Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Breast Invasive Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C10P0XBM
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/C10P0XBM
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: BRCA-TP

  • Number of patients in set: 772

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:BRCA-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 74

  • Mutations seen in COSMIC: 727

  • Significantly mutated genes in COSMIC territory: 15

  • Significantly mutated genesets: 122

Mutation Preprocessing

  • Read 772 MAFs of type "WashU"

  • Total number of mutations in input MAFs: 47116

  • After removing 330 mutations outside chr1-24: 46786

  • After removing 1798 noncoding mutations: 44988

  • After collapsing adjacent/redundant mutations: 44986

Mutation Filtering

  • Number of mutations before filtering: 44986

  • After removing 4216 mutations outside gene set: 40770

  • After removing 87 mutations outside category set: 40683

  • After removing 11 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 36369

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1283
Frame_Shift_Ins 736
In_Frame_Del 756
In_Frame_Ins 266
Missense_Mutation 25965
Nonsense_Mutation 1986
Nonstop_Mutation 38
Silent 8788
Splice_Site 865
Total 40683
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 5184 1101604176 4.7e-06 4.7 3.2 2.2
*Cp(A/C/T)->T 5809 9664813395 6e-07 0.6 0.4 1.7
C->(G/A) 9423 10766417571 8.8e-07 0.88 0.59 4.9
A->mut 5543 10671091617 5.2e-07 0.52 0.35 3.8
indel+null 5849 21437509188 2.7e-07 0.27 0.18 NaN
double_null 81 21437509188 3.8e-09 0.0038 0.0025 NaN
Total 31889 21437509188 1.5e-06 1.5 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).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: BRCA-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: C->(G/A)

