Mutation Analysis (MutSig v1.5)
Uterine Carcinosarcoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C15T3J0N
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C15T3J0N
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 v1.5 was used to generate the results found in this report.

  • Working with individual set: UCS-TP

  • Number of patients in set: 56

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:UCS-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 15

  • Mutations seen in COSMIC: 122

  • Significantly mutated genes in COSMIC territory: 14

  • Significantly mutated genesets: 107

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

Mutation Preprocessing

  • Read 56 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 5885

  • After removing 73 mutations outside chr1-24: 5812

  • After removing 436 blacklisted mutations: 5376

  • After removing 142 noncoding mutations: 5234

Mutation Filtering

  • Number of mutations before filtering: 5234

  • After removing 241 mutations outside gene set: 4993

  • After removing 9 mutations outside category set: 4984

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 241
Frame_Shift_Ins 70
In_Frame_Del 66
In_Frame_Ins 9
Missense_Mutation 3094
Nonsense_Mutation 190
Nonstop_Mutation 2
Silent 1140
Splice_Site 171
Translation_Start_Site 1
Total 4984
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 956 93550090 1e-05 10 4.4 2.1
*Cp(A/C/T)->T 539 752108946 7.2e-07 0.72 0.31 1.7
C->(G/A) 934 845659036 1.1e-06 1.1 0.47 4.7
A->mut 665 804953394 8.3e-07 0.83 0.35 3.9
indel+null 742 1650612430 4.5e-07 0.45 0.19 NaN
double_null 8 1650612430 4.8e-09 0.0048 0.0021 NaN
Total 3844 1650612430 2.3e-06 2.3 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: UCS-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_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene

  • 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: 15. 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_ns_s p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 183136 20 19 12 0 1 5 4 10 0 0 0.0074 1.4e-15 1.9e-11
2 TP53 tumor protein p53 67630 53 50 41 0 13 5 11 12 11 1 1.2e-06 2.4e-15 1.9e-11
3 FBXW7 F-box and WD repeat domain containing 7 137401 22 21 13 0 11 4 5 1 1 0 0.0051 4e-15 1.9e-11
4 PPP2R1A protein phosphatase 2 (formerly 2A), regulatory subunit A , alpha isoform 97739 16 15 9 0 6 3 7 0 0 0 0.0022 4.8e-15 1.9e-11
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 62969 12 10 11 0 0 2 4 1 4 1 0.079 5.2e-15 1.9e-11
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 36117 7 7 2 0 0 2 5 0 0 0 0.35 8.8e-15 2.6e-11
7 CHD4 chromodomain helicase DNA binding protein 4 330111 10 9 10 0 2 1 0 5 2 0 0.055 1.8e-08 0.000043
8 ZBTB7B zinc finger and BTB domain containing 7B 90705 7 6 7 0 1 0 2 1 3 0 0.25 1.9e-08 0.000043
9 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 131829 8 6 8 0 0 1 0 0 7 0 0.69 2.4e-08 0.000049
10 RB1 retinoblastoma 1 (including osteosarcoma) 130797 5 5 5 0 0 0 0 1 4 0 0.44 2.4e-06 0.0043
11 SPOP speckle-type POZ protein 64941 5 4 5 0 1 0 2 2 0 0 0.35 2.9e-06 0.0048
12 ARID1A AT rich interactive domain 1A (SWI-like) 330840 6 6 6 0 0 0 2 1 2 1 0.29 8e-06 0.012
13 MGAM maltase-glucoamylase (alpha-glucosidase) 283797 5 5 5 1 1 1 0 2 1 0 0.48 0.000015 0.021
14 HCFC1R1 host cell factor C1 regulator 1 (XPO1 dependent) 18412 2 2 2 0 0 0 0 0 2 0 1 0.000027 0.036
15 ATP4A ATPase, H+/K+ exchanging, alpha polypeptide 174835 5 5 5 0 3 0 1 0 1 0 0.19 0.000038 0.046
16 MAGEC2 melanoma antigen family C, 2 63056 3 3 3 0 0 0 3 0 0 0 0.57 0.00013 0.14
17 FOXA2 forkhead box A2 63342 3 3 3 0 1 0 1 0 1 0 0.32 0.00014 0.14
18 ALCAM activated leukocyte cell adhesion molecule 101235 3 3 3 0 0 0 1 1 1 0 0.67 0.00016 0.16
19 CDK11B cyclin-dependent kinase 11B 80812 4 3 4 0 1 1 1 1 0 0 0.26 0.00017 0.16
20 BCL2L11 BCL2-like 11 (apoptosis facilitator) 34103 2 2 1 0 0 0 0 0 2 0 1 0.00018 0.16
21 GPRASP1 G protein-coupled receptor associated sorting protein 1 234078 4 4 4 0 0 1 1 1 1 0 0.48 0.00019 0.17
22 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 234905 5 4 5 0 2 1 1 0 1 0 0.21 0.00034 0.28
23 U2AF1 U2 small nuclear RNA auxiliary factor 1 45976 2 2 1 0 0 2 0 0 0 0 0.38 0.00038 0.3
24 SAV1 salvador homolog 1 (Drosophila) 63610 2 2 2 0 0 0 1 0 1 0 0.71 0.00044 0.33
25 APOBEC1 apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 40922 2 2 2 0 1 0 1 0 0 0 0.6 0.00046 0.34
26 NCK1 NCK adaptor protein 1 64118 2 2 2 0 1 1 0 0 0 0 0.56 0.00055 0.36
27 MAGEB2 melanoma antigen family B, 2 44875 2 2 2 1 0 1 0 0 1 0 0.82 0.00057 0.36
28 LYPLA2 lysophospholipase II 40708 2 2 2 1 0 0 0 0 2 0 1 0.00058 0.36
29 YARS tyrosyl-tRNA synthetase 90885 3 3 3 0 1 0 2 0 0 0 0.45 0.00058 0.36
30 SERPINB2 serpin peptidase inhibitor, clade B (ovalbumin), member 2 71156 2 2 2 0 2 0 0 0 0 0 0.5 0.00059 0.36
31 YPEL4 yippee-like 4 (Drosophila) 19703 2 2 2 0 0 1 0 1 0 0 0.5 0.00066 0.38
32 EPHA5 EPH receptor A5 171161 3 3 3 0 0 2 1 0 0 0 0.41 0.00072 0.4
33 KLHL4 kelch-like 4 (Drosophila) 122460 3 3 3 0 1 0 0 2 0 0 0.41 0.00083 0.44
34 USP10 ubiquitin specific peptidase 10 119023 3 3 3 0 1 0 0 1 1 0 0.49 0.00085 0.44
35 NRXN1 neurexin 1 250202 4 4 4 0 1 0 1 1 1 0 0.34 0.00085 0.44
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

FBXW7

Figure S3.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PPP2R1A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PPP2R1A significant gene.

PTEN

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

KRAS

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

CHD4

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CHD4 significant gene.

ZBTB7B

Figure S8.  This figure depicts the distribution of mutations and mutation types across the ZBTB7B significant gene.

PIK3R1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

RB1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

SPOP

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

ARID1A

Figure S12.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

MGAM

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

HCFC1R1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the HCFC1R1 significant gene.

ATP4A

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ATP4A 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: 14. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 7 52 7 2912 101988 1.6e-13 6.2e-10
2 FBXW7 F-box and WD repeat domain containing 7 22 91 17 5096 784 2.7e-13 6.2e-10
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 20 220 18 12320 8404 6.5e-13 9.8e-10
4 TP53 tumor protein p53 53 356 50 19936 15995 1e-12 1.2e-09
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 12 767 12 42952 574 2.1e-12 1.9e-09
6 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 8 33 4 1848 9 1.4e-11 1.1e-08
7 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 5 6 2 336 2 3.1e-07 0.0002
8 RB1 retinoblastoma 1 (including osteosarcoma) 5 267 3 14952 10 6.9e-06 0.0039
9 F13A1 coagulation factor XIII, A1 polypeptide 1 1 1 56 1 0.00013 0.045
10 FERD3L Fer3-like (Drosophila) 2 1 1 56 1 0.00013 0.045

