Mutation Analysis (MutSig v2.0)
Rectum Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C12805VQ
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C12805VQ
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: READ-TP

  • Number of patients in set: 69

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:READ-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 15

  • Mutations seen in COSMIC: 222

  • Significantly mutated genes in COSMIC territory: 10

  • Genes with clustered mutations (≤ 3 aa apart): 117

  • Significantly mutated genesets: 111

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

Mutation Preprocessing

  • Read 38 MAFs of type "Broad"

  • Read 35 MAFs of type "Baylor"

  • Total number of mutations in input MAFs: 29413

  • After removing 257 invalidated mutations: 29156

  • After removing 200 noncoding mutations: 28956

  • After collapsing adjacent/redundant mutations: 21679

Mutation Filtering

  • Number of mutations before filtering: 21679

  • After removing 200 mutations outside gene set: 21479

  • After removing 172 mutations outside category set: 21307

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 20933

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 4
De_novo_Start_OutOfFrame 30
Frame_Shift_Del 151
Frame_Shift_Ins 155
In_Frame_Del 27
In_Frame_Ins 7
Missense_Mutation 14471
Nonsense_Mutation 1779
Nonstop_Mutation 6
Read-through 10
Silent 4629
Splice_Site 38
Total 21307
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
*CpG->T 4919 99673101 0.000049 49 5.4
*Cp(A/C/T)->mut 6673 832257993 8e-06 8 0.89
A->mut 2743 908854391 3e-06 3 0.33
*CpG->(G/A) 135 99673101 1.4e-06 1.4 0.15
indel+null 2050 1840785523 1.1e-06 1.1 0.12
double_null 157 1840785523 8.5e-08 0.085 0.0094
Total 16677 1840785523 9.1e-06 9.1 1
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: READ-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: *Cp(A/C/T)->mut

  • n3 = number of nonsilent mutations of type: A->mut

  • n4 = number of nonsilent mutations of type: *CpG->(G/A)

  • 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_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: 15. 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_cons p_joint p q
1 APC adenomatous polyposis coli 576224 66 57 56 0 1 4 4 0 39 18 3.9e-15 0.97 0 <1.00e-15 <5.97e-12
2 TP53 tumor protein p53 79667 45 45 30 1 19 6 6 2 12 0 1.2e-15 6e-07 0 <1.00e-15 <5.97e-12
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 48604 38 38 8 0 0 36 1 0 1 0 6e-15 0.0029 0 <1.00e-15 <5.97e-12
4 SMAD4 SMAD family member 4 115264 8 8 6 0 2 3 3 0 0 0 8.1e-11 0.2 0.26 5.42e-10 2.43e-06
5 KIAA1804 162266 11 9 9 0 7 3 1 0 0 0 1.2e-08 0.051 0.05 1.39e-08 4.97e-05
6 FBXW7 F-box and WD repeat domain containing 7 177744 12 9 10 0 6 2 2 0 2 0 2e-08 0.08 0.079 3.26e-08 9.74e-05
7 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 40433 5 5 4 0 0 3 2 0 0 0 1.1e-07 0.49 0.026 5.75e-08 0.000147
8 TCF7L2 transcription factor 7-like 2 (T-cell specific, HMG-box) 119026 7 7 7 1 2 3 0 0 2 0 1e-07 0.085 0.11 2.21e-07 0.000495
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 194975 7 7 7 1 1 3 3 0 0 0 2.1e-07 0.46 0.15 5.72e-07 0.00114
10 OPCML opioid binding protein/cell adhesion molecule-like 73709 6 6 6 1 1 3 0 0 2 0 2.8e-07 0.51 0.68 3.17e-06 0.00567
11 KRTAP5-5 keratin associated protein 5-5 34487 2 2 1 0 0 0 0 2 0 0 0.000021 0.0062 0.013 4.50e-06 0.00733
12 SMAD2 SMAD family member 2 98964 5 5 5 0 0 3 1 0 1 0 0.000022 0.37 0.02 6.84e-06 0.0102
13 SPATA8 spermatogenesis associated 8 20140 3 3 3 0 0 0 3 0 0 0 4.2e-06 0.51 0.16 1.03e-05 0.0142
14 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 227547 4 4 2 1 4 0 0 0 0 0 0.024 0.031 0.00013 4.17e-05 0.0533
15 IL1RAPL2 interleukin 1 receptor accessory protein-like 2 139823 5 5 4 2 2 1 0 0 2 0 0.000022 1 0.17 4.90e-05 0.0586
16 FAM123B family with sequence similarity 123B 190503 8 6 8 1 0 2 1 0 5 0 0.000081 0.71 0.14 0.000144 0.161
17 ZIM3 zinc finger, imprinted 3 98103 6 5 6 0 1 1 3 0 1 0 6e-05 0.12 0.25 0.000184 0.194
18 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 152490 5 4 5 0 2 0 0 0 1 2 0.00052 0.62 0.043 0.000260 0.259
19 CSMD1 CUB and Sushi multiple domains 1 392008 12 9 12 2 4 4 2 0 1 1 0.000024 0.75 1 0.000279 0.263
20 SGCB sarcoglycan, beta (43kDa dystrophin-associated glycoprotein) 64145 4 4 4 0 0 3 0 0 0 1 0.000046 0.74 0.7 0.000366 0.328
21 LRRTM2 leucine rich repeat transmembrane neuronal 2 59242 5 4 5 1 1 1 2 1 0 0 0.000035 0.82 1 0.000397 0.333
22 FAT4 FAT tumor suppressor homolog 4 (Drosophila) 968552 17 10 17 5 5 8 3 0 1 0 0.00043 0.56 0.086 0.000411 0.333
23 GFRA1 GDNF family receptor alpha 1 86296 5 5 5 1 1 0 3 0 1 0 0.000046 0.97 0.88 0.000452 0.333
24 CCBP2 chemokine binding protein 2 79700 5 5 5 0 1 2 2 0 0 0 5e-05 0.36 0.84 0.000468 0.333
25 LIFR leukemia inhibitory factor receptor alpha 228178 5 5 5 2 0 2 1 1 1 0 0.00036 0.069 0.12 0.000492 0.333
26 EPYC epiphycan 67872 4 3 4 0 1 1 1 1 0 0 0.0006 0.49 0.075 0.000497 0.333
27 OSBPL6 oxysterol binding protein-like 6 208053 5 5 5 0 1 2 0 2 0 0 0.0003 0.078 0.16 0.000502 0.333
28 FAM133A family with sequence similarity 133, member A 38160 2 2 2 1 0 1 0 0 1 0 0.0012 0.034 0.041 0.000547 0.350
29 CASP14 caspase 14, apoptosis-related cysteine peptidase 51900 5 4 4 0 4 1 0 0 0 0 0.00018 0.7 0.3 0.000599 0.370
30 LPHN3 latrophilin 3 147364 7 6 7 3 3 3 1 0 0 0 0.000059 0.45 1 0.000633 0.374
31 MAP2K3 mitogen-activated protein kinase kinase 3 67262 4 4 4 0 1 1 1 1 0 0 6e-05 0.65 1 0.000648 0.374
32 PCDHA13 protocadherin alpha 13 162857 8 6 8 0 3 1 2 1 1 0 0.000098 0.97 0.66 0.000689 0.385
33 CSMD3 CUB and Sushi multiple domains 3 787754 11 9 11 6 2 4 2 2 1 0 0.00014 0.23 0.52 0.000756 0.402
34 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 71547 3 3 3 0 0 0 0 0 3 0 0.00087 0.35 0.083 0.000764 0.402
35 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 162026 4 4 4 0 1 2 1 0 0 0 0.00083 0.38 0.094 0.000812 0.407
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: 10. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 38 52 37 3588 363199 1.6e-13 7.2e-10
2 TP53 tumor protein p53 45 824 45 56856 17987 1.6e-12 2.4e-09
3 APC adenomatous polyposis coli 66 839 50 57891 1048 1.6e-12 2.4e-09
4 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 5 33 5 2277 5755 3.1e-11 3.5e-08
5 FBXW7 F-box and WD repeat domain containing 7 12 91 6 6279 329 4.5e-11 4.1e-08
6 SMAD4 SMAD family member 4 8 159 6 10971 39 1.2e-09 9.2e-07
7 KRTAP5-5 keratin associated protein 5-5 2 1 2 69 2 1.9e-07 0.00012
8 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 4 42 3 2898 6 3e-06 0.0017
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 7 220 4 15180 1382 0.000013 0.0067
10 LRP1B low density lipoprotein-related protein 1B (deleted in tumors) 20 18 2 1242 2 0.000063 0.028

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
3873 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 38 0 278 416 445 278 416 445
7548 TP53 tumor protein p53 45 0 37 61 105 37 61 105
392 APC adenomatous polyposis coli 66 0 11 21 47 11 21 47
2614 FBXW7 F-box and WD repeat domain containing 7 12 0 6 6 6 6 6 6
4876 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 5 0 6 6 6 6 6 6
6842 SMAD4 SMAD family member 4 8 0 4 4 6 4 4 6
2361 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 4 0 3 3 3 3 3 3
3783 KIAA1804 11 0 2 6 7 2 6 7
3466 IL1RAPL2 interleukin 1 receptor accessory protein-like 2 5 0 1 3 3 1 3 3
2083 DNAH5 dynein, axonemal, heavy chain 5 19 0 1 2 2 1 2 2

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: 111. 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 q
1 WNT_SIGNALING Wnt signaling genes APC, ARHA, AXIN1, C2orf31, CCND1, CCND2, CCND3, CSNK1E, CSNK1E, LOC400927, CTNNB1, DIPA, DVL1, DVL2, DVL3, FBXW2, FOSL1, FRAT1, FZD1, FZD10, FZD2, FZD3, FZD5, FZD6, FZD7, FZD8, FZD9, GSK3B, JUN, LDLR, MAPK10, MAPK9, MYC, PAFAH1B1, PLAU, PPP2R5C, PPP2R5E, PRKCA, PRKCB1, PRKCD, PRKCE, PRKCG, PRKCH, PRKCI, PRKCM, PRKCQ, PRKCZ, PRKD1, RAC1, RHOA, SFRP4, TCF7, WNT1, WNT10A, WNT10B, WNT11, WNT16, WNT2, WNT2B, WNT3, WNT4, WNT5A, WNT5B, WNT6, WNT7A, WNT7B 57 APC(66), AXIN1(1), CTNNB1(4), DVL2(1), DVL3(2), FBXW2(1), FZD1(1), FZD10(2), FZD3(3), FZD6(3), GSK3B(1), LDLR(1), MAPK10(4), MAPK9(2), PLAU(1), PPP2R5C(1), PRKCA(2), PRKCE(2), PRKCG(2), PRKCH(1), PRKCQ(1), PRKD1(5), RHOA(1), SFRP4(1), TCF7(3), WNT10B(1), WNT2(1), WNT2B(2), WNT6(1) 5514820 117 58 107 13 15 27 8 0 49 18 <1.00e-15 <8.25e-14
2 TELPATHWAY Telomerase is a ribonucleotide protein that adds telomeric repeats to the 3' ends of chromosomes. AKT1, BCL2, EGFR, G22P1, HSPCA, IGF1R, KRAS2, MYC, POLR2A, PPP2CA, PRKCA, RB1, TEP1, TERF1, TERT, TNKS, TP53, XRCC5 15 EGFR(1), IGF1R(1), PRKCA(2), RB1(3), TERF1(1), TP53(45), XRCC5(2) 2767314 55 48 40 6 22 9 9 2 13 0 <1.00e-15 <8.25e-14
3 HSA04810_REGULATION_OF_ACTIN_CYTOSKELETON Genes involved in regulation of actin cytoskeleton ABI2, ACTN1, ACTN2, ACTN3, ACTN4, APC, APC2, ARAF, ARHGEF1, ARHGEF12, ARHGEF4, ARHGEF6, ARHGEF7, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, ARPC5, ARPC5L, BAIAP2, BCAR1, BDKRB1, BDKRB2, BRAF, C3orf10, CD14, CDC42, CFL1, CFL2, CHRM1, CHRM2, CHRM3, CHRM4, CHRM5, CRK, CRKL, CSK, CYFIP1, CYFIP2, DIAPH1, DIAPH2, DIAPH3, DOCK1, EGF, EGFR, EZR, F2, F2R, FGD1, FGD3, FGF1, FGF10, FGF11, FGF12, FGF13, FGF14, FGF16, FGF17, FGF18, FGF19, FGF2, FGF20, FGF21, FGF22, FGF23, FGF3, FGF4, FGF5, FGF6, FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FN1, GIT1, GNA12, GNA13, GNG12, GRLF1, GSN, HRAS, INS, IQGAP1, IQGAP2, IQGAP3, ITGA1, ITGA10, ITGA11, ITGA2, ITGA2B, ITGA3, ITGA4, ITGA5, ITGA6, ITGA7, ITGA8, ITGA9, ITGAD, ITGAE, ITGAL, ITGAM, ITGAV, ITGAX, ITGB1, ITGB2, ITGB3, ITGB4, ITGB5, ITGB6, ITGB7, ITGB8, KRAS, LIMK1, LIMK2, LOC200025, LOC645126, LOC653888, MAP2K1, MAP2K2, MAPK1, MAPK3, MLCK, MOS, MRAS, MRCL3, MRLC2, MSN, MYH10, MYH14, MYH9, MYL2, MYL5, MYL7, MYL8P, MYL9, MYLC2PL, MYLK, MYLK2, MYLPF, NCKAP1, NCKAP1L, NRAS, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PDGFA, PDGFB, PDGFRA, PDGFRB, PFN1, PFN2, PFN3, PFN4, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PIP4K2A, PIP4K2B, PIP4K2C, PIP5K1A, PIP5K1B, PIP5K1C, PIP5K3, PPP1CA, PPP1CB, PPP1CC, PPP1R12A, PPP1R12B, PTK2, PXN, RAC1, RAC2, RAC3, RAF1, RDX, RHOA, ROCK1, ROCK2, RRAS, RRAS2, SCIN, SLC9A1, SOS1, SOS2, SSH1, SSH2, SSH3, TIAM1, TIAM2, TMSB4X, TMSB4Y, TMSL3, VAV1, VAV2, VAV3, VCL, WAS, WASF1, WASF2, WASL 203 ABI2(1), ACTN1(2), ACTN2(1), ACTN3(1), ACTN4(1), APC(66), ARHGEF1(1), ARHGEF12(2), ARHGEF4(1), ARHGEF6(3), ARPC2(1), ARPC5L(1), BAIAP2(1), BDKRB2(1), BRAF(2), CDC42(1), CHRM2(3), CHRM4(1), CHRM5(1), CSK(2), CYFIP1(1), CYFIP2(1), DIAPH2(3), DIAPH3(2), DOCK1(2), EGFR(1), F2(1), FGD1(2), FGD3(1), FGF11(1), FGF12(1), FGF13(1), FGF19(1), FGF20(1), FGF5(2), FGFR1(1), FGFR2(5), FN1(4), GIT1(1), GRLF1(5), IQGAP1(3), IQGAP2(3), ITGA10(4), ITGA11(2), ITGA2(1), ITGA2B(2), ITGA4(5), ITGA6(1), ITGA8(3), ITGA9(2), ITGAD(1), ITGAE(2), ITGAL(3), ITGAM(3), ITGAV(4), ITGAX(2), ITGB2(1), ITGB3(2), ITGB4(1), ITGB5(1), ITGB8(1), KRAS(38), LIMK1(1), LIMK2(1), MAP2K1(1), MAP2K2(1), MAPK3(1), MOS(1), MSN(3), MYH10(2), MYH14(3), MYH9(3), MYL9(2), MYLK(3), MYLK2(1), NCKAP1(1), NCKAP1L(4), NRAS(5), PAK1(1), PAK2(1), PAK3(2), PAK7(3), PDGFRA(4), PDGFRB(1), PIK3CA(7), PIK3CD(1), PIK3CG(2), PIK3R1(5), PIK3R3(4), PIP5K1B(1), PIP5K1C(1), PPP1CB(1), PPP1CC(1), PPP1R12A(1), PPP1R12B(4), RAF1(2), RDX(1), RHOA(1), ROCK1(7), ROCK2(4), RRAS2(1), SCIN(1), SLC9A1(2), SOS1(2), SOS2(2), SSH1(2), SSH3(1), TIAM1(5), TIAM2(2), VAV1(2), VAV2(2), VAV3(2), VCL(1), WASF1(2), WASL(2) 26346557 332 66 291 70 74 124 38 4 72 20 1.11e-15 8.25e-14
4 ALKPATHWAY Activin receptor-like kinase 3 (ALK3) is required during gestation for cardiac muscle development. ACVR1, APC, ATF2, AXIN1, BMP10, BMP2, BMP4, BMP5, BMP7, BMPR1A, BMPR2, CHRD, CTNNB1, DVL1, FZD1, GATA4, GSK3B, MADH1, MADH4, MADH5, MADH6, MAP3K7, MEF2C, MYL2, NKX2-5, NOG, NPPA, NPPB, RFC1, TCF1, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, WNT1 31 ACVR1(1), APC(66), ATF2(1), AXIN1(1), BMP10(1), BMP2(1), BMP4(1), BMP5(1), BMP7(1), BMPR2(3), CTNNB1(4), FZD1(1), GSK3B(1), MAP3K7(2), MEF2C(2), NPPB(1), RFC1(4), TGFB2(4), TGFBR1(3), TGFBR3(3) 3414527 102 59 92 3 13 19 9 0 43 18 1.11e-15 8.25e-14
5 HSA04664_FC_EPSILON_RI_SIGNALING_PATHWAY Genes involved in Fc epsilon RI signaling pathway AKT1, AKT2, AKT3, BTK, CSF2, FCER1A, FCER1G, FYN, GAB2, GRB2, HRAS, IL13, IL3, IL4, IL5, INPP5D, KRAS, LAT, LCP2, LYN, MAP2K1, MAP2K2, MAP2K3, MAP2K4, MAP2K6, MAP2K7, MAPK1, MAPK10, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPK8, MAPK9, MS4A2, NRAS, PDK1, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLCG1, PLCG2, PRKCA, PRKCB1, PRKCD, PRKCE, RAC1, RAC2, RAC3, RAF1, SOS1, SOS2, SYK, TNF, VAV1, VAV2, VAV3 74 AKT2(1), AKT3(1), BTK(1), FCER1A(1), FYN(1), GRB2(1), INPP5D(2), KRAS(38), LAT(1), LCP2(1), MAP2K1(1), MAP2K2(1), MAP2K3(4), MAP2K4(2), MAP2K6(1), MAPK10(4), MAPK13(1), MAPK3(1), MAPK8(5), MAPK9(2), MS4A2(2), NRAS(5), PDK1(2), PIK3CA(7), PIK3CD(1), PIK3CG(2), PIK3R1(5), PIK3R3(4), PLA2G4A(3), PLA2G6(2), PLCG2(4), PRKCA(2), PRKCE(2), RAF1(2), SOS1(2), SOS2(2), SYK(3), VAV1(2), VAV2(2), VAV3(2) 6895491 126 49 95 19 28 63 16 2 15 2 1.11e-15 8.25e-14
6 ST_WNT_BETA_CATENIN_PATHWAY Beta-catenin is degraded in the absence of Wnt signaling; when extracellular Wnt binds Frizzled receptors, beta-catenin accumulates in the nucleus and may promote cell survival. AKT1, AKT2, AKT3, ANKRD6, APC, AXIN1, AXIN2, C22orf2, CER1, CSNK1A1, CTNNB1, DACT1, DKK1, DKK2, DKK3, DKK4, DVL1, FRAT1, FSTL1, GSK3A, GSK3B, IDAX, LAMR1, LRP1, MVP, NKD1, NKD2, PIN1, PSEN1, PTPRA, SENP2, SFRP1, TSHB, WIF1 29 AKT2(1), AKT3(1), APC(66), AXIN1(1), AXIN2(2), CTNNB1(4), DACT1(1), DKK1(2), DKK2(1), DKK4(3), FSTL1(1), GSK3B(1), LRP1(3), SENP2(1), SFRP1(1), TSHB(1) 3759900 90 59 80 4 8 14 11 0 39 18 1.33e-15 8.25e-14
7 HSA04370_VEGF_SIGNALING_PATHWAY Genes involved in VEGF signaling pathway AKT1, AKT2, AKT3, BAD, CASP9, CDC42, CHP, HRAS, KDR, KRAS, MAP2K1, MAP2K2, MAPK1, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPKAPK2, MAPKAPK3, NFAT5, NFATC1, NFATC2, NFATC3, NFATC4, NOS3, NRAS, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLCG1, PLCG2, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRKCA, PRKCB1, PRKCG, PTGS2, PTK2, PXN, RAC1, RAC2, RAC3, RAF1, SH2D2A, SHC2, SPHK1, SPHK2, SRC, VEGFA 69 AKT2(1), AKT3(1), CDC42(1), KDR(2), KRAS(38), MAP2K1(1), MAP2K2(1), MAPK13(1), MAPK3(1), NFATC1(1), NFATC2(2), NFATC3(1), NFATC4(1), NRAS(5), PIK3CA(7), PIK3CD(1), PIK3CG(2), PIK3R1(5), PIK3R3(4), PLA2G4A(3), PLA2G6(2), PLCG2(4), PPP3CA(2), PPP3CB(1), PPP3CC(1), PRKCA(2), PRKCG(2), PTGS2(1), RAF1(2), SH2D2A(1), SHC2(1), SPHK1(1) 6915053 99 50 68 19 27 50 10 0 10 2 1.44e-15 8.25e-14
8 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 17 DNAJA3(1), IFNGR1(1), IFNGR2(1), IKBKB(2), JAK2(3), NFKB1(3), RB1(3), TP53(45), USH1C(3), WT1(2) 1809425 64 48 49 6 25 14 7 2 15 1 1.55e-15 8.25e-14
9 TGFBPATHWAY The TGF-beta receptor responds to ligand binding by activating the SMAD family of transcriptional regulations, commonly blocking cell growth. APC, CDH1, CREBBP, EP300, MADH2, MADH3, MADH4, MADH7, MADHIP, MAP2K1, MAP3K7, MAP3K7IP1, MAPK3, SKIL, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2 13 APC(66), CDH1(1), CREBBP(4), EP300(2), MAP2K1(1), MAP3K7(2), MAPK3(1), SKIL(1), TGFB2(4), TGFBR1(3) 2554178 85 57 75 4 5 10 8 0 44 18 1.78e-15 8.25e-14
10 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 BTK(1), CAD(1), CASP3(1), CASP8AP2(6), DAXX(1), DEDD(1), DFFA(1), EGFR(1), EPHB2(1), IL8(1), MAP2K4(2), MAP3K1(2), MAP3K5(1), MAPK10(4), MAPK8(5), MAPK8IP3(1), MAPK9(2), MET(1), NFKB1(3), NFKB2(2), PTPN13(9), RALBP1(2), ROCK1(7), TP53(45), TPX2(1) 6826271 102 50 87 17 34 28 17 3 20 0 2.00e-15 8.25e-14

