Mutation Analysis (MutSig v2.0)
Pan-kidney cohort (KICH+KIRC+KIRP) (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C12B8XF5
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C12B8XF5
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: KIPAN-TP

  • Number of patients in set: 799

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:KIPAN-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 181

  • Mutations seen in COSMIC: 557

  • Significantly mutated genes in COSMIC territory: 73

  • Significantly mutated genesets: 12

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

Mutation Preprocessing

  • Read 799 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 72992

  • After removing 180 mutations outside chr1-24: 72812

  • After removing 8462 blacklisted mutations: 64350

  • After removing 2765 noncoding mutations: 61585

  • After collapsing adjacent/redundant mutations: 57664

Mutation Filtering

  • Number of mutations before filtering: 57664

  • After removing 3320 mutations outside gene set: 54344

  • After removing 275 mutations outside category set: 54069

  • After removing 21 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 50453

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 8
De_novo_Start_OutOfFrame 31
Frame_Shift_Del 3047
Frame_Shift_Ins 3607
In_Frame_Del 621
In_Frame_Ins 131
Missense_Mutation 30147
Nonsense_Mutation 1928
Nonstop_Mutation 74
Silent 11523
Splice_Site 2872
Start_Codon_Del 12
Start_Codon_Ins 2
Start_Codon_SNP 51
Stop_Codon_Del 10
Stop_Codon_Ins 5
Total 54069
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 3751 1275684727 2.9e-06 2.9 1.6 2.1
*Cp(A/C/T)->T 5489 10754905139 5.1e-07 0.51 0.29 1.7
A->G 5663 11723446897 4.8e-07 0.48 0.27 2.3
transver 15290 23754036763 6.4e-07 0.64 0.36 5.1
indel+null 12086 23754036763 5.1e-07 0.51 0.28 NaN
double_null 251 23754036763 1.1e-08 0.011 0.0059 NaN
Total 42530 23754036763 1.8e-06 1.8 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: KIPAN-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_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: 181. 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 VHL von Hippel-Lindau tumor suppressor 330270 241 229 142 2 8 11 25 62 134 1 2.78e-15 <1.00e-15 2.8e-06 0.013 0.000021 0.000 0.000
2 TP53 tumor protein p53 1009555 50 43 41 1 4 6 5 14 17 4 1.67e-15 2.53e-05 0.00048 0.00014 0.000073 0.000 0.000
3 MUC6 mucin 6, oligomeric mucus/gel-forming 4962444 44 28 42 19 4 16 5 17 2 0 1.000 0.589 0 1 0 <1.00e-15 <4.54e-13
4 MET met proto-oncogene (hepatocyte growth factor receptor) 3401454 28 27 18 3 1 7 7 10 3 0 5.73e-09 0.0324 1e-06 0.00019 0 <1.00e-15 <4.54e-13
5 DNMT1 DNA (cytosine-5-)-methyltransferase 1 3769516 23 23 8 0 0 1 4 1 17 0 0.000210 0.170 0 1 0 <1.00e-15 <4.54e-13
6 KIAA0408 KIAA0408 1649188 20 20 4 0 0 0 0 1 19 0 6.42e-07 0.861 0 0.83 0 <1.00e-15 <4.54e-13
7 CCDC136 coiled-coil domain containing 136 2357066 17 17 4 1 1 0 0 1 15 0 0.000357 0.709 0 1 0 <1.00e-15 <4.54e-13
8 SMG7 Smg-7 homolog, nonsense mediated mRNA decay factor (C. elegans) 2787596 20 17 4 2 0 1 0 7 11 1 0.00133 0.199 0 0.9 0 <1.00e-15 <4.54e-13
9 AR androgen receptor (dihydrotestosterone receptor; testicular feminization; spinal and bulbar muscular atrophy; Kennedy disease) 1671456 18 15 10 1 1 3 1 13 0 0 2.45e-07 0.0423 0 1 0 <1.00e-15 <4.54e-13