  • n4 = number of nonsilent mutations of type: A->mut

  • 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: 74. 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 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 956652 29 29 26 0 1 0 3 4 20 1 0.046 0.23 0.061 0 0 0
2 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 11396219 63 61 59 2 5 11 7 4 34 2 0.049 0.19 0.058 0 0 0
3 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 361639 8 8 1 1 0 0 0 0 8 0 0 1 0 1 0 0
4 GIGYF2 GRB10 interacting GYF protein 2 3088772 14 13 4 0 1 0 0 0 13 0 0 1 0 0.86 0 0
5 ZNF384 zinc finger protein 384 1360722 14 14 1 1 0 0 0 0 14 0 0 1 0 0 0 0
6 DCP1B DCP1 decapping enzyme homolog B (S. cerevisiae) 1373345 5 5 1 1 0 0 0 0 5 0 0 0.97 0 0.98 0 0
7 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 2526504 287 261 49 4 5 101 11 154 16 0 0 0 0 1.2e-14 0 0
8 NCOA3 nuclear receptor coactivator 3 3363126 30 29 12 0 1 2 3 2 22 0 0 0.99 0 2.4e-15 0 0
9 AOAH acyloxyacyl hydrolase (neutrophil) 1514305 19 19 1 3 0 0 0 0 19 0 0 1 0 1.3e-14 0 0
10 RBMX RNA binding motif protein, X-linked 966111 14 13 3 1 0 1 0 0 13 0 0 0.52 0 0 0 0
11 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 794236 25 25 23 3 0 2 1 4 17 1 0.0031 0.28 0.0062 0 0 0
12 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 1797680 21 21 20 1 0 3 2 3 13 0 2e-07 0.061 6.8e-06 2.2e-14 0 0
13 MEF2A myocyte enhancer factor 2A 1255054 14 14 3 0 0 0 0 1 13 0 0 0 0 3.7e-15 0 0
14 NCOR2 nuclear receptor co-repressor 2 3826500 29 29 7 1 1 0 2 0 26 0 2e-07 1 5.2e-06 6.3e-15 0 0
15 AKT1 v-akt murine thymoma viral oncogene homolog 1 951700 19 19 2 1 0 18 0 1 0 0 0 6.4e-06 0 0.00012 0 0
16 GATA3 GATA binding protein 3 764273 84 81 50 1 0 1 1 4 77 1 0 0.51 0 0 0 0
17 NR1H2 nuclear receptor subfamily 1, group H, member 2 802056 18 18 5 0 2 0 0 1 15 0 0 1 0 1.9e-15 0 0
18 MAP3K4 mitogen-activated protein kinase kinase kinase 4 3667040 18 18 5 2 0 1 0 0 17 0 0 0.68 0 4.7e-08 0 0
19 TP53 tumor protein p53 974889 261 257 145 3 35 28 32 62 104 0 0 0 0 0 0 0
20 TPRX1 tetra-peptide repeat homeobox 1 736132 8 7 4 0 0 0 0 4 4 0 0 0.88 0 1.4e-07 0 0
21 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 1998729 56 55 49 2 2 4 2 1 47 0 0.65 0.38 0.73 0 0 0
22 ATN1 atrophin 1 2206723 18 17 9 1 0 5 2 0 11 0 8e-05 0.97 0.00032 1.8e-13 2.2e-15 1.7e-12
23 MAP2K4 mitogen-activated protein kinase kinase 4 863577 32 32 28 0 3 2 5 2 20 0 0.072 0.19 0.095 2.6e-15 9e-15 6.5e-12
24 MAP3K1 mitogen-activated protein kinase kinase kinase 1 3179186 69 57 65 3 0 1 6 9 37 16 0.87 0.21 0.64 1e-15 2.3e-14 1.6e-11
25 CBFB core-binding factor, beta subunit 359167 16 16 16 1 0 4 3 4 5 0 0.058 0.3 0.075 1.5e-14 3.9e-14 2.6e-11
26 CTCF CCCTC-binding factor (zinc finger protein) 1695933 18 18 16 3 1 1 3 5 8 0 0.011 0.002 0.0013 1.3e-12 5.7e-14 3.7e-11
27 CCDC144NL coiled-coil domain containing 144 family, N-terminal like 495337 8 8 3 0 1 0 0 0 7 0 0.000027 1 0.00015 1.3e-10 6.4e-13 4e-10
28 AKD1 adenylate kinase domain containing 1 4187803 19 19 10 0 0 2 4 0 13 0 0.72 0.68 1 2e-12 5.7e-11 3.4e-08
29 RB1 retinoblastoma 1 (including osteosarcoma) 2081432 16 14 15 1 0 1 0 2 13 0 0.84 0.21 0.63 8.4e-12 1.4e-10 8.1e-08
30 FOXA1 forkhead box A1 763360 15 15 15 0 1 3 2 4 5 0 0.0091 0.092 0.0066 1.3e-09 2.2e-10 1.2e-07
31 PHLDA1 pleckstrin homology-like domain, family A, member 1 522212 9 9 5 0 0 0 4 0 5 0 0.0097 0.85 0.021 5.9e-10 3.2e-10 1.7e-07
32 VEZF1 vascular endothelial zinc finger 1 1198490 8 8 3 0 0 0 1 0 7 0 1e-05 1 0.000057 9.3e-07 1.3e-09 6.8e-07
33 ZFP36L1 zinc finger protein 36, C3H type-like 1 695039 10 10 10 0 0 1 1 1 7 0 0.021 0.8 0.042 1.6e-09 1.6e-09 8.2e-07
34 NCOR1 nuclear receptor co-repressor 1 5748805 31 31 31 2 0 2 5 2 21 1 0.35 0.56 0.52 7.4e-10 8.7e-09 4.3e-06
35 AQP7 aquaporin 7 796413 9 9 6 1 1 0 1 1 6 0 0.0018 0.63 0.0059 6.5e-08 8.8e-09 4.3e-06
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: 15. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 287 220 268 169840 161927 0 0
2 TP53 tumor protein p53 261 356 248 274832 47662 0 0
3 CDH1 cadherin 1, type 1, E-cadherin (epithelial) 56 185 23 142820 37 0 0
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 29 767 29 592124 1024 0 0
5 MAP2K4 mitogen-activated protein kinase kinase 4 32 15 6 11580 10 6.1e-13 5.3e-10
6 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 21 33 12 25476 20 1.2e-12 8e-10
7 GATA3 GATA binding protein 3 84 34 32 26248 212 1.3e-12 8e-10
8 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 13 42 8 32424 50 1.6e-12 8.5e-10
9 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 25 178 17 137416 57 5.7e-12 2.7e-09
10 FGFR2 fibroblast growth factor receptor 2 (bacteria-expressed kinase, keratinocyte growth factor receptor, craniofacial dysostosis 1, Crouzon syndrome, Pfeiffer syndrome, Jackson-Weiss syndrome) 7 51 5 39372 21 5.5e-09 2.4e-06

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: 122. 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 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(5), E2F1(4), MDM2(2), MYC(1), PIK3CA(287), PIK3R1(21), POLR1A(6), POLR1B(2), POLR1C(2), POLR1D(4), RB1(16), TP53(261) 21722333 611 480 255 16 45 137 49 227 153 0 <1.00e-15 <1.00e-15 <1.31e-14
2 HSA04620_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY Genes involved in Toll-like receptor signaling pathway AKT1, AKT2, AKT3, CASP8, CCL3, CCL4, CCL5, CD14, CD40, CD80, CD86, CHUK, CXCL10, CXCL11, CXCL9, FADD, FOS, IFNA1, IFNA10, IFNA13, IFNA14, IFNA16, IFNA17, IFNA2, IFNA21, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNAR1, IFNAR2, IFNB1, IKBKB, IKBKE, IKBKG, IL12A, IL12B, IL1B, IL6, IL8, IRAK1, IRAK4, IRF3, IRF5, IRF7, JUN, LBP, LY96, MAP2K1, MAP2K2, MAP2K3, MAP2K4, MAP2K6, MAP2K7, MAP3K7, MAP3K7IP1, MAP3K7IP2, MAP3K8, MAPK1, MAPK10, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPK8, MAPK9, MYD88, NFKB1, NFKB2, NFKBIA, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, RAC1, RELA, RIPK1, SPP1, STAT1, TBK1, TICAM1, TICAM2, TIRAP, TLR1, TLR2, TLR3, TLR4, TLR5, TLR6, TLR7, TLR8, TLR9, TNF, TOLLIP, TRAF3, TRAF6 98 AKT1(19), AKT2(3), AKT3(4), CASP8(10), CD14(2), CD40(1), CD86(2), CHUK(1), IFNA1(1), IFNA10(1), IFNA13(1), IFNA14(2), IFNA16(1), IFNA17(1), IFNA2(3), IFNA21(1), IFNA4(1), IFNA6(2), IFNAR1(1), IFNAR2(1), IFNB1(1), IKBKB(4), IKBKE(2), IL12A(1), IL12B(1), IL6(2), IRAK1(2), IRAK4(3), IRF3(3), IRF5(1), IRF7(1), JUN(3), LBP(1), MAP2K1(1), MAP2K2(1), MAP2K3(2), MAP2K4(32), MAP2K6(1), MAP2K7(1), MAP3K7(1), MAP3K8(2), MAPK1(1), MAPK10(2), MAPK13(1), MAPK14(2), MAPK3(1), MAPK8(2), NFKB1(4), NFKB2(3), NFKBIA(1), PIK3CA(287), PIK3CB(6), PIK3CD(4), PIK3CG(3), PIK3R1(21), PIK3R3(2), RELA(1), RIPK1(3), SPP1(2), STAT1(1), TBK1(1), TICAM1(5), TIRAP(1), TLR1(1), TLR2(1), TLR3(5), TLR4(13), TLR5(2), TLR7(8), TLR8(3), TLR9(1), TRAF3(2), TRAF6(3) 97377478 517 400 253 43 27 160 56 187 85 2 <1.00e-15 <1.00e-15 <1.31e-14
3 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(5), ABL2(4), AKT1(19), AKT2(3), AKT3(4), ARAF(4), AREG(1), BRAF(3), BTC(1), CAMK2A(2), CAMK2D(4), CAMK2G(1), CBL(4), CBLB(10), CBLC(2), CDKN1B(7), CRK(1), CRKL(1), EGF(3), EGFR(5), ELK1(2), ERBB2(13), ERBB3(11), ERBB4(6), GAB1(2), GRB2(1), JUN(3), KRAS(6), MAP2K1(1), MAP2K2(1), MAP2K4(32), MAP2K7(1), MAPK1(1), MAPK10(2), MAPK3(1), MAPK8(2), MYC(1), NCK1(1), NCK2(1), NRAS(1), NRG1(2), NRG3(4), PAK1(2), PAK2(2), PAK3(2), PAK4(1), PAK6(1), PAK7(2), PIK3CA(287), PIK3CB(6), PIK3CD(4), PIK3CG(3), PIK3R1(21), PIK3R3(2), PLCG1(6), PLCG2(3), PRKCG(2), PTK2(5), RAF1(1), RPS6KB1(2), RPS6KB2(4), SHC1(1), SHC2(1), SHC3(1), SHC4(2), SOS1(4), SOS2(4), STAT5A(4), STAT5B(5), TGFA(1) 112604599 558 393 290 53 39 160 78 198 83 0 <1.00e-15 <1.00e-15 <1.31e-14
4 APOPTOSIS APAF1, BAD, BAK1, BCL2L7P1, BAX, BCL2, BCL2L1, BCL2L11, BID, BIRC2, BIRC3, BIRC4, BIRC5, BNIP3L, CASP1, CASP10, CASP1, COPl, CASP2, CASP3, CASP4, CASP6, CASP7, CASP8, CASP9, CHUK, CYCS, DFFA, DFFB, FADD, FAS, FASLG, GZMB, HELLS, HRK, IKBKB, IKBKG, IRF1, IRF2, IRF3, IRF4, IRF5, IRF6, IRF7, JUN, LTA, MAP2K4, MAP3K1, MAPK10, MDM2, MYC, NFKB1, NFKBIA, NFKBIB, NFKBIE, PRF1, RELA, RIPK1, TNF, TNFRSF10B, TNFRSF1A, TNFRSF1B, TNFRSF21, TNFRSF25, TNFRSF25, PLEKHG5, TNFSF10, TP53, TP73, TRADD, TRAF1, TRAF2, TRAF3 65 APAF1(3), BAK1(2), BAX(2), BCL2L11(4), BID(4), BIRC3(1), CASP1(1), CASP2(3), CASP4(1), CASP6(2), CASP7(1), CASP8(10), CASP9(1), CHUK(1), DFFB(2), FAS(1), FASLG(2), IKBKB(4), IRF1(1), IRF3(3), IRF5(1), IRF6(2), IRF7(1), JUN(3), LTA(1), MAP2K4(32), MAP3K1(69), MAPK10(2), MDM2(2), MYC(1), NFKB1(4), NFKBIA(1), NFKBIE(1), PLEKHG5(3), PRF1(2), RELA(1), RIPK1(3), TNFRSF1A(1), TNFRSF21(2), TNFRSF25(1), TP53(261), TP73(1), TRAF1(1), TRAF3(2) 61619955 447 372 322 16 51 55 60 83 181 17 <1.00e-15 <1.00e-15 <1.31e-14
5 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 56 ALG2(2), BAK1(2), BAX(2), BFAR(2), BTK(4), CAD(10), CASP8(10), CSNK1A1(1), DAXX(2), EGFR(5), EPHB2(3), IL1A(1), MAP2K4(32), MAP2K7(1), MAP3K1(69), MAP3K5(2), MAPK1(1), MAPK10(2), MAPK8(2), MAPK8IP1(2), MAPK8IP2(2), MAPK8IP3(3), MET(7), NFAT5(6), NFKB1(4), NFKB2(3), NFKBIA(1), NFKBIE(1), NR0B2(2), PTPN13(5), RALBP1(1), RIPK1(3), ROCK1(4), SMPD1(1), TP53(261), TUFM(2) 75893988 461 368 336 27 53 55 68 87 181 17 <1.00e-15 <1.00e-15 <1.31e-14
