Mutation Analysis (MutSig v2.0)
Prostate Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1GB22H5
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1GB22H5
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 was used to generate the results found in this report.

  • Working with individual set: PRAD-TP

  • Number of patients in set: 251

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): 16

  • Mutations seen in COSMIC: 92

  • Significantly mutated genes in COSMIC territory: 7

  • Significantly mutated genesets: 26

  • Significantly mutated genesets: (excluding sig. mutated genes):0

Mutation Preprocessing

  • Read 251 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 17449

  • After removing 155 mutations outside chr1-24: 17294

  • After removing 1347 blacklisted mutations: 15947

  • After removing 277 noncoding mutations: 15670

Mutation Filtering

  • Number of mutations before filtering: 15670

  • After removing 636 mutations outside gene set: 15034

  • After removing 12 mutations outside category set: 15022

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 579
Frame_Shift_Ins 166
In_Frame_Del 165
In_Frame_Ins 17
Missense_Mutation 9127
Nonsense_Mutation 541
Nonstop_Mutation 7
Silent 3890
Splice_Site 530
Total 15022
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->(A/T) 3535 416115424 8.5e-06 8.5 5.7 2.1
*Cp(A/C/T)->(A/T) 3000 3377759523 8.9e-07 0.89 0.59 2.7
A->(C/G) 1501 3631611686 4.1e-07 0.41 0.28 3.4
flip 1091 7425486633 1.5e-07 0.15 0.098 5.3
indel+null 1995 7425486633 2.7e-07 0.27 0.18 NaN
double_null 10 7425486633 1.3e-09 0.0013 0.0009 NaN
Total 11132 7425486633 1.5e-06 1.5 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->(A/T)

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

  • n3 = number of nonsilent mutations of type: A->(C/G)

  • n4 = number of nonsilent mutations of type: flip

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

  • n6 = number of nonsilent mutations of type: double_null

  • p_classic = p-value for the observed amount of nonsilent mutations being elevated in this gene

