Mutation Analysis (MutSig v2.0)
Stomach Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1MP52KW
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/C1MP52KW
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: STAD-TP

  • Number of patients in set: 289

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:STAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 152

  • Mutations seen in COSMIC: 681

  • Significantly mutated genes in COSMIC territory: 48

  • Significantly mutated genesets: 19

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

Mutation Preprocessing

  • Read 289 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 148519

  • After removing 3211 noncoding mutations: 145308

  • After collapsing adjacent/redundant mutations: 144914

Mutation Filtering

  • Number of mutations before filtering: 144914

  • After removing 6771 mutations outside gene set: 138143

  • After removing 1007 mutations outside category set: 137136

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 129356

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 33
De_novo_Start_OutOfFrame 84
Frame_Shift_Del 10154
Frame_Shift_Ins 3290
In_Frame_Del 955
In_Frame_Ins 112
Missense_Mutation 80377
Nonsense_Mutation 4052
Nonstop_Mutation 87
Silent 33667
Splice_Site 4214
Start_Codon_Del 20
Start_Codon_Ins 4
Start_Codon_SNP 75
Stop_Codon_Del 12
Total 137136
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 29596 468903824 0.000063 63 5.2 2.1
*Np(A/C/T)->transit 25023 6698174757 3.7e-06 3.7 0.31 2
*ApG->G 4036 1298784747 3.1e-06 3.1 0.25 2.1
transver 21795 8465863328 2.6e-06 2.6 0.21 5
indel+null 22057 8465863328 2.6e-06 2.6 0.21 NaN
double_null 960 8465863328 1.1e-07 0.11 0.0093 NaN
Total 103467 8465863328 0.000012 12 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: STAD-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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->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: 152. 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 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 945337 72 57 34 2 11 44 4 9 4 0 1.3e-15 2.22e-08 0.00038 0.024 0.000095 0.000 0.000
2 TP53 tumor protein p53 354913 143 138 87 0 37 26 2 22 50 6 3.3e-15 <1.00e-15 0 0 0 <1.00e-15 <7.24e-13
3 RNF43 ring finger protein 43 627712 56 49 17 2 2 4 0 0 43 7 5.8e-15 0.289 0 0.23 0 <1.00e-15 <7.24e-13
4 BZRAP1 benzodiazapine receptor (peripheral) associated protein 1 1434697 47 46 17 5 6 4 1 2 34 0 2.9e-13 0.511 0 1 0 <1.00e-15 <7.24e-13
5 XYLT2 xylosyltransferase II 650967 35 32 10 3 6 2 0 0 27 0 3e-07 0.515 0 0.94 0 <1.00e-15 <7.24e-13
6 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 733965 30 29 27 4 2 9 2 8 9 0 1.6e-14 0.0411 0.00016 0.000051 0 <1.00e-15 <7.24e-13
7 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 197544 28 28 6 0 0 22 0 6 0 0 8.6e-15 0.000111 0 9.2e-06 0 <1.00e-15 <7.24e-13
8 LARP4B La ribonucleoprotein domain family, member 4B 645702 29 27 8 2 2 2 0 1 24 0 2.4e-06 0.403 0 0.73 0 <1.00e-15 <7.24e-13
9 FHOD3 formin homology 2 domain containing 3 1202775 33 26 21 12 10 3 1 4 15 0 1 0.873 0.00021 0.00028 0 <1.00e-15 <7.24e-13
10 PGM5 phosphoglucomutase 5 395150 29 25 7 0 4 19 0 1 5 0 1.1e-10 1.90e-05 0 1 0 <1.00e-15 <7.24e-13
11 SMAD4 SMAD family member 4 488947 26 24 21 1 5 6 0 8 5 2 1.8e-15 0.0174 0 0.16 0 <1.00e-15 <7.24e-13
12 LMAN1 lectin, mannose-binding, 1 449568 19 19 4 2 0 1 0 0 18 0 0.000087 0.832 0 0.48 0 <1.00e-15 <7.24e-13
13 FRMD4A FERM domain containing 4A 814697 18 18 6 2 2 2 0 0 14 0 0.07 0.620 0 0.00028 0 <1.00e-15 <7.24e-13
14 PAMR1 peptidase domain containing associated with muscle regeneration 1 605240 18 17 9 4 1 3 1 3 10 0 0.16 0.806 8e-06 0.0045 0 <1.00e-15 <7.24e-13
15 RHOA ras homolog gene family, member A 172822 17 16 13 0 1 8 0 8 0 0 4.9e-15 0.00855 0 0.37 0 <1.00e-15 <7.24e-13
16 CCDC153 coiled-coil domain containing 153 112274 8 8 2 0 1 0 0 0 7 0 0.0001 0.818 0.00027 1.4e-06 0 <1.00e-15 <7.24e-13
17 C1QTNF5 C1q and tumor necrosis factor related protein 5 125388 6 6 2 0 0 0 0 0 6 0 0.0062 0.810 0 0.97 0 <1.00e-15 <7.24e-13
18 CABP5 calcium binding protein 5 157714 5 5 1 2 0 0 0 0 5 0 0.066 1.000 0 0.99 0 <1.00e-15 <7.24e-13
19 NT5M 5',3'-nucleotidase, mitochondrial 149775 5 5 1 2 0 0 0 0 5 0 0.069 1.000 0 0.000016 0 <1.00e-15 <7.24e-13
20 RHOQ ras homolog gene family, member Q 183077 5 5 1 0 0 0 0 0 5 0 0.1 1.000 0 1 0 <1.00e-15 <7.24e-13
21 HIATL1 hippocampus abundant transcript-like 1 415607 4 4 4 0 1 0 0 1 2 0 0.72 0.151 0.2 0 0 <1.00e-15 <7.24e-13
22 DOLPP1 dolichyl pyrophosphate phosphatase 1 216349 3 3 3 0 2 0 0 0 1 0 0.55 0.212 0.8 0 0 <1.00e-15 <7.24e-13
23 GRPEL1 GrpE-like 1, mitochondrial (E. coli) 191298 3 3 3 0 0 1 1 0 1 0 0.39 0.272 0.07 0 0 <1.00e-15 <7.24e-13
24 RAB4B RAB4B, member RAS oncogene family 186016 2 2 2 1 0 0 0 1 1 0 0.38 0.837 0.16 0 0 <1.00e-15 <7.24e-13
25 ROPN1B ropporin, rhophilin associated protein 1B 179931 2 2 2 1 1 0 0 0 1 0 0.57 0.713 0.89 0 0 <1.00e-15 <7.24e-13
26 B2M beta-2-microglobulin 107442 22 17 15 1 0 3 0 2 10 7 5.2e-15 0.246 0.0055 0.43 0.011 2.11e-15 1.47e-12
27 ARID1A AT rich interactive domain 1A (SWI-like) 1686335 98 90 80 4 6 7 1 4 60 20 5e-15 0.000828 0.63 0.032 0.12 2.08e-14 1.39e-11
28 GNG12 guanine nucleotide binding protein (G protein), gamma 12 65589 11 11 3 2 0 2 0 0 9 0 9.1e-08 0.814 8e-07 0.49 9.4e-06 2.45e-11 1.58e-08
29 FBXW7 F-box and WD repeat domain containing 7 715336 28 27 18 1 14 4 0 0 10 0 2.3e-08 0.0104 4e-05 0.14 0.000061 3.90e-11 2.43e-08
30 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 345472 29 23 21 4 1 4 0 5 15 4 1.4e-11 0.462 0.14 1 0.2 7.70e-11 4.65e-08
31 EDNRB endothelin receptor type B 395127 29 27 22 4 7 3 1 6 11 1 3.4e-11 0.127 0.044 0.59 0.089 8.40e-11 4.91e-08
32 HLA-B major histocompatibility complex, class I, B 287706 20 20 16 0 1 3 2 2 10 2 3.3e-09 0.0129 0.1 0.0004 0.0012 1.06e-10 5.97e-08
33 OR5M3 olfactory receptor, family 5, subfamily M, member 3 265275 16 15 9 1 2 1 3 3 7 0 1e-08 0.197 0.00038 0.24 0.00064 1.79e-10 9.74e-08
34 DCLK1 doublecortin-like kinase 1 629325 34 32 34 4 10 5 2 9 8 0 8.5e-11 0.0228 0.05 0.86 0.081 1.83e-10 9.74e-08
35 CNBD1 cyclic nucleotide binding domain containing 1 276093 13 13 8 1 1 1 3 7 1 0 3.2e-08 0.0831 0.062 0.0019 0.00076 6.13e-10 3.17e-07
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

TP53

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

RNF43

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

BZRAP1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the BZRAP1 significant gene.

XYLT2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the XYLT2 significant gene.

CDH1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

KRAS

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

LARP4B

Figure S8.  This figure depicts the distribution of mutations and mutation types across the LARP4B significant gene.

FHOD3

Figure S9.  This figure depicts the distribution of mutations and mutation types across the FHOD3 significant gene.

PGM5

Figure S10.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

SMAD4

Figure S11.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

LMAN1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the LMAN1 significant gene.

FRMD4A

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FRMD4A significant gene.

PAMR1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the PAMR1 significant gene.

RHOA

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

CCDC153

Figure S16.  This figure depicts the distribution of mutations and mutation types across the CCDC153 significant gene.

C1QTNF5

Figure S17.  This figure depicts the distribution of mutations and mutation types across the C1QTNF5 significant gene.

CABP5

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CABP5 significant gene.

NT5M

Figure S19.  This figure depicts the distribution of mutations and mutation types across the NT5M significant gene.

RHOQ

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

HIATL1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the HIATL1 significant gene.

DOLPP1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the DOLPP1 significant gene.

GRPEL1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the GRPEL1 significant gene.

RAB4B

Figure S24.  This figure depicts the distribution of mutations and mutation types across the RAB4B significant gene.

ROPN1B

Figure S25.  This figure depicts the distribution of mutations and mutation types across the ROPN1B significant gene.

B2M

Figure S26.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

ARID1A

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

GNG12

Figure S28.  This figure depicts the distribution of mutations and mutation types across the GNG12 significant gene.

FBXW7

Figure S29.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PTEN

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

EDNRB

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

HLA-B

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

OR5M3

Figure S33.  This figure depicts the distribution of mutations and mutation types across the OR5M3 significant gene.

DCLK1

Figure S34.  This figure depicts the distribution of mutations and mutation types across the DCLK1 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: 48. 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) 37 6 8 1734 8 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 28 52 27 15028 197519 0 0
3 TP53 tumor protein p53 143 356 133 102884 35095 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 72 220 62 63580 22978 0 0
5 FBXW7 F-box and WD repeat domain containing 7 28 91 18 26299 892 0 0
6 SMAD4 SMAD family member 4 26 159 21 45951 73 0 0
7 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 30 185 15 53465 42 0 0
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 29 767 29 221663 785 0 0
9 APC adenomatous polyposis coli 43 839 22 242471 474 1.2e-12 6e-10
10 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 15 42 8 12138 80 5e-12 2.3e-09