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: 107. 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 G1_TO_S_CELL_CYCLE_REACTOME ATM, CCNA1, CCNB1, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNG2, CCNH, CDC25A, CDC45L, CDK2, CDK4, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CREB3, CREB3L1, CREB3L3, CREB3L4, CREBL1, CREBL1, TNXB, E2F1, E2F2, E2F3, E2F4, E2F5, E2F6, FLJ14001, GADD45A, GBA2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, MNAT1, MYC, MYT1, NACA, NACA, FKSG17, ORC1L, ORC2L, ORC3L, ORC4L, ORC5L, ORC6L, PCNA, POLA2, POLE, POLE2, PRIM1, PRIM2A, RB1, RBL1, RPA1, RPA2, RPA3, TFDP1, TFDP2, TP53, WEE1 64 ATM(1), CCND1(1), CCNE2(1), CDKN2B(1), E2F1(1), MCM2(1), MCM3(1), MCM7(1), MYC(2), RB1(5), TNXB(3), TP53(53) 6467211 71 53 59 3 18 6 14 16 15 2 2.7e-06 <1.00e-15 <8.36e-14
2 HSA04110_CELL_CYCLE Genes involved in cell cycle ABL1, ANAPC1, ANAPC10, ANAPC11, ANAPC2, ANAPC4, ANAPC5, ANAPC7, ATM, ATR, BUB1, BUB1B, BUB3, CCNA1, CCNA2, CCNB1, CCNB2, CCNB3, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNH, CDC14A, CDC14B, CDC16, CDC2, CDC20, CDC23, CDC25A, CDC25B, CDC25C, CDC26, CDC27, CDC45L, CDC6, CDC7, CDK2, CDK4, CDK6, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CHEK1, CHEK2, CREBBP, CUL1, DBF4, E2F1, E2F2, E2F3, EP300, ESPL1, FZR1, GADD45A, GADD45B, GADD45G, GSK3B, hCG_1982709, HDAC1, HDAC2, LOC440917, LOC728919, MAD1L1, MAD2L1, MAD2L2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, ORC1L, ORC2L, ORC3L, ORC4L, ORC5L, ORC6L, PCNA, PKMYT1, PLK1, PRKDC, PTTG1, PTTG2, RB1, RBL1, RBL2, RBX1, SFN, SKP1, SKP2, SMAD2, SMAD3, SMAD4, SMC1A, SMC1B, TFDP1, TGFB1, TGFB2, TGFB3, TP53, WEE1, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 109 ATM(1), CCND1(1), CCNE2(1), CDKN2B(1), CHEK2(1), CREBBP(3), E2F1(1), EP300(1), MAD1L1(3), MCM2(1), MCM3(1), MCM7(1), PLK1(1), PRKDC(2), RB1(5), SMAD4(1), SMC1A(2), TGFB1(1), TP53(53) 11242046 81 53 69 5 19 9 13 18 20 2 2e-05 <1.00e-15 <8.36e-14
3 G2PATHWAY Activated Cdc2-cyclin B kinase regulates the G2/M transition; DNA damage stimulates the DNA-PK/ATM/ATR kinases, which inactivate Cdc2. ATM, ATR, BRCA1, CCNB1, CDC2, CDC25A, CDC25B, CDC25C, CDC34, CDKN1A, CDKN2D, CHEK1, CHEK2, EP300, GADD45A, MDM2, MYT1, PLK, PRKDC, RPS6KA1, TP53, WEE1, YWHAH, YWHAQ 22 ATM(1), CHEK2(1), EP300(1), PRKDC(2), TP53(53) 3451486 58 51 46 2 13 6 11 14 13 1 0.000062 <1.00e-15 <8.36e-14
4 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 CCND1(1), E2F1(1), TP53(53) 715602 55 51 43 0 14 6 11 12 11 1 2.3e-07 <1.00e-15 <8.36e-14
