Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Prostate Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1X065FM
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1X065FM
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: 83

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

  • Significantly mutated genes (q ≤ 0.1): 1

  • Mutations seen in COSMIC: 28

  • Significantly mutated genes in COSMIC territory: 7

  • Significantly mutated genesets: 1

Mutation Preprocessing

  • Read 83 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 5917

  • After removing 18 mutations outside chr1-24: 5899

  • After removing 304 noncoding mutations: 5595

Mutation Filtering

  • Number of mutations before filtering: 5595

  • After removing 207 mutations outside gene set: 5388

  • After removing 4 mutations outside category set: 5384

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 150
Frame_Shift_Ins 77
In_Frame_Del 51
In_Frame_Ins 13
Missense_Mutation 3294
Nonsense_Mutation 185
Nonstop_Mutation 2
Silent 1497
Splice_Site 102
Translation_Start_Site 13
Total 5384
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 840 138713067 6.1e-06 6.1 3.9 2.1
*Np(A/C/T)->transit 901 1965699488 4.6e-07 0.46 0.29 2
*ApG->G 107 381313535 2.8e-07 0.28 0.18 2.1
transver 1456 2485726090 5.9e-07 0.59 0.37 5
indel+null 580 2485726090 2.3e-07 0.23 0.15 NaN
double_null 3 2485726090 1.2e-09 0.0012 0.00077 NaN
Total 3887 2485726090 1.6e-06 1.6 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).

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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->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: 1. 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 ZNF285 zinc finger protein 285 148155 4 3 2 1 0 0 2 2 0 0 0.000012 1.8e-06 0 1 0 0
2 NKX3-1 NK3 homeobox 1 43527 5 5 5 0 0 2 0 2 1 0 0.12 0.011 0.032 7e-05 0.000031 0.28
3 SLC2A6 solute carrier family 2 (facilitated glucose transporter), member 6 97622 2 2 1 0 0 0 0 2 0 0 0.012 0.000024 0.000024 1 0.00028 1
4 CLSTN1 calsyntenin 1 242387 3 3 1 0 0 0 0 3 0 0 0.000081 0.07 0.00013 0.33 0.00049 1
5 YBX1 Y box binding protein 1 68945 4 3 2 0 0 2 0 2 0 0 0.016 0.0069 0.0026 0.02 0.00056 1
6 CCNF cyclin F 199411 3 3 1 1 0 0 0 3 0 0 0.000086 0.029 0.00032 0.24 0.00078 1
7 SPOP speckle-type POZ protein 96345 4 4 3 0 0 0 1 3 0 0 0.008 0.3 0.0097 0.011 0.0011 1
8 NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4, 18kDa (NADH-coenzyme Q reductase) 45401 3 3 1 0 0 0 0 3 0 0 0.000077 0.34 0.00019 1 0.0018 1
9 AGT angiotensinogen (serpin peptidase inhibitor, clade A, member 8) 122342 3 3 1 0 0 0 0 3 0 0 0.000084 1 0.0021 0.13 0.0025 1
10 SETD5 SET domain containing 5 345156 4 1 4 1 0 3 0 1 0 0 0.00019 0.43 0.00037 0.79 0.0027 1
11 C1orf116 chromosome 1 open reading frame 116 150780 2 2 2 0 0 1 0 1 0 0 0.33 0.0021 0.002 0.23 0.0041 1
12 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 199245 3 3 3 0 0 1 0 2 0 0 0.0013 0.29 0.0022 0.29 0.0053 1
13 SLITRK4 SLIT and NTRK-like family, member 4 208728 3 3 2 0 0 0 0 0 3 0 0.051 1 0.13 0.0082 0.0082 1
14 C9orf150 chromosome 9 open reading frame 150 47265 3 3 1 0 0 0 0 0 3 0 0.000095 1 0.0012 1 0.0094 1
15 GPATCH4 G patch domain containing 4 97579 2 2 1 0 0 0 0 0 2 0 0.0097 0.29 0.071 0.018 0.0097 1
16 DUSP27 dual specificity phosphatase 27 (putative) 264959 3 3 1 1 0 0 0 3 0 0 0.000086 0.92 0.0029 0.53 0.012 1
17 TP53 tumor protein p53 105521 5 5 5 0 3 0 0 1 1 0 0.076 0.0015 0.0069 0.24 0.012 1
18 FIP1L1 FIP1 like 1 (S. cerevisiae) 152119 3 3 1 0 0 0 0 0 3 0 8e-05 1 0.0017 1 0.013 1
19 ZNF492 zinc finger protein 492 123622 4 4 3 0 0 3 0 1 0 0 0.00047 0.56 0.0018 1 0.013 1
20 MMP12 matrix metallopeptidase 12 (macrophage elastase) 112366 2 2 2 0 0 0 0 2 0 0 0.67 0.016 0.032 0.067 0.015 1
21 POM121 POM121 membrane glycoprotein (rat) 216520 3 3 1 0 0 0 0 3 0 0 9e-05 0.37 0.0023 1 0.016 1
22 CDKN1B cyclin-dependent kinase inhibitor 1B (p27, Kip1) 50142 2 2 2 0 0 0 0 0 2 0 0.54 0.5 0.6 0.004 0.017 1
23 CYP2D6 cytochrome P450, family 2, subfamily D, polypeptide 6 101528 4 4 2 2 0 1 0 3 0 0 0.0022 0.82 0.01 0.29 0.02 1
24 OR2AE1 olfactory receptor, family 2, subfamily AE, member 1 81008 2 2 2 0 1 0 0 0 1 0 0.18 0.0093 0.051 0.06 0.021 1
25 ATG10 ATG10 autophagy related 10 homolog (S. cerevisiae) 57021 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.023 0.023 1
26 C19orf53 chromosome 19 open reading frame 53 25569 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.024 0.024 1
27 CDC27 cell division cycle 27 homolog (S. cerevisiae) 210416 10 8 8 8 0 1 0 8 1 0 0.01 0.36 0.02 0.18 0.024 1
28 NKX2-4 NK2 homeobox 4 23952 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.025 0.025 1
29 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 1228308 8 7 7 0 0 1 0 2 4 1 0.063 0.73 0.11 0.035 0.025 1
30 LHX3 LIM homeobox 3 74497 2 2 2 0 0 1 0 1 0 0 0.53 0.044 0.058 0.073 0.027 1
31 ZMYM3 zinc finger, MYM-type 3 288038 5 4 5 0 0 0 0 2 3 0 0.55 0.18 0.4 0.011 0.028 1
32 OR4A16 olfactory receptor, family 4, subfamily A, member 16 82009 2 2 2 0 0 1 0 1 0 0 0.23 0.0042 0.0074 0.59 0.028 1
33 CPEB4 cytoplasmic polyadenylation element binding protein 4 185085 3 3 3 0 0 0 0 1 2 0 0.15 1 0.26 0.017 0.028 1
34 BANF2 barrier to autointegration factor 2 23572 2 2 2 0 1 0 0 1 0 0 0.98 0.94 1 0.0045 0.029 1
35 GNPNAT1 glucosamine-phosphate N-acetyltransferase 1 47717 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.029 0.029 1
ZNF285

