Mutation Analysis (MutSig v2.0)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1D21X1G
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/C1D21X1G
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: HNSC-TP

  • Number of patients in set: 511

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:HNSC-TP.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: 856

  • Significantly mutated genes in COSMIC territory: 15

  • Significantly mutated genesets: 60

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

Mutation Preprocessing

  • Read 511 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 120167

  • After removing 21 mutations outside chr1-24: 120146

  • After removing 3704 blacklisted mutations: 116442

  • After removing 6176 noncoding mutations: 110266

  • After collapsing adjacent/redundant mutations: 100303

Mutation Filtering

  • Number of mutations before filtering: 100303

  • After removing 5391 mutations outside gene set: 94912

  • After removing 150 mutations outside category set: 94762

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 49
De_novo_Start_OutOfFrame 79
Frame_Shift_Del 2021
Frame_Shift_Ins 952
In_Frame_Del 465
In_Frame_Ins 55
Missense_Mutation 59473
Nonsense_Mutation 4576
Nonstop_Mutation 79
Silent 23954
Splice_Site 2964
Start_Codon_Del 5
Start_Codon_Ins 2
Start_Codon_SNP 88
Total 94762
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 10574 839327783 0.000013 13 2.7 2.1
*Cp(A/C/T)->T 15382 6847176767 2.2e-06 2.2 0.48 1.7
C->(G/A) 21902 7686504550 2.8e-06 2.8 0.61 4.8
A->mut 11703 7377330205 1.6e-06 1.6 0.34 3.9
indel+null 11105 15063834755 7.4e-07 0.74 0.16 NaN
double_null 142 15063834755 9.4e-09 0.0094 0.002 NaN
Total 70808 15063834755 4.7e-06 4.7 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: HNSC-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5.  Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

Significantly Mutated Genes

Column Descriptions:

  • N = number of sequenced bases in this gene across the individual set

  • n = number of (nonsilent) mutations in this gene across the individual set

  • npat = number of patients (individuals) with at least one nonsilent mutation

  • nsite = number of unique sites having a non-silent mutation

  • nsil = number of silent mutations in this gene across the individual set

  • n1 = number of nonsilent mutations of type: *CpG->T

  • n2 = number of nonsilent mutations of type: *Cp(A/C/T)->T

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

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

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

  • n6 = number of nonsilent mutations of type: double_null

  • p_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 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 3188473 99 90 94 9 16 17 15 10 40 1 2.89e-15 2.65e-07 0.00024 0.14 0.00036 0.000 0.000
2 CASP8 caspase 8, apoptosis-related cysteine peptidase 891984 60 54 48 1 3 8 8 8 31 2 3.44e-15 2.19e-06 0.58 0.000017 0.00018 0.000 0.000
3 TP53 tumor protein p53 629002 432 364 213 6 72 45 60 69 176 10 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <1.21e-12
4 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 431282 114 112 54 1 4 3 6 6 92 3 <1.00e-15 5.47e-11 0 0 0 <1.00e-15 <1.21e-12
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1678341 97 94 36 1 3 54 6 31 3 0 2.00e-15 1.69e-11 0 0.00047 0 <1.00e-15 <1.21e-12
6 NSD1 nuclear receptor binding SET domain protein 1 4170623 72 62 69 2 2 9 13 5 37 6 4.55e-15 0.000330 0.0001 0.000013 0 <1.00e-15 <1.21e-12
7 FBXW7 F-box and WD repeat domain containing 7 1273127 34 33 25 4 4 2 11 5 11 1 5.90e-10 0.272 4e-07 0.19 0 <1.00e-15 <1.21e-12
8 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 331971 34 31 10 0 7 4 19 3 1 0 2.44e-15 1.57e-05 0 6.4e-06 0 <1.00e-15 <1.21e-12
9 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 913695 28 27 19 2 0 6 13 8 1 0 5.62e-14 0.0574 0 0 0 <1.00e-15 <1.21e-12
10 ZNF750 zinc finger protein 750 1113745 24 22 23 1 0 1 4 4 15 0 9.40e-09 0.0593 0.00084 0.00016 0 <1.00e-15 <1.21e-12
11 KRT17 keratin 17 679085 6 6 3 2 0 0 0 0 6 0 0.0560 1.000 0 0.88 0 <1.00e-15 <1.21e-12
12 NRF1 nuclear respiratory factor 1 784336 5 5 5 0 0 1 2 0 2 0 0.163 0.310 0.75 0 0 <1.00e-15 <1.21e-12
13 GATA2 GATA binding protein 2 635524 2 2 2 1 0 0 0 0 2 0 0.758 0.659 0.049 0 0 <1.00e-15 <1.21e-12
14 NEDD8 neural precursor cell expressed, developmentally down-regulated 8 127929 2 2 2 0 0 0 1 0 1 0 0.0493 0.659 0.88 0 0 <1.00e-15 <1.21e-12
15 ULK2 unc-51-like kinase 2 (C. elegans) 1556817 2 2 2 2 0 0 1 0 1 0 0.995 0.943 0.82 0 0 <1.00e-15 <1.21e-12
16 OR6C65 olfactory receptor, family 6, subfamily C, member 65 474443 16 16 7 1 0 3 1 1 11 0 1.55e-12 0.430 8.4e-06 0.64 0.000068 4.00e-15 4.50e-12
17 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 6977289 123 112 118 12 2 7 10 11 77 16 3.55e-15 0.000253 0.16 0.03 0.032 4.22e-15 4.50e-12
18 HLA-B major histocompatibility complex, class I, B 504575 26 24 21 1 0 1 8 2 15 0 4.33e-15 0.00658 0.033 0.065 0.037 6.00e-15 6.03e-12
19 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 880651 26 24 17 2 5 7 0 5 9 0 2.04e-12 0.00297 0.0036 0.097 0.0046 3.12e-13 2.98e-10
20 HLA-A major histocompatibility complex, class I, A 565415 24 22 21 3 1 0 1 6 16 0 4.46e-12 0.137 0.099 0.38 0.12 1.63e-11 1.48e-08
21 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 317803 15 14 8 0 6 4 2 3 0 0 1.46e-10 0.00386 0.18 0.062 0.075 2.86e-10 2.47e-07
22 EP300 E1A binding protein p300 3759447 38 38 31 1 5 9 6 7 11 0 4.99e-08 0.000406 0.00022 0.02 0.00029 3.79e-10 3.12e-07
23 OR2M5 olfactory receptor, family 2, subfamily M, member 5 481362 20 17 19 0 4 2 10 2 2 0 7.73e-11 0.00511 0.58 0.87 0.78 1.48e-09 1.16e-06
24 POM121L12 POM121 transmembrane nucleoporin-like 12 444628 25 23 25 4 6 2 10 3 4 0 2.89e-09 0.0524 0.19 0.2 0.22 1.42e-08 1.08e-05
25 MAPK1 mitogen-activated protein kinase 1 506892 9 9 2 0 7 1 0 0 1 0 2.91e-05 0.0486 4e-05 0.05 0.000053 3.28e-08 2.38e-05
26 EPHA2 EPH receptor A2 1452412 27 24 24 2 6 1 2 0 16 2 2.68e-07 0.0231 0.0068 0.22 0.0063 3.59e-08 2.41e-05
27 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 621569 14 14 14 0 1 1 2 2 8 0 2.95e-08 0.0580 0.21 0.015 0.058 3.59e-08 2.41e-05
28 DPPA2 developmental pluripotency associated 2 472642 14 14 13 1 4 2 4 4 0 0 6.58e-09 0.0964 0.62 0.31 0.57 7.70e-08 4.98e-05
29 RHOA ras homolog gene family, member A 305578 10 10 7 1 0 1 6 2 1 0 5.98e-07 0.296 0.055 0.082 0.044 4.87e-07 0.000304
30 AGTR1 angiotensin II receptor, type 1 553924 13 13 13 1 2 5 2 4 0 0 2.17e-07 0.0690 0.51 0.29 0.54 1.99e-06 0.00120
31 KIR3DL2 killer cell immunoglobulin-like receptor, three domains, long cytoplasmic tail, 2 457495 9 9 7 1 3 1 3 0 2 0 5.97e-05 0.204 0.0021 0.83 0.0045 4.32e-06 0.00253
32 B2M beta-2-microglobulin 190082 9 8 8 0 0 2 2 0 5 0 3.51e-07 0.282 0.72 0.65 0.9 5.03e-06 0.00285
33 NPFFR2 neuropeptide FF receptor 2 808643 18 17 18 0 1 3 5 6 3 0 7.00e-07 0.0126 0.45 0.45 0.6 6.54e-06 0.00359
34 RASA1 RAS p21 protein activator (GTPase activating protein) 1 1552003 18 18 16 0 1 0 3 3 10 1 5.29e-06 0.0268 0.42 0.051 0.12 9.73e-06 0.00518
35 EYA1 eyes absent homolog 1 (Drosophila) 935398 17 16 17 1 3 2 6 5 1 0 3.44e-06 0.0638 0.33 0.086 0.23 1.19e-05 0.00618
NOTCH1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

