Mutation Analysis (MutSig v2.0)
Thyroid Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1BP028G
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1BP028G
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: 496

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): 30

  • Mutations seen in COSMIC: 385

  • Significantly mutated genes in COSMIC territory: 16

  • Significantly mutated genesets: 90

  • Significantly mutated genesets: (excluding sig. mutated genes):5

Mutation Preprocessing

  • Read 496 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 15662

  • After removing 107 mutations outside chr1-24: 15555

  • After removing 3213 blacklisted mutations: 12342

  • After removing 1779 noncoding mutations: 10563

  • After collapsing adjacent/redundant mutations: 10050

Mutation Filtering

  • Number of mutations before filtering: 10050

  • After removing 597 mutations outside gene set: 9453

  • After removing 6 mutations outside category set: 9447

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 11
De_novo_Start_OutOfFrame 18
Frame_Shift_Del 404
Frame_Shift_Ins 107
In_Frame_Del 165
In_Frame_Ins 28
Missense_Mutation 5832
Nonsense_Mutation 300
Nonstop_Mutation 10
Silent 2275
Splice_Site 287
Start_Codon_Del 2
Start_Codon_Ins 1
Start_Codon_SNP 7
Total 9447
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 1159 807310784 1.4e-06 1.4 2.9 2.1
*Cp(A/C/T)->T 1353 6606127664 2e-07 0.2 0.41 1.7
A->G 1059 7116374150 1.5e-07 0.15 0.3 2.3
transver 2268 14529812598 1.6e-07 0.16 0.32 5
indel+null 1327 14529812598 9.1e-08 0.091 0.19 NaN
double_null 6 14529812598 4.1e-10 0.00041 0.00084 NaN
Total 7172 14529812598 4.9e-07 0.49 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: 30. 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 1103063 291 291 3 2 0 0 2 288 1 0 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <3.62e-12
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 290637 40 40 2 0 0 0 31 9 0 0 2.55e-15 1.34e-06 0 0.000038 0 <1.00e-15 <3.62e-12
3 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 321984 17 17 2 0 0 0 14 3 0 0 1.01e-14 0.0575 0 0.000045 0 <1.00e-15 <3.62e-12
4 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 329497 11 11 2 0 0 0 0 0 11 0 4.77e-15 1.000 0 0.99 0 <1.00e-15 <3.62e-12
5 TMEM184A transmembrane protein 184A 559188 5 5 1 0 0 0 0 0 5 0 1.50e-05 1.000 0 1 0 <1.00e-15 <3.62e-12
6 DLX6 distal-less homeobox 6 198621 7 7 3 0 0 0 0 0 7 0 5.25e-12 1.000 1.8e-06 0.99 6.4e-06 1.33e-15 4.02e-12
7 RPTN repetin 1172030 11 10 6 1 0 2 0 0 9 0 1.00e-10 0.745 0.00018 0.0077 1e-05 3.56e-14 9.21e-11
8 EIF1AX eukaryotic translation initiation factor 1A, X-linked 218439 8 7 7 0 0 3 0 2 2 1 2.56e-12 0.183 0.072 0.12 0.084 6.53e-12 1.48e-08
9 ZNF878 zinc finger protein 878 797461 4 4 1 0 0 0 0 4 0 0 7.31e-05 0.542 4e-07 1 0.000026 4.06e-08 8.17e-05
10 TG thyroglobulin 4161323 21 21 21 5 1 1 1 5 13 0 2.63e-08 0.907 0.076 0.75 0.14 7.43e-08 0.000134
11 NUP93 nucleoporin 93kDa 1260705 4 4 2 0 0 1 0 0 3 0 0.000734 0.118 4e-06 0.27 0.000012 1.78e-07 0.000292
