Mutation Analysis (MutSig v1.5)
Pancreatic Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1ZG6R4R
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1ZG6R4R
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 v1.5 was used to generate the results found in this report.

  • Working with individual set: PAAD-TP

  • Number of patients in set: 91

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): 383

  • Mutations seen in COSMIC: 233

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 39

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

Mutation Preprocessing

  • Read 91 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 46505

  • After removing 41 mutations outside chr1-24: 46464

  • After removing 9234 blacklisted mutations: 37230

  • After removing 2712 noncoding mutations: 34518

  • After collapsing adjacent/redundant mutations: 34144

Mutation Filtering

  • Number of mutations before filtering: 34144

  • After removing 1706 mutations outside gene set: 32438

  • After removing 186 mutations outside category set: 32252

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 2148
Frame_Shift_Ins 759
In_Frame_Del 2235
In_Frame_Ins 57
Missense_Mutation 17837
Nonsense_Mutation 1093
Nonstop_Mutation 22
Silent 6936
Splice_Site 1019
Translation_Start_Site 146
Total 32252
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 5900 159989074 0.000037 37 4 2.1
*Cp(A/C/T)->T 4352 1265837400 3.4e-06 3.4 0.38 1.7
C->(G/A) 4257 1425826474 3e-06 3 0.33 4.7
A->mut 3430 1349588894 2.5e-06 2.5 0.28 3.9
indel+null 7213 2775415368 2.6e-06 2.6 0.28 NaN
double_null 164 2775415368 5.9e-08 0.059 0.0065 NaN
Total 25316 2775415368 9.1e-06 9.1 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: PAAD-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: C->(G/A)

  • n4 = number of nonsilent mutations of type: A->mut

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

  • n6 = number of nonsilent mutations of type: double_null

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

  • 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: 383. 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_ns_s p q
1 TP53 tumor protein p53 113885 59 59 48 0 15 4 8 11 21 0 7.6e-07 <1.00e-15 <5.89e-12
2 PRDM8 PR domain containing 8 120852 23 23 2 0 0 0 1 0 22 0 0.79 <1.00e-15 <5.89e-12
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 63759 66 65 4 1 0 29 30 7 0 0 0.000015 1.67e-15 5.89e-12
4 OR10A7 olfactory receptor, family 10, subfamily A, member 7 86814 30 30 2 0 0 0 0 0 30 0 1 2.22e-15 5.89e-12
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 90711 22 21 14 0 0 3 1 1 17 0 0.022 2.66e-15 5.89e-12
6 MED9 mediator complex subunit 9 40576 17 17 1 1 0 0 0 0 17 0 1 3.11e-15 5.89e-12
7 TNFSF9 tumor necrosis factor (ligand) superfamily, member 9 57756 19 19 1 1 0 0 0 0 19 0 1 3.33e-15 5.89e-12
8 TMC4 transmembrane channel-like 4 180364 19 19 2 0 0 0 0 1 18 0 0.84 4.00e-15 5.89e-12
9 SRP14 signal recognition particle 14kDa (homologous Alu RNA binding protein) 39114 18 18 1 0 0 0 0 0 18 0 1 4.44e-15 5.89e-12
10 TMEM184A transmembrane protein 184A 112531 19 18 3 0 2 0 0 0 17 0 0.36 5.11e-15 5.89e-12
11 MST1 macrophage stimulating 1 (hepatocyte growth factor-like) 203121 21 15 9 1 2 7 1 4 6 1 0.016 5.66e-15 5.89e-12
12 OTUD4 OTU domain containing 4 285067 26 24 4 1 0 1 0 1 24 0 0.82 6.11e-15 5.89e-12
13 GAS2L2 growth arrest-specific 2 like 2 241174 23 23 4 0 0 0 0 3 20 0 0.46 6.44e-15 5.89e-12
14 EGR1 early growth response 1 148810 17 16 7 0 0 0 2 2 13 0 0.42 7.11e-15 5.89e-12
15 THBS4 thrombospondin 4 259717 21 21 3 0 0 1 0 0 20 0 0.61 7.33e-15 5.89e-12
16 CXXC4 CXXC finger 4 55055 13 13 2 0 0 1 0 0 12 0 0.66 7.33e-15 5.89e-12
17 MEPCE methylphosphate capping enzyme 157888 19 18 3 0 0 0 0 0 19 0 0.77 8.22e-15 5.89e-12
18 IFNGR2 interferon gamma receptor 2 (interferon gamma transducer 1) 87795 13 13 1 0 0 0 0 0 13 0 1 8.22e-15 5.89e-12
19 TMCO1 transmembrane and coiled-coil domains 1 54067 13 12 3 0 0 0 1 1 11 0 0.66 8.22e-15 5.89e-12
20 IPP intracisternal A particle-promoted polypeptide 162560 17 17 2 0 0 0 0 0 16 1 0.86 8.33e-15 5.89e-12
21 C19orf55 chromosome 19 open reading frame 55 93580 18 18 3 0 0 0 2 0 16 0 0.64 8.44e-15 5.89e-12
22 SMAD4 SMAD family member 4 154913 17 17 15 0 3 0 1 3 10 0 0.06 8.66e-15 5.89e-12
23 PHF13 PHD finger protein 13 83591 14 14 1 0 0 0 0 0 14 0 1 8.77e-15 5.89e-12
24 CIR1 corepressor interacting with RBPJ, 1 117733 16 16 1 0 0 0 0 0 16 0 1 8.88e-15 5.89e-12
25 FOXP2 forkhead box P2 212455 20 20 5 6 0 0 0 0 20 0 1 8.99e-15 5.89e-12
26 OR10A2 olfactory receptor, family 10, subfamily A, member 2 83356 15 15 1 0 0 0 0 0 15 0 1 9.44e-15 5.89e-12
27 CCDC28B coiled-coil domain containing 28B 56691 16 16 2 0 1 0 0 0 15 0 0.7 9.66e-15 5.89e-12
28 DDX55 DEAD (Asp-Glu-Ala-Asp) box polypeptide 55 163097 19 19 1 0 0 0 0 0 19 0 1 9.77e-15 5.89e-12
29 FGF10 fibroblast growth factor 10 58042 14 14 1 0 0 0 0 0 14 0 1 9.88e-15 5.89e-12
30 TMEM40 transmembrane protein 40 64554 16 16 2 0 0 0 0 0 16 0 1 1.02e-14 5.89e-12
31 MED15 mediator complex subunit 15 219970 28 24 5 0 0 0 1 1 26 0 0.68 1.03e-14 5.89e-12
32 POP5 processing of precursor 5, ribonuclease P/MRP subunit (S. cerevisiae) 46543 12 12 1 0 0 0 0 0 12 0 1 1.05e-14 5.89e-12
33 ST6GALNAC5 ST6 (alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6-sialyltransferase 5 87682 16 16 2 0 0 0 1 0 15 0 0.8 1.08e-14 5.89e-12
34 WASF3 WAS protein family, member 3 140226 17 17 2 1 0 0 0 0 17 0 1 1.12e-14 5.89e-12
35 AJAP1 adherens junctions associated protein 1 105310 15 14 6 0 2 0 3 0 10 0 0.16 1.13e-14 5.89e-12
TP53

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

PRDM8

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PRDM8 significant gene.

KRAS

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

OR10A7

Figure S4.  This figure depicts the distribution of mutations and mutation types across the OR10A7 significant gene.

CDKN2A

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

MED9

Figure S6.  This figure depicts the distribution of mutations and mutation types across the MED9 significant gene.

TNFSF9

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TNFSF9 significant gene.

TMC4

Figure S8.  This figure depicts the distribution of mutations and mutation types across the TMC4 significant gene.

SRP14

Figure S9.  This figure depicts the distribution of mutations and mutation types across the SRP14 significant gene.

TMEM184A

Figure S10.  This figure depicts the distribution of mutations and mutation types across the TMEM184A significant gene.

MST1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the MST1 significant gene.

OTUD4

Figure S12.  This figure depicts the distribution of mutations and mutation types across the OTUD4 significant gene.

GAS2L2

Figure S13.  This figure depicts the distribution of mutations and mutation types across the GAS2L2 significant gene.

EGR1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the EGR1 significant gene.

THBS4

Figure S15.  This figure depicts the distribution of mutations and mutation types across the THBS4 significant gene.

CXXC4

Figure S16.  This figure depicts the distribution of mutations and mutation types across the CXXC4 significant gene.

MEPCE

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

IFNGR2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the IFNGR2 significant gene.

TMCO1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the TMCO1 significant gene.

IPP

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

C19orf55

Figure S21.  This figure depicts the distribution of mutations and mutation types across the C19orf55 significant gene.

SMAD4

Figure S22.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

PHF13

Figure S23.  This figure depicts the distribution of mutations and mutation types across the PHF13 significant gene.

CIR1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the CIR1 significant gene.

FOXP2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the FOXP2 significant gene.

OR10A2

Figure S26.  This figure depicts the distribution of mutations and mutation types across the OR10A2 significant gene.

CCDC28B

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CCDC28B significant gene.

FGF10

Figure S28.  This figure depicts the distribution of mutations and mutation types across the FGF10 significant gene.

TMEM40

Figure S29.  This figure depicts the distribution of mutations and mutation types across the TMEM40 significant gene.

MED15

Figure S30.  This figure depicts the distribution of mutations and mutation types across the MED15 significant gene.

POP5

Figure S31.  This figure depicts the distribution of mutations and mutation types across the POP5 significant gene.

ST6GALNAC5

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ST6GALNAC5 significant gene.

WASF3

Figure S33.  This figure depicts the distribution of mutations and mutation types across the WASF3 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: 10. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TTK TTK protein kinase 9 2 8 182 24 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 66 52 66 4732 860617 0 0
3 GNAS GNAS complex locus 13 7 7 637 1285 0 0
4 TP53 tumor protein p53 59 356 55 32396 16811 0 0
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 22 332 22 30212 779 0 0
6 SMAD4 SMAD family member 4 17 159 10 14469 34 0 0
7 TNFRSF9 tumor necrosis factor receptor superfamily, member 9 7 1 4 91 4 1.6e-14 1.1e-11
8 ADAMTS18 ADAM metallopeptidase with thrombospondin type 1 motif, 18 10 8 3 728 6 4.8e-08 0.000027
9 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 5 12 2 1092 2 0.000049 0.025
10 NF2 neurofibromin 2 (merlin) 5 550 5 50050 5 0.00011 0.051

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: 39. 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 TELPATHWAY Telomerase is a ribonucleotide protein that adds telomeric repeats to the 3' ends of chromosomes. AKT1, BCL2, EGFR, G22P1, HSPCA, IGF1R, KRAS2, MYC, POLR2A, PPP2CA, PRKCA, RB1, TEP1, TERF1, TERT, TNKS, TP53, XRCC5 15 AKT1(2), EGFR(2), IGF1R(3), POLR2A(2), PPP2CA(1), RB1(3), TEP1(10), TERF1(6), TERT(6), TNKS(3), TP53(59), XRCC5(2) 3909142 99 65 80 8 24 10 12 18 34 1 0.000023 <1.00e-15 <2.05e-13
2 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(8), CDC25A(3), CDC25C(2), CDK4(2), MYT1(10), RB1(3), TP53(59), YWHAH(1) 2418316 88 64 74 5 19 8 14 17 30 0 0.000046 <1.00e-15 <2.05e-13
3 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(3), ATM(8), CCNE1(1), CDK4(2), MDM2(2), RB1(3), TP53(59) 2504477 78 63 67 4 18 7 14 15 24 0 0.000027 <1.00e-15 <2.05e-13
4 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(2), ATM(8), CSNK1D(1), FHL2(1), HIC1(2), HIF1A(1), MAPK8(2), MDM2(2), TP53(59) 2904975 82 64 71 5 16 6 14 19 27 0 0.000031 1.89e-15 2.30e-13
5 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(7), CDKN2A(22), MDM2(2), PIK3CA(4), PIK3R1(1), POLR1A(3), POLR1B(3), RB1(3), TBX2(1), TP53(59) 2829804 105 64 85 3 19 12 15 15 44 0 4.6e-09 2.55e-15 2.30e-13
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(8), ATR(9), CDC25C(2), TP53(59), YWHAH(1) 2182623 79 64 67 5 17 6 12 15 29 0 0.0011 2.55e-15 2.30e-13
7 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 ARF1(1), CDK4(2), CDKN2A(22), MDM2(2), NXT1(1), TP53(59) 1183860 87 61 68 1 18 7 12 12 38 0 5.3e-09 3.22e-15 2.30e-13
8 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(7), ATM(8), BRCA1(5), MAPK8(2), MDM2(2), MRE11A(3), NFKBIA(2), RBBP8(9), RELA(1), TP53(59) 4111596 98 69 78 2 19 9 16 15 39 0 2.3e-07 3.55e-15 2.30e-13
9 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 ABL1(7), ATM(8), ATR(9), CCNA1(3), CCNE1(1), CDC25A(3), CDK4(2), CDK6(2), CDKN2A(22), DHFR(1), GSK3B(1), RB1(3), SKP2(2), TGFB1(1), TGFB2(2), TP53(59) 4177722 126 67 103 11 21 14 20 19 52 0 0.000033 4.33e-15 2.30e-13
10 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(59) 972295 60 60 49 0 15 4 9 11 21 0 6.1e-08 4.55e-15 2.30e-13

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 HSA00785_LIPOIC_ACID_METABOLISM Genes involved in lipoic acid metabolism LIAS, LIPT1, LOC387787 2 LIAS(2) 207846 2 2 2 0 0 0 1 0 1 0 0.88 0.066 1
2 RANPATHWAY RanGEF (aka RCC1) and RanGFP regulate the GTP- or GDP-bound state of Ran, creating a Ran gradient across the nuclear membrane that is used in nuclear import. CHC1, RAN, RANBP1, RANBP2, RANGAP1 4 RANBP1(1), RANBP2(13), RANGAP1(2) 1152807 16 8 12 2 1 2 2 4 6 1 0.33 0.085 1
3 ST_G_ALPHA_S_PATHWAY The G-alpha-s protein activates adenylyl cyclases, which catalyze cAMP formation. ASAH1, BF, BFAR, BRAF, CAMP, CREB1, CREB3, CREB5, EPAC, GAS, GRF2, MAPK1, RAF1, SNX13, SRC, TERF2IP 12 ASAH1(1), BFAR(2), BRAF(3), CAMP(2), CREB1(2), SNX13(5), SRC(2), TERF2IP(1) 1553443 18 9 18 2 3 2 2 4 7 0 0.19 0.087 1
4 NUCLEOTIDE_GPCRS ADORA1, ADORA2A, ADORA2B, ADORA3, GPR23, LTB4R, P2RY1, P2RY2, P2RY5, P2RY6 7 ADORA1(1), ADORA2A(1), ADORA3(4), P2RY1(2), P2RY2(1), P2RY6(1) 749557 10 6 10 1 5 2 2 0 1 0 0.07 0.09 1
5 GLUCOCORTICOID_MINERALOCORTICOID_METABOLISM CPN2, CYP11A1, CYP11B2, CYP17A1, HSD11B1, HSD11B2, HSD3B1, HSD3B2 8 CPN2(2), CYP11A1(2), CYP11B2(4), CYP17A1(1), HSD11B1(1), HSD3B1(2), HSD3B2(1) 948112 13 9 10 3 2 2 3 2 4 0 0.51 0.1 1
6 P35ALZHEIMERSPATHWAY p35, a neuron-specific activator of cyclin-dependent kinase 5, is cleaved to p25 in Alzheimer's disease and promotoes hyperphosphorylated tau formation and apoptosis. APP, CAPN1, CAPNS1, CAPNS2, CDK5, CDK5R1, CSNK1A1, CSNK1D, GSK3B, MAPT, PPP2CA 10 CAPN1(1), CAPNS1(3), CAPNS2(1), CDK5(3), CDK5R1(1), CSNK1D(1), GSK3B(1), MAPT(2), PPP2CA(1) 1100149 14 8 12 1 4 3 0 2 5 0 0.091 0.15 1
7 RABPATHWAY Rab family GTPases regulate vesicle transport, endocytosis and exocytosis, and vesicle docking via interactions with the rabphilins. ACTA1, MEL, RAB11A, RAB1A, RAB2, RAB27A, RAB3A, RAB4A, RAB5A, RAB6A, RAB7, RAB9A 9 ACTA1(4), RAB11A(1), RAB27A(1), RAB3A(1), RAB4A(1), RAB6A(1), RAB9A(1) 584670 10 4 10 1 5 2 2 1 0 0 0.1 0.17 1
8 ACHPATHWAY Nicotinic acetylcholine receptors are ligand-gated ion channels that primarily mediate neuromuscular signaling and may inhibit neuronal apoptosis via the AKT pathway. AKT1, BAD, CHRNB1, CHRNG, FOXO3A, MUSK, PIK3CA, PIK3R1, PTK2, PTK2B, RAPSN, SRC, TERT, TNFSF6, YWHAH 13 AKT1(2), BAD(1), CHRNB1(2), CHRNG(1), MUSK(3), PIK3CA(4), PIK3R1(1), PTK2(4), SRC(2), TERT(6), YWHAH(1) 2309601 27 13 27 4 3 7 2 5 10 0 0.054 0.19 1
9 C21_STEROID_HORMONE_METABOLISM AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 10 CYP11A1(2), CYP11B2(4), CYP17A1(1), HSD11B1(1), HSD3B1(2), HSD3B2(1) 1180868 11 8 8 3 2 1 2 2 4 0 0.73 0.2 1
10 HSA00140_C21_STEROID_HORMONE_METABOLISM Genes involved in C21-steroid hormone metabolism AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 10 CYP11A1(2), CYP11B2(4), CYP17A1(1), HSD11B1(1), HSD3B1(2), HSD3B2(1) 1180868 11 8 8 3 2 1 2 2 4 0 0.73 0.2 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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