TP53

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

CDKN2A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

NSD1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

FBXW7

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

HRAS

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

NFE2L2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

ZNF750

Figure S9.  This figure depicts the distribution of mutations and mutation types across the ZNF750 significant gene.

KRT17

Figure S10.  This figure depicts the distribution of mutations and mutation types across the KRT17 significant gene.

NRF1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the NRF1 significant gene.

GATA2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the GATA2 significant gene.

NEDD8

Figure S13.  This figure depicts the distribution of mutations and mutation types across the NEDD8 significant gene.

ULK2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ULK2 significant gene.

OR6C65

Figure S15.  This figure depicts the distribution of mutations and mutation types across the OR6C65 significant gene.

FAT1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

HLA-B

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

TGFBR2

Figure S18.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

HLA-A

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

RAC1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

EP300

Figure S21.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

OR2M5

Figure S22.  This figure depicts the distribution of mutations and mutation types across the OR2M5 significant gene.

POM121L12

Figure S23.  This figure depicts the distribution of mutations and mutation types across the POM121L12 significant gene.

MAPK1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the MAPK1 significant gene.

EPHA2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the EPHA2 significant gene.

PTEN

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

DPPA2

Figure S27.  This figure depicts the distribution of mutations and mutation types across the DPPA2 significant gene.

RHOA

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

AGTR1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the AGTR1 significant gene.

KIR3DL2

Figure S30.  This figure depicts the distribution of mutations and mutation types across the KIR3DL2 significant gene.

B2M

Figure S31.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

NPFFR2

Figure S32.  This figure depicts the distribution of mutations and mutation types across the NPFFR2 significant gene.

RASA1

Figure S33.  This figure depicts the distribution of mutations and mutation types across the RASA1 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: 15. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 34 19 32 9709 7854 0 0
2 TP53 tumor protein p53 432 356 398 181916 75536 0 0
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 97 220 82 112420 39060 0 0
4 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 114 332 112 169652 4733 0 0
5 FBXW7 F-box and WD repeat domain containing 7 34 91 23 46501 520 0 0
6 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 13 62 7 31682 5409 2.8e-10 2.1e-07
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 14 767 14 391937 527 1.1e-08 6.9e-06
8 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 9 33 5 16863 13 2.4e-08 0.000014
9 SMAD4 SMAD family member 4 14 159 7 81249 17 1.7e-07 0.000085
10 RB1 retinoblastoma 1 (including osteosarcoma) 17 267 8 136437 23 4e-07 0.00018