12 PPM1D protein phosphatase 1D magnesium-dependent, delta isoform 775885 6 6 6 0 0 1 0 0 5 0 4.64e-07 0.700 0.016 0.86 0.044 3.86e-07 0.000582
13 PRMT8 protein arginine methyltransferase 8 600533 3 3 2 0 0 0 2 1 0 0 0.000976 0.549 0.00025 1 0.00034 5.34e-06 0.00743
14 GYPE glycophorin E 114552 3 3 1 0 0 0 0 0 3 0 6.46e-06 0.546 NaN NaN NaN 6.46e-06 0.00789
15 NDUFAF2 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, assembly factor 2 212396 3 3 1 0 0 0 0 0 3 0 7.35e-06 0.294 NaN NaN NaN 7.35e-06 0.00789
16 KRTAP4-11 keratin associated protein 4-11 254777 4 4 3 0 3 0 0 1 0 0 6.53e-07 0.756 0.55 0.72 0.73 7.38e-06 0.00789
17 AKT1 v-akt murine thymoma viral oncogene homolog 1 715150 5 5 3 1 0 3 0 2 0 0 1.83e-05 0.303 0.016 0.31 0.026 7.41e-06 0.00789
18 ABL1 c-abl oncogene 1, receptor tyrosine kinase 1718428 5 5 2 1 0 1 0 0 4 0 0.000357 0.834 0.0016 0.086 0.0018 9.94e-06 0.00999
19 SUMO3 SMT3 suppressor of mif two 3 homolog 3 (S. cerevisiae) 150357 3 3 1 0 0 0 0 3 0 0 1.25e-05 0.652 NaN NaN NaN 1.25e-05 0.0119
20 COL5A3 collagen, type V, alpha 3 2407158 8 8 8 0 3 1 0 3 1 0 1.35e-05 0.0991 0.05 1 0.084 1.66e-05 0.0150
21 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 338314 5 5 3 2 0 0 1 4 0 0 0.00902 0.909 0.01 0.0011 0.00017 2.21e-05 0.0190
22 NLRP6 NLR family, pyrin domain containing 6 907843 4 4 2 0 0 0 3 1 0 0 0.000345 0.467 0.071 0.0057 0.005 2.46e-05 0.0202
23 SLC31A2 solute carrier family 31 (copper transporters), member 2 210165 3 3 2 0 0 0 0 1 2 0 4.00e-05 0.811 NaN NaN NaN 4.00e-05 0.0315
24 ZNF578 zinc finger protein 578 885308 3 3 2 0 0 2 0 1 0 0 0.00242 0.428 0.0052 0.01 0.0014 4.53e-05 0.0341
25 RANBP9 RAN binding protein 9 873865 3 3 1 0 0 0 0 3 0 0 0.00762 0.607 0.00012 1 0.00047 4.87e-05 0.0352
26 ANKRD36 ankyrin repeat domain 36 874610 6 5 6 0 0 1 2 1 2 0 2.98e-05 0.255 0.094 0.51 0.19 7.33e-05 0.0510
27 SLA Src-like-adaptor 409991 4 4 4 0 0 0 1 1 2 0 1.00e-05 0.626 0.84 0.56 0.87 0.000111 0.0715
28 EIF3F eukaryotic translation initiation factor 3, subunit F 538571 4 4 4 0 1 0 2 0 1 0 0.000154 0.220 0.049 0.3 0.058 0.000113 0.0715
29 S100A7 S100 calcium binding protein A7 155744 3 3 3 0 0 0 0 3 0 0 4.57e-05 0.679 0.1 0.8 0.2 0.000115 0.0715
30 SPTA1 spectrin, alpha, erythrocytic 1 (elliptocytosis 2) 3697508 8 8 8 0 1 4 0 1 2 0 0.000160 0.0356 0.69 0.016 0.084 0.000165 0.0996
31 TPTE2 transmembrane phosphoinositide 3-phosphatase and tensin homolog 2 794356 6 5 5 1 0 0 0 5 1 0 3.28e-05 0.559 0.28 0.95 0.43 0.000173 0.101
32 BMP2K BMP2 inducible kinase 1645768 3 3 1 1 0 0 0 3 0 0 0.0279 0.819 0.000082 0.94 0.00085 0.000275 0.156
33 PRSS55 protease, serine, 55 530125 4 4 4 0 0 1 1 2 0 0 9.82e-05 0.310 0.28 0.073 0.3 0.000332 0.182
34 TUBGCP6 tubulin, gamma complex associated protein 6 2447040 3 3 1 1 0 0 3 0 0 0 0.0736 0.788 0.00011 1 0.00043 0.000359 0.191
35 OR56A1 olfactory receptor, family 56, subfamily A, member 1 476393 2 2 2 0 1 1 0 0 0 0 0.00683 0.342 0.16 0.0039 0.0049 0.000377 0.195
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.