6 SIG_CHEMOTAXIS Genes related to chemotaxis ACTR2, ACTR3, AKT1, AKT2, AKT3, ANGPTL2, ARHGAP1, ARHGAP4, ARHGEF11, BTK, CDC42, CFL1, CFL2, GDI1, GDI2, INPPL1, ITPR1, ITPR2, ITPR3, LIMK1, MYLK, MYLK2, P101-PI3K, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PDK1, PIK3CA, PIK3CD, PIK3CG, PIK3R1, PITX2, PPP1R13B, PTEN, RACGAP1, RHO, ROCK1, ROCK2, RPS4X, SAG, WASF1, WASL 44 AKT1(19), AKT2(3), AKT3(4), ANGPTL2(1), ARHGAP4(1), ARHGEF11(3), BTK(4), GDI1(4), INPPL1(4), ITPR1(10), ITPR2(7), ITPR3(6), LIMK1(4), MYLK(8), MYLK2(2), PAK1(2), PAK2(2), PAK3(2), PAK4(1), PAK6(1), PAK7(2), PDK1(1), PIK3CA(287), PIK3CD(4), PIK3CG(3), PIK3R1(21), PITX2(3), PPP1R13B(3), PTEN(29), RHO(4), ROCK1(4), ROCK2(4), RPS4X(2), SAG(1), WASF1(5), WASL(1) 78418068 462 367 203 41 24 143 46 182 66 1 <1.00e-15 <1.00e-15 <1.31e-14
7 HSA00562_INOSITOL_PHOSPHATE_METABOLISM Genes involved in inositol phosphate metabolism CARKL, FN3K, IMPA1, IMPA2, INPP1, INPP4A, INPP4B, INPP5A, INPP5B, INPP5E, INPPL1, IPMK, ISYNA1, ITGB1BP3, ITPK1, ITPKA, ITPKB, MINPP1, MIOX, OCRL, PI4KA, PI4KB, PIB5PA, PIK3C3, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIP4K2A, PIP4K2B, PIP4K2C, PIP5K1A, PIP5K1B, PIP5K1C, PIP5K3, PLCB1, PLCB2, PLCB3, PLCB4, PLCD1, PLCD3, PLCD4, PLCE1, PLCG1, PLCG2, PLCZ1, PTEN, PTPMT1, SKIP, SYNJ1, SYNJ2 47 FN3K(1), IMPA1(1), INPP4A(4), INPP4B(5), INPP5A(2), INPP5B(5), INPPL1(4), IPMK(1), ITGB1BP3(1), ITPK1(1), ITPKA(1), ITPKB(7), MINPP1(1), OCRL(6), PI4KA(5), PI4KB(1), PIK3C3(2), PIK3CA(287), PIK3CB(6), PIK3CD(4), PIK3CG(3), PIP4K2A(1), PIP4K2C(6), PIP5K1A(2), PIP5K1B(1), PIP5K1C(4), PLCB1(4), PLCB2(2), PLCB3(3), PLCB4(7), PLCD1(1), PLCD3(3), PLCD4(1), PLCE1(12), PLCG1(6), PLCG2(3), PLCZ1(8), PTEN(29), SYNJ1(2), SYNJ2(1) 81472703 444 366 200 36 28 119 52 180 64 1 <1.00e-15 <1.00e-15 <1.31e-14
8 SIG_PIP3_SIGNALING_IN_CARDIAC_MYOCTES Genes related to PIP3 signaling in cardiac myocytes AKT1, AKT2, AKT3, BAD, BCL2L1, CDC42, CDK2, CDKN1B, CDKN2A, CREB1, CREB3, CREB5, EBP, ERBB4, F2RL2, FOXO3A, FRAP1, GAB1, GADD45A, GRB2, GSK3A, GSK3B, IFI27, IGF1, IGFBP1, INPPL1, IRS1, IRS2, IRS4, MET, MYC, NOLC1, P101-PI3K, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PARD3, PARD6A, PDK1, PIK3CA, PIK3CD, PPP1R13B, PREX1, PSCD3, PTEN, PTK2, PTPN1, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KB1, SFN, SHC1, SLC2A4, SOS1, SOS2, TSC1, TSC2, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 62 AKT1(19), AKT2(3), AKT3(4), CDK2(1), CDKN1B(7), CREB1(1), CREB3(1), CREB5(1), EBP(1), ERBB4(6), F2RL2(1), GAB1(2), GRB2(1), GSK3A(3), IFI27(2), IGF1(1), INPPL1(4), IRS1(2), IRS4(6), MET(7), MYC(1), NOLC1(2), PAK1(2), PAK2(2), PAK3(2), PAK4(1), PAK6(1), PAK7(2), PARD3(4), PDK1(1), PIK3CA(287), PIK3CD(4), PPP1R13B(3), PREX1(10), PTEN(29), PTK2(5), RPS6KA1(2), RPS6KA2(4), RPS6KA3(4), RPS6KB1(2), SHC1(1), SLC2A4(1), SOS1(4), SOS2(4), TSC1(4), TSC2(2), YWHAB(1), YWHAG(1), YWHAZ(1) 82302068 460 366 200 39 29 142 52 175 61 1 <1.00e-15 <1.00e-15 <1.31e-14