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 q
1 C21_STEROID_HORMONE_METABOLISM AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 11 AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) 837086 11 10 11 2 3 5 1 0 2 0 0.0014 0.3
2 HSA00140_C21_STEROID_HORMONE_METABOLISM Genes involved in C21-steroid hormone metabolism AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 11 AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) 837086 11 10 11 2 3 5 1 0 2 0 0.0014 0.3
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(1), ERBB4(5), NRG2(2), NRG3(4), PRKCA(2) 908762 14 9 14 1 4 5 1 1 3 0 0.0014 0.3
4 HCMVPATHWAY Cytomegalovirus activates MAP kinase pathways in the host cell, inducing transcription of viral genes. AKT1, CREB1, MAP2K1, MAP2K2, MAP2K3, MAP2K6, MAP3K1, MAPK1, MAPK14, MAPK3, NFKB1, PIK3CA, PIK3R1, RB1, RELA, SP1 15 MAP2K1(1), MAP2K2(1), MAP2K3(4), MAP2K6(1), MAP3K1(2), MAPK3(1), NFKB1(3), PIK3R1(5), RB1(3) 1720824 21 10 21 3 7 4 4 1 3 2 0.004 0.54
5 HSA00240_PYRIMIDINE_METABOLISM Genes involved in pyrimidine metabolism AICDA, AK3, CAD, CANT1, CDA, CMPK, CTPS, CTPS2, DCK, DCTD, DHODH, DPYD, DPYS, DTYMK, DUT, ECGF1, ENTPD1, ENTPD3, ENTPD4, ENTPD5, ENTPD6, ENTPD8, ITPA, NME1, NME2, NME4, NME6, NME7, NP, NT5C, NT5C1A, NT5C1B, NT5C2, NT5C3, NT5E, NT5M, NUDT2, PNPT1, POLA1, POLA2, POLD1, POLD2, POLD3, POLD4, POLE, POLE2, POLE3, POLE4, POLR1A, POLR1B, POLR1C, POLR1D, POLR2A, POLR2B, POLR2C, POLR2D, POLR2E, POLR2F, POLR2G, POLR2H, POLR2I, POLR2J, POLR2K, POLR2L, POLR3A, POLR3B, POLR3G, POLR3GL, POLR3H, POLR3K, PRIM1, PRIM2, RFC5, RRM1, RRM2, RRM2B, TK1, TK2, TXNRD1, TXNRD2, TYMS, UCK1, UCK2, UMPS, UPB1, UPP1, UPP2, UPRT, ZNRD1 86 AICDA(1), CAD(1), CTPS(1), DCK(1), DHODH(1), DPYD(6), DPYS(1), DTYMK(1), ENTPD5(1), ENTPD6(1), NME6(1), NME7(2), NT5C1B(1), NT5C2(1), NT5E(1), PNPT1(5), POLA1(3), POLE(4), POLE2(1), POLR1A(3), POLR1B(2), POLR2B(3), POLR2K(1), POLR3A(4), POLR3B(5), POLR3K(1), PRIM2(3), RFC5(1), RRM1(1), TK2(1), TXNRD1(1), TXNRD2(1), TYMS(1), UMPS(1), UPB1(2), UPP2(1), UPRT(1) 7933506 67 28 65 15 18 26 10 0 13 0 0.0046 0.54
6 CREMPATHWAY The transcription factor CREM activates a post-meiotic transcriptional cascade culminating in spermatogenesis. ADCY1, CREM, FHL5, FSHB, FSHR, GNAS, XPO1 7 ADCY1(4), FHL5(3), FSHB(1), FSHR(1), XPO1(1) 917313 10 9 10 4 4 1 3 1 1 0 0.0053 0.54
7 GSPATHWAY Activated G-protein coupled receptors stimulate cAMP production and thus activate protein kinase A, involved in a number of signal transduction pathways. ADCY1, GNAS, GNB1, GNGT1, PRKACA, PRKAR1A 6 ADCY1(4), GNGT1(1), PRKACA(1), PRKAR1A(4) 607553 10 8 10 1 3 4 1 0 2 0 0.0071 0.62
8 PAR1PATHWAY Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. ADCY1, ARHA, ARHGEF1, F2, F2R, F2RL3, GNA12, GNA13, GNAI1, GNAQ, GNB1, GNGT1, MAP3K7, PIK3CA, PIK3R1, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2B, ROCK1 18 ADCY1(4), ARHGEF1(1), F2(1), GNAI1(1), GNAQ(1), GNGT1(1), MAP3K7(2), PIK3R1(5), PPP1R12B(4), PRKCA(2), ROCK1(7) 2322908 29 13 29 7 8 7 5 0 7 2 0.008 0.62
9 NEUROTRANSMITTERSPATHWAY Biosynthesis of neurotransmitters DBH, GAD1, HDC, PNMT, TH, TPH1 6 DBH(1), GAD1(2), HDC(5), TPH1(2) 572489 10 7 10 2 3 5 1 0 1 0 0.01 0.69
10 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM Genes involved in androgen and estrogen metabolism AKR1C4, AKR1D1, ARSD, ARSE, CARM1, CYP11B1, CYP11B2, CYP19A1, HEMK1, HSD11B1, HSD11B2, HSD17B1, HSD17B12, HSD17B2, HSD17B3, HSD17B7, HSD17B8, HSD3B1, HSD3B2, LCMT1, LCMT2, METTL2B, METTL6, PRMT2, PRMT3, PRMT5, PRMT6, PRMT7, PRMT8, SRD5A1, SRD5A2, STS, SULT1E1, SULT2A1, SULT2B1, UGT1A1, UGT1A10, UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT2A1, UGT2A3, UGT2B10, UGT2B11, UGT2B15, UGT2B17, UGT2B28, UGT2B4, UGT2B7, WBSCR22 53 AKR1C4(1), AKR1D1(1), CYP11B1(4), CYP19A1(3), HSD17B2(1), HSD17B3(1), HSD3B1(1), HSD3B2(1), LCMT1(2), METTL2B(1), METTL6(3), PRMT3(1), PRMT7(1), PRMT8(2), SRD5A2(1), STS(1), SULT1E1(1), SULT2A1(1), UGT1A4(1), UGT1A6(1), UGT1A8(1), UGT1A9(1), UGT2A3(2), UGT2B11(2), UGT2B17(3), UGT2B28(1), UGT2B4(1), UGT2B7(2) 4462401 42 18 42 9 9 19 6 1 7 0 0.012 0.7
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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