TMEM184A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TMEM184A significant gene.

DLX6

Figure S5.  This figure depicts the distribution of mutations and mutation types across the DLX6 significant gene.

RPTN

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

EIF1AX

Figure S7.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

ZNF878

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ZNF878 significant gene.

TG

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

NUP93

Figure S10.  This figure depicts the distribution of mutations and mutation types across the NUP93 significant gene.

PPM1D

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PPM1D significant gene.

PRMT8

Figure S12.  This figure depicts the distribution of mutations and mutation types across the PRMT8 significant gene.

KRTAP4-11

Figure S13.  This figure depicts the distribution of mutations and mutation types across the KRTAP4-11 significant gene.

AKT1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the AKT1 significant gene.

ABL1

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ABL1 significant gene.

COL5A3

Figure S16.  This figure depicts the distribution of mutations and mutation types across the COL5A3 significant gene.

KRAS

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

NLRP6

Figure S18.  This figure depicts the distribution of mutations and mutation types across the NLRP6 significant gene.

SLC31A2

Figure S19.  This figure depicts the distribution of mutations and mutation types across the SLC31A2 significant gene.

ZNF578

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ZNF578 significant gene.

RANBP9

Figure S21.  This figure depicts the distribution of mutations and mutation types across the RANBP9 significant gene.

ANKRD36

Figure S22.  This figure depicts the distribution of mutations and mutation types across the ANKRD36 significant gene.

SLA

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

S100A7

Figure S24.  This figure depicts the distribution of mutations and mutation types across the S100A7 significant gene.

SPTA1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the SPTA1 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: 16. 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 17 19 17 9424 3536 3.3e-13 1.3e-09
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 40 33 40 16368 51920 5.8e-13 1.3e-09
3 BRAF v-raf murine sarcoma viral oncogene homolog B1 291 89 290 44144 4168112 1.5e-12 2.3e-09
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 5 52 5 25792 29804 3.7e-12 4.1e-09
5 PRNP prion protein (p27-30) (Creutzfeldt-Jakob disease, Gerstmann-Strausler-Scheinker syndrome, fatal familial insomnia) 2 1 2 496 2 3e-08 0.000027
6 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 3 220 3 109120 51 0.000025 0.019
7 TP53 tumor protein p53 4 356 3 176576 68 0.0001 0.067
8 C4BPA complement component 4 binding protein, alpha 1 1 1 496 1 0.00024 0.069
9 CNKSR1 connector enhancer of kinase suppressor of Ras 1 2 1 1 496 1 0.00024 0.069
10 PCGF2 polycomb group ring finger 2 2 1 1 496 1 0.00024 0.069

