Mutation Analysis (MutSig v2.0)
Liver Hepatocellular Carcinoma
14 July 2016  |  awg_lihc__2016_07_14
Maintainer Information
Citation Information
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/C1445M01
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: LIHC

  • Number of patients in set: 372

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:LIHC.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 76

  • Mutations seen in COSMIC: 331

  • Significantly mutated genes in COSMIC territory: 14

  • Significantly mutated genesets: 45

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

Mutation Preprocessing
  • Read 373 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 53406

  • After removing 202 mutations outside chr1-24: 53204

  • After removing 178 blacklisted mutations: 53026

  • After removing 1113 noncoding mutations: 51913

  • After collapsing adjacent/redundant mutations: 51877

Mutation Filtering
  • Number of mutations before filtering: 51877

  • After removing 732 mutations outside patient set: 51145

  • After removing 2751 mutations outside gene set: 48394

  • After removing 190 mutations outside category set: 48204

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 44530

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 4
De_novo_Start_OutOfFrame 4
Frame_Shift_Del 3936
Frame_Shift_Ins 608
In_Frame_Del 313
In_Frame_Ins 96
Missense_Mutation 28575
Nonsense_Mutation 1628
Nonstop_Mutation 51
Silent 10707
Splice_Site 2198
Start_Codon_Del 9
Start_Codon_Ins 2
Start_Codon_SNP 56
Stop_Codon_Del 17
Total 48204
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 2557 691387354 3.7e-06 3.7 1.2 2.1
A->G 8533 5788472151 1.5e-06 1.5 0.47 2.4
*Cp(A/C/T)->T 4227 5433163909 7.8e-07 0.78 0.25 1.7
transver 13313 11913023414 1.1e-06 1.1 0.36 5
indel+null 8682 11913023414 7.3e-07 0.73 0.23 NaN
double_null 184 11913023414 1.5e-08 0.015 0.0049 NaN
Total 37496 11913023414 3.1e-06 3.1 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: LIHC.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: A->G