Figure S1.  This figure depicts the distribution of mutations and mutation types across the ZNF285 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 TP53 tumor protein p53 5 356 5 29548 1608 1.7e-09 7.6e-06
2 CHEK2 CHK2 checkpoint homolog (S. pombe) 2 2 2 166 2 3.3e-08 0.000076
3 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 3 138 3 11454 1229 9.4e-07 0.0014
4 ACSM2B acyl-CoA synthetase medium-chain family member 2B 1 1 1 83 1 0.00013 0.098
5 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 1 1 1 83 1 0.00013 0.098
6 KCNH1 potassium voltage-gated channel, subfamily H (eag-related), member 1 1 1 1 83 1 0.00013 0.098
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 3 767 3 63661 15 0.00015 0.099
8 CHAT choline acetyltransferase 2 2 1 166 1 0.00026 0.13
9 CYP4F2 cytochrome P450, family 4, subfamily F, polypeptide 2 1 2 1 166 2 0.00026 0.13
10 ACVR2A activin A receptor, type IIA 1 3 1 249 1 0.00039 0.16

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: 1. 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 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 CDKN1B(2), PRB1(3), TP53(5) 1062488 10 10 10 0 3 1 0 3 3 0 0.12 6.4e-06 0.0039
2 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(2), AKT1(1), ATM(5), TP53(5) 2602579 13 12 13 0 4 6 0 2 1 0 0.015 0.00034 0.1
3 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(1), CCNE2(1), CDKN1B(2), PRB1(3) 1130432 7 7 7 0 0 2 0 3 2 0 0.25 0.00099 0.2
4 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(5), TP53(5) 2266716 11 10 11 0 3 5 0 2 1 0 0.034 0.0014 0.22
5 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), TP53(5) 879118 6 6 6 0 3 1 0 1 1 0 0.16 0.0022 0.23
6 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(5), CHEK2(2), TP53(5) 1994178 12 11 11 2 3 6 0 2 1 0 0.26 0.0022 0.23
7 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(5), TP53(5) 2195302 10 9 10 1 3 4 0 2 1 0 0.18 0.0032 0.28
8 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ATM(5), CCNA1(1), CDKN1B(2), DHFR(1), TP53(5) 3787641 14 12 14 0 3 5 0 2 4 0 0.032 0.0056 0.4
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(5), TLN1(1), TP53(5) 3433242 13 12 13 0 3 6 0 3 1 0 0.019 0.0058 0.4
10 SMALL_LIGAND_GPCRS C9orf47, CNR1, CNR2, DNMT1, EDG1, EDG2, EDG5, EDG6, MTNR1A, MTNR1B, PTAFR, PTGDR, PTGER1, PTGER2, PTGER4, PTGFR, PTGIR, TBXA2R 13 DNMT1(3), MTNR1A(1), PTGER2(1), TBXA2R(2) 1410721 7 7 7 1 3 2 0 1 1 0 0.19 0.011 0.65
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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle