Mutation Analysis (MutSig v2.0)
Thyroid Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C19W0D0S
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C19W0D0S
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: 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

  • Significantly mutated genes (q ≤ 0.1): 10

  • Mutations seen in COSMIC: 312

  • Significantly mutated genes in COSMIC territory: 9

  • Significantly mutated genesets: 91

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

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_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: 10. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).

rank gene description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_classic p_ns_s p_clust p_cons p_joint p q
1 BRAF v-raf murine sarcoma viral oncogene homolog B1 891836 240 240 6 1 0 1 1 234 4 0 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <6.03e-12
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 234967 34 34 2 0 0 0 27 7 0 0 3.00e-15 8.81e-06 0 0.00022 0 <1.00e-15 <6.03e-12
3 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 260071 14 14 2 0 0 0 11 3 0 0 1.60e-14 0.0940 0 0.00014 0 <1.00e-15 <6.03e-12
4 EIF1AX eukaryotic translation initiation factor 1A, X-linked 176670 6 6 5 0 0 3 0 1 2 0 2.92e-11 0.235 0.028 0.033 0.016 1.36e-11 6.14e-08
5 NUP93 nucleoporin 93kDa 1019335 4 4 2 0 0 1 0 0 3 0 0.000128 0.118 3.8e-06 0.27 0.000012 3.22e-08 0.000116
6 NLRP6 NLR family, pyrin domain containing 6 732735 3 3 1 0 0 0 3 0 0 0 0.000999 0.579 0.00021 0.000028 4.8e-06 9.67e-08 0.000291
7 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 275782 4 4 3 0 0 0 1 3 0 0 3.07e-06 0.414 0.036 0.0028 0.003 1.79e-07 0.000463
8 PPM1D protein phosphatase 1D magnesium-dependent, delta isoform 625741 5 5 5 0 0 1 0 0 4 0 4.70e-07 0.700 0.026 0.89 0.066 5.70e-07 0.00129
9 S100A7 S100 calcium binding protein A7 125914 3 3 3 0 0 0 0 3 0 0 1.49e-05 0.679 0.1 0.8 0.2 4.06e-05 0.0803
10 CHEK2 CHK2 checkpoint homolog (S. pombe) 635291 5 5 5 0 0 0 1 3 1 0 5.54e-06 0.333 0.4 0.63 0.59 4.44e-05 0.0803
11 CDH8 cadherin 8, type 2 977851 4 4 4 1 1 0 0 3 0 0 0.000337 0.658 0.89 0.006 0.039 0.000160 0.263
12 TBC1D7 TBC1 domain family, member 7 363943 2 2 2 0 0 1 0 0 1 0 0.000700 0.548 0.19 0.011 0.022 0.000190 0.286
13 OR56A1 olfactory receptor, family 56, subfamily A, member 1 385098 2 2 2 0 1 1 0 0 0 0 0.00399 0.342 0.16 0.0039 0.0049 0.000231 0.321
14 SAMD1 sterile alpha motif domain containing 1 179200 2 2 2 0 1 0 1 0 0 0 0.000209 0.451 0.086 0.57 0.13 0.000319 0.412
15 SPTA1 spectrin, alpha, erythrocytic 1 (elliptocytosis 2) 2989128 6 6 6 0 0 3 0 1 2 0 0.000430 0.0708 0.43 0.028 0.077 0.000374 0.450
16 BAGE B melanoma antigen 50513 1 1 1 0 1 0 0 0 0 0 0.000416 0.500 NaN NaN NaN 0.000416 0.470
17 TMSB15A thymosin beta 15a 58475 2 2 2 0 0 1 0 1 0 0 5.07e-05 0.592 0.23 0.5 1 0.000552 0.544
18 CD163 CD163 molecule 1404730 4 4 4 0 2 1 1 0 0 0 0.000364 0.228 0.12 0.14 0.14 0.000559 0.544
19 MAP3K3 mitogen-activated protein kinase kinase kinase 3 810959 3 3 3 0 0 2 0 1 0 0 0.00291 0.279 0.015 0.07 0.018 0.000572 0.544
20 SLC5A2 solute carrier family 5 (sodium/glucose cotransporter), member 2 809014 3 3 3 0 1 1 0 1 0 0 0.00186 0.267 0.062 0.05 0.032 0.000641 0.580
21 CYB5R2 cytochrome b5 reductase 2 335914 2 2 2 0 0 1 0 0 1 0 0.000722 0.503 NaN NaN NaN 0.000722 0.587
22 ATM ataxia telangiectasia mutated 3729176 5 5 5 0 0 1 1 2 1 0 0.00881 0.334 0.038 0.014 0.008 0.000745 0.587
23 MSI1 musashi homolog 1 (Drosophila) 314023 3 3 3 0 1 0 0 1 1 0 0.000112 0.502 0.37 0.69 0.63 0.000746 0.587
24 SLC25A45 solute carrier family 25, member 45 357268 3 3 3 1 1 1 1 0 0 0 0.000193 0.704 0.49 0.28 0.44 0.000889 0.670
25 LMX1B LIM homeobox transcription factor 1, beta 387423 2 2 1 0 0 0 0 0 2 0 0.00199 1.000 0.012 0.038 0.047 0.000969 0.699
26 C19orf35 chromosome 19 open reading frame 35 221020 2 2 2 0 1 0 1 0 0 0 0.00215 0.479 0.19 0.033 0.048 0.00106 0.699
27 EFCAB1 EF-hand calcium binding domain 1 258650 2 2 2 0 1 0 0 0 1 0 0.000175 0.730 0.59 0.67 0.66 0.00116 0.699
28 BRIX1 BRX1, biogenesis of ribosomes, homolog (S. cerevisiae) 362700 3 3 3 0 0 1 1 1 0 0 0.000197 0.411 0.47 0.9 0.6 0.00119 0.699
29 SLA Src-like-adaptor 331456 3 3 3 0 0 0 1 0 2 0 0.000120 0.755 0.84 0.8 1 0.00120 0.699
30 ARFGEF2 ADP-ribosylation factor guanine nucleotide-exchange factor 2 (brefeldin A-inhibited) 2155748 4 4 4 0 0 2 0 1 1 0 0.00767 0.209 0.011 0.93 0.017 0.00131 0.699
31 ANKRD54 ankyrin repeat domain 54 237758 2 2 2 0 0 0 0 0 2 0 0.00132 0.819 NaN NaN NaN 0.00132 0.699
32 SPINK9 serine peptidase inhibitor, Kazal type 9 107428 1 1 1 0 1 0 0 0 0 0 0.00134 0.500 NaN NaN NaN 0.00134 0.699
33 CD38 CD38 molecule 372944 2 2 2 0 1 0 0 1 0 0 0.00759 0.534 0.73 0.0042 0.018 0.00138 0.699
34 ADO 2-aminoethanethiol (cysteamine) dioxygenase 142942 2 2 2 0 0 0 0 2 0 0 0.000143 0.648 0.53 0.68 1 0.00141 0.699
35 DLC1 deleted in liver cancer 1 1894669 4 4 3 1 0 0 1 3 0 0 0.00810 0.769 0.13 0.011 0.018 0.00142 0.699
BRAF

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

NRAS

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NRAS 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.

KRAS

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

PPM1D

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PPM1D significant gene.

S100A7

Figure S9.  This figure depicts the distribution of mutations and mutation types across the S100A7 significant gene.

CHEK2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CHEK2 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

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 0. Number of genesets displayed: 10

rank geneset description genes N_genes mut_tally N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 6 ATM(5), ATR(3), CHEK1(1), TP53(3) 8877061 12 12 12 1 0 2 1 3 6 0 0.18 0.00033 0.12
2 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(2), ATM(5), CDKN1A(1), RB1(2), TP53(3) 10776925 13 13 13 0 1 3 1 3 5 0 0.038 0.00045 0.12
3 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(1), MYC(1), PIK3CA(2), PIK3R1(1), POLR1A(1), POLR1B(2), RB1(2), TP53(3), TWIST1(1) 12103444 14 14 14 0 2 2 1 2 7 0 0.014 0.00067 0.12
4 SA_PTEN_PATHWAY PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. AKT1, AKT2, AKT3, BPNT1, GRB2, ILK, MAPK1, MAPK3, PDK1, PIK3CA, PIK3CD, PIP3-E, PTEN, PTK2B, RBL2, SHC1, SOS1 16 AKT1(3), AKT2(2), PIK3CA(2), PIK3CD(1), PTEN(2), PTK2B(2), RBL2(1), SHC1(1), SOS1(1) 12167760 15 15 14 2 2 6 1 4 1 1 0.1 0.0008 0.12
5 ATRBRCAPATHWAY BRCA1 and 2 block cell cycle progression in response to DNA damage and promote double-stranded break repair; mutations induce breast cancer susceptibility. ATM, ATR, BRCA1, BRCA2, CHEK1, CHEK2, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, HUS1, MRE11A, NBS1, RAD1, RAD17, RAD50, RAD51, RAD9A, TP53, TREX1 20 ATM(5), ATR(3), BRCA1(1), BRCA2(3), CHEK1(1), FANCD2(3), FANCF(1), FANCG(2), TP53(3), TREX1(1) 25596031 23 22 23 2 0 5 4 5 9 0 0.042 0.0011 0.14
6 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 AKT1(3), ATM(5), CDKN1A(1), HIF1A(1), TP53(3) 12386329 13 13 12 1 0 3 2 4 4 0 0.11 0.0016 0.14
7 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 18 ABL1(1), ATM(5), BRCA1(1), CDKN1A(1), CHEK1(1), JUN(1), TP53(3), TP73(3) 17118506 16 16 16 0 1 6 2 3 4 0 0.0083 0.0016 0.14
8 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 16 AKT1(3), MAP2K6(1), MAP3K1(2), PIK3CA(2), PIK3R1(1), RB1(2), SP1(1) 11567588 12 12 11 1 1 3 1 5 2 0 0.12 0.0029 0.21
9 TCAPOPTOSISPATHWAY HIV infection upregulates Fas ligand in macrophages and CD4 in helper T cells, leading to widespread Fas-induced T cell apoptosis. CCR5, CD28, CD3D, CD3E, CD3G, CD3Z, CD4, TNFRSF6, TNFSF6, TRA@, TRB@ 6 CD28(1), CD3D(1), CD3E(1), CD4(1) 1916305 4 4 4 0 2 0 1 0 1 0 0.35 0.0036 0.21
10 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(5), CHEK1(1), RB1(2), TP53(3) 10466190 11 11 11 0 1 3 1 2 4 0 0.044 0.0037 0.21
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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