  • p_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene

  • 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: 16. 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_classic p_ns_s p_clust p_cons p_joint p q
1 TP53 tumor protein p53 310636 20 20 17 1 8 2 5 0 5 0 6.1e-15 0.044 0.000093 0.00047 0.000044 0.000 0.000
2 FOXA1 forkhead box A1 269759 11 11 9 2 1 0 4 2 3 1 1.4e-12 0.71 0.000027 0.064 6.4e-06 3.33e-16 3.02e-12
3 SPOP speckle-type POZ protein 291266 24 24 10 0 0 2 16 5 1 0 5.1e-15 0.0043 0 0.61 0 <1.00e-15 <4.53e-12
4 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 601492 9 9 7 0 0 2 5 2 0 0 2.2e-08 0.068 1.4e-06 0.026 0 <1.00e-15 <4.53e-12
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 289090 13 13 13 0 0 2 1 0 10 0 7e-15 0.32 0.2 0.92 0.35 8.50e-14 3.08e-10
6 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 317204 4 4 2 0 3 0 0 1 0 0 0.000052 0.34 4e-05 0.58 0.000076 8.09e-08 0.000244
7 TMEM216 transmembrane protein 216 80630 4 4 1 0 0 0 0 0 4 0 1.5e-06 0.38 0.0051 1 0.014 3.75e-07 0.000970
8 ATM ataxia telangiectasia mutated 2339347 12 12 12 0 0 5 2 4 1 0 5.5e-06 0.1 0.3 0.0048 0.016 1.49e-06 0.00338
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 820334 9 8 9 1 2 2 3 2 0 0 5.4e-07 0.32 0.27 0.13 0.21 1.92e-06 0.00387
10 BRAF v-raf murine sarcoma viral oncogene homolog B1 559308 6 6 5 0 0 1 2 2 1 0 0.000012 0.29 0.06 0.017 0.013 2.72e-06 0.00492
11 LMOD2 leiomodin 2 (cardiac) 261451 3 3 1 1 0 0 0 0 3 0 0.00055 1 0.00017 0.3 0.0011 9.52e-06 0.0157
12 MED12 mediator complex subunit 12 1403740 5 5 4 0 0 3 0 2 0 0 0.015 0.25 0.000052 0.1 0.000054 1.19e-05 0.0180
13 NKX3-1 NK3 homeobox 1 138283 4 4 4 0 0 0 3 0 1 0 7.7e-06 0.55 0.23 0.029 0.17 1.88e-05 0.0263
14 LRRIQ3 leucine-rich repeats and IQ motif containing 3 452715 6 6 6 0 1 2 2 0 1 0 3.3e-06 0.24 0.9 0.76 1 4.52e-05 0.0585
15 RYBP RING1 and YY1 binding protein 164700 4 4 4 0 0 1 2 0 1 0 8.6e-06 0.37 0.46 0.23 0.45 5.21e-05 0.0608
16 STAT3 signal transducer and activator of transcription 3 (acute-phase response factor) 595046 6 6 6 1 0 2 2 1 1 0 0.000079 0.5 0.025 0.55 0.051 5.37e-05 0.0608
17 OR5AS1 olfactory receptor, family 5, subfamily AS, member 1 244425 4 4 4 0 2 1 0 1 0 0 3e-05 0.3 0.17 0.57 0.27 0.000104 0.105
18 ETV3 ets variant gene 3 110772 3 3 3 0 0 0 1 0 2 0 0.00016 0.73 0.02 0.49 0.05 0.000104 0.105
19 IL10RA interleukin 10 receptor, alpha 425072 3 3 3 0 1 0 1 0 1 0 0.0051 0.34 0.023 0.0026 0.0022 0.000140 0.134
20 ACBD7 acyl-Coenzyme A binding domain containing 7 70448 2 2 2 0 0 1 1 0 0 0 0.00016 0.61 NaN NaN NaN 0.000164 0.142
21 NTM neurotrimin 292609 4 4 4 0 1 1 0 0 2 0 0.00024 0.23 0.057 0.057 0.061 0.000181 0.142
22 OR4D5 olfactory receptor, family 4, subfamily D, member 5 241178 4 4 4 0 3 1 0 0 0 0 0.000016 0.22 0.71 0.59 1 0.000188 0.142
23 LCE1F late cornified envelope 1F 90360 3 2 3 0 1 1 0 1 0 0 0.00063 0.43 0.01 0.57 0.025 0.000191 0.142
24 KDM6A lysine (K)-specific demethylase 6A 947423 6 6 6 0 0 0 1 1 4 0 0.00032 0.49 0.2 0.02 0.052 0.000197 0.142
25 SLC10A2 solute carrier family 10 (sodium/bile acid cotransporter family), member 2 267554 5 5 5 0 1 3 0 0 1 0 0.000019 0.16 0.51 0.72 0.89 0.000200 0.142
26 ZNF208 zinc finger protein 208 890859 6 6 5 0 0 2 3 1 0 0 0.000039 0.25 0.27 0.93 0.44 0.000204 0.142
27 ITGA2B integrin, alpha 2b (platelet glycoprotein IIb of IIb/IIIa complex, antigen CD41) 694879 3 3 3 1 1 1 0 0 1 0 0.076 0.74 0.12 0.00014 0.00024 0.000218 0.146
28 CLEC1A C-type lectin domain family 1, member A 215787 4 4 4 0 1 0 1 2 0 0 3e-05 0.41 0.69 0.27 0.7 0.000248 0.161
29 FAM83B family with sequence similarity 83, member B 760674 5 5 5 1 0 3 0 2 0 0 0.00075 0.68 0.37 0.0052 0.03 0.000259 0.162
30 A1CF APOBEC1 complementation factor 488615 4 4 4 1 1 1 0 0 2 0 0.0006 0.74 0.033 0.39 0.046 0.000314 0.185
31 HIST1H2BG histone cluster 1, H2bg 96635 3 3 3 0 0 0 0 1 2 0 0.000043 0.82 0.5 0.9 0.64 0.000317 0.185
32 ANO4 anoctamin 4 717203 6 6 6 0 2 1 0 2 1 0 0.00022 0.21 0.47 0.036 0.14 0.000333 0.187
33 SMARCA1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 1 786561 5 5 5 0 0 0 0 2 3 0 0.00049 0.48 0.039 0.35 0.061 0.000340 0.187
34 NBPF10 neuroblastoma breakpoint family, member 10 778131 7 7 6 0 1 2 3 1 0 0 0.000031 0.16 0.99 0.83 1 0.000354 0.187
35 C1orf173 chromosome 1 open reading frame 173 1129964 7 7 7 1 2 2 0 1 2 0 0.00022 0.49 0.079 0.76 0.14 0.000365 0.187
TP53

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

FOXA1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

SPOP

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

CTNNB1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

PTEN

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

IDH1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

TMEM216

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TMEM216 significant gene.