10 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 3512848 15 15 4 1 0 0 0 2 11 2 0.0140 0.722 0 0.95 0 <1.00e-15 <4.54e-13
11 CCDC91 coiled-coil domain containing 91 1067734 15 15 3 0 0 0 1 1 13 0 1.67e-06 0.0840 0 0.44 0 <1.00e-15 <4.54e-13
12 DPP3 dipeptidyl-peptidase 3 1718407 14 14 2 2 0 1 0 0 13 0 0.00379 0.974 0 1 0 <1.00e-15 <4.54e-13
13 PCF11 PCF11, cleavage and polyadenylation factor subunit, homolog (S. cerevisiae) 3563792 15 14 11 3 0 2 10 3 0 0 0.132 0.0645 0 0.98 0 <1.00e-15 <4.54e-13
14 ZNF814 zinc finger protein 814 1612679 19 14 9 0 0 9 1 6 3 0 4.16e-07 0.0108 0 0.75 0 <1.00e-15 <4.54e-13
15 NAPSA napsin A aspartic peptidase 940650 13 13 3 0 1 0 0 0 11 1 5.88e-06 0.639 0 1 0 <1.00e-15 <4.54e-13
16 TAS2R3 taste receptor, type 2, member 3 760105 14 13 5 0 0 0 1 13 0 0 3.17e-08 0.0596 0 0.96 0 <1.00e-15 <4.54e-13
17 ACSL3 acyl-CoA synthetase long-chain family member 3 1755361 13 12 3 0 0 1 0 10 2 0 0.000538 0.0939 0 0.0095 0 <1.00e-15 <4.54e-13
18 EFNB3 ephrin-B3 640934 12 12 1 0 0 0 0 0 12 0 7.98e-06 1.000 0 0.58 0 <1.00e-15 <4.54e-13
19 OSBPL3 oxysterol binding protein-like 3 2179992 12 12 3 2 0 0 0 0 11 1 0.0131 0.655 0 0.053 0 <1.00e-15 <4.54e-13
20 SPDYE3 speedy homolog E3 (Xenopus laevis) 596839 12 12 1 0 0 0 0 0 12 0 7.01e-06 1.000 0 0.17 0 <1.00e-15 <4.54e-13
21 TSKS testis-specific serine kinase substrate 1274882 12 12 3 0 0 1 0 1 10 0 0.000640 0.449 0 0.85 0 <1.00e-15 <4.54e-13
22 C1S complement component 1, s subcomponent 1683078 16 11 3 2 0 1 0 7 8 0 0.00406 0.386 0 0.00029 0 <1.00e-15 <4.54e-13
23 ABCC1 ATP-binding cassette, sub-family C (CFTR/MRP), member 1 3655790 11 10 8 2 2 2 1 1 5 0 0.252 0.385 0.015 2.8e-06 0 <1.00e-15 <4.54e-13
24 PHYH phytanoyl-CoA 2-hydroxylase 772598 10 10 2 0 0 0 0 1 9 0 0.000127 0.856 0 1 0 <1.00e-15 <4.54e-13
25 CHSY1 chondroitin sulfate synthase 1 1667499 9 9 3 1 0 1 0 1 7 0 0.0329 0.869 0.00037 6e-05 0 <1.00e-15 <4.54e-13
26 OR4A47 olfactory receptor, family 4, subfamily A, member 47 724643 10 9 2 0 0 0 0 10 0 0 4.08e-05 0.158 0 0.92 0 <1.00e-15 <4.54e-13
27 SDHAF2 succinate dehydrogenase complex assembly factor 2 412193 9 9 1 0 0 0 0 0 9 0 1.41e-05 0.236 0 0.0065 0 <1.00e-15 <4.54e-13
28 ARPC2 actin related protein 2/3 complex, subunit 2, 34kDa 734989 8 8 2 0 0 0 0 0 8 0 0.00126 0.280 0 0.44 0 <1.00e-15 <4.54e-13
29 RRAS2 related RAS viral (r-ras) oncogene homolog 2 436389 8 8 1 0 0 0 0 0 8 0 0.000118 0.300 0 0.14 0 <1.00e-15 <4.54e-13
30 TRH thyrotropin-releasing hormone 494445 8 8 1 1 0 0 0 0 8 0 0.000297 1.000 0 0.42 0 <1.00e-15 <4.54e-13
31 EXTL2 exostoses (multiple)-like 2 765127 7 7 2 0 0 0 0 1 6 0 0.00738 0.317 0 0.083 0 <1.00e-15 <4.54e-13
32 RBPJL recombination signal binding protein for immunoglobulin kappa J region-like 1074947 7 7 2 1 0 0 1 0 6 0 0.0200 0.928 4e-07 0.00013 0 <1.00e-15 <4.54e-13
33 ZMAT2 zinc finger, matrin type 2 496129 7 7 1 1 0 0 0 0 7 0 0.000937 0.767 2e-07 0.29 0 <1.00e-15 <4.54e-13
34 FAP fibroblast activation protein, alpha 1875668 6 6 1 1 0 0 0 0 6 0 0.308 0.649 0 0.0026 0 <1.00e-15 <4.54e-13
35 PRB1 proline-rich protein BstNI subfamily 1 700331 6 6 1 1 0 0 0 0 6 0 0.0149 1.000 0 0.99 0 <1.00e-15 <4.54e-13
VHL