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: 90. 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(5), AKT2(1), AKT3(1), ARRB1(1), ARRB2(1), BRAF(291), CACNA1A(2), CACNA1B(3), CACNA1C(2), CACNA1D(4), CACNA1E(5), CACNA1G(3), CACNA1H(1), CACNA1S(1), CACNA2D1(5), CACNA2D3(1), CACNA2D4(2), CACNB3(1), CACNG7(1), CDC42(1), DUSP5(1), DUSP7(1), ECSIT(2), FGF20(1), FGF5(1), FGF7(1), FGFR2(1), FLNA(1), FLNC(4), HRAS(17), IL1R1(2), JUN(1), KRAS(5), MAP2K1(1), MAP2K6(1), MAP3K1(3), MAP3K3(3), MAP3K6(1), MAP3K8(1), MAP4K4(1), MAPK10(1), MAPK8IP2(1), MAPKAPK3(1), MYC(1), NF1(2), NFATC4(3), NRAS(40), PDGFRB(1), PLA2G2A(1), PLA2G5(2), PLA2G6(1), PTPRR(2), RAP1A(1), RASA1(2), RASGRF2(2), RASGRP1(1), RPS6KA1(1), RPS6KA4(1), SOS1(2), SOS2(2), TAOK2(2), TAOK3(1), TGFBR1(1), TGFBR2(1), TNFRSF1A(1), TP53(4) 210566400 459 378 114 39 20 26 60 330 23 0 <1.00e-15 <1.00e-15 <6.84e-14
2 HSA04730_LONG_TERM_DEPRESSION Genes involved in long-term depression ARAF, BRAF, C7orf16, CACNA1A, CRH, CRHR1, GNA11, GNA12, GNA13, GNAI1, GNAI2, GNAI3, GNAO1, GNAQ, GNAS, GNAZ, GRIA1, GRIA2, GRIA3, GRID2, GRM1, GRM5, GUCY1A2, GUCY1A3, GUCY1B3, GUCY2C, GUCY2D, GUCY2F, HRAS, IGF1, IGF1R, ITPR1, ITPR2, ITPR3, KRAS, LYN, MAP2K1, MAP2K2, MAPK1, MAPK3, NOS1, NOS2A, NOS3, NPR1, NPR2, NRAS, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLCB1, PLCB2, PLCB3, PLCB4, PPP2CA, PPP2CB, PPP2R1A, PPP2R1B, PPP2R2A, PPP2R2B, PPP2R2C, PRKCA, PRKCB1, PRKCG, PRKG1, PRKG2, RAF1, RYR1 74 BRAF(291), CACNA1A(2), CRH(1), CRHR1(1), GNAS(3), GRIA1(1), GRIA2(2), GRID2(1), GRM1(3), GUCY1A3(1), HRAS(17), IGF1R(3), ITPR1(2), ITPR2(6), KRAS(5), LYN(1), MAP2K1(1), NOS1(1), NPR1(2), NRAS(40), PLA2G2A(1), PLA2G5(2), PLA2G6(1), PLCB1(1), PLCB2(1), PLCB3(1), PLCB4(1), PPP2R1A(3), PPP2R1B(1), PPP2R2B(1), PRKG1(1), RYR1(8) 81240079 406 368 61 13 15 8 52 323 8 0 <1.00e-15 <1.00e-15 <6.84e-14
3 HSA04720_LONG_TERM_POTENTIATION Genes involved in long-term potentiation ADCY1, ADCY8, ARAF, ATF4, BRAF, CACNA1C, CALM1, CALM2, CALM3, CALML3, CALML6, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CAMK4, CHP, CREBBP, EP300, GNAQ, GRIA1, GRIA2, GRIN1, GRIN2A, GRIN2B, GRIN2C, GRIN2D, GRM1, GRM5, HRAS, ITPR1, ITPR2, ITPR3, KRAS, MAP2K1, MAP2K2, MAPK1, MAPK3, NRAS, PLCB1, PLCB2, PLCB3, PLCB4, PPP1CA, PPP1CB, PPP1CC, PPP1R12A, PPP1R1A, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB1, PRKCG, PRKX, PRKY, RAF1, RAP1A, RAP1B, RAPGEF3, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KA6 