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

  • 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: 76. 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 AXIN1 axin 1 865916 25 24 24 1 0 1 0 3 21 0 8.6e-15 0.042 0.004 0.03 0.0016 5.55e-16 3.12e-12
2 TP53 tumor protein p53 478886 117 114 85 1 7 15 7 38 50 0 2.9e-15 9.3e-11 0 0.00028 0 <1.00e-15 <3.12e-12
3 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 891774 102 96 27 3 0 30 18 50 4 0 3.2e-15 1.3e-10 0 0.0012 0 <1.00e-15 <3.12e-12
4 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 679322 15 13 12 0 0 3 1 9 2 0 2.6e-08 0.043 0 0.00054 0 <1.00e-15 <3.12e-12
5 TCEAL6 transcription elongation factor A (SII)-like 6 206636 9 4 4 0 0 3 4 2 0 0 0.0015 0.048 0 0.048 0 <1.00e-15 <3.12e-12
6 TOE1 target of EGR1, member 1 (nuclear) 580488 2 2 2 0 0 0 1 0 1 0 0.44 0.46 1 0 0 <1.00e-15 <3.12e-12
7 RB1 retinoblastoma 1 (including osteosarcoma) 1020253 24 21 23 0 0 0 0 5 18 1 2.6e-14 0.044 0.05 0.68 0.087 7.76e-14 2.07e-10
8 ALB albumin 699495 46 43 40 2 0 3 2 7 28 6 5.8e-15 0.16 0.54 0.89 0.73 1.44e-13 3.37e-10
9 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 830020 19 19 19 1 0 0 0 5 13 1 7.9e-14 0.17 0.31 0.1 0.2 5.07e-13 1.05e-09
10 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 261198 11 11 11 0 0 1 0 5 5 0 4.8e-10 0.16 0.07 0.000011 0.000064 9.93e-13 1.86e-09
11 ARID1A AT rich interactive domain 1A (SWI-like) 2224562 33 32 31 2 0 2 1 5 24 1 4e-13 0.12 0.96 0.7 1 1.17e-11 1.99e-08
12 KEAP1 kelch-like ECH-associated protein 1 686886 19 17 19 0 3 4 0 7 5 0 1.1e-11 0.03 0.14 0.28 0.22 6.79e-11 1.06e-07
13 CDC27 cell division cycle 27 homolog (S. cerevisiae) 879104 15 15 8 1 1 1 1 2 10 0 9.4e-09 0.43 0.00063 0.91 0.0017 4.15e-10 5.97e-07
14 KRT10 keratin 10 (epidermolytic hyperkeratosis; keratosis palmaris et plantaris) 569280 11 9 4 1 7 0 0 3 1 0 4.4e-06 0.083 9.4e-06 0.09 0.000013 1.38e-09 1.85e-06
15 KIAA0040 KIAA0040 113088 7 5 4 0 0 0 3 3 1 0 9.4e-07 0.092 0.000029 0.92 0.0001 2.32e-09 2.89e-06
16 KCNN3 potassium intermediate/small conductance calcium-activated channel, subfamily N, member 3 824020 12 12 9 0 0 1 0 8 3 0 6.2e-06 0.17 0.000014 0.99 0.000046 6.55e-09 7.66e-06
17 APOB apolipoprotein B (including Ag(x) antigen) 5087988 44 39 42 4 1 8 3 10 22 0 1.2e-08 0.1 0.19 0.26 0.21 5.09e-08 5.60e-05
18 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 1045882 12 12 12 1 0 2 0 2 8 0 0.000012 0.46 0.00016 0.39 0.00034 8.04e-08 8.35e-05
19 KRT2 keratin 2 (epidermal ichthyosis bullosa of Siemens) 699702 12 12 11 2 1 0 0 1 10 0 4.3e-06 0.74 0.00051 0.36 0.0014 1.17e-07 0.000115
20 NRD1 nardilysin (N-arginine dibasic convertase) 1406365 14 13 7 1 0 3 0 11 0 0 0.00011 0.2 0.000014 1 0.000064 1.44e-07 0.000134
21 ARID2 AT rich interactive domain 2 (ARID, RFX-like) 2069493 23 22 23 2 0 1 1 5 14 2 1.4e-08 0.16 0.53 0.84 0.79 2.07e-07 0.000185
22 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 454915 11 11 11 1 0 0 1 2 8 0 2.8e-08 0.62 0.27 0.72 0.46 2.48e-07 0.000203
23 RPS6KA3 ribosomal protein S6 kinase, 90kDa, polypeptide 3 828758 15 14 14 0 0 2 1 5 7 0 1.8e-08 0.034 0.72 0.53 0.72 2.49e-07 0.000203
24 CRIP3 cysteine-rich protein 3 239794 8 6 5 0 1 0 3 4 0 0 0.000025 0.079 0.00033 0.18 0.00066 3.13e-07 0.000244
25 ACVR2A activin A receptor, type IIA 583880 13 11 13 1 0 2 0 2 8 1 3.5e-08 0.32 0.54 0.9 1 6.31e-07 0.000472
26 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1217832 13 13 8 1 1 3 3 6 0 0 0.000013 0.12 0.06 0.0099 0.0068 1.49e-06 0.00107
27 EEF1A1 eukaryotic translation elongation factor 1 alpha 1 421755 9 9 7 0 0 1 4 4 0 0 2.7e-07 0.066 0.41 0.15 0.39 1.79e-06 0.00124
28 ATXN1 ataxin 1 840496 11 10 8 0 1 0 0 5 5 0 0.0009 0.19 0.000047 1 0.00018 2.64e-06 0.00176
29 CNGA3 cyclic nucleotide gated channel alpha 3 781898 11 11 9 1 3 2 2 4 0 0 5.3e-06 0.12 0.16 0.0095 0.033 2.86e-06 0.00184
30 CEBPA CCAAT/enhancer binding protein (C/EBP), alpha 262947 5 4 4 1 0 1 1 3 0 0 0.0036 0.5 8.8e-06 0.96 0.000051 2.97e-06 0.00185
31 PRAMEF4 PRAME family member 4 370377 4 4 1 0 0 0 0 4 0 0 0.016 0.49 1.4e-06 0.32 0.000014 3.67e-06 0.00222
32 BRD7 bromodomain containing 7 733628 10 10 10 0 0 1 0 1 8 0 3.5e-06 0.32 0.032 0.93 0.072 4.11e-06 0.00240
33 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 174836 6 6 6 1 0 0 0 4 2 0 5.4e-06 0.56 0.59 0.013 0.055 4.76e-06 0.00270
34 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 473849 8 8 5 0 3 0 0 4 1 0 3e-05 0.18 0.006 0.85 0.012 5.64e-06 0.00311
35 ZNF714 zinc finger protein 714 550670 8 8 7 0 0 2 2 4 0 0 0.000078 0.12 0.0035 0.93 0.007 8.44e-06 0.00451
TP53