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

TP53

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

MUC6

Figure S3.  This figure depicts the distribution of mutations and mutation types across the MUC6 significant gene.

MET

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

DNMT1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the DNMT1 significant gene.

KIAA0408

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KIAA0408 significant gene.

CCDC136

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CCDC136 significant gene.

SMG7

Figure S8.  This figure depicts the distribution of mutations and mutation types across the SMG7 significant gene.

AR

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

ARAP3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the ARAP3 significant gene.

CCDC91

Figure S11.  This figure depicts the distribution of mutations and mutation types across the CCDC91 significant gene.

DPP3

Figure S12.  This figure depicts the distribution of mutations and mutation types across the DPP3 significant gene.

PCF11

Figure S13.  This figure depicts the distribution of mutations and mutation types across the PCF11 significant gene.

ZNF814

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ZNF814 significant gene.

NAPSA

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

TAS2R3

Figure S16.  This figure depicts the distribution of mutations and mutation types across the TAS2R3 significant gene.

ACSL3

Figure S17.  This figure depicts the distribution of mutations and mutation types across the ACSL3 significant gene.

EFNB3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the EFNB3 significant gene.

OSBPL3

Figure S19.  This figure depicts the distribution of mutations and mutation types across the OSBPL3 significant gene.

SPDYE3

Figure S20.  This figure depicts the distribution of mutations and mutation types across the SPDYE3 significant gene.

TSKS

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

C1S

Figure S22.  This figure depicts the distribution of mutations and mutation types across the C1S significant gene.

ABCC1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the ABCC1 significant gene.

PHYH

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

CHSY1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the CHSY1 significant gene.

OR4A47

Figure S26.  This figure depicts the distribution of mutations and mutation types across the OR4A47 significant gene.

ARPC2

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ARPC2 significant gene.

TRH

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

RBPJL

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

ZMAT2

Figure S30.  This figure depicts the distribution of mutations and mutation types across the ZMAT2 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: 73. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 VHL von Hippel-Lindau tumor suppressor 241 541 237 432259 5752 0 0
2 MET met proto-oncogene (hepatocyte growth factor receptor) 28 34 10 27166 48 0 0
3 TP53 tumor protein p53 50 356 43 284444 3913 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 16 220 13 175780 4647 0 0
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 35 767 35 612833 669 0 0
6 SMARCB1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily b, member 1 10 129 8 103071 24 2.8e-11 2.1e-08
7 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 6 52 6 41548 73031 2.2e-10 1.4e-07
8 NF2 neurofibromin 2 (merlin) 16 550 10 439450 59 1.2e-08 7e-06
9 PTCH1 patched homolog 1 (Drosophila) 10 256 7 204544 10 1.3e-07 0.000062
10 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 24 30 4 23970 5 1.4e-07 0.000062

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: 12. 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 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS Genes involved in ubiquitin mediated proteolysis ANAPC1, ANAPC10, ANAPC11, ANAPC2, ANAPC4, ANAPC5, ANAPC7, BTRC, CDC16, CDC20, CDC23, CDC26, CDC27, CUL1, CUL2, CUL3, FBXW11, FBXW7, FZR1, ITCH, LOC728919, RBX1, SKP1, SKP2, SMURF1, SMURF2, TCEB1, TCEB2, UBA1, UBE2C, UBE2D1, UBE2D2, UBE2D3, UBE2D4, UBE2E1, UBE2E2, UBE2E3, VHL, WWP1, WWP2 39 ANAPC1(4), ANAPC10(1), ANAPC2(2), ANAPC4(5), ANAPC5(4), ANAPC7(3), BTRC(4), CDC16(4), CDC20(3), CDC23(3), CDC27(10), CUL1(5), CUL2(4), CUL3(17), FBXW11(1), FBXW7(5), FZR1(4), ITCH(1), RBX1(1), SKP2(2), SMURF1(1), SMURF2(4), TCEB1(4), TCEB2(1), UBA1(4), UBE2D1(2), UBE2D2(1), UBE2D3(2), UBE2E2(1), VHL(241), WWP1(7), WWP2(4) 48311765 355 309 250 22 15 20 45 104 167 4 4.8e-12 <1.00e-15 <3.08e-13
2 VEGFPATHWAY Vascular endothelial growth factor (VEGF) is upregulated by hypoxic conditions and promotes normal blood vessel formation and angiogenesis related to tumor growth or cardiac disease. ARNT, EIF1, EIF1A, EIF2B1, EIF2B2, EIF2B3, EIF2B4, EIF2B5, EIF2S1, EIF2S2, EIF2S3, ELAVL1, FLT1, FLT4, HIF1A, HRAS, KDR, NOS3, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, PTK2, PXN, SHC1, VEGF, VHL 25 ARNT(2), EIF1(2), EIF2B1(1), EIF2B2(1), EIF2B3(1), EIF2B4(1), EIF2B5(3), EIF2S2(2), EIF2S3(2), FLT1(8), FLT4(15), HIF1A(5), HRAS(1), KDR(6), NOS3(3), PIK3CA(16), PIK3R1(5), PLCG1(3), PRKCA(3), PTK2(3), PXN(3), SHC1(4), VHL(241) 40195015 331 284 225 25 21 26 34 87 161 2 7.4e-10 <1.00e-15 <3.08e-13
3 HIFPATHWAY Under normal conditions, hypoxia inducible factor HIF-1 is degraded; under hypoxic conditions, it activates transcription of genes controlled by hpoxic response elements (HREs). ARNT, ASPH, COPS5, CREB1, EDN1, EP300, EPO, HIF1A, HSPCA, JUN, LDHA, NOS3, P4HB, VEGF, VHL 13 ARNT(2), ASPH(1), COPS5(2), CREB1(1), EP300(16), HIF1A(5), JUN(2), NOS3(3), P4HB(2), VHL(241) 19872252 275 249 173 15 9 11 29 72 152 2 1.7e-09 1.67e-15 3.42e-13
4 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 HDAC1(2), MAX(5), MYC(1), SP1(2), SP3(3), TP53(50), WT1(3) 8263058 66 56 57 5 4 7 6 21 24 4 0.00055 4.31e-14 6.63e-12
5 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), ARF3(3), CDK2(2), CDK4(7), CDKN1A(3), CDKN1B(1), CDKN2A(4), CFL1(1), E2F1(1), E2F2(1), NXT1(1), PRB1(6), TP53(50) 9636795 81 65 64 7 4 6 9 20 37 5 0.0014 8.19e-14 1.01e-11
6 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 CHUK(2), DNAJC3(2), EIF2S2(2), NFKB1(1), NFKBIA(1), RELA(7), TP53(50) 11781948 65 54 53 3 4 10 5 17 24 5 0.000087 6.90e-11 7.08e-09
7 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(6), AKT1(1), ATM(23), BAX(1), CDKN1A(3), CPB2(6), CSNK1A1(2), FHL2(1), HIC1(1), HIF1A(5), HSPA1A(1), IGFBP3(1), NFKBIB(2), TP53(50) 24711057 103 87 90 7 7 12 11 30 37 6 0.000022 2.43e-08 2.14e-06
8 SA_PTEN_PATHWAY PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. AKT1, AKT2, AKT3, BPNT1, GRB2, ILK, MAPK1, MAPK3, PDK1, PIK3CA, PIK3CD, PIP3-E, PTEN, PTK2B, RBL2, SHC1, SOS1 16 AKT1(1), AKT2(4), AKT3(2), BPNT1(3), GRB2(3), ILK(4), MAPK1(1), MAPK3(3), PDK1(1), PIK3CA(16), PIK3CD(2), PTEN(35), PTK2B(4), RBL2(3), SHC1(4), SOS1(7) 23851936 93 81 85 5 7 18 9 22 33 4 6.9e-06 2.08e-07 1.60e-05
9 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(4), ATM(23), BAX(1), CCNE1(1), CDK2(2), CDK4(7), CDKN1A(3), E2F1(1), PCNA(3), RB1(4), TIMP3(4), TP53(50) 21482122 103 75 87 9 6 10 11 25 44 7 0.00071 7.01e-06 0.000479
10 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(23), CDC25A(2), CDC25B(1), CDC25C(4), CDK2(2), CDK4(7), CHEK1(1), MYT1(9), RB1(4), TP53(50), WEE1(2) 21017184 105 83 92 12 7 16 13 29 34 6 0.001 0.000297 0.0183

