Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Thyroid Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C18P5Z6M
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C18P5Z6M
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: THCA-TP

  • Number of patients in set: 401

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:THCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 6

  • Mutations seen in COSMIC: 312

  • Significantly mutated genes in COSMIC territory: 9

  • Significantly mutated genesets: 91

Mutation Preprocessing

  • Read 401 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 7430

  • After removing 2 mutations outside chr1-24: 7428

  • After removing 23 blacklisted mutations: 7405

  • After removing 61 noncoding mutations: 7344

  • After collapsing adjacent/redundant mutations: 6975

Mutation Filtering

  • Number of mutations before filtering: 6975

  • After removing 256 mutations outside gene set: 6719

  • After removing 3 mutations outside category set: 6716

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 196
Frame_Shift_Ins 33
In_Frame_Del 27
In_Frame_Ins 6
Missense_Mutation 4350
Nonsense_Mutation 240
Nonstop_Mutation 5
Silent 1644
Splice_Site 215
Total 6716
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 810 651888269 1.2e-06 1.2 2.9 2.1
*Cp(A/C/T)->T 1012 5343350203 1.9e-07 0.19 0.44 1.7
A->G 816 5758499319 1.4e-07 0.14 0.33 2.3
transver 1712 11753737791 1.5e-07 0.15 0.34 5
indel+null 719 11753737791 6.1e-08 0.061 0.14 NaN
double_null 3 11753737791 2.6e-10 0.00026 0.00059 NaN
Total 5072 11753737791 4.3e-07 0.43 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: THCA-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: *Cp(A/C/T)->T

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

  • n4 = number of nonsilent mutations of type: transver

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_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: 6. 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_clust p_cons p_joint p_cv p q
1 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 234967 34 34 2 0 0 0 27 7 0 0 0 0.00022 0 0 0 0
2 BRAF v-raf murine sarcoma viral oncogene homolog B1 891836 240 240 6 1 0 1 1 234 4 0 0 0 0 5.6e-16 0 0
3 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 260071 14 14 2 0 0 0 11 3 0 0 0 0.00014 0 1.1e-09 0 0
4 EIF1AX eukaryotic translation initiation factor 1A, X-linked 176670 6 6 5 0 0 3 0 1 2 0 0.028 0.033 0.016 3.2e-07 1e-07 0.00046
5 NUP93 nucleoporin 93kDa 1019335 4 4 2 0 0 1 0 0 3 0 3.8e-06 0.27 0.000012 0.011 2.1e-06 0.0075
6 NLRP6 NLR family, pyrin domain containing 6 732735 3 3 1 0 0 0 3 0 0 0 0.00021 0.000028 4.8e-06 0.16 0.000012 0.036
7 PPM1D protein phosphatase 1D magnesium-dependent, delta isoform 625741 5 5 5 0 0 1 0 0 4 0 0.026 0.89 0.066 0.00032 0.00025 0.64
8 MUC7 mucin 7, secreted 457922 2 2 2 1 0 0 1 0 1 0 0.44 0.011 0.014 0.051 0.006 1
9 OR56A1 olfactory receptor, family 56, subfamily A, member 1 385098 2 2 2 0 1 1 0 0 0 0 0.16 0.0039 0.0049 0.16 0.0064 1
10 C20orf144 chromosome 20 open reading frame 144 53233 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.011 0.011 1
11 S100A7 S100 calcium binding protein A7 125914 3 3 3 0 0 0 0 3 0 0 0.1 0.8 0.2 0.0081 0.012 1
12 PCDHAC2 protocadherin alpha subfamily C, 2 1182850 5 5 5 8 2 0 1 2 0 0 NaN NaN NaN 0.012 0.012 1
13 RAB27A RAB27A, member RAS oncogene family 273189 2 2 2 0 1 0 0 0 1 0 0.017 0.8 0.19 0.011 0.015 1
14 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 275782 4 4 3 0 0 0 1 3 0 0 0.036 0.0028 0.003 0.96 0.02 1
15 BAGE B melanoma antigen 50513 1 1 1 0 1 0 0 0 0 0 NaN NaN NaN 0.021 0.021 1
16 WIPF1 WAS/WASL interacting protein family, member 1 613843 2 2 2 1 0 1 0 1 0 0 0.75 0.0053 0.0062 0.53 0.022 1
17 TMSB15A thymosin beta 15a 58475 2 2 2 0 0 1 0 1 0 0 0.23 0.5 1 0.0034 0.023 1
18 CRH corticotropin releasing hormone 79709 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.023 0.023 1
19 IARS isoleucyl-tRNA synthetase 1564420 3 3 3 0 0 1 0 1 1 0 0.24 0.0053 0.012 0.3 0.023 1
20 C19orf35 chromosome 19 open reading frame 35 221020 2 2 2 0 1 0 1 0 0 0 0.19 0.033 0.048 0.079 0.025 1
21 ATR ataxia telangiectasia and Rad3 related 3219782 3 3 3 1 0 0 0 1 2 0 0.0036 0.28 0.0042 0.99 0.027 1
22 MSI1 musashi homolog 1 (Drosophila) 314023 3 3 3 0 1 0 0 1 1 0 0.37 0.69 0.63 0.0075 0.03 1
23 TMEM47 transmembrane protein 47 118810 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.032 0.032 1
24 IL11 interleukin 11 72760 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.037 0.037 1
25 CST6 cystatin E/M 111752 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.037 0.037 1
26 TBC1D7 TBC1 domain family, member 7 363943 2 2 2 0 0 1 0 0 1 0 0.19 0.011 0.022 0.32 0.043 1
27 PDF peptide deformylase (mitochondrial) 73258 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.043 0.043 1
28 AMDHD1 amidohydrolase domain containing 1 463710 2 2 2 0 0 1 0 0 1 0 0.36 0.051 0.085 0.085 0.043 1
29 FAM162B family with sequence similarity 162, member B 132553 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.046 0.046 1
30 ATM ataxia telangiectasia mutated 3729176 5 5 5 0 0 1 1 2 1 0 0.038 0.014 0.008 1 0.047 1
31 CXorf61 chromosome X open reading frame 61 140343 1 1 1 0 0 1 0 0 0 0 NaN NaN NaN 0.047 0.047 1
32 FUNDC1 FUN14 domain containing 1 168618 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.05 0.05 1
33 CACNA1A calcium channel, voltage-dependent, P/Q type, alpha 1A subunit 2130097 2 2 2 0 1 1 0 0 0 0 0.14 0.014 0.0095 0.98 0.053 1
34 COMTD1 catechol-O-methyltransferase domain containing 1 106851 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.054 0.054 1
35 SLC27A4 solute carrier family 27 (fatty acid transporter), member 4 783281 2 2 2 0 2 0 0 0 0 0 0.052 0.043 0.024 0.4 0.054 1
NRAS

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

BRAF

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

HRAS

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

EIF1AX

Figure S4.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

NUP93

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NUP93 significant gene.

NLRP6

Figure S6.  This figure depicts the distribution of mutations and mutation types across the NLRP6 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: 9. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 14 19 14 7619 2912 2.9e-13 1.1e-09
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 34 33 34 13233 44132 5e-13 1.1e-09
3 BRAF v-raf murine sarcoma viral oncogene homolog B1 240 89 238 35689 3392099 1.3e-12 2e-09
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 4 52 4 20852 15018 2.7e-10 3.1e-07
5 C4BPA complement component 4 binding protein, alpha 1 1 1 401 1 0.00017 0.087
6 PCGF2 polycomb group ring finger 2 2 1 1 401 1 0.00017 0.087
7 SEZ6L seizure related 6 homolog (mouse)-like 2 1 1 401 1 0.00017 0.087
8 SMC3 structural maintenance of chromosomes 3 1 1 1 401 1 0.00017 0.087
9 TNS1 tensin 1 3 1 1 401 1 0.00017 0.087
10 DCC deleted in colorectal carcinoma 2 3 1 1203 1 0.00052 0.21

