Mutation Analysis (MutSig v2.0)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1QR4WBX
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1QR4WBX
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: KIRC-TP

  • Number of patients in set: 451

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:KIRC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 212

  • Mutations seen in COSMIC: 432

  • Significantly mutated genes in COSMIC territory: 58

  • Significantly mutated genesets: 11

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

Mutation Preprocessing

  • Read 451 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 46768

  • After removing 23 mutations outside chr1-24: 46745

  • After removing 7797 blacklisted mutations: 38948

  • After removing 2073 noncoding mutations: 36875

  • After collapsing adjacent/redundant mutations: 33030

Mutation Filtering

  • Number of mutations before filtering: 33030

  • After removing 1948 mutations outside gene set: 31082

  • After removing 124 mutations outside category set: 30958

  • After removing 7 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 28879

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 26
Frame_Shift_Del 1541
Frame_Shift_Ins 2938
In_Frame_Del 299
In_Frame_Ins 54
Missense_Mutation 16661
Nonsense_Mutation 1202
Nonstop_Mutation 44
Silent 6174
Splice_Site 1972
Start_Codon_Del 7
Start_Codon_Ins 2
Start_Codon_SNP 26
Stop_Codon_Del 2
Stop_Codon_Ins 2
Total 30958
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 1780 666857343 2.7e-06 2.7 1.4 2.2
*Cp(A/C/T)->T 3269 5856172488 5.6e-07 0.56 0.29 1.7
A->G 2701 6472983367 4.2e-07 0.42 0.22 2.3
transver 8935 12996013198 6.9e-07 0.69 0.36 5.1
indel+null 7981 12996013198 6.1e-07 0.61 0.32 NaN
double_null 114 12996013198 8.8e-09 0.0088 0.0046 NaN
Total 24780 12996013198 1.9e-06 1.9 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: KIRC-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: 212. 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 164008 237 225 140 2 8 11 24 60 133 1 <1.00e-15 <1.00e-15 0.0063 0.052 0.0061 <2.22e-16 <3.51e-13
2 DNMT1 DNA (cytosine-5-)-methyltransferase 1 2083111 21 21 6 0 0 1 3 1 16 0 1.61e-06 0.221 0 1 0 <1.00e-15 <3.51e-13
3 KIAA0408 KIAA0408 931597 18 18 2 0 0 0 0 0 18 0 4.90e-08 1.000 0 0.72 0 <1.00e-15 <3.51e-13
4 CCDC136 coiled-coil domain containing 136 1318310 16 16 3 0 1 0 0 0 15 0 6.09e-06 0.413 0 1 0 <1.00e-15 <3.51e-13
5 SMG7 Smg-7 homolog, nonsense mediated mRNA decay factor (C. elegans) 1558778 19 16 3 0 0 0 0 7 11 1 7.10e-06 0.0364 0 0.84 0 <1.00e-15 <3.51e-13
6 CCDC91 coiled-coil domain containing 91 614810 15 15 3 0 0 0 1 1 13 0 7.48e-09 0.0849 0 0.44 0 <1.00e-15 <3.51e-13
7 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 1928794 14 14 3 0 0 0 0 1 11 2 0.000387 0.533 0 0.97 0 <1.00e-15 <3.51e-13
8 DPP3 dipeptidyl-peptidase 3 945518 14 14 2 1 0 1 0 0 13 0 1.82e-05 0.919 0 1 0 <1.00e-15 <3.51e-13
9 TAS2R3 taste receptor, type 2, member 3 429539 14 13 5 0 0 0 1 13 0 0 8.78e-11 0.0596 0 0.96 0 <1.00e-15 <3.51e-13