ATM

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

PIK3CA

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

BRAF

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

LMOD2

Figure S11.  This figure depicts the distribution of mutations and mutation types across the LMOD2 significant gene.

MED12

Figure S12.  This figure depicts the distribution of mutations and mutation types across the MED12 significant gene.

NKX3-1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the NKX3-1 significant gene.

LRRIQ3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the LRRIQ3 significant gene.

RYBP

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

STAT3

Figure S16.  This figure depicts the distribution of mutations and mutation types across the STAT3 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 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 9 138 8 34638 3282 3e-13 8e-10
2 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 9 220 9 55220 1953 4.6e-13 8e-10
3 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 4 5 4 1255 5968 5.3e-13 8e-10
4 TP53 tumor protein p53 20 356 20 89356 6877 7.1e-13 8e-10
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 13 767 13 192517 188 1.3e-12 1.2e-09
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 6 89 4 22339 210 5.1e-08 0.000038
7 SMAD4 SMAD family member 4 4 159 4 39909 19 5.1e-07 0.00033
8 ATAD1 ATPase family, AAA domain containing 1 1 1 1 251 1 0.00038 0.13
9 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 2 1 1 251 1 0.00038 0.13
10 KCNH1 potassium voltage-gated channel, subfamily H (eag-related), member 1 1 1 1 251 1 0.00038 0.13

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: 26. 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 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(20) 2651631 23 22 20 1 8 3 5 1 6 0 0.012 6.5e-12 4e-09
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(4), AKT1(1), ATM(12), CDKN1A(2), CPB2(1), HIC1(1), HSPA1A(1), MDM2(1), NQO1(1), TP53(20) 7808812 44 38 41 2 15 9 8 4 8 0 0.00094 1.4e-11 4e-09
3 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 CDK4(1), CDKN1A(2), CDKN1B(4), CDKN2A(1), CFL1(1), MDM2(1), PRB1(1), TP53(20) 3197612 31 29 28 3 11 3 5 0 12 0 0.063 2e-11 4e-09
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), CHEK2(1), TP53(20) 5977834 33 30 30 2 8 8 7 4 6 0 0.022 4.1e-11 6.4e-09
5 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), CDK4(1), CDKN1A(2), MDM2(1), RB1(3), TP53(20) 6785968 40 34 37 3 11 9 8 4 7 1 0.0075 3.5e-10 4.4e-08
6 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), BAD(1), CASP7(1), PRKCA(1), PTK2(2), PXN(1), STAT1(1), TLN1(2), TP53(20) 10294761 43 40 40 1 10 13 8 5 7 0 0.00016 8.4e-10 8.7e-08
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(12), CDC25A(1), CDC25B(1), CDK4(1), MYT1(1), RB1(3), TP53(20) 6574080 39 35 36 4 11 8 8 5 6 1 0.026 9.9e-10 8.8e-08
8 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(3), CDKN2A(1), MDM2(1), PIK3CA(9), PIK3R1(2), POLR1A(4), POLR1B(1), POLR1C(2), RAC1(1), RB1(3), TP53(20) 7626178 47 37 44 3 14 9 11 4 8 1 0.00086 2.2e-09 1.7e-07
9 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 NFKB1(2), RELA(1), TP53(20) 3678521 23 22 20 1 8 5 5 0 5 0 0.016 4e-09 2.7e-07
10 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 16 AKT1(1), BCAR1(1), CDKN1B(4), MAPK1(1), PDPK1(1), PIK3CA(9), PIK3R1(2), PTEN(13), PTK2(2), SHC1(2), SOS1(1) 7236178 37 33 37 3 8 8 4 2 15 0 0.05 4.9e-08 3e-06

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 0. 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 LONGEVITYPATHWAY Caloric restriction in animals often increases lifespan, which may occur via decreased IGF receptor expression and consequent expression of stress-resistance proteins. AKT1, CAT, FOXO3A, GH1, GHR, HRAS, IGF1, IGF1R, PIK3CA, PIK3R1, SHC1, SOD1, SOD2, SOD3 12 AKT1(1), CAT(2), GHR(2), HRAS(2), IGF1R(2), PIK3R1(2), SHC1(2), SOD2(1), SOD3(1) 4184639 15 15 15 1 5 5 3 0 2 0 0.07 0.0044 1
2 TERCPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. NFYA, NFYB, NFYC, RB1, SP1, SP3 6 NFYA(1), NFYC(2), RB1(3), SP1(1), SP3(2) 2482692 9 8 9 1 1 3 1 1 2 1 0.22 0.0063 1
3 IL18PATHWAY Pro-inflammatory IL-18 is activated in macrophages by caspase-1 cleavage and, in conjunction with IL-12, stimulates Th1 cell differentiation. CASP1, IFNG, IL12A, IL12B, IL18, IL2 6 CASP1(4) 1113489 4 4 4 1 1 1 1 1 0 0 0.67 0.016 1
4 HSA00670_ONE_CARBON_POOL_BY_FOLATE Genes involved in one carbon pool by folate ALDH1L1, AMT, ATIC, DHFR, FTCD, GART, MTFMT, MTHFD1, MTHFD1L, MTHFD2, MTHFR, MTHFS, MTR, SHMT1, SHMT2, TYMS 16 ALDH1L1(3), AMT(1), ATIC(3), DHFR(1), FTCD(1), GART(1), MTHFD1(1), MTHFD1L(1), MTHFR(2), SHMT1(3), SHMT2(1) 7105204 18 17 18 2 4 6 0 2 6 0 0.098 0.022 1
5 ONE_CARBON_POOL_BY_FOLATE ALDH1L1, AMT, ATIC, ATP6V0C, SHMT1, DHFR, GART, MTHFD1, MTHFD1L, MTHFD2, MTHFR, MTHFS, MTR, SHMT1, SHMT2, TYMS 15 ALDH1L1(3), AMT(1), ATIC(3), DHFR(1), GART(1), MTHFD1(1), MTHFD1L(1), MTHFR(2), SHMT1(3), SHMT2(1) 6699692 17 16 17 2 4 6 0 2 5 0 0.12 0.03 1
6 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 11 AKT1(1), HRAS(2), KLK2(1), NTRK1(3), PIK3R1(2), PLCG1(1), PRKCA(1), SHC1(2), SOS1(1) 5013584 14 13 14 1 6 5 1 1 1 0 0.073 0.039 1
7 ERK5PATHWAY Signaling between a tissue and its innervating axon stimulates retrograde transport via Trk receptors, which activate Erk5, which induces transcription of anti-apoptotic factors. AKT1, CREB1, GRB2, HRAS, MAPK1, MAPK3, MAPK7, MEF2A, MEF2B, MEF2C, MEF2D, NTRK1, PIK3CA, PIK3R1, PLCG1, RPS6KA1, SHC1 16 AKT1(1), HRAS(2), MAPK1(1), MEF2C(2), MEF2D(2), NTRK1(3), PIK3R1(2), PLCG1(1), RPS6KA1(1), SHC1(2) 6302690 17 17 17 1 10 5 2 0 0 0 0.019 0.042 1
8 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(2) 271587 2 2 2 1 1 1 0 0 0 0 0.8 0.048 1
9 ACETAMINOPHENPATHWAY Acetaminophen selectively inhibits Cox-3, which is localized to the brain, and yields the toxic metabolite NAPQI when processed by CAR in the liver. CYP1A2, CYP2E1, CYP3A, NR1I3, PTGS1, PTGS2 5 CYP1A2(1), NR1I3(1), PTGS1(1), PTGS2(3) 1997020 6 6 6 1 2 3 0 1 0 0 0.37 0.055 1
10 IL10PATHWAY The cytokine IL-10 inhibits the inflammatory response by macrophages via activation of heme oxygenase 1. BLVRA, BLVRB, HMOX1, IL10, IL10RA, IL10RB, IL1A, IL6, JAK1, STAT1, STAT3, STAT5A, TNF 12 BLVRB(1), HMOX1(1), IL10RA(3), IL6(1), JAK1(2), STAT1(1), STAT5A(1), TNF(1) 3979294 11 10 11 1 4 3 3 0 1 0 0.12 0.06 1
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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