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

CTNNB1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

NFE2L2

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

TCEAL6

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TCEAL6 significant gene.

TOE1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the TOE1 significant gene.

RB1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ALB

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

BAP1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

CDKN2A

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

ARID1A

Figure S10.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

KEAP1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

CDC27

Figure S12.  This figure depicts the distribution of mutations and mutation types across the CDC27 significant gene.

KRT10

Figure S13.  This figure depicts the distribution of mutations and mutation types across the KRT10 significant gene.

KIAA0040

Figure S14.  This figure depicts the distribution of mutations and mutation types across the KIAA0040 significant gene.

KCNN3

Figure S15.  This figure depicts the distribution of mutations and mutation types across the KCNN3 significant gene.

APOB

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

IL6ST

Figure S17.  This figure depicts the distribution of mutations and mutation types across the IL6ST significant gene.

KRT2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the KRT2 significant gene.

NRD1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the NRD1 significant gene.

ARID2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ARID2 significant gene.

PTEN

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

RPS6KA3

Figure S22.  This figure depicts the distribution of mutations and mutation types across the RPS6KA3 significant gene.

CRIP3

Figure S23.  This figure depicts the distribution of mutations and mutation types across the CRIP3 significant gene.

ACVR2A

Figure S24.  This figure depicts the distribution of mutations and mutation types across the ACVR2A significant gene.

PIK3CA

Figure S25.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

EEF1A1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the EEF1A1 significant gene.

ATXN1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ATXN1 significant gene.

CNGA3

Figure S28.  This figure depicts the distribution of mutations and mutation types across the CNGA3 significant gene.

CEBPA

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

PRAMEF4

Figure S30.  This figure depicts the distribution of mutations and mutation types across the PRAMEF4 significant gene.

BRD7

Figure S31.  This figure depicts the distribution of mutations and mutation types across the BRD7 significant gene.

CDKN1A

Figure S32.  This figure depicts the distribution of mutations and mutation types across the CDKN1A significant gene.

IDH1

Figure S33.  This figure depicts the distribution of mutations and mutation types across the IDH1 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: 14. 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 102 138 91 51336 32233 0 0
2 TP53 tumor protein p53 117 356 106 132432 16489 0 0
3 RB1 retinoblastoma 1 (including osteosarcoma) 24 267 15 99324 28 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 13 220 9 81840 6579 9.9e-12 1.1e-08
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 11 332 10 123504 197 1.4e-11 1.3e-08
6 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 8 5 4 1860 5968 4.9e-11 3.7e-08
7 GNAS GNAS complex locus 10 7 4 2604 840 1.9e-10 1.2e-07
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 11 767 11 285324 195 3.4e-09 1.9e-06
9 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 6 52 5 19344 45832 6.6e-09 3.3e-06
10 RPTOR regulatory associated protein of MTOR, complex 1 4 4 2 1488 2 0.000011 0.005