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: 19. 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 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(38), CDC25A(6), CDC25B(4), CDC25C(12), CDK2(3), CHEK1(4), MYT1(19), RB1(13), TP53(143), WEE1(4), YWHAH(3) 7559184 249 176 182 21 58 52 5 42 82 10 3.9e-10 <1.00e-15 <1.66e-13
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(8), ATM(38), BAX(6), BCL2(3), CCND1(1), CCNE1(5), CDK2(3), CDKN1A(3), E2F1(3), MDM2(5), PCNA(2), RB1(13), TIMP3(6), TP53(143) 7778948 239 175 170 22 55 51 4 37 82 10 1.9e-09 <1.00e-15 <1.66e-13
3 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(40), DAXX(10), PAX3(11), PML(12), RARA(3), RB1(13), SIRT1(6), SP100(15), TNF(3), TNFRSF1A(6), TNFRSF1B(3), TP53(143) 8160663 265 174 206 31 78 60 4 38 79 6 6.5e-11 <1.00e-15 <1.66e-13
4 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(4), DNAJC3(3), EIF2S1(2), EIF2S2(2), NFKB1(7), NFKBIA(1), RELA(5), TP53(143) 4197551 167 146 111 5 41 32 2 30 56 6 1.6e-13 1.11e-15 1.66e-13
5 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(38), ATR(18), CDC25C(12), CHEK1(4), CHEK2(8), TP53(143), YWHAH(3) 6857303 226 171 161 19 55 41 3 38 79 10 1.4e-07 1.44e-15 1.66e-13
6 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(26), AKT1(3), ATM(38), BAX(6), CDKN1A(3), CPB2(10), CSNK1A1(3), CSNK1D(2), FHL2(4), HIC1(6), HIF1A(7), HSPA1A(2), IGFBP3(6), MAPK8(5), MDM2(5), NFKBIB(6), NQO1(3), TP53(143) 8909084 278 183 210 27 67 56 6 44 94 11 3.3e-11 1.78e-15 1.66e-13
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(3), APAF1(8), ATM(38), BAD(3), BAX(6), BCL2(3), BID(2), CASP3(2), CASP6(1), CASP7(3), CASP9(3), EIF2S1(2), PRKCA(5), PTK2(11), PXN(4), STAT1(10), TLN1(23), TP53(143) 11749843 270 180 203 27 72 58 8 38 85 9 3.9e-11 1.89e-15 1.66e-13
8 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(7), CDKN2A(13), E2F1(3), MDM2(5), MYC(5), PIK3CA(72), PIK3R1(11), POLR1A(15), POLR1B(8), POLR1C(3), POLR1D(4), RB1(13), TBX2(6), TP53(143), TWIST1(2) 8710873 310 201 212 35 73 93 7 42 87 8 4.9e-13 2.55e-15 1.97e-13
9 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(5), CCND1(1), CDK2(3), CDKN1A(3), CDKN2A(13), CFL1(1), E2F1(3), E2F2(4), MDM2(5), NXT1(2), PRB1(4), TP53(143) 3621793 187 157 130 11 49 39 3 26 62 8 2.3e-12 2.89e-15 1.98e-13
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(4), HSPA1A(2), IFNG(2), IFNGR1(6), IFNGR2(2), IKBKB(8), JAK2(13), LIN7A(9), NFKB1(7), NFKBIA(1), RB1(13), RELA(5), TNF(3), TNFRSF1A(6), TNFRSF1B(3), TP53(143), USH1C(4), WT1(3) 7791981 234 167 175 33 55 50 3 45 74 7 4e-07 3.44e-15 2.12e-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(11) 311023 11 11 11 0 3 2 1 1 4 0 0.04 0.00022 0.13
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(1), DCN(8), FMOD(10), KERA(1), LUM(7) 1561475 27 24 27 4 12 4 1 7 3 0 0.07 0.31 1
3 HSA00785_LIPOIC_ACID_METABOLISM Genes involved in lipoic acid metabolism LIAS, LIPT1, LOC387787 2 LIAS(3), LIPT1(5) 652455 8 8 7 1 2 3 0 0 3 0 0.27 0.45 1
4 HSA00643_STYRENE_DEGRADATION Genes involved in styrene degradation FAH, GSTZ1, HGD 3 FAH(8), GSTZ1(3), HGD(4) 953469 15 13 14 3 4 3 0 4 4 0 0.38 0.46 1
5 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 3 CD28(1), HLA-DRA(8) 632681 9 9 9 2 4 3 0 0 2 0 0.41 0.53 1
6 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(6), TPI1(1) 706305 7 7 7 1 2 2 1 1 1 0 0.31 0.6 1
7 FOSBPATHWAY FOSB gene expression and drug abuse CDK5, FOSB, GRIA2, JUND, PPP1R1B 5 CDK5(2), FOSB(5), GRIA2(23), JUND(2), PPP1R1B(1) 1603188 33 27 33 6 7 10 1 9 6 0 0.064 0.63 1
8 INOSITOL_METABOLISM ALDH6A1, ALDOA, ALDOB, ALDOC, TPI1 5 ALDH6A1(6), ALDOA(1), ALDOB(6), ALDOC(6), TPI1(1) 1682865 20 20 20 3 3 7 1 6 3 0 0.12 0.64 1
9 TCRMOLECULE T Cell Receptor and CD3 Complex CD3D, CD3E, CD3G, CD3Z, TRA@, TRB@ 3 CD3E(2), CD3G(1) 488715 3 3 3 1 0 1 1 0 1 0 0.82 0.7 1
10 ASBCELLPATHWAY B cells require interaction with helper T cells to produce antigen-specific immunoglobulins as a key element of the human immune response. CD28, CD4, CD80, HLA-DRA, HLA-DRB1, IL10, IL2, IL4, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 7 CD28(1), CD80(4), HLA-DRA(8), IL10(2), IL4(1) 1318652 16 16 16 3 8 3 0 2 3 0 0.21 0.71 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle