Mutation Analysis (MutSig v2.0)
Brain Lower Grade Glioma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1JH3K7H
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/C1JH3K7H
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: LGG-TP

  • Number of patients in set: 513

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:LGG-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 64

  • Mutations seen in COSMIC: 947

  • Significantly mutated genes in COSMIC territory: 17

  • Significantly mutated genesets: 103

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

Mutation Preprocessing

  • Read 513 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 45095

  • After removing 17 mutations outside chr1-24: 45078

  • After removing 2804 blacklisted mutations: 42274

  • After removing 2020 noncoding mutations: 40254

Mutation Filtering

  • Number of mutations before filtering: 40254

  • After removing 2013 mutations outside gene set: 38241

  • After removing 177 mutations outside category set: 38064

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 35872

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1167
Frame_Shift_Ins 366
In_Frame_Del 508
In_Frame_Ins 28
Missense_Mutation 23995
Nonsense_Mutation 1464
Nonstop_Mutation 22
Silent 8981
Splice_Site 1368
Translation_Start_Site 165
Total 38064
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 8103 834182675 9.7e-06 9.7 5 2.1
*Cp(A/C/T)->T 4940 6833838767 7.2e-07 0.72 0.37 1.7
A->G 3600 7376116495 4.9e-07 0.49 0.25 2.3
transver 7505 15044137937 5e-07 0.5 0.26 5
indel+null 4778 15044137937 3.2e-07 0.32 0.16 NaN
double_null 156 15044137937 1e-08 0.01 0.0054 NaN
Total 29082 15044137937 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: LGG-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: 64. 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 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 2021570 46 35 29 1 7 15 2 19 3 0 <1.00e-15 1.64e-06 0.0008 0.0033 0.000036 <0.000 <0.000
2 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 1212453 23 22 17 2 1 2 4 0 15 1 3.22e-15 0.354 9.6e-06 0.87 0.000037 0.000 0.000
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1683168 50 45 29 0 1 13 16 9 11 0 3.22e-15 5.12e-07 0.0089 0.0072 0.0017 2.22e-16 1.21e-12
4 ATRX alpha thalassemia/mental retardation syndrome X-linked (RAD54 homolog, S. cerevisiae) 3849661 201 191 174 7 2 4 17 9 158 11 2.78e-15 1.92e-05 0.005 0.26 0.0066 6.66e-16 1.21e-12
5 ZBTB20 zinc finger and BTB domain containing 20 1043909 22 21 19 3 4 1 6 4 7 0 2.09e-13 0.137 0.00066 0.025 0.00013 9.99e-16 1.21e-12
6 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 650235 398 398 2 0 378 0 0 20 0 0 1.22e-15 <1.00e-15 0 1 0 <1.00e-15 <1.21e-12
7 TP53 tumor protein p53 630319 312 248 141 2 107 30 47 63 58 7 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <1.21e-12
8 CIC capicua homolog (Drosophila) 2157807 118 108 83 1 41 5 6 14 46 6 1.33e-15 7.97e-12 0 0.032 0 <1.00e-15 <1.21e-12
9 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 3106806 52 42 40 3 4 8 2 11 24 3 1.22e-15 0.00226 0 0.068 0 <1.00e-15 <1.21e-12
10 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 597213 20 20 3 0 0 12 2 6 0 0 6.88e-15 0.000138 0 1 0 <1.00e-15 <1.21e-12
11 ATAD3C ATPase family, AAA domain containing 3C 522969 2 2 2 1 0 0 0 1 1 0 0.207 0.808 0.96 0 0 <1.00e-15 <1.21e-12
12 HEATR3 HEAT repeat containing 3 909034 2 2 2 0 1 0 0 0 1 0 0.244 0.340 0.43 0 0 <1.00e-15 <1.21e-12
13 NCK1 NCK adaptor protein 1 587634 2 2 2 0 0 0 0 0 2 0 0.162 0.592 1 0 0 <1.00e-15 <1.21e-12
14 PRCP prolylcarboxypeptidase (angiotensinase C) 811876 2 2 2 0 1 0 0 0 1 0 0.190 0.491 0.66 0 0 <1.00e-15 <1.21e-12
15 TEAD3 TEA domain family member 3 606431 2 2 2 1 0 1 0 0 1 0 0.239 0.670 0.052 0 0 <1.00e-15 <1.21e-12
16 FUBP1 far upstream element (FUSE) binding protein 1 1015005 49 48 44 1 0 0 1 1 45 2 <1.00e-15 0.0396 0.22 0.99 0.37 <1.35e-14 <1.53e-11
17 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 4433370 38 33 37 2 0 4 2 5 16 11 4.66e-15 0.0174 0.16 0.83 0.28 4.60e-14 4.90e-11
18 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 614037 25 25 23 0 1 4 4 7 9 0 6.66e-15 0.00421 0.67 0.62 1 2.24e-13 2.25e-10
19 TCF12 transcription factor 12 (HTF4, helix-loop-helix transcription factors 4) 1162876 16 15 15 0 0 0 0 0 16 0 7.89e-13 0.748 0.12 0.13 0.1 2.53e-12 2.41e-09
20 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 2304232 29 26 26 5 7 3 4 9 6 0 2.28e-09 0.147 0.00044 0.24 0.0015 9.36e-11 8.47e-08
21 STK19 serine/threonine kinase 19 556290 11 10 4 0 0 0 2 1 8 0 6.20e-09 0.417 0.00027 0.65 0.00062 1.05e-10 9.08e-08
22 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 350099 7 7 3 0 0 0 0 0 7 0 6.85e-08 0.838 0.00037 0.99 0.001 1.73e-09 1.42e-06
23 EIF1AX eukaryotic translation initiation factor 1A, X-linked 225875 4 4 3 1 1 1 1 1 0 0 2.54e-05 0.546 0.00031 0.038 0.000037 2.03e-08 1.60e-05
24 ARID1A AT rich interactive domain 1A (SWI-like) 2980984 25 20 25 2 1 2 0 5 16 1 3.47e-09 0.0870 0.62 0.77 1 7.11e-08 5.37e-05
25 CREBZF CREB/ATF bZIP transcription factor 534938 7 7 2 0 0 0 0 1 6 0 3.03e-05 0.799 0.0001 0.23 0.00019 1.12e-07 8.14e-05
26 ANKRD30A ankyrin repeat domain 30A 1913017 14 13 14 1 5 1 2 4 2 0 5.43e-08 0.0488 0.98 0.89 1 9.62e-07 0.000670
27 KRT15 keratin 15 719460 6 6 5 1 6 0 0 0 0 0 0.000211 0.325 0.00042 0.79 0.0009 3.12e-06 0.00209
28 ZNF709 zinc finger protein 709 994832 4 4 1 0 0 4 0 0 0 0 0.00559 0.312 8e-07 0.98 0.000036 3.29e-06 0.00209
29 SPANXD SPANX family, member D 152977 5 5 5 0 1 1 1 2 0 0 5.37e-07 0.197 0.21 0.22 0.38 3.35e-06 0.00209
30 MED9 mediator complex subunit 9 223034 3 3 1 1 0 0 0 0 3 0 0.000979 1.000 0.000094 0.28 0.00026 4.18e-06 0.00250
31 NIPBL Nipped-B homolog (Drosophila) 4360490 23 18 23 0 0 4 0 5 13 1 3.72e-07 0.0244 0.49 0.68 0.71 4.28e-06 0.00250
32 LHFPL1 lipoma HMGIC fusion partner-like 1 346093 4 4 3 1 3 0 0 1 0 0 0.000365 0.767 0.00057 0.14 0.0012 7.03e-06 0.00388
33 MYH8 myosin, heavy chain 8, skeletal muscle, perinatal 3057171 15 14 15 2 6 2 0 5 2 0 0.000243 0.103 0.19 0.00074 0.0019 7.07e-06 0.00388
34 RBPJ recombination signal binding protein for immunoglobulin kappa J region 789071 7 7 6 0 0 0 1 0 6 0 3.72e-05 0.471 0.0079 0.67 0.013 7.49e-06 0.00399
35 CUL4B cullin 4B 1358008 12 10 12 2 0 1 3 4 4 0 5.24e-06 0.378 0.067 0.36 0.13 1.00e-05 0.00519
EGFR

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

PIK3R1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

ATRX

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

ZBTB20

Figure S5.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

IDH1

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

TP53

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CIC

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

NOTCH1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

IDH2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the IDH2 significant gene.

ATAD3C

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ATAD3C significant gene.

HEATR3

Figure S12.  This figure depicts the distribution of mutations and mutation types across the HEATR3 significant gene.

NCK1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the NCK1 significant gene.

PRCP

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

TEAD3

Figure S15.  This figure depicts the distribution of mutations and mutation types across the TEAD3 significant gene.

FUBP1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

NF1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

PTEN

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

TCF12

Figure S19.  This figure depicts the distribution of mutations and mutation types across the TCF12 significant gene.

SMARCA4

Figure S20.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

STK19

Figure S21.  This figure depicts the distribution of mutations and mutation types across the STK19 significant gene.

EMG1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the EMG1 significant gene.

EIF1AX

Figure S23.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

ARID1A

Figure S24.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

CREBZF

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

ANKRD30A

Figure S26.  This figure depicts the distribution of mutations and mutation types across the ANKRD30A significant gene.

KRT15

Figure S27.  This figure depicts the distribution of mutations and mutation types across the KRT15 significant gene.

ZNF709

Figure S28.  This figure depicts the distribution of mutations and mutation types across the ZNF709 significant gene.

MED9

Figure S29.  This figure depicts the distribution of mutations and mutation types across the MED9 significant gene.

NIPBL

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

LHFPL1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the LHFPL1 significant gene.

MYH8

Figure S32.  This figure depicts the distribution of mutations and mutation types across the MYH8 significant gene.

RBPJ

Figure S33.  This figure depicts the distribution of mutations and mutation types across the RBPJ 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: 17. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 312 356 301 182628 103672 0 0
2 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 50 220 43 112860 10264 0 0
3 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 46 293 31 150309 437 0 0
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 25 767 24 393471 693 0 0
5 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 398 5 398 2565 593816 2.5e-14 1.9e-11
6 FUBP1 far upstream element (FUSE) binding protein 1 49 4 5 2052 2 2.8e-14 1.9e-11
7 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 20 6 20 3078 1660 3e-14 1.9e-11
8 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 29 30 7 15390 4 1.5e-13 8e-11
9 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 23 33 13 16929 22 1.6e-13 8e-11
10 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 52 292 12 149796 26 1.1e-12 4.9e-10