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: 45. 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 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(2), CDKN2A(11), E2F1(3), MDM2(1), MYC(2), PIK3CA(13), PIK3R1(4), POLR1A(7), POLR1B(2), POLR1C(1), RB1(24), TBX2(2), TP53(117), TWIST1(2) 11429598 191 151 153 6 11 22 10 63 84 1 8.1e-12 <1.00e-15 <1.14e-13
2 WNTPATHWAY The Wnt glycoprotein binds to membrane-bound receptors such as Frizzled to activate a number of signaling pathways, including that of beta-catenin. APC, AXIN1, BTRC, CCND1, CREBBP, CSNK1A1, CSNK1D, CSNK2A1, CTBP1, CTNNB1, DVL1, FRAT1, FZD1, GSK3B, HDAC1, MADH4, MAP3K7, MAP3K7IP1, MYC, NLK, PPARD, PPP2CA, TCF1, TLE1, WIF1, WNT1 23 APC(12), AXIN1(25), BTRC(5), CCND1(1), CREBBP(6), CSNK1A1(2), CSNK2A1(2), CTBP1(1), CTNNB1(102), DVL1(3), FZD1(2), GSK3B(3), MAP3K7(3), MYC(2), NLK(2), PPP2CA(2), TLE1(6), WIF1(6), WNT1(2) 17083595 187 151 110 14 2 47 21 75 41 1 3e-09 <1.00e-15 <1.14e-13
3 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(2), APAF1(9), ATM(9), BAX(3), BCL2(1), CASP3(3), CASP6(2), CASP9(1), PRKCA(1), PTK2(9), PXN(2), STAT1(5), TLN1(10), TP53(117) 15287002 174 142 141 7 12 33 10 57 62 0 4.6e-11 <1.00e-15 <1.14e-13
4 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(6), DAXX(1), PAX3(4), PML(2), RARA(1), RB1(24), SIRT1(2), SP100(1), TNF(1), TNFRSF1A(1), TNFRSF1B(1), TP53(117) 10745023 161 135 128 11 7 21 8 51 73 1 8.3e-07 <1.00e-15 <1.14e-13
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), CCND1(1), CDKN1A(6), CDKN1B(5), CDKN2A(11), CFL1(1), E2F1(3), MDM2(1), TP53(117) 4705549 146 134 113 4 7 17 7 54 61 0 2.6e-10 <1.00e-15 <1.14e-13
6 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(2), ATM(9), BRCA1(9), CDKN1A(6), CHEK1(5), CHEK2(5), JUN(2), MAPK8(1), MDM2(1), NFKB1(3), NFKBIA(2), RAD50(6), RAD51(2), RBBP8(3), RELA(4), TP53(117), TP73(2) 16637482 179 147 147 14 11 25 13 62 67 1 1.4e-06 1.11e-15 1.14e-13
7 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(8), EIF2S2(1), NFKB1(3), NFKBIA(2), RELA(4), TP53(117) 5747826 135 122 103 8 7 20 10 44 54 0 7.6e-07 1.67e-15 1.18e-13
8 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), BCL2(1), EGFR(6), IGF1R(11), MYC(2), POLR2A(7), PPP2CA(2), PRKCA(1), RB1(24), TEP1(13), TERF1(5), TERT(2), TNKS(3), TP53(117), XRCC5(4) 15748769 200 159 166 15 9 31 10 64 85 1 1.4e-07 1.78e-15 1.18e-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(2), ATM(9), ATR(15), CCNA1(3), CCND1(1), CCNE1(1), CDK6(1), CDKN1A(6), CDKN1B(5), CDKN2A(11), CDKN2B(1), E2F1(3), GSK3B(3), RB1(24), SKP2(1), TFDP1(2), TGFB1(1), TGFB2(4), TGFB3(2), TP53(117) 17015204 212 161 178 12 9 25 9 80 87 2 4.2e-09 1.89e-15 1.18e-13
