Mutation Analysis (MutSig v2.0)
Stomach and Esophageal carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1XW4J9K
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/C1XW4J9K
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: STES-TP

  • Number of patients in set: 580

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:STES-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 197

  • Mutations seen in COSMIC: 1210

  • Significantly mutated genes in COSMIC territory: 75

  • Significantly mutated genesets: 22

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

Mutation Preprocessing

  • Read 580 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 267407

  • After removing 288 mutations outside chr1-24: 267119

  • After removing 8542 blacklisted mutations: 258577

  • After removing 23914 noncoding mutations: 234663

  • After collapsing adjacent/redundant mutations: 224620

Mutation Filtering

  • Number of mutations before filtering: 224620

  • After removing 12971 mutations outside gene set: 211649

  • After removing 806 mutations outside category set: 210843

  • After removing 8 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 197058

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 30
De_novo_Start_OutOfFrame 64
Frame_Shift_Del 15436
Frame_Shift_Ins 4374
In_Frame_Del 1576
In_Frame_Ins 242
Missense_Mutation 126931
Nonsense_Mutation 7431
Nonstop_Mutation 132
Silent 47538
Splice_Site 6871
Start_Codon_Del 27
Start_Codon_Ins 16
Start_Codon_SNP 133
Stop_Codon_Del 32
Stop_Codon_Ins 10
Total 210843
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 42797 953754146 0.000045 45 4.7 2.1
*Cp(A/C/T)->T 21401 7820268565 2.7e-06 2.7 0.29 1.7
A->G 20019 8431578648 2.4e-06 2.4 0.25 2.3
transver 42843 17205601359 2.5e-06 2.5 0.26 5
indel+null 35473 17205601359 2.1e-06 2.1 0.22 NaN
double_null 767 17205601359 4.5e-08 0.045 0.0047 NaN
Total 163300 17205601359 9.5e-06 9.5 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: STES-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.