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: 103. 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 GLUTATHIONE_METABOLISM ANPEP, G6PD, GCLC, GCLM, GGT1, GPX1, GPX2, GPX3, GPX4, GPX5, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, PGD 30 ANPEP(3), G6PD(2), GCLC(1), GGT1(2), GPX2(2), GPX4(1), GSS(1), GSTA1(1), GSTA2(1), GSTA3(1), GSTA4(1), GSTM4(1), GSTM5(1), GSTT1(1), GSTZ1(3), IDH1(398), IDH2(20), PGD(1) 13770087 441 422 28 13 385 16 7 29 4 0 <1.00e-15 <1.00e-15 <2.93e-14
2 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(3), ACO1(5), ACO2(4), ACSS1(1), ACSS2(4), FH(1), IDH1(398), IDH2(20) 10145121 436 421 23 1 384 16 4 29 3 0 <1.00e-15 <1.00e-15 <2.93e-14
3 HSA00020_CITRATE_CYCLE Genes involved in citrate cycle (TCA cycle) ACLY, ACO1, ACO2, CLYBL, CS, DLD, DLST, FH, IDH1, IDH2, IDH3A, IDH3B, IDH3G, LOC283398, LOC441996, MDH1, MDH2, OGDH, OGDHL, PC, PCK1, PCK2, SDHA, SDHB, SDHC, SDHD, SUCLA2, SUCLG1, SUCLG2 27 ACLY(3), ACO1(5), ACO2(4), CLYBL(1), DLD(1), FH(1), IDH1(398), IDH2(20), IDH3B(1), OGDH(1), OGDHL(4), PC(2), PCK1(3), SDHA(4), SDHC(2), SUCLG2(1) 22764387 451 420 37 9 388 18 9 32 4 0 <1.00e-15 <1.00e-15 <2.93e-14
4 CITRATE_CYCLE_TCA_CYCLE ACO1, ACO2, CS, DLD, DLST, DLSTP, FH, IDH1, IDH2, IDH3A, IDH3B, IDH3G, MDH1, MDH2, PC, PCK1, SDHA, SDHA, SDHAL2, SDHB, SUCLA2, SUCLG1, SUCLG2 20 ACO1(5), ACO2(4), DLD(1), FH(1), IDH1(398), IDH2(20), IDH3B(1), PC(2), PCK1(3), SDHA(4), SUCLG2(1) 15706931 440 419 26 2 384 17 7 29 3 0 <1.00e-15 <1.00e-15 <2.93e-14
5 REDUCTIVE_CARBOXYLATE_CYCLE_CO2_FIXATION ACO1, ACO2, FH, IDH1, IDH2, MDH1, MDH2, SDHB, SUCLA2 9 ACO1(5), ACO2(4), FH(1), IDH1(398), IDH2(20) 6791681 428 419 15 0 381 14 4 28 1 0 <1.00e-15 <1.00e-15 <2.93e-14
6 HSA04210_APOPTOSIS Genes involved in apoptosis AIFM1, AKT1, AKT2, AKT3, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, BIRC2, BIRC3, BIRC4, CAPN1, CAPN2, CASP10, CASP3, CASP6, CASP7, CASP8, CASP9, CFLAR, CHP, CHUK, CSF2RB, CYCS, DFFA, DFFB, ENDOG, FADD, FAS, FASLG, IKBKB, IKBKG, IL1A, IL1B, IL1R1, IL1RAP, IL3, IL3RA, IRAK1, IRAK2, IRAK3, IRAK4, MAP3K14, MYD88, NFKB1, NFKB2, NFKBIA, NGFB, NTRK1, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRKACA, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, RELA, RIPK1, TNF, TNFRSF10A, TNFRSF10B, TNFRSF10C, TNFRSF10D, TNFRSF1A, TNFSF10, TP53, TRADD, TRAF2 80 AIFM1(4), AKT1(1), APAF1(3), ATM(8), BAX(1), BCL2(1), BIRC2(2), CASP10(1), CASP8(2), CFLAR(1), CSF2RB(2), CYCS(2), DFFA(2), FAS(1), FASLG(1), IKBKB(1), IL1B(2), IL1R1(2), IL1RAP(1), IL3(1), IL3RA(2), IRAK1(1), IRAK2(2), IRAK3(6), IRAK4(2), NFKB1(1), NFKB2(1), NFKBIA(2), NTRK1(3), PIK3CA(50), PIK3CB(3), PIK3CD(3), PIK3CG(5), PIK3R1(23), PIK3R2(1), PIK3R3(1), PIK3R5(1), PPP3CA(1), PPP3CB(1), PPP3CC(1), PPP3R2(1), PRKACG(1), PRKAR1A(2), RELA(1), RIPK1(3), TNF(1), TNFRSF10C(1), TNFRSF10D(1), TP53(312), TRADD(1), TRAF2(2) 63687268 475 316 277 38 128 59 77 102 101 8 <1.00e-15 <1.00e-15 <2.93e-14
7 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(1), BCL2(1), EGFR(46), IGF1R(7), POLR2A(7), PPP2CA(4), PRKCA(5), RB1(6), TEP1(8), TERF1(1), TERT(2), TNKS(1), TP53(312), XRCC5(3) 21504324 404 294 216 10 130 47 57 94 68 8 <1.00e-15 <1.00e-15 <2.93e-14