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: 60. 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 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(1), AKT1(2), AKT2(4), AKT3(6), APAF1(12), ATM(16), BAD(1), BCL2(1), BCL2L1(2), BID(3), BIRC2(3), BIRC3(2), CAPN1(3), CAPN2(5), CASP10(2), CASP3(2), CASP6(5), CASP7(3), CASP8(60), CASP9(1), CFLAR(2), CHUK(6), CSF2RB(7), FADD(3), FAS(5), FASLG(1), IKBKB(11), IL1A(1), IL1B(1), IL1R1(4), IL1RAP(6), IL3(1), IL3RA(5), IRAK1(3), IRAK2(2), IRAK3(9), IRAK4(3), NFKB1(5), NFKB2(5), NFKBIA(1), NTRK1(3), PIK3CA(97), PIK3CB(6), PIK3CD(8), PIK3CG(20), PIK3R1(9), PIK3R2(5), PIK3R3(4), PIK3R5(10), PPP3CA(2), PPP3CB(1), PRKACA(4), PRKACB(3), PRKACG(2), PRKAR1A(4), PRKAR1B(4), PRKAR2B(3), RELA(2), RIPK1(2), TNFRSF10A(3), TNFRSF10B(1), TNFRSF10D(1), TNFRSF1A(2), TNFSF10(1), TP53(432), TRADD(1), TRAF2(2) 63750063 847 442 552 87 120 166 133 154 262 12 <1.00e-15 <1.00e-15 <3.42e-14
2 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(8), CDKN2A(114), MDM2(3), MYC(6), PIK3CA(97), PIK3R1(9), POLR1A(9), POLR1B(3), POLR1C(2), RAC1(15), RB1(17), TBX2(4), TP53(432), TWIST1(1) 15458536 720 423 370 24 91 114 88 120 294 13 <1.00e-15 <1.00e-15 <3.42e-14
3 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 65 APAF1(12), ATM(16), ATR(24), BAI1(8), BID(3), CASP3(2), CASP8(60), CASP9(1), CCNB1(2), CCNB3(11), CCND1(3), CCND2(2), CCNE1(4), CCNE2(4), CCNG1(1), CCNG2(4), CDK4(5), CDK6(1), CDKN2A(114), CHEK1(1), CHEK2(4), DDB2(4), EI24(2), FAS(5), GADD45A(1), GADD45G(1), GTSE1(9), IGF1(1), IGFBP3(1), MDM2(3), MDM4(1), PERP(1), PMAIP1(2), PPM1D(7), PTEN(14), RCHY1(1), RFWD2(2), RRM2(1), RRM2B(1), SERPINB5(1), SERPINE1(7), SESN1(2), SESN2(4), SESN3(4), SFN(7), SIAH1(4), STEAP3(4), THBS1(8), TNFRSF10B(1), TP53(432), TSC2(7), ZMAT3(2) 49912643 822 419 531 66 100 106 120 133 348 15 <1.00e-15 <1.00e-15 <3.42e-14
4 ST_FAS_SIGNALING_PATHWAY The Fas receptor induces apoptosis and NF-kB activation when bound to Fas ligand. ADPRT, ALG2, BAK1, BAX, BFAR, BIRC4, BTK, CAD, CASP10, CASP3, CASP8, CASP8AP2, CD7, CDK2AP1, CSNK1A1, DAXX, DEDD, DEDD2, DFFA, DIABLO, EGFR, EPHB2, FADD, FAF1, FAIM2, FREQ, HRB, HSPB1, IL1A, IL8, MAP2K4, MAP2K7, MAP3K1, MAP3K5, MAPK1, MAPK10, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, MCP, MET, NFAT5, NFKB1, NFKB2, NFKBIA, NFKBIB, NFKBIE, NFKBIL1, NFKBIL2, NR0B2, PFN1, PFN2, PTPN13, RALBP1, RIPK1, ROCK1, SMPD1, TNFRSF6, TNFRSF6B, TP53, TPX2, TRAF2, TUFM, VIL2 59 ALG2(2), BAK1(1), BTK(8), CAD(5), CASP10(2), CASP3(2), CASP8(60), CSNK1A1(1), DAXX(6), DEDD(1), DEDD2(5), DIABLO(1), EGFR(19), EPHB2(3), FADD(3), FAF1(2), IL1A(1), MAP2K4(2), MAP2K7(2), MAP3K1(6), MAP3K5(6), MAPK1(9), MAPK10(4), MAPK8(4), MAPK8IP1(4), MAPK8IP2(2), MAPK8IP3(9), MAPK9(4), MET(4), NFAT5(12), NFKB1(5), NFKB2(5), NFKBIA(1), NFKBIB(1), NFKBIE(1), NFKBIL1(1), NR0B2(1), PFN1(1), PFN2(1), PTPN13(12), RALBP1(3), RIPK1(2), ROCK1(19), TNFRSF6B(4), TP53(432), TPX2(5), TRAF2(2) 55608973 686 419 448 68 109 98 121 102 243 13 <1.00e-15 <1.00e-15 <3.42e-14