9 SIG_INSULIN_RECEPTOR_PATHWAY_IN_CARDIAC_MYOCYTES Genes related to the insulin receptor pathway AKT1, AKT2, AKT3, BRD4, CAP1, CBL, CDC42, CDKN2A, F2RL2, FLOT1, FLOT2, FOXO1A, GRB2, GSK3A, GSK3B, IGFBP1, INPPL1, IRS1, IRS2, IRS4, LNPEP, MAPK1, MAPK3, PARD3, PARD6A, PDK1, PIK3CA, PIK3CD, PIK3R1, PPYR1, PSCD3, PTEN, PTPN1, RAF1, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KB1, SERPINB6, SFN, SHC1, SLC2A4, SORBS1, SOS1, SOS2, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 48 AKT1(19), AKT2(3), AKT3(4), BRD4(2), CAP1(2), CBL(4), F2RL2(1), FLOT1(1), FLOT2(2), GRB2(1), GSK3A(3), INPPL1(4), IRS1(2), IRS4(6), MAPK1(1), MAPK3(1), PARD3(4), PDK1(1), PIK3CA(287), PIK3CD(4), PIK3R1(21), PPYR1(1), PTEN(29), RAF1(1), RPS6KA1(2), RPS6KA2(4), RPS6KA3(4), RPS6KB1(2), SERPINB6(1), SHC1(1), SLC2A4(1), SORBS1(5), SOS1(4), SOS2(4), YWHAB(1), YWHAG(1), YWHAZ(1) 62745024 435 362 176 35 25 135 43 172 59 1 <1.00e-15 <1.00e-15 <1.31e-14
10 PPARAPATHWAY Peroxisome proliferators regulate gene expression via PPAR/RXR heterodimers which bind to peroxisome-proliferator response elements (PPREs). ACOX1, APOA1, APOA2, CD36, CITED2, CPT1B, CREBBP, DUSP1, DUT, EHHADH, EP300, FABP1, FAT, FRA8B, HSD17B4, HSPA1A, HSPCA, INS, JUN, LPL, MAPK1, MAPK3, ME1, MRPL11, MYC, NCOA1, NCOR1, NCOR2, NFKBIA, NOS2A, NR0B2, NR1H3, NR2F1, NRIP1, PDGFA, PIK3CA, PIK3R1, PPARA, PPARBP, PPARGC1, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCA, PRKCB1, PTGS2, RB1, RELA, RXRA, SP1, SRA1, STAT5A, STAT5B, TNF 49 ACOX1(2), CD36(1), CITED2(2), CPT1B(2), CREBBP(7), EHHADH(3), EP300(7), FABP1(1), HSD17B4(6), JUN(3), LPL(1), MAPK1(1), MAPK3(1), MRPL11(1), MYC(1), NCOA1(2), NCOR1(31), NCOR2(29), NFKBIA(1), NR0B2(2), NR2F1(1), NRIP1(3), PIK3CA(287), PIK3R1(21), PPARA(2), PRKACG(1), PRKAR1A(4), PRKAR2A(1), PRKAR2B(1), PTGS2(2), RB1(16), RELA(1), RXRA(1), SP1(3), SRA1(1), STAT5A(4), STAT5B(5) 68924350 458 361 195 30 20 120 40 172 105 1 <1.00e-15 <1.00e-15 <1.31e-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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