5 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 16 ITGB1(1), PDK2(1), PIK3CA(20), PIK3R1(8), PTEN(12) 1601926 42 29 33 0 1 8 9 12 11 1 0.000067 <1.00e-15 <8.36e-14
6 RAC1PATHWAY Rac-1 is a Rho family G protein that stimulates formation of actin-dependent structures such as filopodia and lamellopodia. ARFIP2, CDK5, CDK5R1, CFL1, CHN1, LIMK1, MAP3K1, MYL2, MYLK, NCF2, PAK1, PDGFRA, PIK3CA, PIK3R1, PLD1, PPP1R12B, RAC1, RALBP1, RPS6KB1, TRIO, VAV1, WASF1 22 MAP3K1(1), MYLK(2), NCF2(1), PIK3CA(20), PIK3R1(8), RAC1(1), TRIO(1) 2914394 34 29 26 1 4 6 6 10 8 0 0.0034 <1.00e-15 <8.36e-14
7 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 TP53(53) 813982 53 50 41 1 13 5 11 12 11 1 0.000016 1.11e-15 8.36e-14
8 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 66 APAF1(2), BCL2L1(1), BCL2L11(2), CASP4(1), IRF2(1), LTA(1), MAP3K1(1), MYC(2), TP53(53) 4816924 64 51 51 2 15 7 11 14 16 1 4.2e-06 1.44e-15 8.36e-14
9 TELPATHWAY Telomerase is a ribonucleotide protein that adds telomeric repeats to the 3' ends of chromosomes. AKT1, BCL2, EGFR, G22P1, HSPCA, IGF1R, KRAS2, MYC, POLR2A, PPP2CA, PRKCA, RB1, TEP1, TERF1, TERT, TNKS, TP53, XRCC5 15 MYC(2), POLR2A(2), RB1(5), TNKS(1), TP53(53) 2347887 63 52 51 0 14 6 11 16 15 1 2.8e-08 1.78e-15 8.36e-14
10 IGF1RPATHWAY Insulin-like growth factor receptor IGF-1R promotes cell growth and inhibits apoptosis on binding of ligands IGF-1 and 2 via Ras activation and the AKT pathway. AKT1, BAD, GRB2, HRAS, IGF1R, IRS1, MAP2K1, MAPK1, MAPK3, PIK3CA, PIK3R1, RAF1, SHC1, SOS1, YWHAH 15 IRS1(2), PIK3CA(20), PIK3R1(8) 1580367 30 25 22 1 1 6 5 10 8 0 0.0091 1.89e-15 8.36e-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 ACTINYPATHWAY The Arp 2/3 complex localizes to the Y-junction of polymerizing actin fibers that enable lamellipod extension and consequent cell motility. ABI-2, ACTA1, ACTR2, ACTR3, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, NCK1, NCKAP1, NTRK1, PIR, PSMA7, RAC1, WASF1, WASF2, WASF3, WASL 18 ACTA1(1), ACTR3(1), NCK1(2), NCKAP1(1), NTRK1(2), RAC1(1), WASF3(1) 1267510 9 8 9 1 3 1 3 0 2 0 0.22 0.0021 1
2 CTLA4PATHWAY T cell activation requires interaction with an antigen-MHC-I complex on an antigen-presenting cell (APC), as well as CD28 interaction with the APC's CD80 or 86. CD28, CD3D, CD3E, CD3G, CD3Z, CD80, CD86, CTLA4, GRB2, HLA-DRA, HLA-DRB1, ICOS, ICOSL, IL2, ITK, LCK, PIK3CA, PIK3R1, PTPN11, TRA@, TRB@ 15 CD3E(1), CD80(1), CD86(1), HLA-DRA(1), IL2(1) 751579 5 5 5 0 2 2 0 1 0 0 0.15 0.0054 1