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: 91. 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 HSA04010_MAPK_SIGNALING_PATHWAY Genes involved in MAPK signaling pathway ACVR1B, ACVR1C, AKT1, AKT2, AKT3, ARRB1, ARRB2, ATF2, ATF4, BDNF, BRAF, CACNA1A, CACNA1B, CACNA1C, CACNA1D, CACNA1E, CACNA1F, CACNA1G, CACNA1H, CACNA1I, CACNA1S, CACNA2D1, CACNA2D2, CACNA2D3, CACNA2D4, CACNB1, CACNB2, CACNB3, CACNB4, CACNG1, CACNG2, CACNG3, CACNG4, CACNG5, CACNG6, CACNG7, CACNG8, CASP3, CD14, CDC25B, CDC42, CHP, CHUK, CRK, CRKL, DAXX, DDIT3, DUSP1, DUSP10, DUSP14, DUSP16, DUSP2, DUSP3, DUSP4, DUSP5, DUSP6, DUSP7, DUSP8, DUSP9, ECSIT, EGF, EGFR, ELK1, ELK4, EVI1, FAS, FASLG, 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, FLNA, FLNB, FLNC, FOS, GADD45A, GADD45B, GADD45G, GNA12, GNG12, GRB2, HRAS, IKBKB, IKBKG, IL1A, IL1B, IL1R1, IL1R2, JUN, JUND, KRAS, LOC653852, MAP2K1, MAP2K1IP1, MAP2K2, MAP2K3, MAP2K4, MAP2K5, MAP2K6, MAP2K7, MAP3K1, MAP3K10, MAP3K12, MAP3K13, MAP3K14, MAP3K2, MAP3K3, MAP3K4, MAP3K5, MAP3K6, MAP3K7, MAP3K7IP1, MAP3K7IP2, MAP3K8, MAP4K1, MAP4K2, MAP4K3, MAP4K4, MAPK1, MAPK10, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPK7, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, MAPKAPK2, MAPKAPK3, MAPKAPK5, MAPT, MAX, MEF2C, MKNK1, MKNK2, MOS, MRAS, MYC, NF1, NFATC2, NFATC4, NFKB1, NFKB2, NGFB, NLK, NR4A1, NRAS, NTF3, NTF5, NTRK1, NTRK2, PAK1, PAK2, PDGFA, PDGFB, PDGFRA, PDGFRB, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PPM1A, PPM1B, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PPP5C, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB1, PRKCG, PRKX, PRKY, PTPN5, PTPN7, PTPRR, RAC1, RAC2, RAC3, RAF1, RAP1A, RAP1B, RAPGEF2, RASA1, RASA2, RASGRF1, RASGRF2, RASGRP1, RASGRP2, RASGRP3, RASGRP4, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KA4, RPS6KA5, RPS6KA6, RRAS, RRAS2, SOS1, SOS2, SRF, STK3, STK4, STMN1, TAOK1, TAOK2, TAOK3, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TNF, TNFRSF1A, TP53, TRAF2, TRAF6, ZAK 247 AKT1(3), AKT2(2), ARRB1(1), BRAF(240), CACNA1A(2), CACNA1B(2), CACNA1C(1), CACNA1D(2), CACNA1E(5), CACNA1G(3), CACNA1S(1), CACNA2D1(2), CACNA2D3(1), CACNA2D4(2), CACNB3(1), CACNG7(1), CASP3(1), CDC42(1), DUSP5(1), DUSP7(1), ECSIT(1), FGF20(1), FGF5(1), FGF7(1), FGFR2(1), FLNA(1), FLNC(3), HRAS(14), IL1R1(2), JUN(1), KRAS(4), MAP2K6(1), MAP3K1(2), MAP3K3(3), MAP3K6(1), MAP4K4(1), MAPK10(1), MAPK8IP2(1), MAPKAPK3(1), MYC(1), NF1(2), NFATC4(3), NRAS(34), PDGFRB(1), PLA2G2A(1), PLA2G5(1), PPP3R2(1), PTPRR(1), RAP1A(1), RASA1(1), RASGRF2(2), RASGRP1(1), SOS1(1), TGFBR2(1), TP53(3) 170374057 369 311 89 27 13 23 51 266 16 0 4.33e-15 <1.00e-15 <6.16e-14
