Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Rectum Adenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C16T0JQ7
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C16T0JQ7
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 and MutSigCV v0.9 merged result 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): 3

  • Mutations seen in COSMIC: 222

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 111

Mutation Preprocessing

  • Read 38 MAFs of type "Broad"

  • Read 35 MAFs of type "Baylor-SOLiD"

  • 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_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: 3. 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_cons p_joint p_cv p q
1 APC adenomatous polyposis coli 576224 66 57 56 0 1 4 4 0 39 18 0.97 0 6.6e-15 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 48604 38 38 8 0 0 36 1 0 1 0 0.0029 0 8.1e-11 0 0
3 TP53 tumor protein p53 79667 45 45 30 1 19 6 6 2 12 0 6e-07 0 5e-15 0 0
4 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 40433 5 5 4 0 0 3 2 0 0 0 0.49 0.026 0.00034 0.00011 0.5
5 FBXW7 F-box and WD repeat domain containing 7 177744 12 9 10 0 6 2 2 0 2 0 0.08 0.079 0.00036 0.00032 1
6 SMAD2 SMAD family member 2 98964 5 5 5 0 0 3 1 0 1 0 0.37 0.02 0.0056 0.0011 1
7 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 0.031 0.00013 1 0.0013 1
8 SMAD4 SMAD family member 4 115264 8 8 6 0 2 3 3 0 0 0 0.2 0.26 0.00054 0.0014 1
9 PPPDE1 38842 2 1 2 0 0 1 0 0 1 0 0.37 0.29 0.00051 0.0014 1
10 ZNF706 zinc finger protein 706 15822 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.0018 0.0018 1
11 PFDN1 prefoldin subunit 1 22914 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.0021 0.0021 1
12 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 71547 3 3 3 0 0 0 0 0 3 0 0.35 0.083 0.0027 0.0021 1
13 MARCKSL1 MARCKS-like 1 28945 2 2 1 0 0 0 0 0 2 0 0.2 0.091 0.0034 0.0028 1
14 TCF7L2 transcription factor 7-like 2 (T-cell specific, HMG-box) 119026 7 7 7 1 2 3 0 0 2 0 0.085 0.11 0.003 0.0031 1
15 KIAA1804 162266 11 9 9 0 7 3 1 0 0 0 0.051 0.05 0.0094 0.0041 1
16 PALMD palmdelphin 114488 3 2 3 0 1 1 0 0 1 0 0.28 0.041 0.013 0.0047 1
17 DYNLRB2 dynein, light chain, roadblock-type 2 20963 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.005 0.005 1
18 NIT2 nitrilase family, member 2 58349 2 2 1 0 0 1 0 0 1 0 0.16 0.069 0.0087 0.0051 1
19 GLRX glutaredoxin (thioltransferase) 22470 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.0056 0.0056 1
20 TLL2 tolloid-like 2 209091 3 3 2 2 2 0 1 0 0 0 0.22 0.001 0.82 0.0067 1
21 BOLA3 bolA homolog 3 (E. coli) 24127 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.0077 0.0077 1
22 KRTAP5-5 keratin associated protein 5-5 34487 2 2 1 0 0 0 0 2 0 0 0.0062 0.013 0.078 0.0081 1
23 HEBP2 heme binding protein 2 34871 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.0082 0.0082 1
24 PECAM1 platelet/endothelial cell adhesion molecule (CD31 antigen) 74138 1 1 1 0 0 1 0 0 0 0 NaN NaN 0.0082 0.0082 1
25 IQCK IQ motif containing K 56949 2 2 2 0 1 0 0 0 1 0 0.3 0.21 0.005 0.0084 1
26 SIP1 survival of motor neuron protein interacting protein 1 54290 2 2 2 0 0 0 0 0 2 0 0.24 0.74 0.0015 0.0087 1
27 GLT8D2 glycosyltransferase 8 domain containing 2 74554 2 2 2 1 0 1 0 0 1 0 0.64 0.23 0.0053 0.0093 1
28 FAM123B family with sequence similarity 123B 190503 8 6 8 1 0 2 1 0 5 0 0.71 0.14 0.0085 0.0094 1
29 C6orf125 chromosome 6 open reading frame 125 25522 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.01 0.01 1
30 MAPK10 mitogen-activated protein kinase 10 99738 4 4 4 0 0 1 1 0 2 0 0.64 0.67 0.002 0.01 1
31 C6orf162 chromosome 6 open reading frame 162 20829 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.011 0.011 1
32 HSPB3 heat shock 27kDa protein 3 30908 1 1 1 0 0 0 0 0 1 0 NaN NaN 0.011 0.011 1
33 BAG5 BCL2-associated athanogene 5 80849 4 2 3 0 2 0 0 0 2 0 0.14 0.049 0.034 0.012 1
34 FAM49B family with sequence similarity 49, member B 70006 2 2 2 0 0 0 0 0 2 0 0.16 0.42 0.004 0.013 1
35 TRIM69 tripartite motif-containing 69 99933 2 2 2 1 0 1 0 0 1 0 0.0073 0.015 0.12 0.013 1
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)

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: 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
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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