10 G2PATHWAY Activated Cdc2-cyclin B kinase regulates the G2/M transition; DNA damage stimulates the DNA-PK/ATM/ATR kinases, which inactivate Cdc2. ATM, ATR, BRCA1, CCNB1, CDC2, CDC25A, CDC25B, CDC25C, CDC34, CDKN1A, CDKN2D, CHEK1, CHEK2, EP300, GADD45A, MDM2, MYT1, PLK, PRKDC, RPS6KA1, TP53, WEE1, YWHAH, YWHAQ 22 ATM(9), ATR(15), BRCA1(9), CCNB1(2), CDC25B(2), CDC25C(3), CDC34(1), CDKN1A(6), CHEK1(5), CHEK2(5), EP300(11), MDM2(1), MYT1(2), PRKDC(6), RPS6KA1(1), TP53(117), WEE1(2) 24294020 197 162 164 16 11 25 15 73 71 2 2.9e-07 2.11e-15 1.18e-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 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(7) 395753 7 7 7 0 1 2 0 4 0 0 0.19 0.00058 0.36
2 MTA3PATHWAY The estrogen receptor regulates proliferation in mammary epithelia via MTA3 activation; loss of either protein is implicated in breast cancer. ALDOA, CTSD, ESR1, GAPD, GREB1, HSPB1, HSPB2, MTA1, MTA3, PDZK1, TUBA1, TUBA2, TUBA3, TUBA4, TUBA6, TUBA8 10 CTSD(1), ESR1(6), GREB1(12), HSPB1(1), HSPB2(1), MTA1(6), PDZK1(4), TUBA8(2) 6506963 33 32 31 2 3 13 6 7 4 0 0.00099 0.0023 0.71
3 CCR3PATHWAY CCR3 is a G-protein coupled receptor that recruits eosinophils to inflammation sites via chemokine ligands. ARHA, CCL11, CCR3, CFL1, GNAQ, GNAS, GNB1, GNGT1, HRAS, LIMK1, MAP2K1, MAPK1, MAPK3, MYL2, NOX1, PIK3C2G, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2, RAF1, ROCK2 21 CCL11(1), CCR3(3), CFL1(1), GNAQ(1), GNAS(10), GNB1(2), LIMK1(4), MAPK1(3), NOX1(3), PIK3C2G(7), PLCB1(8), PPP1R12B(4), PRKCA(1), PTK2(9), RAF1(2), ROCK2(3) 14537713 62 52 59 2 7 16 7 22 10 0 0.000023 0.0098 1
4 STILBENE_COUMARINE_AND_LIGNIN_BIOSYNTHESIS EPX, GBA3, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, TPO, TYR 10 EPX(3), LPO(4), MPO(5), PRDX1(1), PRDX2(2), PRDX6(1), TPO(13), TYR(5) 5528691 34 31 34 3 2 6 8 11 7 0 0.0076 0.0098 1
5 METHANE_METABOLISM ADH5, ATP6V0C, SHMT1, CAT, EPX, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, SHMT1, SHMT2, TPO 13 ADH5(2), ATP6V0C(2), CAT(1), EPX(3), LPO(4), MPO(5), PRDX1(1), PRDX2(2), PRDX6(1), SHMT1(2), SHMT2(4), TPO(13) 6710725 40 34 40 3 2 9 6 11 12 0 0.0059 0.017 1
6 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 7 CHRM1(3), GNAQ(1), GNB1(2), HTR2C(3), PLCB1(8), TUB(3) 3981712 20 18 20 1 1 3 2 6 8 0 0.064 0.027 1
7 HBXPATHWAY Hbx is a hepatitis B protein that activates a number of transcription factors, possibly by inducing calcium release from the mitochondrion to the cytoplasm. CREB1, GRB2, HBXIP, HRAS, PTK2B, SHC1, SOS1, SRC 8 CREB1(1), PTK2B(5), SHC1(3), SOS1(8), SRC(3) 4901533 20 20 20 1 2 6 4 4 3 1 0.018 0.03 1
8 PROTEASOME PSMA1, PSMA2, PSMA3, PSMA4, PSMA5, PSMA6, PSMA7, PSMB1, PSMB10, PSMB2, PSMB3, PSMB4, PSMB5, PSMB6, PSMB7, PSMB8, PSMB9 17 PSMA1(2), PSMA3(1), PSMA4(2), PSMA5(3), PSMA7(3), PSMB1(1), PSMB10(2), PSMB2(2), PSMB3(1), PSMB5(3), PSMB6(1), PSMB7(1), PSMB9(1) 4919552 23 21 23 1 0 7 4 8 4 0 0.014 0.037 1
9 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 IFNG(3), IL12A(6), IL12B(2), IL18(2) 1718224 13 12 13 2 0 1 3 7 2 0 0.34 0.038 1
10 HSA00750_VITAMIN_B6_METABOLISM Genes involved in vitamin B6 metabolism AOX1, PDXK, PDXP, PNPO, PSAT1 5 AOX1(11), PDXK(1), PNPO(1), PSAT1(2) 2699768 15 13 15 1 0 8 1 3 3 0 0.072 0.046 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)