2 HSA04910_INSULIN_SIGNALING_PATHWAY Genes involved in insulin signaling pathway ACACA, ACACB, AKT1, AKT2, AKT3, ARAF, BAD, BRAF, CALM1, CALM2, CALM3, CALML3, CALML6, CBL, CBLB, CBLC, CRK, CRKL, EIF4EBP1, ELK1, EXOC7, FASN, FBP1, FBP2, FLOT1, FLOT2, FOXO1, FRAP1, G6PC, G6PC2, GCK, GRB2, GSK3B, GYS1, GYS2, HRAS, IKBKB, INPP5D, INS, INSR, IRS1, IRS2, IRS4, KIAA1303, KRAS, LIPE, MAP2K1, MAP2K2, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MKNK1, MKNK2, NRAS, PCK1, PCK2, PDE3A, PDE3B, PDPK1, PFKL, PFKM, PFKP, PHKA1, PHKA2, PHKB, PHKG1, PHKG2, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PKLR, PKM2, PPARGC1A, PPP1CA, PPP1CB, PPP1CC, PPP1R3A, PPP1R3B, PPP1R3C, PPP1R3D, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACA, PRKACB, PRKACG, PRKAG1, PRKAG2, PRKAG3, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCI, PRKCZ, PRKX, PRKY, PTPN1, PTPRF, PYGB, PYGL, PYGM, RAF1, RAPGEF1, RHEB, RHOQ, RPS6, RPS6KB1, RPS6KB2, SH2B2, SHC1, SHC2, SHC3, SHC4, SKIP, SLC2A4, SOCS1, SOCS2, SOCS3, SOCS4, SORBS1, SOS1, SOS2, SREBF1, TRIP10, TSC1, TSC2 131 ACACA(1), ACACB(1), AKT1(3), AKT2(2), BRAF(240), EXOC7(1), FASN(1), FLOT1(1), FLOT2(1), GYS2(1), HRAS(14), INPP5D(1), IRS1(1), IRS2(1), KRAS(4), MAPK10(1), NRAS(34), PCK2(1), PDE3A(1), PFKP(2), PHKA2(2), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), PPARGC1A(1), PPP1R3B(1), PRKAG2(1), PRKAR2A(1), PYGB(1), RAPGEF1(2), RHOQ(2), RPS6KB2(1), SHC1(1), SOS1(1), SREBF1(1), TRIP10(1) 95676922 337 303 57 19 11 10 46 262 8 0 2.11e-15 <1.00e-15 <6.16e-14
3 HSA04650_NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY Genes involved in natural killer cell mediated cytotoxicity ARAF, BID, BRAF, CASP3, CD244, CD247, CD48, CHP, CSF2, FAS, FASLG, FCER1G, FCGR3A, FCGR3B, FYN, GRB2, GZMB, HCST, HLA-A, HLA-B, HLA-C, HLA-E, HLA-G, HRAS, ICAM1, ICAM2, IFNA1, IFNA10, IFNA13, IFNA14, IFNA16, IFNA17, IFNA2, IFNA21, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNAR1, IFNAR2, IFNB1, IFNG, IFNGR1, IFNGR2, ITGAL, ITGB2, KIR2DL1, KIR2DL2, KIR2DL3, KIR2DL4, KIR2DL5A, KIR2DS1, KIR2DS2, KIR3DL1, KIR3DL2, KLRC1, KLRC2, KLRC3, KLRD1, KLRK1, KRAS, LAT, LCK, LCP2, LOC652578, MAP2K1, MAP2K2, MAPK1, MAPK3, MICA, MICB, NCR1, NCR2, NCR3, NFAT5, NFATC1, NFATC2, NFATC3, NFATC4, NRAS, PAK1, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLCG1, PLCG2, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRF1, PRKCA, PRKCB1, PRKCG, PTK2B, PTPN11, PTPN6, RAC1, RAC2, RAC3, RAF1, SH2D1A, SH2D1B, SH3BP2, SHC1, SHC2, SHC3, SHC4, SOS1, SOS2, SYK, TNF, TNFRSF10A, TNFRSF10B, TNFRSF10C, TNFRSF10D, TNFSF10, TYROBP, ULBP1, ULBP2, ULBP3, VAV1, VAV2, VAV3, ZAP70 126 BRAF(240), CASP3(1), HLA-E(1), HRAS(14), IFNAR2(1), IFNGR1(1), ITGAL(4), KIR2DL1(1), KIR3DL2(2), KRAS(4), LCK(1), NCR1(1), NFAT5(2), NFATC1(1), NFATC4(3), NRAS(34), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), PPP3R2(1), PTK2B(2), SHC1(1), SOS1(1), SYK(1), ULBP1(1) 67770272 327 300 48 15 9 9 43 258 8 0 <1.00e-15 <1.00e-15 <6.16e-14
