e-08
10 G2PATHWAY Activated Cdc2-cyclin B kinase regulates the G2/M transition; DNA damage stimulates the DNA-PK/ATM/ATR kinases, which inactivate Cdc2. ATM, ATR, BRCA1, CCNB1, CDC2, CDC25A, CDC25B, CDC25C, CDC34, CDKN1A, CDKN2D, CHEK1, CHEK2, EP300, GADD45A, MDM2, MYT1, PLK, PRKDC, RPS6KA1, TP53, WEE1, YWHAH, YWHAQ 22 ATM(12), CDC25A(1), CDC25B(2), CDKN1A(2), EP300(4), MDM2(1), MYT1(1), PRKDC(7), RPS6KA1(1), TP53(24), YWHAH(1), YWHAQ(1) 16314278 57 47 52 2 19 10 6 14 8 0 0.000017 2.6e-09 1.6e-07
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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