5 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(16), CCNA1(7), CCNB1(2), CCND1(3), CCND2(2), CCNE1(4), CCNE2(4), CCNG2(4), CDC25A(3), CDK4(5), CDKN1B(2), CDKN2A(114), CDKN2C(1), CDKN2D(1), CREB3L1(4), CREB3L3(9), CREB3L4(2), E2F2(3), E2F3(3), E2F4(3), E2F5(6), E2F6(1), GADD45A(1), GBA2(6), MCM2(5), MCM3(4), MCM4(7), MCM5(2), MCM6(4), MCM7(8), MDM2(3), MNAT1(1), MYC(6), MYT1(11), NACA(24), PCNA(1), POLA2(2), POLE(11), PRIM1(3), RB1(17), RBL1(12), RPA1(5), RPA2(1), TFDP1(2), TFDP2(1), TNXB(25), TP53(432), WEE1(2) 58898340 795 418 513 78 106 110 136 114 315 14 <1.00e-15 <1.00e-15 <3.42e-14
6 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(8), ATM(16), ATR(24), CCNA1(7), CCND1(3), CCNE1(4), CDC25A(3), CDK4(5), CDK6(1), CDKN1B(2), CDKN2A(114), DHFR(2), GSK3B(3), HDAC1(1), RB1(17), SKP2(4), TFDP1(2), TGFB1(1), TGFB2(4), TGFB3(1), TP53(432) 22993891 654 398 374 32 85 68 93 99 296 13 <1.00e-15 <1.00e-15 <3.42e-14
7 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(16), ATR(24), BRCA1(12), CCNB1(2), CDC25A(3), CDC25B(4), CDC25C(4), CDC34(4), CDKN2D(1), CHEK1(1), CHEK2(4), EP300(38), GADD45A(1), MDM2(3), MYT1(11), PRKDC(28), RPS6KA1(10), TP53(432), WEE1(2), YWHAH(2), YWHAQ(3) 31973159 605 398 379 37 94 84 105 104 208 10 <1.00e-15 <1.00e-15 <3.42e-14
8 ATRBRCAPATHWAY BRCA1 and 2 block cell cycle progression in response to DNA damage and promote double-stranded break repair; mutations induce breast cancer susceptibility. ATM, ATR, BRCA1, BRCA2, CHEK1, CHEK2, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, HUS1, MRE11A, NBS1, RAD1, RAD17, RAD50, RAD51, RAD9A, TP53, TREX1 21 ATM(16), ATR(24), BRCA1(12), BRCA2(17), CHEK1(1), CHEK2(4), FANCA(7), FANCC(3), FANCD2(9), FANCF(2), FANCG(2), HUS1(2), MRE11A(3), RAD17(7), RAD50(10), RAD51(1), RAD9A(2), TP53(432), TREX1(4) 33566948 558 393 339 36 80 83 92 96 197 10 <1.00e-15 <1.00e-15 <3.42e-14
9 ST_JNK_MAPK_PATHWAY JNKs are MAP kinases regulated by several levels of kinases (MAPKK, MAPKKK) and phosphorylate transcription factors and regulatory proteins. AKT1, ATF2, CDC42, DLD, DUSP10, DUSP4, DUSP8, GAB1, GADD45A, GCK, IL1R1, JUN, MAP2K4, MAP2K5, MAP2K7, MAP3K1, MAP3K10, MAP3K11, MAP3K12, MAP3K13, MAP3K2, MAP3K3, MAP3K4, MAP3K5, MAP3K7, MAP3K7IP1, MAP3K7IP2, MAP3K9, MAPK10, MAPK7, MAPK8, MAPK9, MYEF2, NFATC3, NR2C2, PAPPA, SHC1, TP53, TRAF6, ZAK 38 AKT1(2), ATF2(1), CDC42(3), DLD(1), DUSP10(3), DUSP4(1), DUSP8(1), GAB1(5), GADD45A(1), GCK(4), IL1R1(4), JUN(1), MAP2K4(2), MAP2K5(3), MAP2K7(2), MAP3K1(6), MAP3K10(5), MAP3K11(2), MAP3K12(8), MAP3K13(15), MAP3K2(2), MAP3K3(2), MAP3K4(14), MAP3K5(6), MAP3K7(8), MAP3K9(9), MAPK10(4), MAPK7(6), MAPK8(4), MAPK9(4), MYEF2(8), NFATC3(5), NR2C2(1), PAPPA(13), SHC1(2), TP53(432), TRAF6(3), ZAK(5) 38482261 598 393 376 50 95 82 117 94 200 10 <1.00e-15 <1.00e-15 <3.42e-14
10 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 DNAJA3(3), IFNG(2), IFNGR1(4), IFNGR2(4), IKBKB(11), JAK2(5), LIN7A(4), NFKB1(5), NFKBIA(1), RB1(17), RELA(2), TNFRSF1A(2), TNFRSF1B(2), TP53(432), USH1C(3), WT1(3) 13883618 500 388 280 29 77 56 82 77 198 10 <1.00e-15 <1.00e-15 <3.42e-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 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(2) 387333 2 2 2 0 0 0 0 0 2 0 0.66 0.29 1
2 SULFUR_METABOLISM BPNT1, PAPSS1, PAPSS2, SULT1A2, SULT1A3, SULT1A3, SULT1A4, SULT1E1, SULT2A1, SUOX 7 BPNT1(2), PAPSS1(6), PAPSS2(6), SULT1A2(2), SULT1E1(5), SULT2A1(2), SUOX(2) 4654771 25 23 25 2 5 7 5 5 3 0 0.027 0.36 1
3 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(3), PGLYRP2(6) 1385935 9 9 9 2 1 3 2 2 1 0 0.35 0.6 1
4 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(2), TPI1(4) 1259018 6 6 6 2 1 3 2 0 0 0 0.65 0.69 1
5 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 7 CCNE1(4), CDC34(4), CUL1(11), RB1(17), TFDP1(2) 5002135 38 33 38 8 3 11 5 3 16 0 0.11 0.7 1
6 SA_G2_AND_M_PHASES Cdc25 activates the cdc2/cyclin B complex to induce the G2/M transition. CDC2, CDC25A, CDC25B, CDK7, CDKN1A, CHEK1, NEK1, WEE1 7 CDC25A(3), CDC25B(4), CHEK1(1), NEK1(9), WEE1(2) 5234638 19 19 19 1 4 4 6 1 4 0 0.092 0.73 1
7 RABPATHWAY Rab family GTPases regulate vesicle transport, endocytosis and exocytosis, and vesicle docking via interactions with the rabphilins. ACTA1, MEL, RAB11A, RAB1A, RAB2, RAB27A, RAB3A, RAB4A, RAB5A, RAB6A, RAB7, RAB9A 9 ACTA1(4), RAB11A(1), RAB1A(2), RAB3A(2), RAB4A(1), RAB5A(3) 3216067 13 13 13 1 5 4 2 1 1 0 0.041 0.74 1
8 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(6), CYP2C9(6) 1540877 12 12 12 3 0 4 5 2 1 0 0.41 0.76 1
9 NUCLEOTIDE_SUGARS_METABOLISM GALE, GALT, TGDS, UGDH, UXS1 5 GALT(2), TGDS(3), UGDH(3), UXS1(2) 2930825 10 10 10 0 0 1 5 3 1 0 0.13 0.78 1
10 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(3), CD4(1), HLA-DRA(1), HLA-DRB1(2) 1803977 7 7 6 2 0 1 0 3 3 0 0.75 0.79 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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