8 HSA04115_P53_SIGNALING_PATHWAY Genes involved in p53 signaling pathway APAF1, ATM, ATR, BAI1, BAX, BBC3, BID, CASP3, CASP8, CASP9, CCNB1, CCNB2, CCNB3, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNG1, CCNG2, CD82, CDC2, CDK2, CDK4, CDK6, CDKN1A, CDKN2A, CHEK1, CHEK2, CYCS, DDB2, EI24, FAS, GADD45A, GADD45B, GADD45G, GTSE1, IGF1, IGFBP3, LRDD, MDM2, MDM4, P53AIP1, PERP, PMAIP1, PPM1D, PTEN, RCHY1, RFWD2, RPRM, RRM2, RRM2B, SCOTIN, SERPINB5, SERPINE1, SESN1, SESN2, SESN3, SFN, SIAH1, STEAP3, THBS1, TNFRSF10B, TP53, TP53I3, TP73, TSC2, ZMAT3 64 APAF1(3), ATM(8), ATR(6), BAI1(4), BAX(1), CASP8(2), CCNB1(2), CCNB2(1), CCNB3(4), CCND1(4), CCNE1(1), CCNE2(1), CCNG2(2), CDK2(1), CDK4(1), CDKN1A(1), CDKN2A(4), CHEK1(3), CHEK2(3), CYCS(2), DDB2(2), EI24(4), FAS(1), GTSE1(4), IGF1(1), MDM2(3), MDM4(1), PPM1D(3), PTEN(25), RCHY1(1), RFWD2(4), RRM2B(1), SERPINB5(2), SERPINE1(2), SESN1(1), SESN2(1), SESN3(1), SFN(2), SIAH1(3), STEAP3(2), THBS1(4), TP53(312), TP53I3(1), TSC2(3), ZMAT3(3) 49759824 441 293 267 30 128 48 72 98 88 7 <1.00e-15 <1.00e-15 <2.93e-14
9 G1_TO_S_CELL_CYCLE_REACTOME ATM, CCNA1, CCNB1, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNG2, CCNH, CDC25A, CDC45L, CDK2, CDK4, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CREB3, CREB3L1, CREB3L3, CREB3L4, CREBL1, CREBL1, TNXB, E2F1, E2F2, E2F3, E2F4, E2F5, E2F6, FLJ14001, GADD45A, GBA2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, MNAT1, MYC, MYT1, NACA, NACA, FKSG17, ORC1L, ORC2L, ORC3L, ORC4L, ORC5L, ORC6L, PCNA, POLA2, POLE, POLE2, PRIM1, PRIM2A, RB1, RBL1, RPA1, RPA2, RPA3, TFDP1, TFDP2, TP53, WEE1 64 ATM(8), CCNA1(2), CCNB1(2), CCND1(4), CCNE1(1), CCNE2(1), CCNG2(2), CCNH(2), CDC25A(1), CDK2(1), CDK4(1), CDKN1A(1), CDKN1B(3), CDKN2A(4), CDKN2C(3), CREB3(3), CREB3L1(1), CREB3L3(1), E2F1(1), E2F2(1), E2F3(1), E2F5(1), GBA2(1), MCM3(1), MCM4(3), MCM5(1), MCM6(3), MCM7(4), MDM2(3), MYT1(7), NACA(5), POLA2(1), POLE(8), PRIM1(1), RB1(6), RBL1(4), RPA1(3), TNXB(11), TP53(312), WEE1(1) 58855578 420 277 249 35 126 39 62 90 96 7 <1.00e-15 <1.00e-15 <2.93e-14
10 APOPTOSIS APAF1, BAD, BAK1, BCL2L7P1, BAX, BCL2, BCL2L1, BCL2L11, BID, BIRC2, BIRC3, BIRC4, BIRC5, BNIP3L, CASP1, CASP10, CASP1, COPl, CASP2, CASP3, CASP4, CASP6, CASP7, CASP8, CASP9, CHUK, CYCS, DFFA, DFFB, FADD, FAS, FASLG, GZMB, HELLS, HRK, IKBKB, IKBKG, IRF1, IRF2, IRF3, IRF4, IRF5, IRF6, IRF7, JUN, LTA, MAP2K4, MAP3K1, MAPK10, MDM2, MYC, NFKB1, NFKBIA, NFKBIB, NFKBIE, PRF1, RELA, RIPK1, TNF, TNFRSF10B, TNFRSF1A, TNFRSF1B, TNFRSF21, TNFRSF25, TNFRSF25, PLEKHG5, TNFSF10, TP53, TP73, TRADD, TRAF1, TRAF2, TRAF3 66 APAF1(3), BAK1(2), BAX(1), BCL2(1), BCL2L11(1), BIRC2(2), CASP1(4), CASP10(1), CASP2(1), CASP4(1), CASP8(2), CYCS(2), DFFA(2), FAS(1), FASLG(1), GZMB(1), HELLS(3), IKBKB(1), IRF1(4), IRF2(1), IRF3(3), IRF4(2), IRF5(1), IRF6(2), IRF7(3), MAP3K1(3), MAPK10(1), MDM2(3), NFKB1(1), NFKBIA(2), NFKBIE(1), PLEKHG5(3), PRF1(3), RELA(1), RIPK1(3), TNF(1), TNFRSF1B(2), TNFRSF21(2), TNFRSF25(1), TP53(312), TRADD(1), TRAF2(2), TRAF3(1) 43592440 389 266 218 26 134 43 52 83 70 7 <1.00e-15 <1.00e-15 <2.93e-14