67 ADCY8(1), BRAF(291), CACNA1C(2), CALML6(1), CAMK2A(1), CAMK2B(1), CREBBP(1), GRIA1(1), GRIA2(2), GRIN2A(2), GRIN2B(4), GRIN2D(3), GRM1(3), HRAS(17), ITPR1(2), ITPR2(6), KRAS(5), MAP2K1(1), NRAS(40), PLCB1(1), PLCB2(1), PLCB3(1), PLCB4(1), RAP1A(1), RPS6KA1(1) 73321784 390 363 47 14 12 7 51 312 8 0 <1.00e-15 <1.00e-15 <6.84e-14
4 HSA04510_FOCAL_ADHESION Genes involved in focal adhesion ACTB, ACTG1, ACTN1, ACTN2, ACTN3, ACTN4, AKT1, AKT2, AKT3, ARHGAP5, BAD, BCAR1, BCL2, BIRC2, BIRC3, BIRC4, BRAF, CAPN2, CAV1, CAV2, CAV3, CCND1, CCND2, CCND3, CDC42, CHAD, COL11A1, COL11A2, COL1A1, COL1A2, COL2A1, COL3A1, COL4A1, COL4A2, COL4A4, COL4A6, COL5A1, COL5A2, COL5A3, COL6A1, COL6A2, COL6A3, COL6A6, COMP, CRK, CRKL, CTNNB1, DIAPH1, DOCK1, EGF, EGFR, ELK1, ERBB2, FARP2, FIGF, FLNA, FLNB, FLNC, FLT1, FN1, FYN, GRB2, GRLF1, GSK3B, HGF, HRAS, IBSP, IGF1, IGF1R, ILK, ITGA1, ITGA10, ITGA11, ITGA2, ITGA2B, ITGA3, ITGA4, ITGA5, ITGA6, ITGA7, ITGA8, ITGA9, ITGAV, ITGB1, ITGB3, ITGB4, ITGB5, ITGB6, ITGB7, ITGB8, JUN, KDR, LAMA1, LAMA2, LAMA3, LAMA4, LAMA5, LAMB1, LAMB2, LAMB3, LAMB4, LAMC1, LAMC2, LAMC3, LOC653852, MAP2K1, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MET, MLCK, MRCL3, MRLC2, MYL2, MYL5, MYL7, MYL8P, MYL9, MYLC2PL, MYLK, MYLK2, MYLPF, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PARVA, PARVB, PARVG, PDGFA, PDGFB, PDGFC, PDGFD, PDGFRA, PDGFRB, PDPK1, PGF, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PIP5K1C, PPP1CA, PPP1CB, PPP1CC, PPP1R12A, PRKCA, PRKCB1, PRKCG, PTEN, PTK2, PXN, RAC1, RAC2, RAC3, RAF1, RAP1A, RAP1B, RAPGEF1, RELN, RHOA, ROCK1, ROCK2, SHC1, SHC2, SHC3, SHC4, SOS1, SOS2, SPP1, SRC, THBS1, THBS2, THBS3, THBS4, TLN1, TLN2, TNC, TNN, TNR, TNXB, VASP, VAV1, VAV2, VAV3, VCL, VEGFA, VEGFB, VEGFC, VTN, VWF, ZYX 192 ACTB(1), ACTG1(1), AKT1(5), AKT2(1), AKT3(1), BAD(1), BRAF(291), CDC42(1), COL11A1(1), COL11A2(2), COL1A1(1), COL2A1(1), COL3A1(2), COL4A1(3), COL4A2(2), COL4A4(2), COL4A6(1), COL5A1(4), COL5A3(8), COL6A2(3), COL6A3(2), COL6A6(3), CTNNB1(2), ERBB2(1), FARP2(1), FIGF(1), FLNA(1), FLNC(4), FN1(3), FYN(1), HRAS(17), IGF1R(3), ITGA10(3), ITGA3(2), ITGA7(2), ITGA8(1), ITGA9(1), ITGAV(1), ITGB1(2), ITGB3(1), ITGB8(1), JUN(1), KDR(2), LAMA2(1), LAMA3(3), LAMA4(4), LAMA5(2), LAMB1(1), LAMB2(1), LAMB4(1), LAMC1(2), LAMC2(1), LAMC3(2), MAP2K1(1), MAPK10(1), MET(2), MYLK(4), PAK3(2), PAK7(2), PDGFRB(1), PIK3CA(3), PIK3CB(1), PIK3CD(2), PIK3CG(1), PIK3R1(2), PIK3R5(5), PTEN(2), RAP1A(1), RAPGEF1(2), RELN(2), SHC1(1), SOS1(2), SOS2(2), SRC(2), THBS1(1), THBS2(2), THBS3(1), THBS4(1), TLN1(1), TLN2(3), TNC(1), TNN(1), TNR(3), TNXB(3), VAV2(1), VCL(2), VEGFA(1), VTN(1), VWF(1), ZYX(1) 273450375 471 354 166 55 29 34 29 351 27 1 4.12e-11 <1.00e-15 <6.84e-14
5 HSA04320_DORSO_VENTRAL_AXIS_FORMATION Genes involved in dorso-ventral axis formation BRAF, CPEB1, EGFR, ERBB2, ERBB4, ETS1, ETS2, ETV6, ETV7, FMN2, GRB2, KRAS, MAP2K1, MAPK1, MAPK3, NOTCH1, NOTCH2, NOTCH3, NOTCH4, PIWIL1, PIWIL2, PIWIL3, PIWIL4, RAF1, SOS1, SOS2, SPIRE1, SPIRE2 28 BRAF(291), ERBB2(1), ERBB4(3), ETS1(2), KRAS(5), MAP2K1(1), NOTCH2(1), NOTCH3(1), NOTCH4(4), PIWIL1(1), PIWIL2(2), SOS1(2), SOS2(2) 38572470 316 301 26 11 2 4 7 300 3 0 2.66e-15 <1.00e-15 <6.84e-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(5), APC(3), BRAF(291), CAMP(1), ITPR1(2), ITPR2(6), KCNJ9(1), MAPK10(1), PHKA2(3), PIK3CA(3), PIK3CD(2), PIK3R1(2), PITX2(2), SRC(2) 39418229 324 301 34 8 7 5 2 302 8 0 <1.00e-15 <1.00e-15 <6.84e-14
7 ST_G_ALPHA_I_PATHWAY Gi and Go proteins are members of the same family that transduce cellular signals through both their alpha and beta subunits. AKT1, AKT2, AKT3, ASAH1, BF, BRAF, DAG1, DRD2, EGFR, EPHB2, GRB2, ITPKA, ITPKB, ITPR1, ITPR2, ITPR3, KCNJ3, KCNJ5, KCNJ9, MAPK1, PI3, PIK3CB, PITX2, PLCB1, PLCB2, PLCB3, PLCB4, RAF1, RAP1GA1, RGS20, SHC1, SOS1, SOS2, SRC, STAT3, TERF2IP 34 AKT1(5), AKT2(1), AKT3(1), BRAF(291), ITPR1(2), ITPR2(6), KCNJ9(1), PIK3CB(1), PITX2(2), PLCB1(1), PLCB2(1), PLCB3(1), PLCB4(1), SHC1(1), SOS1(2), SOS2(2), SRC(2) 43042654 321 299 31 6 8 7 3 300 3 0 <1.00e-15 <1.00e-15 <6.84e-14
8 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(5), AKT2(1), AKT3(1), BRAF(291), DDIT4(1), FIGF(1), HIF1A(1), PIK3CA(3), PIK3CB(1), PIK3CD(2), PIK3CG(1), PIK3R1(2), PIK3R5(5), RICTOR(1), RPS6KA1(1), RPS6KB2(1), ULK3(1), VEGFA(1) 39206098 320 296 30 10 4 6 5 297 8 0 <1.00e-15 <1.00e-15 <6.84e-14
9 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 12 AKT1(5), HRAS(17), PIK3CA(3), PIK3R1(2), PLCG1(1), SHC1(1), SOS1(2) 11466569 31 31 14 1 2 4 14 9 2 0 0.000739 <1.00e-15 <6.84e-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 BFAR(2), BRAF(291), CAMP(1), SNX13(1), SRC(2) 8121202 297 291 9 4 3 0 2 289 3 0 <1.00e-15 1.22e-15 7.52e-14