4 HSA04012_ERBB_SIGNALING_PATHWAY Genes involved in ErbB signaling pathway ABL1, ABL2, AKT1, AKT2, AKT3, ARAF, AREG, BAD, BRAF, BTC, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CBL, CBLB, CBLC, CDKN1A, CDKN1B, CRK, CRKL, EGF, EGFR, EIF4EBP1, ELK1, ERBB2, ERBB3, ERBB4, EREG, FRAP1, GAB1, GRB2, GSK3B, HBEGF, HRAS, JUN, KRAS, MAP2K1, MAP2K2, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MYC, NCK1, NCK2, NRAS, NRG1, NRG2, NRG3, NRG4, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLCG1, PLCG2, PRKCA, PRKCB1, PRKCG, PTK2, RAF1, RPS6KB1, RPS6KB2, SHC1, SHC2, SHC3, SHC4, SOS1, SOS2, SRC, STAT5A, STAT5B, TGFA 85 ABL1(1), ABL2(1), AKT1(3), AKT2(2), BRAF(240), CAMK2A(1), CAMK2B(1), CDKN1A(1), ERBB2(1), ERBB3(1), ERBB4(2), HRAS(14), JUN(1), KRAS(4), MAPK10(1), MYC(1), NCK1(2), NRAS(34), NRG1(1), NRG2(1), PAK3(1), PAK7(2), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), RPS6KB2(1), SHC1(1), SOS1(1), SRC(1), STAT5B(1) 61538338 330 298 50 9 8 8 46 258 9 1 <1.00e-15 <1.00e-15 <6.16e-14
5 ST_INTEGRIN_SIGNALING_PATHWAY Integrins are transmembrane receptors that mediate cell growth, survival, and migration by binding to ligands in the extracellular matrix. ABL1, ACK1, ACTN1, ACTR2, ACTR3, AKT1, AKT2, AKT3, ANGPTL2, ARHGEF6, ARHGEF7, BCAR1, BRAF, CAV1, CDC42, CDKN2A, CRK, CSE1L, DDEF1, DOCK1, EPHB2, FYN, GRAF, GRB2, GRB7, GRF2, GRLF1, ILK, ITGA1, ITGA10, ITGA11, ITGA2, ITGA3, ITGA4, ITGA5, ITGA6, ITGA7, ITGA8, ITGA9, ITGB3BP, MAP2K4, MAP2K7, MAP3K11, MAPK1, MAPK10, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, MRAS, MYLK, MYLK2, P4HB, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PIK3CA, PIK3CB, PKLR, PLCG1, PLCG2, PTEN, PTK2, RAF1, RALA, RHO, ROCK1, ROCK2, SHC1, SOS1, SOS2, SRC, TERF2IP, TLN1, TLN2, VASP, WAS, ZYX 78 ABL1(1), AKT1(3), AKT2(2), ANGPTL2(1), ARHGEF6(1), ARHGEF7(1), BRAF(240), CDC42(1), GRB7(1), ITGA10(1), ITGA3(2), ITGA7(1), ITGA8(1), MAPK10(1), MAPK8IP2(1), MYLK(3), P4HB(1), PAK3(1), PAK7(2), PIK3CA(2), PIK3CB(1), PTEN(2), SHC1(1), SOS1(1), SRC(1), TLN2(2) 72966816 275 251 40 13 8 9 3 248 6 1 2.26e-12 <1.00e-15 <6.16e-14
6 ST_ADRENERGIC Adrenergic receptors respond to epinephrine and norepinephrine signaling. AKT1, APC, AR, ASAH1, BF, BRAF, CAMP, CCL13, CCL15, CCL16, DAG1, EGFR, GAS, GNA11, GNA15, GNAI1, GNAQ, ITPKA, ITPKB, ITPR1, ITPR2, ITPR3, KCNJ3, KCNJ5, KCNJ9, MAPK1, MAPK10, MAPK14, PHKA2, PIK3CA, PIK3CD, PIK3R1, PITX2, PTX1, PTX3, RAF1, SRC 34 AKT1(3), APC(2), BRAF(240), ITPR1(2), ITPR2(5), MAPK10(1), PHKA2(2), PIK3CA(2), PIK3CD(1), PIK3R1(1), PITX2(2), SRC(1) 31888074 262 246 27 6 5 5 1 244 7 0 9.66e-15 <1.00e-15 <6.16e-14
7 HSA04150_MTOR_SIGNALING_PATHWAY Genes involved in mTOR signaling pathway AKT1, AKT2, AKT3, BRAF, CAB39, DDIT4, EIF4B, EIF4EBP1, FIGF, FRAP1, GBL, HIF1A, IGF1, INS, KIAA1303, LYK5, MAPK1, MAPK3, PDPK1, PGF, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PRKAA1, PRKAA2, RHEB, RICTOR, RPS6, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KA6, RPS6KB1, RPS6KB2, STK11, TSC1, TSC2, ULK1, ULK2, ULK3, VEGFA, VEGFB, VEGFC 44 AKT1(3), AKT2(2), BRAF(240), FIGF(1), HIF1A(1), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), RPS6KB2(1), ULK3(1), VEGFA(1) 31724050 259 242 24 4 3 4 5 240 7 0 <1.00e-15 <1.00e-15 <6.16e-14
8 ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS Rat-derived PC12 cells respond to nerve growth factor (NGF) and PACAP to differentiate into neuronal cells. AKT1, ASAH1, ATF1, BRAF, CAMP, CREB1, CREB3, CREB5, CREBBP, CRKL, DAG1, EGR1, EGR2, EGR3, EGR4, ELK1, FRS2, GAS, GNAQ, GRF2, JUN, MAP1B, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK3, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, NTRK1, OPN1LW, PACAP, PIK3C2G, PIK3CA, PIK3CD, PIK3R1, PTPN11, RPS6KA3, SH2B, SHC1, SRC, TERF2IP, TH, TUBA3 42 AKT1(3), BRAF(240), CREBBP(1), JUN(1), MAP1B(3), MAPK10(1), MAPK8IP2(1), PIK3C2G(1), PIK3CA(2), PIK3CD(1), PIK3R1(1), SHC1(1), SRC(1) 30662299 257 242 22 5 4 6 1 240 6 0 2.00e-15 <1.00e-15 <6.16e-14
9 ST_ERK1_ERK2_MAPK_PATHWAY The Erk1 and Erk2 MAP kinase pathways are regulated by Raf, Mos, and Tpl-2. ARAF1, ATF1, BAD, BRAF, COPEB, CREB1, CREB3, CREB5, DUSP4, DUSP6, DUSP9, EEF2K, EIF4E, GRB2, HTATIP, MAP2K1, MAP2K2, MAP3K8, MAPK1, MAPK3, MKNK1, MKNK2, MOS, NFKB1, RAP1A, RPS6KA1, RPS6KA2, RPS6KA3, SHC1, SOS1, SOS2, TRAF3 29 BRAF(240), EEF2K(1), RAP1A(1), SHC1(1), SOS1(1) 17612692 244 241 10 3 1 3 1 235 4 0 1.33e-15 <1.00e-15 <6.16e-14
10 ST_G_ALPHA_S_PATHWAY The G-alpha-s protein activates adenylyl cyclases, which catalyze cAMP formation. ASAH1, BF, BFAR, BRAF, CAMP, CREB1, CREB3, CREB5, EPAC, GAS, GRF2, MAPK1, RAF1, SNX13, SRC, TERF2IP 12 BRAF(240), SNX13(1), SRC(1) 6581484 242 240 8 2 0 1 1 235 5 0 <1.00e-15 <1.00e-15 <6.16e-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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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