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 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(4), CYP2C9(3) 1546684 7 7 7 0 3 2 0 1 1 0 0.13 0.0029 1
2 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 14 ARF1(1), CCND1(4), CDK2(1), CDK4(1), CDKN1A(1), CDKN1B(3), CDKN2A(4), CFL1(1), E2F1(1), E2F2(1), MDM2(3), PRB1(1) 5771295 22 17 22 3 5 1 4 4 8 0 0.087 0.0034 1
3 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(2), CCND1(4), CCNE1(1), CCNE2(1), CDK2(1), CDK4(1), CDKN1B(3), CDKN2A(4), E2F1(1), E2F2(1), PRB1(1) 6796377 20 16 20 0 4 1 5 2 8 0 0.0026 0.0097 1
4 RIBOFLAVIN_METABOLISM ACP1, ACP2, ACP5, ACPP, ACPT, ENPP1, ENPP3, FLAD1, RFK, TYR 10 ACP1(1), ACPP(4), ENPP1(4), ENPP3(2), FLAD1(3), TYR(4) 7393124 18 15 18 1 6 2 3 5 2 0 0.028 0.017 1
5 SKP2E2FPATHWAY E2F-1, a transcription factor that promotes the G1/S transition, is repressed by Rb and activated by cdk2/cyclin E. CCNA1, CCNE1, CDC34, CDK2, CUL1, E2F1, RB1, SKP1A, SKP2, TFDP1 9 CCNA1(2), CCNE1(1), CDC34(2), CDK2(1), CUL1(1), E2F1(1), RB1(6), SKP2(3) 6521310 17 14 17 1 2 3 4 1 7 0 0.068 0.023 1
6 HSA00643_STYRENE_DEGRADATION Genes involved in styrene degradation FAH, GSTZ1, HGD 3 FAH(2), GSTZ1(3), HGD(5) 1697424 10 6 10 2 4 0 1 2 3 0 0.31 0.031 1
7 CELLCYCLEPATHWAY Cyclins interact with cyclin-dependent kinases to form active kinase complexes that regulate progression through the cell cycle. CCNA1, CCNB1, CCND1, CCND2, CCND3, CCNE1, CCNH, CDC2, CDC25A, CDK2, CDK4, CDK6, CDK7, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CDKN2D, E2F1, RB1, RBL1, TFDP1 22 CCNA1(2), CCNB1(2), CCND1(4), CCNE1(1), CCNH(2), CDC25A(1), CDK2(1), CDK4(1), CDKN1A(1), CDKN1B(3), CDKN2A(4), CDKN2C(3), E2F1(1), RB1(6), RBL1(4) 12244687 36 25 36 4 7 3 8 5 13 0 0.02 0.043 1
8 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 8 CCNE1(1), CDC34(2), CDK2(1), CUL1(1), E2F1(1), FBXW7(5), RB1(6) 6310719 17 13 17 1 4 3 2 2 6 0 0.06 0.045 1
9 P27PATHWAY p27 blocks the G1/S transition by inhibiting the checkpoint kinase cdk2/cyclin E and is inhibited by cdk2-mediated ubiquitination. CCNE1, CDK2, CDKN1B, CKS1B, CUL1, E2F1, NEDD8, RB1, RBX1, SKP1A, SKP2, TFDP1, UBE2M 12 CCNE1(1), CDK2(1), CDKN1B(3), CUL1(1), E2F1(1), RB1(6), RBX1(1), SKP2(3), UBE2M(1) 6533825 18 15 18 2 1 4 4 1 8 0 0.14 0.045 1
10 HSA00740_RIBOFLAVIN_METABOLISM Genes involved in riboflavin metabolism ACP1, ACP2, ACP5, ACP6, ACPP, ACPT, ENPP1, ENPP3, FLAD1, LHPP, MTMR1, MTMR2, MTMR6, PHPT1, RFK, TYR 16 ACP1(1), ACPP(4), ENPP1(4), ENPP3(2), FLAD1(3), MTMR1(4), MTMR2(3), MTMR6(1), TYR(4) 11461538 26 20 26 2 6 4 5 7 4 0 0.018 0.05 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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