10 ACSL3 acyl-CoA synthetase long-chain family member 3 997929 13 12 3 0 0 1 0 10 2 0 5.23e-06 0.0941 0 0.0096 0 <1.00e-15 <3.51e-13
11 EFNB3 ephrin-B3 348243 12 12 1 0 0 0 0 0 12 0 9.42e-08 1.000 0 0.56 0 <1.00e-15 <3.51e-13
12 NAPSA napsin A aspartic peptidase 515598 12 12 2 0 1 0 0 0 10 1 3.66e-07 0.637 0 0.99 0 <1.00e-15 <3.51e-13
13 OSBPL3 oxysterol binding protein-like 3 1231143 12 12 3 1 0 0 0 0 11 1 0.000342 0.450 2e-07 0.052 0 <1.00e-15 <3.51e-13
14 SPDYE3 speedy homolog E3 (Xenopus laevis) 358182 12 12 1 0 0 0 0 0 12 0 1.87e-07 1.000 0 0.17 0 <1.00e-15 <3.51e-13
15 C1S complement component 1, s subcomponent 949879 16 11 3 2 0 1 0 7 8 0 9.99e-05 0.386 0 0.00029 0 <1.00e-15 <3.51e-13
16 PKD2 polycystic kidney disease 2 (autosomal dominant) 1063183 12 11 3 0 0 1 0 11 0 0 5.37e-05 0.104 8e-07 0.00021 0 <1.00e-15 <3.51e-13
17 SLC26A4 solute carrier family 26, member 4 1015348 11 11 3 3 1 0 0 1 9 0 0.00358 0.553 2e-06 0.041 0 <1.00e-15 <3.51e-13
18 TSKS testis-specific serine kinase substrate 691209 11 11 2 0 0 1 0 0 10 0 5.28e-05 0.548 0 0.78 0 <1.00e-15 <3.51e-13
19 PHYH phytanoyl-CoA 2-hydroxylase 429107 10 10 2 0 0 0 0 1 9 0 2.67e-06 0.858 0 1 0 <1.00e-15 <3.51e-13
20 OR4A47 olfactory receptor, family 4, subfamily A, member 47 408792 10 9 2 0 0 0 0 10 0 0 8.49e-07 0.158 0 0.92 0 <1.00e-15 <3.51e-13
21 PREP prolyl endopeptidase 973443 9 9 2 0 0 0 0 0 9 0 0.00185 0.181 0 0.27 0 <1.00e-15 <3.51e-13
22 SDHAF2 succinate dehydrogenase complex assembly factor 2 232996 9 9 1 0 0 0 0 0 9 0 4.55e-07 0.236 0 0.0067 0 <1.00e-15 <3.51e-13
23 SLC4A5 solute carrier family 4, sodium bicarbonate cotransporter, member 5 1541933 9 9 2 0 0 0 0 0 9 0 0.0553 0.828 0 0.0012 0 <1.00e-15 <3.51e-13
24 ARPC2 actin related protein 2/3 complex, subunit 2, 34kDa 412986 8 8 2 0 0 0 0 0 8 0 5.70e-05 0.280 0 0.46 0 <1.00e-15 <3.51e-13
25 CHSY1 chondroitin sulfate synthase 1 938583 8 8 2 0 0 0 0 1 7 0 0.0109 0.851 0.000021 2e-07 0 <1.00e-15 <3.51e-13
26 PDE9A phosphodiesterase 9A 831641 8 8 1 0 0 0 0 0 8 0 0.0106 1.000 0 0.5 0 <1.00e-15 <3.51e-13
27 RRAS2 related RAS viral (r-ras) oncogene homolog 2 238375 8 8 1 0 0 0 0 0 8 0 5.14e-06 0.308 0 0.15 0 <1.00e-15 <3.51e-13
28 TRH thyrotropin-releasing hormone 243937 8 8 1 0 0 0 0 0 8 0 8.58e-06 1.000 0 0.44 0 <1.00e-15 <3.51e-13
29 NETO2 neuropilin (NRP) and tolloid (TLL)-like 2 707598 7 7 2 0 0 0 1 0 6 0 0.00347 0.245 0 0.34 0 <1.00e-15 <3.51e-13
30 PCGF1 polycomb group ring finger 1 340537 7 7 1 1 0 0 0 0 7 0 0.000259 1.000 0 0.96 0 <1.00e-15 <3.51e-13
31 RBPJL recombination signal binding protein for immunoglobulin kappa J region-like 565554 7 7 2 0 0 0 1 0 6 0 0.00130 0.803 2e-07 0.00016 0 <1.00e-15 <3.51e-13
32 SHANK1 SH3 and multiple ankyrin repeat domains 1 1347926 7 7 1 2 0 0 0 0 7 0 0.145 1.000 0 0.0012 0 <1.00e-15 <3.51e-13
33 ZMAT2 zinc finger, matrin type 2 279511 7 7 1 1 0 0 0 0 7 0 6.48e-05 0.768 2e-07 0.29 0 <1.00e-15 <3.51e-13
34 FAP fibroblast activation protein, alpha 1072599 6 6 1 0 0 0 0 0 6 0 0.0775 0.388 0 0.0027 0 <1.00e-15 <3.51e-13
35 FBXO24 F-box protein 24 780619 6 6 1 0 0 0 0 0 5 1 0.0184 1.000 0 0.13 0 <1.00e-15 <3.51e-13
VHL

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

DNMT1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the DNMT1 significant gene.

KIAA0408

Figure S3.  This figure depicts the distribution of mutations and mutation types across the KIAA0408 significant gene.

CCDC136

Figure S4.  This figure depicts the distribution of mutations and mutation types across the CCDC136 significant gene.

SMG7

Figure S5.  This figure depicts the distribution of mutations and mutation types across the SMG7 significant gene.

CCDC91

Figure S6.  This figure depicts the distribution of mutations and mutation types across the CCDC91 significant gene.

ARAP3

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ARAP3 significant gene.

DPP3

Figure S8.  This figure depicts the distribution of mutations and mutation types across the DPP3 significant gene.

TAS2R3

Figure S9.  This figure depicts the distribution of mutations and mutation types across the TAS2R3 significant gene.

ACSL3

Figure S10.  This figure depicts the distribution of mutations and mutation types across the ACSL3 significant gene.

EFNB3

Figure S11.  This figure depicts the distribution of mutations and mutation types across the EFNB3 significant gene.

NAPSA

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

OSBPL3

Figure S13.  This figure depicts the distribution of mutations and mutation types across the OSBPL3 significant gene.

SPDYE3

Figure S14.  This figure depicts the distribution of mutations and mutation types across the SPDYE3 significant gene.

C1S

Figure S15.  This figure depicts the distribution of mutations and mutation types across the C1S significant gene.

PKD2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the PKD2 significant gene.

SLC26A4

Figure S17.  This figure depicts the distribution of mutations and mutation types across the SLC26A4 significant gene.

TSKS

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

PHYH

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

OR4A47

Figure S20.  This figure depicts the distribution of mutations and mutation types across the OR4A47 significant gene.

ARPC2

Figure S21.  This figure depicts the distribution of mutations and mutation types across the ARPC2 significant gene.

CHSY1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the CHSY1 significant gene.

PDE9A

Figure S23.  This figure depicts the distribution of mutations and mutation types across the PDE9A significant gene.

TRH

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

NETO2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the NETO2 significant gene.

PCGF1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the PCGF1 significant gene.

RBPJL

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

SHANK1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the SHANK1 significant gene.

ZMAT2

Figure S29.  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: 58. 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 237 541 233 243991 5671 0 0
2 TP53 tumor protein p53 15 356 13 160556 863 0 0
3 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 21 767 21 345917 558 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 10 220 8 99220 2986 3e-11 3.4e-08
5 PTCH1 patched homolog 1 (Drosophila) 9 256 7 115456 10 4.1e-09 3.7e-06
6 STXBP3 syntaxin binding protein 3 3 1 2 451 2 3.7e-07 0.00028
7 KLK10 kallikrein-related peptidase 10 3 2 2 902 2 1.5e-06 0.00083
8 ZFYVE26 zinc finger, FYVE domain containing 26 7 2 2 902 2 1.5e-06 0.00083
9 NEK8 NIMA (never in mitosis gene a)- related kinase 8 2 3 2 1353 2 3.3e-06 0.0017
10 ARAP3 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 3 14 4 2 1804 4 5.9e-06 0.0027

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: 11. 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), ANAPC2(1), ANAPC4(5), ANAPC5(1), ANAPC7(2), BTRC(2), CDC16(3), CDC20(1), CDC23(2), CDC27(1), CUL1(3), CUL2(1), CUL3(6), FBXW11(1), FBXW7(2), FZR1(3), ITCH(1), SKP2(1), SMURF1(1), SMURF2(2), TCEB1(3), TCEB2(1), UBA1(1), UBE2D1(2), UBE2D2(1), UBE2D3(2), UBE2E2(1), VHL(237), WWP2(3) 26842932 294 255 193 13 10 17 29 83 153 2 9.2e-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), EIF2B5(2), EIF2S2(2), FLT1(7), FLT4(7), HIF1A(3), HRAS(1), KDR(5), NOS3(2), PIK3CA(10), PIK3R1(2), PLCG1(2), PRKCA(2), PTK2(1), PXN(1), SHC1(3), VHL(237) 22290046 294 252 193 16 12 21 29 80 151 1 5.4e-11 <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), COPS5(1), EP300(11), HIF1A(3), JUN(2), NOS3(2), VHL(237) 11058426 258 235 158 10 8 11 27 68 143 1 2.2e-11 4.22e-15 8.66e-13
4 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(3), AKT3(1), GRB2(2), ILK(4), MAPK3(1), PDK1(1), PIK3CA(10), PIK3CD(1), PTEN(21), PTK2B(3), RBL2(2), SHC1(3), SOS1(5) 13295530 58 51 53 3 4 13 4 14 22 1 0.00037 1.93e-07 2.97e-05
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 HDAC1(2), MAX(5), SP1(2), SP3(2), TP53(15), WT1(3) 4549903 29 25 27 3 1 3 1 10 12 2 0.14 0.000105 0.0110
6 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 4 CD28(1), CD4(10), HLA-DRA(1), HLA-DRB1(1) 1356343 13 13 7 1 1 1 0 1 9 1 0.7 0.000111 0.0110
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), ARF3(1), CDK2(2), CDK4(6), CDKN1A(1), CDKN2A(3), CFL1(1), E2F1(1), PRB1(6), TP53(15) 5336707 37 29 27 3 1 2 4 6 22 2 0.11 0.000127 0.0110
8 SA_TRKA_RECEPTOR The TrkA receptor binds nerve growth factor to activate MAP kinase pathways and promote cell growth. AKT1, AKT2, AKT3, ARHA, CDKN1A, ELK1, GRB2, HRAS, MAP2K1, MAP2K2, NGFB, NGFR, NTRK1, PIK3CA, PIK3CD, SHC1, SOS1 15 AKT1(1), AKT2(3), AKT3(1), CDKN1A(1), ELK1(1), GRB2(2), HRAS(1), NGFR(1), NTRK1(5), PIK3CA(10), PIK3CD(1), SHC1(3), SOS1(5) 10262631 35 34 31 1 2 10 3 16 4 0 0.00068 0.000142 0.0110
9 CDC42RACPATHWAY PI3 kinase stimulates cell migration by activating cdc42, which activates ARP2/3, which in turn promotes formation of new actin fibers. ACTR2, ACTR3, ARHA, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, CDC42, PAK1, PDGFRA, PIK3CA, PIK3R1, RAC1, WASL 14 ACTR2(1), ARPC2(8), CDC42(1), PAK1(2), PDGFRA(5), PIK3CA(10), PIK3R1(2), WASL(6) 8954221 35 35 26 2 0 7 2 13 13 0 0.012 0.000252 0.0173
10 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 17 ABCB1(4), AKT1(1), ATM(15), CDKN1A(1), CPB2(5), CSNK1A1(2), FHL2(1), HIF1A(3), IGFBP3(1), NFKBIB(1), TP53(15) 13158403 49 43 44 3 1 6 5 14 21 2 0.006 0.000387 0.0238

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 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(2), GOT1(3), GOT2(2), TAT(1), TYR(5) 3135385 13 13 13 1 1 0 3 4 5 0 0.27 0.0042 1
2 CHREBPPATHWAY Carbohydrate responsive element binding protein (chREBP) is a transcription factor inhibited by cAMP and activated by high carbohydrate levels. ADCY1, BG1, BUCS1, GNAS, GNB1, GNGT1, PPP2CA, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACB, PRKACG, PRKAG1, PRKAG2, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, WBSCR14 16 ADCY1(2), GNAS(5), GNB1(2), PPP2CA(1), PRKAB1(1), PRKACB(2), PRKACG(2), PRKAG1(4), PRKAG2(4), PRKAR1A(2), PRKAR2B(2) 9130690 27 27 27 1 3 3 2 12 7 0 0.015 0.0086 1
3 EEA1PATHWAY The FYVE-finger proteins EEA1 and HRS are localized to endosome membranes and regulate sorting and ubiquitination in the vesicle transport system. EEA1, EGF, EGFR, HGS, RAB5A, TF, TFRC 7 EEA1(6), EGF(4), EGFR(9), HGS(2), RAB5A(1), TFRC(2) 8444563 24 23 22 0 4 1 5 6 8 0 0.0056 0.011 1
4 SA_TRKA_RECEPTOR The TrkA receptor binds nerve growth factor to activate MAP kinase pathways and promote cell growth. AKT1, AKT2, AKT3, ARHA, CDKN1A, ELK1, GRB2, HRAS, MAP2K1, MAP2K2, NGFB, NGFR, NTRK1, PIK3CA, PIK3CD, SHC1, SOS1 14 AKT1(1), AKT2(3), AKT3(1), CDKN1A(1), ELK1(1), GRB2(2), HRAS(1), NGFR(1), NTRK1(5), PIK3CD(1), SHC1(3), SOS1(5) 8805146 25 24 24 1 2 6 2 12 3 0 0.01 0.015 1
5 CYSTEINE_METABOLISM CARS, CTH, GOT1, GOT2, LDHA, LDHB, LDHC, MPST 8 CARS(6), CTH(1), GOT1(3), GOT2(2), LDHB(1), LDHC(3), MPST(2) 4479216 18 18 16 2 1 0 2 5 10 0 0.39 0.017 1
6 HSA00750_VITAMIN_B6_METABOLISM Genes involved in vitamin B6 metabolism AOX1, PDXK, PDXP, PNPO, PSAT1 5 AOX1(7), PDXK(2), PDXP(1), PSAT1(1) 3151763 11 11 11 0 2 1 0 6 2 0 0.094 0.018 1
7 UREACYCLEPATHWAY Ammonia released from amino acid deamination is used to produce carbamoyl phosphate, which is used to convert ornithine to citrulline, from which urea is eventually formed. ARG1, ASL, ASS, CPS1, GLS, GLUD1, GOT1 6 ARG1(1), ASL(4), CPS1(4), GLS(3), GOT1(3) 5133932 15 15 15 1 0 3 1 6 5 0 0.18 0.041 1
8 HSA00720_REDUCTIVE_CARBOXYLATE_CYCLE Genes involved in reductive carboxylate cycle (CO2 fixation) ACLY, ACO1, ACO2, ACSS1, ACSS2, FH, IDH1, IDH2, LOC441996, MDH1, MDH2, SUCLA2 11 ACLY(6), ACO1(4), ACSS1(2), ACSS2(7), IDH1(2), IDH2(5), MDH1(1), SUCLA2(1) 8812773 28 23 24 2 1 5 3 8 10 1 0.048 0.058 1
9 GSPATHWAY Activated G-protein coupled receptors stimulate cAMP production and thus activate protein kinase A, involved in a number of signal transduction pathways. ADCY1, GNAS, GNB1, GNGT1, PRKACA, PRKAR1A 6 ADCY1(2), GNAS(5), GNB1(2), PRKACA(1), PRKAR1A(2) 4071859 12 12 12 1 1 1 0 9 1 0 0.29 0.064 1
10 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(3), CYP2E1(1), NR1I3(1), PTGS1(2), PTGS2(4) 3459591 11 11 11 2 1 1 1 4 3 1 0.53 0.065 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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