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: 197. 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 TP53 tumor protein p53 714664 374 343 174 3 100 36 33 67 133 5 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <5.93e-13
2 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1893996 101 84 42 2 13 37 29 18 4 0 5.55e-15 8.45e-12 8e-07 0.001 0 <1.00e-15 <5.93e-13
3 RNF43 ring finger protein 43 1293590 58 47 24 5 3 4 4 1 39 7 1.19e-13 0.366 0 0.28 0 <1.00e-15 <5.93e-13
4 FBXW7 F-box and WD repeat domain containing 7 1444846 46 44 30 1 19 4 2 4 17 0 7.06e-14 0.000330 0 0.0015 0 <1.00e-15 <5.93e-13
5 PGM5 phosphoglucomutase 5 862117 46 43 12 3 11 0 26 1 8 0 8.55e-15 0.000104 0 1 0 <1.00e-15 <5.93e-13
6 ZBTB20 zinc finger and BTB domain containing 20 1159206 51 42 22 12 12 5 2 2 29 1 0.0779 0.590 0 0.9 0 <1.00e-15 <5.93e-13
7 SMAD4 SMAD family member 4 976078 45 41 35 2 9 8 0 16 11 1 4.66e-15 0.00217 2e-07 0.34 0 <1.00e-15 <5.93e-13
8 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 399691 40 40 6 0 0 32 0 8 0 0 6.55e-15 1.22e-05 0 0.0064 0 <1.00e-15 <5.93e-13
9 XYLT2 xylosyltransferase II 1338459 46 40 17 5 9 2 3 0 31 1 0.000285 0.448 0 0.98 0 <1.00e-15 <5.93e-13
10 KRT75 keratin 75 977700 40 38 10 3 3 3 1 31 2 0 1.54e-13 0.0103 0 0.083 0 <1.00e-15 <5.93e-13
11 BRD8 bromodomain containing 8 2342679 38 37 15 1 2 2 1 28 5 0 2.74e-06 0.00162 0 1 0 <1.00e-15 <5.93e-13
12 FHOD3 formin homology 2 domain containing 3 2407911 41 36 27 2 10 3 2 7 19 0 0.0121 0.00694 0.000069 0.000053 0 <1.00e-15 <5.93e-13
13 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 440989 36 35 31 7 6 6 1 5 17 1 6.50e-09 0.288 0.0016 1.8e-06 0 <1.00e-15 <5.93e-13
14 LARP4B La ribonucleoprotein domain family, member 4B 1297666 38 34 16 3 4 2 1 3 28 0 0.000103 0.185 0 0.75 0 <1.00e-15 <5.93e-13
15 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 1490075 34 33 30 3 3 6 6 11 8 0 9.36e-11 0.00436 0.000016 0.00013 0 <1.00e-15 <5.93e-13
16 MCM8 minichromosome maintenance complex component 8 1499479 30 28 13 5 3 19 4 3 1 0 0.0606 0.0899 4e-07 0.018 0 <1.00e-15 <5.93e-13
17 P4HTM prolyl 4-hydroxylase, transmembrane (endoplasmic reticulum) 755582 28 27 9 1 5 1 1 21 0 0 1.36e-09 0.00598 0 1 0 <1.00e-15 <5.93e-13
18 CBWD1 COBW domain containing 1 603486 23 22 4 2 1 0 1 1 20 0 4.50e-06 0.169 0 1.4e-06 0 <1.00e-15 <5.93e-13
19 RHOA ras homolog gene family, member A 344430 23 22 17 0 2 4 6 10 1 0 5.44e-15 0.00182 0 0.41 0 <1.00e-15 <5.93e-13
20 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1028668 20 18 16 1 0 6 3 9 2 0 1.34e-05 0.0446 0 0.000014 0 <1.00e-15 <5.93e-13
21 ZBTB7C zinc finger and BTB domain containing 7C 870081 19 17 9 7 3 1 0 0 15 0 0.146 0.994 0 0.0016 0 <1.00e-15 <5.93e-13
22 MVK mevalonate kinase 697187 16 16 6 2 1 1 0 3 11 0 0.0239 0.687 1.6e-06 0.000028 0 <1.00e-15 <5.93e-13
23 GLT6D1 glycosyltransferase 6 domain containing 1 488430 15 15 5 2 0 0 1 13 1 0 5.79e-06 0.323 0.000061 0 0 <1.00e-15 <5.93e-13
24 HOXD8 homeobox D8 345139 15 14 6 2 0 0 0 2 11 2 0.000211 0.931 0 0.98 0 <1.00e-15 <5.93e-13
25 WNT16 wingless-type MMTV integration site family, member 16 649035 16 14 7 1 3 1 1 1 10 0 0.0146 0.256 0.00024 0.000013 0 <1.00e-15 <5.93e-13
26 GNG12 guanine nucleotide binding protein (G protein), gamma 12 131600 12 12 4 2 0 1 1 0 10 0 1.42e-06 0.812 2e-07 0.33 0 <1.00e-15 <5.93e-13
27 PLA2G1B phospholipase A2, group IB (pancreas) 268531 8 8 1 0 0 0 0 8 0 0 0.000498 0.316 0 0.89 0 <1.00e-15 <5.93e-13
28 RHOQ ras homolog gene family, member Q 366836 5 5 1 0 0 0 0 0 5 0 0.395 1.000 0 1 0 <1.00e-15 <5.93e-13
29 HIATL1 hippocampus abundant transcript-like 1 835975 4 4 4 1 1 0 0 1 2 0 0.957 0.366 0.2 0 0 <1.00e-15 <5.93e-13
30 DOLPP1 dolichyl pyrophosphate phosphatase 1 425780 3 3 3 0 2 0 0 0 1 0 0.839 0.213 0.8 0 0 <1.00e-15 <5.93e-13
31 ROPN1B ropporin, rhophilin associated protein 1B 365968 2 2 2 1 1 0 0 0 1 0 0.842 0.714 0.89 0 0 <1.00e-15 <5.93e-13
32 HLA-B major histocompatibility complex, class I, B 586555 36 35 31 0 1 3 3 6 21 2 1.03e-14 0.00146 0.017 0.17 0.025 9.44e-15 5.42e-12
33 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 701507 43 37 32 4 2 5 1 9 22 4 <1.00e-15 0.169 0.17 0.99 0.29 <1.05e-14 <5.87e-12
34 B2M beta-2-microglobulin 215025 27 20 19 1 0 2 2 4 14 5 7.99e-15 0.118 0.036 0.37 0.057 1.67e-14 9.00e-12
35 CSMD1 CUB and Sushi multiple domains 1 5223170 148 111 136 8 34 11 20 59 24 0 <1.00e-15 7.55e-12 0.47 0.83 1 <3.55e-14 <1.86e-11
TP53

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

PIK3CA

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

RNF43

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

FBXW7

Figure S4.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PGM5

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

ZBTB20

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

SMAD4

Figure S7.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

KRAS

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

XYLT2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the XYLT2 significant gene.