3 IL5PATHWAY Pro-inflammatory IL-5 is secretes by activated T cells, eosinophils, and mast cells, and stimulates the proliferation and activation of eosinophils in bone marrow. CCL11, CCR3, CD4, HLA-DRA, HLA-DRB1, IL1B, IL4, IL5, IL5RA, IL6 10 CCR3(1), HLA-DRA(1), IL1B(1), IL5RA(1) 445601 4 4 4 0 1 1 2 0 0 0 0.26 0.0055 1
4 ASBCELLPATHWAY B cells require interaction with helper T cells to produce antigen-specific immunoglobulins as a key element of the human immune response. CD28, CD4, CD80, HLA-DRA, HLA-DRB1, IL10, IL2, IL4, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 8 CD80(1), HLA-DRA(1), IL2(1) 331916 3 3 3 0 2 1 0 0 0 0 0.28 0.0098 1
5 INTRINSICPATHWAY The intrinsic prothrombin activation pathway is activated by traumatized blood vessels and induces clot formation. COL4A1, COL4A2, COL4A3, COL4A4, COL4A5, COL4A6, F10, F11, F12, F2, F2R, F5, F8, F9, FGA, FGB, FGG, KLKB1, KNG, PROC, PROS1, SERPINC1, SERPING1 22 COL4A1(1), COL4A2(1), COL4A4(1), COL4A5(1), COL4A6(1), F10(1), F12(1), F2(1), F5(1), F8(3), F9(2), FGB(1), KLKB1(2), PROS1(1) 3694262 18 13 18 2 4 2 4 4 4 0 0.093 0.021 1
6 SA_PROGRAMMED_CELL_DEATH Programmed cell death, or apoptosis, eliminates damaged or unneeded cells. APAF1, BAD, BAK1, BAX, BCL10, BCL2, BCL2L1, BCL2L11, BID, CASP8AP2, CASP9, CES1 12 APAF1(2), BCL2L1(1), BCL2L11(2) 903234 5 5 4 1 1 1 0 0 3 0 0.61 0.021 1
7 TOB1PATHWAY TGF-beta signaling activates SMADs, which interact with intracellular Tob to maintain unstimulated T cells by repressing IL-2 expression. CD28, CD3D, CD3E, CD3G, CD3Z, IFNG, IL2, IL2RA, IL4, MADH3, MADH4, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, TOB1, TOB2, TRA@, TRB@ 16 CD3E(1), IL2(1), TGFB1(1), TGFBR3(1), TOB2(1) 881985 5 5 5 0 2 1 0 1 1 0 0.19 0.022 1
8 PARKINPATHWAY In Parkinson's disease, dopaminergic neurons contain Lewy bodies consisting of alpha-synuclein and parkin, an E3 ubiquitin ligase that targets glycosylated alpha-synuclein. GPR37, PARK2, PNUTL1, SNCA, SNCAIP, UBE2E2, UBE2F, UBE2G1, UBE2G2, UBE2L3, UBE2L6, UBL1 10 GPR37(2), SNCAIP(1), UBE2G1(1) 537177 4 4 4 1 1 1 0 1 1 0 0.56 0.022 1
9 EPHA4PATHWAY Eph Kinases and ephrins support platelet aggregation ACTA1, EPHA4, EPHB1, FYN, ITGA1, ITGB1, L1CAM, LYN, RAP1B, SELP 10 ACTA1(1), EPHB1(2), ITGA1(1), ITGB1(1), L1CAM(2) 1314247 7 6 7 1 1 2 1 1 2 0 0.31 0.036 1
10 FIBRINOLYSISPATHWAY Thrombin cleavage of fibrinogen results in rapid formation of fibrin threads that form a mesh to capture platelets and other blood cells into a clot. CPB2, F13A1, F2, F2R, FGA, FGB, FGG, PLAT, PLAU, PLG, SERPINB2, SERPINE1 12 F13A1(1), F2(1), FGB(1), SERPINB2(2) 1114388 5 5 5 0 3 0 0 0 2 0 0.3 0.037 1
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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