Mutation Analysis (MutSig v2.0)
Stomach Adenocarcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1Z0365M
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Stomach Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1Z0365M
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: 116

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

  • Significantly mutated genes (q ≤ 0.1): 37

  • Mutations seen in COSMIC: 291

  • Significantly mutated genes in COSMIC territory: 19

  • Genes with clustered mutations (≤ 3 aa apart): 969

  • Significantly mutated genesets: 17

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

Mutation Preprocessing

  • Read 116 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 192216

  • After removing 5994 blacklisted mutations: 186222

  • After removing 102470 noncoding mutations: 83752

  • After collapsing adjacent/redundant mutations: 64521

Mutation Filtering

  • Number of mutations before filtering: 64521

  • After removing 316 mutations outside gene set: 64205

  • After removing 72 mutations outside category set: 64133

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 63743

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1639
Frame_Shift_Ins 233
In_Frame_Del 111
In_Frame_Ins 7
Missense_Mutation 41478
Nonsense_Mutation 1924
Nonstop_Mutation 47
Silent 17734
Splice_Site 936
Translation_Start_Site 24
Total 64133
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 14400 187756957 0.000077 77 5.6 2.1
*Np(A/C/T)->transit 14106 2700753364 5.2e-06 5.2 0.38 2
*ApG->G 1984 523468245 3.8e-06 3.8 0.28 2.1
transver 11010 3411978566 3.2e-06 3.2 0.24 5
indel+null 4829 3411978566 1.4e-06 1.4 0.1 NaN
double_null 69 3411978566 2e-08 0.02 0.0015 NaN
Total 46398 3411978566 0.000014 14 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).

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

CoMut Plot

Figure 3.  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: 37. 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_cons p_joint p q
1 TP53 tumor protein p53 144134 56 52 41 1 18 12 1 7 17 1 1.1e-15 2.6e-06 1.6e-06 0 <1.00e-15 <2.57e-12
2 PGM5 phosphoglucomutase 5 164179 19 16 5 0 3 14 0 0 2 0 1.2e-09 0.00064 1 0 <1.00e-15 <2.57e-12
3 CBWD1 COBW domain containing 1 115744 15 14 2 0 0 1 0 0 14 0 5.1e-11 0.076 8.8e-06 0 <1.00e-15 <2.57e-12
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 81393 14 14 6 0 0 10 0 4 0 0 6.1e-14 0.013 0.00087 0 <1.00e-15 <2.57e-12
5 TRIM48 tripartite motif-containing 48 74295 10 10 2 0 0 9 0 1 0 0 6.5e-08 0.018 0.86 0 <1.00e-15 <2.57e-12
6 RPL22 ribosomal protein L22 44234 9 9 1 0 0 0 0 0 9 0 6e-09 1 0.06 0 <1.00e-15 <2.57e-12
7 XPOT exportin, tRNA (nuclear export receptor for tRNAs) 345938 6 6 1 10 0 6 0 0 0 0 1 1 0.98 0 <1.00e-15 <2.57e-12
8 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 381238 32 24 19 2 5 19 3 4 1 0 5.7e-12 0.0015 0.05 0.0037 6.84e-13 1.54e-09
9 ACVR2A activin A receptor, type IIA 183945 14 13 5 0 0 3 0 1 10 0 3.4e-09 0.28 0.022 0.000027 2.89e-12 5.78e-09
10 RHOA ras homolog gene family, member A 69368 8 7 4 0 0 5 0 3 0 0 4.1e-08 0.089 0.23 0.000064 7.28e-11 1.31e-07
11 ARID1A AT rich interactive domain 1A (SWI-like) 674991 24 22 23 1 4 1 0 4 13 2 3.2e-10 0.03 0.14 0.42 3.19e-09 5.21e-06
12 OR8H3 olfactory receptor, family 8, subfamily H, member 3 109388 10 10 8 1 0 4 3 3 0 0 4.5e-08 0.1 0.016 0.048 4.48e-08 6.73e-05
13 EDNRB endothelin receptor type B 161210 13 12 12 2 5 4 0 1 3 0 1.3e-07 0.14 0.95 0.2 4.57e-07 0.000595
14 ZNF804B zinc finger protein 804B 471407 20 18 19 1 0 6 0 11 3 0 7.3e-08 0.042 0.74 0.34 4.63e-07 0.000595
15 IRF2 interferon regulatory factor 2 125493 10 8 10 1 4 0 0 4 1 1 0.00012 0.2 0.034 0.00062 1.33e-06 0.00160
16 IAPP islet amyloid polypeptide 32248 4 4 3 0 0 0 0 4 0 0 0.00012 0.47 0.98 0.002 3.99e-06 0.00449
17 PCDH15 protocadherin 15 860677 23 22 23 3 1 5 5 8 4 0 1.8e-06 0.033 1 0.38 1.07e-05 0.0114
18 SPRYD5 SPRY domain containing 5 106259 8 8 6 0 0 0 1 2 5 0 9.6e-07 0.45 1 1 1.42e-05 0.0142
19 TUSC3 tumor suppressor candidate 3 124898 9 9 8 0 3 1 0 5 0 0 8.6e-06 0.13 0.2 0.18 2.26e-05 0.0214
20 FGF22 fibroblast growth factor 22 21067 3 3 1 1 0 0 0 0 3 0 0.0011 1 0.98 0.0016 2.52e-05 0.0227
21 HLA-B major histocompatibility complex, class I, B 115097 9 9 9 0 1 2 1 1 3 1 4.8e-06 0.059 0.17 0.4 2.73e-05 0.0234
22 PTH2 parathyroid hormone 2 24302 3 3 1 0 0 0 0 3 0 0 0.0013 0.43 0.13 0.0016 3.07e-05 0.0252
23 C17orf63 chromosome 17 open reading frame 63 8520 3 3 3 0 1 0 0 1 1 0 0.000035 0.33 NaN NaN 3.47e-05 0.0272
24 SMAD4 SMAD family member 4 197386 8 7 7 1 3 1 0 2 2 0 0.000087 0.41 0.12 0.032 3.81e-05 0.0286
25 POTEG POTE ankyrin domain family, member G 142733 6 6 6 0 0 4 1 0 1 0 0.00092 0.13 0.79 0.004 4.97e-05 0.0358
26 RNF43 ring finger protein 43 253364 14 13 9 2 1 4 0 0 9 0 0.000052 0.42 0.21 0.085 5.96e-05 0.0413
27 WBSCR17 Williams-Beuren syndrome chromosome region 17 208730 14 12 12 1 6 5 2 1 0 0 0.000072 0.026 0.66 0.094 8.72e-05 0.0582
28 PHF2 PHD finger protein 2 308623 13 12 5 4 2 1 0 1 9 0 0.011 0.88 0.43 0.00068 9.57e-05 0.0606
29 TPTE transmembrane phosphatase with tensin homology 201815 15 14 15 3 2 0 1 11 1 0 1e-05 0.44 0.89 0.75 9.75e-05 0.0606
30 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 294862 12 11 12 4 1 4 1 4 2 0 0.00099 0.49 0.018 0.0086 0.000109 0.0650
31 CPS1 carbamoyl-phosphate synthetase 1, mitochondrial 541853 14 13 14 2 3 2 2 6 1 0 0.0036 0.22 0.19 0.0024 0.000112 0.0650
32 INO80E INO80 complex subunit E 47311 5 5 2 0 1 0 0 0 4 0 0.00042 0.64 0.036 0.022 0.000118 0.0662
33 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 132764 6 5 6 1 0 3 0 3 0 0 0.044 0.39 0.00012 0.00025 0.000134 0.0734
34 PARK2 Parkinson disease (autosomal recessive, juvenile) 2, parkin 165616 9 9 9 1 3 3 0 2 1 0 0.00021 0.17 0.49 0.069 0.000174 0.0922
35 TM7SF4 transmembrane 7 superfamily member 4 165300 7 7 7 1 1 0 2 2 2 0 0.000064 0.32 0.91 0.25 0.000194 0.0981
TP53

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

PGM5

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.

KRAS

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

TRIM48

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TRIM48 significant gene.

RPL22

Figure S5.  This figure depicts the distribution of mutations and mutation types across the RPL22 significant gene.

XPOT

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

PIK3CA

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

ACVR2A

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ACVR2A significant gene.

RHOA

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

ARID1A

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

OR8H3

Figure S11.  This figure depicts the distribution of mutations and mutation types across the OR8H3 significant gene.

EDNRB

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

ZNF804B

Figure S13.  This figure depicts the distribution of mutations and mutation types across the ZNF804B significant gene.

IRF2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the IRF2 significant gene.

PCDH15

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PCDH15 significant gene.

SPRYD5

Figure S16.  This figure depicts the distribution of mutations and mutation types across the SPRYD5 significant gene.

TUSC3

Figure S17.  This figure depicts the distribution of mutations and mutation types across the TUSC3 significant gene.

FGF22

Figure S18.  This figure depicts the distribution of mutations and mutation types across the FGF22 significant gene.

C17orf63

Figure S19.  This figure depicts the distribution of mutations and mutation types across the C17orf63 significant gene.

SMAD4

Figure S20.  This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.

POTEG

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

RNF43

Figure S22.  This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.

WBSCR17

Figure S23.  This figure depicts the distribution of mutations and mutation types across the WBSCR17 significant gene.

PHF2

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PHF2 significant gene.

TPTE

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

CDH1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.

CPS1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CPS1 significant gene.

INO80E

Figure S28.  This figure depicts the distribution of mutations and mutation types across the INO80E significant gene.

ELF3

Figure S29.  This figure depicts the distribution of mutations and mutation types across the ELF3 significant gene.

PARK2

Figure S30.  This figure depicts the distribution of mutations and mutation types across the PARK2 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: 19. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 ACVR2A activin A receptor, type IIA 14 3 10 348 10 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 14 52 13 6032 86315 0 0
3 TP53 tumor protein p53 56 356 52 41296 18767 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 32 220 29 25520 10169 0 0
5 SMAD4 SMAD family member 4 8 159 7 18444 23 9.9e-09 9e-06
6 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 16 6 3 696 3 1.4e-07 0.00011
7 PKHD1 polycystic kidney and hepatic disease 1 (autosomal recessive) 18 8 3 928 3 3.3e-07 0.00021
8 FBXW7 F-box and WD repeat domain containing 7 8 91 5 10556 278 4.5e-07 0.00025
9 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 12 185 6 21460 27 6.7e-07 0.00034
10 ACIN1 apoptotic chromatin condensation inducer 1 6 1 2 116 2 1.2e-06 0.00051

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)

Clustered Mutations

Table 5.  Get Full Table Genes with Clustered Mutations

num gene desc n mindist nmuts0 nmuts3 nmuts12 npairs0 npairs3 npairs12
8924 PGM5 phosphoglucomutase 5 19 0 92 92 120 92 92 120
1975 CBWD1 COBW domain containing 1 15 0 91 91 91 91 91 91
12381 TP53 tumor protein p53 56 0 54 98 176 54 98 176
9019 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 32 0 38 71 83 38 71 83
12491 TRIM48 tripartite motif-containing 48 10 0 36 36 45 36 36 45
6359 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 14 0 25 55 56 25 55 56
501 ANAPC1 anaphase promoting complex subunit 1 13 0 15 15 15 15 15 15
13203 XPOT exportin, tRNA (nuclear export receptor for tRNAs) 6 0 15 15 15 15 15 15
10103 RHOA ras homolog gene family, member A 8 0 10 11 16 10 11 16
4232 FAT4 FAT tumor suppressor homolog 4 (Drosophila) 61 0 4 5 14 4 5 14

Note:

n - number of mutations in this gene in the individual set.

mindist - distance (in aa) between closest pair of mutations in this gene

npairs3 - how many pairs of mutations are within 3 aa of each other.

npairs12 - how many pairs of mutations are within 12 aa of each other.

Geneset Analyses

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 17. 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 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 DNAJC3(1), EIF2S1(1), EIF2S2(2), MAP3K14(2), NFKB1(5), RELA(1), TP53(56) 1708094 68 57 53 4 21 14 1 12 19 1 0.000037 4e-15 8.5e-13
2 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(13), ATR(5), CDC25C(2), CHEK1(1), CHEK2(5), TP53(56), YWHAH(1) 2781580 83 64 67 9 26 21 3 10 21 2 0.00084 4.4e-15 8.5e-13
3 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(2), MAX(1), SP1(3), SP3(3), TP53(56), WT1(1) 1216894 66 57 51 7 21 16 1 8 19 1 0.000092 5.8e-15 8.5e-13
4 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(8), AKT1(2), ATM(13), CDKN1A(1), CPB2(3), FHL2(2), HIC1(1), HIF1A(2), HSPA1A(1), IGFBP3(4), MAPK8(3), MDM2(3), NFKBIB(4), NQO1(2), TP53(56) 3603665 105 71 89 14 34 26 3 15 25 2 4e-05 6.7e-15 8.5e-13
5 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 ARF1(2), CCND1(1), CDK2(2), CDKN1A(1), CDKN2A(3), CFL1(1), E2F2(2), MDM2(3), NXT1(1), PRB1(2), TP53(56) 1409760 74 61 59 8 24 19 2 8 20 1 0.000094 6.9e-15 8.5e-13
6 CHEMICALPATHWAY DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 20 AKT1(2), APAF1(2), ATM(13), BAD(1), BCL2(1), BID(1), CASP3(1), CASP6(1), CASP7(2), CASP9(1), EIF2S1(1), PTK2(7), PXN(1), STAT1(4), TLN1(11), TP53(56) 4749058 105 64 89 14 37 29 5 11 21 2 0.000046 5.9e-14 6.1e-12
7 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(1), HSPA1A(1), IFNG(2), IFNGR1(2), IFNGR2(1), IKBKB(3), JAK2(8), LIN7A(4), NFKB1(5), RB1(7), RELA(1), TNF(1), TNFRSF1A(2), TNFRSF1B(1), TP53(56), USH1C(1), WT1(1) 3158351 97 64 80 14 26 24 2 21 23 1 0.00037 1.5e-13 1.3e-11
8 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(13), CDC25A(2), CDC25B(2), CDC25C(2), CDK2(2), CHEK1(1), MYT1(9), RB1(7), TP53(56), YWHAH(1) 3061869 95 64 78 11 29 27 3 12 22 2 0.00011 2e-13 1.5e-11
9 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(2), CDKN2A(3), MDM2(3), PIK3CA(32), PIK3R1(5), POLR1A(5), POLR1C(2), POLR1D(1), RB1(7), TBX2(3), TP53(56) 3505057 119 74 90 21 31 42 5 15 25 1 0.00024 8e-10 5.5e-08
10 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(2), ATM(13), BCL2(1), CCND1(1), CCNE1(3), CDK2(2), CDKN1A(1), MDM2(3), PCNA(2), RB1(7), TIMP3(2), TP53(56) 3148338 93 63 76 14 26 28 3 12 22 2 0.001 1.6e-08 1e-06

Table 7.  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(5) 125186 5 5 5 1 1 0 1 1 2 0 0.55 0.0089 1
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(2), FMOD(9), KERA(1), LUM(2) 629673 16 14 16 2 8 3 0 5 0 0 0.082 0.032 1
3 ERBB4PATHWAY ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 6 ADAM17(3), ERBB4(16), NRG2(4), NRG3(9), PSEN1(1) 1555655 33 24 33 5 7 13 4 5 4 0 0.023 0.056 1
4 TCRMOLECULE T Cell Receptor and CD3 Complex CD3D, CD3E, CD3G, CD3Z, TRA@, TRB@ 3 CD3E(2), CD3G(2) 196753 4 4 3 1 0 1 1 0 2 0 0.82 0.1 1
5 VOBESITYPATHWAY The adipose tissue of obese individuals overexpresses a key glucocorticoid-metabolizing enzyme, activating inactive circulating corticosteroids and inducing insulin resistance. APM1, HSD11B1, LPL, NR3C1, PPARG, RETN, RXRA, TNF 7 LPL(2), NR3C1(4), PPARG(1), RXRA(2), TNF(1) 999771 10 10 10 1 2 1 1 5 1 0 0.21 0.21 1
6 EOSINOPHILSPATHWAY Recruitment of eosinophils in the inflammatory response observed in asthma occurs via the chemoattractant eotaxin binding to the CCR3 receptor. CCL11, CCL5, CCR3, CSF2, HLA-DRA, HLA-DRB1, IL3, IL5 8 CCL11(1), CCL5(1), CCR3(4), HLA-DRA(3), HLA-DRB1(1), IL3(1) 526404 11 10 11 3 4 4 0 2 1 0 0.35 0.23 1
7 GCRPATHWAY Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. ADRB2, AKT1, ANXA1, CALM1, CALM2, CALM3, CRN, GNAS, GNB1, GNGT1, HSPCA, NFKB1, NOS3, NPPA, NR3C1, PIK3CA, PIK3R1, RELA, SYT1 16 ADRB2(3), AKT1(2), ANXA1(3), CALM1(1), CALM2(2), CALM3(1), GNAS(11), GNGT1(3), NFKB1(5), NOS3(3), NPPA(1), NR3C1(4), PIK3R1(5), RELA(1) 2722623 45 28 45 7 13 12 0 11 9 0 0.041 0.26 1
8 TOB1PATHWAY TGF-beta signaling activates SMADs, which interact with intracellular Tob to maintain unstimulated T cells by repressing IL-2 expression. CD28, CD3D, CD3E, CD3G, CD3Z, IFNG, IL2, IL2RA, IL4, MADH3, MADH4, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, TOB1, TOB2, TRA@, TRB@ 16 CD3E(2), CD3G(2), IFNG(2), IL2RA(1), TGFB1(3), TGFB2(6), TGFB3(3), TGFBR1(2), TGFBR2(6), TGFBR3(2), TOB1(1), TOB2(4) 1836086 34 24 33 6 6 11 3 10 4 0 0.11 0.3 1
9 FLUMAZENILPATHWAY Flumazenil is a benzodiazepine receptor antagonist that may induce protective preconditioning in ischemic cardiomyocytes. GABRA1, GABRA2, GABRA3, GABRA4, GABRA5, GABRA6, GPX1, PRKCE, SOD1 9 GABRA1(5), GABRA2(5), GABRA3(5), GABRA4(4), GABRA5(4), GABRA6(5), PRKCE(5) 1366369 33 21 33 9 11 7 5 9 1 0 0.2 0.31 1
10 PEPIPATHWAY Proepithelin (PEPI) induces epithelial cells to secrete IL-8, which promotes elastase secretion by neutrophils. ELA1, ELA2, ELA2A, ELA2B, ELA3B, GRN, IL8, SLPI 3 GRN(3), IL8(1), SLPI(1) 296007 5 4 5 1 2 2 0 1 0 0 0.39 0.38 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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