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 BETAOXIDATIONPATHWAY Beta-Oxidation of Fatty Acids ACADL, ACADM, ACADS, ACAT1, ECHS1, HADHA 6 ACADL(3), ACADM(3), ACADS(3), ACAT1(1), ECHS1(3), HADHA(4) 6407869 17 17 16 0 3 3 6 5 0 0 0.0031 0.014 1
2 LYSINE_BIOSYNTHESIS AADAT, AASDH, AASDHPPT, AASS, KARS 5 AADAT(2), AASDH(6), AASDHPPT(3), AASS(9), KARS(1) 8277290 21 21 21 1 0 5 5 7 4 0 0.026 0.026 1
3 HSA00300_LYSINE_BIOSYNTHESIS Genes involved in lysine biosynthesis AADAT, AASDHPPT, AASS, KARS 4 AADAT(2), AASDHPPT(3), AASS(9), KARS(1) 5630342 15 15 15 1 0 3 4 5 3 0 0.092 0.04 1
4 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(3) 605111 3 3 3 0 0 0 0 1 2 0 0.86 0.054 1
5 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(3), GOT1(3), GOT2(3), TAT(3), TYR(5) 5574296 17 17 17 2 3 1 3 4 6 0 0.26 0.056 1
6 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 RAN(3), RANBP1(2), RANBP2(26), RANGAP1(1) 9694037 32 29 26 3 2 7 4 9 10 0 0.026 0.065 1
7 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(3), GOT2(3), TAT(3) 3127345 9 9 9 1 2 1 2 0 4 0 0.34 0.077 1
8 BBCELLPATHWAY Fas ligand expression by T cells induces apoptosis in Fas-expressing, inactive B cells. CD28, CD4, HLA-DRA, HLA-DRB1, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 3 CD28(1), HLA-DRA(1), HLA-DRB1(6) 1493903 8 7 8 2 1 2 1 2 2 0 0.58 0.08 1
9 CAPROLACTAM_DEGRADATION AKR1A1, ECHS1, EHHADH, HADHA, SDS 5 AKR1A1(1), ECHS1(3), EHHADH(6), HADHA(4) 5764259 14 14 13 1 1 3 5 3 2 0 0.045 0.1 1
10 CYANOAMINO_ACID_METABOLISM ATP6V0C, SHMT1, GBA3, GGT1, SHMT1, SHMT2 5 GGT1(4), SHMT1(4), SHMT2(6) 4859216 14 14 14 2 2 1 3 4 4 0 0.23 0.1 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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