KRT75

Figure S10.  This figure depicts the distribution of mutations and mutation types across the KRT75 significant gene.

BRD8

Figure S11.  This figure depicts the distribution of mutations and mutation types across the BRD8 significant gene.

FHOD3

Figure S12.  This figure depicts the distribution of mutations and mutation types across the FHOD3 significant gene.

CDKN2A

Figure S13.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

LARP4B

Figure S14.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

CDH1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

MCM8

Figure S16.  This figure depicts the distribution of mutations and mutation types across the MCM8 significant gene.

P4HTM

Figure S17.  This figure depicts the distribution of mutations and mutation types across the P4HTM significant gene.

CBWD1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CBWD1 significant gene.

RHOA

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

NFE2L2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

ZBTB7C

Figure S21.  This figure depicts the distribution of mutations and mutation types across the ZBTB7C significant gene.

MVK

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

GLT6D1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the GLT6D1 significant gene.

HOXD8

Figure S24.  This figure depicts the distribution of mutations and mutation types across the HOXD8 significant gene.

WNT16

Figure S25.  This figure depicts the distribution of mutations and mutation types across the WNT16 significant gene.

GNG12

Figure S26.  This figure depicts the distribution of mutations and mutation types across the GNG12 significant gene.

PLA2G1B

Figure S27.  This figure depicts the distribution of mutations and mutation types across the PLA2G1B significant gene.

RHOQ

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

HIATL1

Figure S29.  This figure depicts the distribution of mutations and mutation types across the HIATL1 significant gene.

DOLPP1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the DOLPP1 significant gene.

ROPN1B

Figure S31.  This figure depicts the distribution of mutations and mutation types across the ROPN1B significant gene.

HLA-B

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

PTEN

Figure S33.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

B2M

Figure S34.  This figure depicts the distribution of mutations and mutation types across the B2M 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: 75. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 49 6 8 3480 8 0 0
2 TP53 tumor protein p53 374 356 349 206480 97557 0 0
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 40 52 39 30160 333261 0 0
4 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 35 42 18 24360 136 0 0
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 101 220 87 127600 33572 0 0
6 FBXW7 F-box and WD repeat domain containing 7 46 91 28 52780 1207 0 0
7 SMAD4 SMAD family member 4 45 159 38 92220 135 0 0
8 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 36 138 16 80040 3753 0 0
9 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 36 332 35 192560 766 0 0
10 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 34 185 17 107300 55 0 0

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: 22. 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 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 ABCB1(40), AKT1(7), ATM(71), BAX(3), CDKN1A(7), CPB2(11), CSNK1A1(7), CSNK1D(5), FHL2(2), HIC1(11), HIF1A(10), HSPA1A(4), IGFBP3(7), MAPK8(7), MDM2(10), NFKBIB(8), NQO1(4), TP53(374) 17893088 588 409 375 41 145 76 53 118 187 9 <1.00e-15 <1.00e-15 <9.40e-14
2 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(11), ATM(71), BAX(3), BCL2(4), CCND1(3), CCNE1(7), CDK2(5), CDK4(2), CDKN1A(7), E2F1(6), MDM2(10), PCNA(2), RB1(22), TIMP3(12), TP53(374) 15654398 539 398 327 33 128 60 53 104 184 10 <1.00e-15 <1.00e-15 <9.40e-14
3 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(8), HSPA1A(4), IFNG(3), IFNGR1(11), IFNGR2(2), IKBKB(12), JAK2(14), LIN7A(11), NFKB1(10), NFKBIA(1), RB1(22), RELA(7), TNF(3), TNFRSF1A(6), TNFRSF1B(4), TP53(374), USH1C(8), WT1(9) 15735204 509 387 306 53 131 55 46 98 173 6 <1.00e-15 <1.00e-15 <9.40e-14
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(59), DAXX(14), HRAS(2), PAX3(14), PML(20), RARA(4), RB1(22), SIRT1(13), SP100(26), TNF(3), TNFRSF1A(6), TNFRSF1B(4), TP53(374) 16317424 561 385 354 46 151 57 61 100 187 5 <1.00e-15 <1.00e-15 <9.40e-14
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(6), CCND1(3), CDK2(5), CDK4(2), CDKN1A(7), CDKN1B(1), CDKN2A(36), CFL1(2), E2F1(6), E2F2(7), MDM2(10), NXT1(4), PRB1(5), TP53(374) 7199165 468 372 259 22 121 54 40 82 164 7 <1.00e-15 <1.00e-15 <9.40e-14
6 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 CHUK(10), DNAJC3(4), EIF2S1(3), EIF2S2(3), NFKB1(10), NFKBIA(1), RELA(7), TP53(374) 8514474 412 355 211 14 106 41 37 79 144 5 <1.00e-15 <1.00e-15 <9.40e-14
7 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(7), APAF1(11), ATM(71), BAD(4), BAX(3), BCL2(4), BCL2L1(2), BID(3), CASP3(2), CASP6(2), CASP7(5), CASP9(4), EIF2S1(3), PRKCA(9), PTK2(12), PXN(9), STAT1(14), TLN1(35), TP53(374) 23579568 574 403 366 41 158 68 53 108 179 8 <1.00e-15 1.11e-15 9.40e-14
8 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(10), MAX(4), MYC(6), SP1(6), SP3(7), TP53(374), WT1(9) 6045387 416 360 214 17 112 44 37 76 142 5 <1.00e-15 1.22e-15 9.40e-14
9 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(12), ATM(71), BRCA1(22), CDKN1A(7), CHEK1(7), CHEK2(13), JUN(6), MAPK8(7), MDM2(10), MRE11A(9), NFKB1(10), NFKBIA(1), RAD50(15), RAD51(4), RBBP8(8), RELA(7), TP53(374), TP73(9) 25517326 592 409 375 48 134 64 55 125 205 9 <1.00e-15 1.44e-15 9.88e-14
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(71), ATR(33), BRCA1(22), CCNB1(4), CDC25A(8), CDC25B(8), CDC25C(11), CDC34(2), CDKN1A(7), CDKN2D(5), CHEK1(7), CHEK2(13), EP300(39), MDM2(10), MYT1(26), PRKDC(70), RPS6KA1(10), TP53(374), WEE1(7), YWHAH(3), YWHAQ(5) 36402256 735 425 517 86 177 81 82 157 228 10 <1.00e-15 2.55e-15 1.56e-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(15) 619862 15 15 13 1 6 1 2 1 5 0 0.055 0.00052 0.32
2 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 BGN(2), DCN(16), FMOD(14), KERA(7), LUM(11) 3111171 50 43 49 4 16 4 5 20 5 0 0.00095 0.052 1
3 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(3), FOSB(7), GRIA2(34), JUND(2), PPP1R1B(3) 3217314 49 41 49 7 8 10 7 17 7 0 0.01 0.42 1
4 HSA00643_STYRENE_DEGRADATION Genes involved in styrene degradation FAH, GSTZ1, HGD 3 FAH(9), GSTZ1(2), HGD(8) 1923828 19 19 17 3 5 1 3 4 6 0 0.25 0.56 1
5 HSA00785_LIPOIC_ACID_METABOLISM Genes involved in lipoic acid metabolism LIAS, LIPT1, LOC387787 2 LIAS(5), LIPT1(5) 1307022 10 10 9 1 2 3 1 0 3 1 0.18 0.58 1
6 ALKALOID_BIOSYNTHESIS_II ABP1, AOC2, AOC3, CES1, ESD 5 AOC2(14), AOC3(18), CES1(21), ESD(1) 5206909 54 48 51 6 16 4 4 13 17 0 0.018 0.79 1
7 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(8), TPI1(3) 1411081 11 11 11 2 5 2 1 2 1 0 0.25 0.84 1
8 NUCLEOTIDE_SUGARS_METABOLISM GALE, GALT, TGDS, UGDH, UXS1 5 GALE(2), GALT(3), TGDS(7), UGDH(11), UXS1(9) 3359335 32 29 31 4 9 3 6 8 6 0 0.035 0.9 1
9 HSA03060_PROTEIN_EXPORT Genes involved in protein export OXA1L, SEC61A2, SRP19, SRP54, SRP68, SRP72, SRP9, SRPR 8 OXA1L(4), SEC61A2(5), SRP19(3), SRP54(11), SRP68(8), SRP72(16), SRP9(2), SRPR(18) 6486893 67 55 64 6 16 9 12 11 19 0 0.001 0.94 1
10 LDLPATHWAY Low density lipoproteins (LDL) are present in blood plasma, contain cholesterol and triglycerides, and contribute to atherogenic plaque formation. ACAT1, CCL2, CSF1, IL6, LDLR, LPL 6 ACAT1(9), CCL2(1), CSF1(6), IL6(1), LDLR(15), LPL(11) 4576270 43 39 39 7 11 5 4 6 17 0 0.027 0.95 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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