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 5. 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 7 ATM(7), ATR(3), CHEK1(1), CHEK2(4), TP53(4) 11753511 19 19 19 1 0 2 3 6 8 0 0.053 6.2e-06 0.0038
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(4), ATM(7), CDKN1A(1), RB1(2), TP53(4) 13321231 18 18 18 0 1 4 3 4 6 0 0.0095 8e-05 0.025
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 15 CDKN2A(1), MYC(1), PIK3CA(3), PIK3R1(2), POLR1A(1), POLR1B(2), RB1(2), TBX2(1), TP53(4), TWIST1(1) 13251283 18 18 18 0 3 1 1 4 9 0 0.0082 0.00022 0.035
4 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 ATM(7), BRCA1(1), CDKN1A(1), CHEK1(1), CHEK2(4), JUN(1), RAD51(1), TP53(4), TP73(3) 20228606 23 22 23 1 1 6 4 6 6 0 0.012 0.00023 0.035
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 21 ATM(7), ATR(3), BRCA1(1), BRCA2(3), CHEK1(1), CHEK2(4), FANCC(1), FANCD2(3), FANCF(1), FANCG(2), RAD17(2), RAD51(1), TP53(4), TREX1(1) 32415292 34 32 33 3 0 6 7 10 11 0 0.018 0.00042 0.052
6 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(7), CHEK1(1), MYT1(1), RB1(2), TP53(4), WEE1(1) 12935159 16 15 16 1 1 3 2 4 6 0 0.095 0.0011 0.12
7 SULFUR_METABOLISM BPNT1, PAPSS1, PAPSS2, SULT1A2, SULT1A3, SULT1A3, SULT1A4, SULT1E1, SULT2A1, SUOX 7 PAPSS1(2), SULT1E1(1), SULT2A1(1), SUOX(3) 4511431 7 7 7 0 1 1 0 1 4 0 0.18 0.0017 0.13
8 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 15 AKT2(1), AKT3(1), PIK3CA(3), PIK3CD(2), PTEN(2), PTK2B(2), RBL2(1), SHC1(1), SOS1(2) 14325600 15 15 15 1 3 4 0 4 3 1 0.063 0.0017 0.13
9 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY The phosphoinositide-3 kinase pathway produces the lipid second messenger PIP3 and regulates cell growth, survival, and movement. A1BG, AKT1, AKT2, AKT3, BAD, BTK, CDKN2A, CSL4, DAF, DAPP1, FOXO1A, GRB2, GSK3A, GSK3B, IARS, IGFBP1, INPP5D, P14, PDK1, PIK3CA, PPP1R13B, PSCD3, PTEN, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KB1, SFN, SHC1, SOS1, SOS2, TEC, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 32 AKT2(1), AKT3(1), BAD(1), CDKN2A(1), IARS(3), IGFBP1(1), INPP5D(1), PIK3CA(3), PPP1R13B(1), PTEN(2), RPS6KA1(1), SHC1(1), SOS1(2), SOS2(2), YWHAE(1), YWHAG(1) 25875881 23 23 23 1 2 5 1 7 7 1 0.018 0.0024 0.16
10 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(1), GOT2(2), TAT(1) 1942591 4 4 4 0 1 0 0 2 1 0 0.49 0.009 0.55
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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