Mutation Analysis (MutSig v1.5)
Uterine Carcinosarcoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1N58KB7
Maintained by David Heiman (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/C1N58KB7
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: 57

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

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

  • Significantly mutated genes (q ≤ 0.1): 19

  • Mutations seen in COSMIC: 139

  • Significantly mutated genes in COSMIC territory: 13

  • Significantly mutated genesets: 104

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

Mutation Preprocessing

  • Read 57 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 11339

  • After removing 78 mutations outside chr1-24: 11261

  • After removing 432 blacklisted mutations: 10829

  • After removing 889 noncoding mutations: 9940

Mutation Filtering

  • Number of mutations before filtering: 9940

  • After removing 511 mutations outside gene set: 9429

  • After removing 38 mutations outside category set: 9391

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 81
In_Frame_Del 66
In_Frame_Ins 10
Missense_Mutation 6146
Nonsense_Mutation 592
Nonstop_Mutation 13
Silent 1922
Splice_Site 284
Translation_Start_Site 36
Total 9391
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 1706 95243737 0.000018 18 4 2.1
*Cp(A/C/T)->T 829 765648006 1.1e-06 1.1 0.24 1.7
C->(G/A) 1893 860891743 2.2e-06 2.2 0.49 4.7
A->mut 1752 819427697 2.1e-06 2.1 0.48 3.9
indel+null 1257 1680319440 7.5e-07 0.75 0.17 NaN
double_null 32 1680319440 1.9e-08 0.019 0.0043 NaN
Total 7469 1680319440 4.4e-06 4.4 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: 19. 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 TP53 tumor protein p53 68846 55 51 43 0 14 5 11 12 12 1 6.6e-07 2.7e-15 3.4e-11
2 FBXW7 F-box and WD repeat domain containing 7 139842 24 22 15 0 12 4 5 1 2 0 0.0031 4.8e-15 3.4e-11
3 PPP2R1A protein phosphatase 2 (formerly 2A), regulatory subunit A , alpha isoform 99487 17 16 10 0 7 3 7 0 0 0 0.0015 7.1e-15 3.4e-11
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 186411 22 20 13 0 3 5 4 10 0 0 0.0057 9.1e-15 3.4e-11
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 64171 15 11 14 0 1 2 4 2 5 1 0.042 9.3e-15 3.4e-11
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 36696 7 7 2 0 0 2 5 0 0 0 0.35 1.2e-14 3.5e-11
7 CHD4 chromodomain helicase DNA binding protein 4 336006 12 10 12 0 2 1 0 6 3 0 0.037 1e-08 0.000026
8 ZBTB7B zinc finger and BTB domain containing 7B 92321 7 6 7 0 1 0 2 1 3 0 0.25 2.7e-08 0.000061
9 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 134194 8 6 8 0 0 1 0 0 7 0 0.69 3.7e-08 0.000075
10 RB1 retinoblastoma 1 (including osteosarcoma) 133287 6 6 6 0 0 0 0 1 4 1 0.4 1.8e-07 0.00033
11 SPOP speckle-type POZ protein 66102 5 4 5 0 1 0 2 2 0 0 0.35 3.9e-06 0.0063
12 NDUFAF2 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, assembly factor 2 23615 3 3 1 0 3 0 0 0 0 0 0.29 4.2e-06 0.0063
13 ARID1A AT rich interactive domain 1A (SWI-like) 336825 8 7 8 0 1 0 2 1 3 1 0.16 4.7e-06 0.0065
14 MGAM maltase-glucoamylase (alpha-glucosidase) 289007 7 6 7 1 2 1 1 2 1 0 0.34 1e-05 0.013
15 MAGEC2 melanoma antigen family C, 2 64182 5 4 5 0 0 1 4 0 0 0 0.3 0.000016 0.02
16 LYPLA2 lysophospholipase II 41440 3 3 3 0 0 0 1 0 2 0 0.78 0.000031 0.034
17 PCSK5 proprotein convertase subtilisin/kexin type 5 160383 5 5 2 0 0 0 0 5 0 0 0.37 0.000032 0.034
18 ATP4A ATPase, H+/K+ exchanging, alpha polypeptide 177895 5 5 5 0 3 0 1 0 1 0 0.19 0.000052 0.051
19 HCFC1R1 host cell factor C1 regulator 1 (XPO1 dependent) 18746 2 2 2 0 0 0 0 0 2 0 1 0.000054 0.051
20 TREX2 three prime repair exonuclease 2 22043 2 2 2 0 0 2 0 0 0 0 0.27 0.00024 0.21
21 FOXA2 forkhead box A2 64487 3 3 3 0 1 0 1 0 1 0 0.32 0.00025 0.21
22 KLHL4 kelch-like 4 (Drosophila) 124723 4 4 4 0 1 0 1 2 0 0 0.36 0.00026 0.21
23 ALCAM activated leukocyte cell adhesion molecule 103047 3 3 3 0 0 0 1 1 1 0 0.67 0.00029 0.23
24 SAV1 salvador homolog 1 (Drosophila) 64779 3 3 3 0 0 0 1 1 1 0 0.52 0.00033 0.24
25 FAM92B family with sequence similarity 92, member B 52370 3 3 3 0 0 1 1 0 1 0 0.35 0.00033 0.24
26 BCL2L11 BCL2-like 11 (apoptosis facilitator) 34712 2 2 1 0 0 0 0 0 2 0 1 0.00035 0.24
27 NRXN1 neurexin 1 254644 5 5 5 0 1 1 1 1 1 0 0.21 0.00037 0.25
28 EPHA5 EPH receptor A5 174300 5 4 5 0 1 2 2 0 0 0 0.25 0.00041 0.26
29 MAMLD1 mastermind-like domain containing 1 135529 4 4 3 0 0 0 1 2 1 0 0.49 0.00041 0.26
30 OR4C6 olfactory receptor, family 4, subfamily C, member 6 53124 3 3 3 0 0 1 1 0 1 0 0.46 0.00043 0.26
31 TPTE transmembrane phosphatase with tensin homology 98357 5 3 5 0 1 1 0 0 2 1 0.2 0.00045 0.26
32 EBF2 early B-cell factor 2 97845 4 4 4 0 0 1 2 0 1 0 0.29 0.00048 0.27
33 DPP10 dipeptidyl-peptidase 10 138928 5 4 5 1 0 0 2 2 1 0 0.64 0.0005 0.28
34 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 239091 5 4 5 0 2 1 1 0 1 0 0.21 0.00056 0.28
35 TMUB2 transmembrane and ubiquitin-like domain containing 2 53523 3 3 3 0 2 1 0 0 0 0 0.31 0.00058 0.28
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

FBXW7

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PPP2R1A

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PPP2R1A significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA 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.

MAGEC2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the MAGEC2 significant gene.

LYPLA2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the LYPLA2 significant gene.

PCSK5

Figure S16.  This figure depicts the distribution of mutations and mutation types across the PCSK5 significant gene.

ATP4A

Figure S17.  This figure depicts the distribution of mutations and mutation types across the ATP4A significant gene.

HCFC1R1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the HCFC1R1 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: 13. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 FBXW7 F-box and WD repeat domain containing 7 24 91 19 5187 788 0 0
2 TP53 tumor protein p53 55 356 52 20292 16225 0 0
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 7 52 7 2964 101988 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 22 220 20 12540 8438 0 0
5 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 15 767 15 43719 769 0 0
6 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 8 33 4 1881 9 2e-10 1.5e-07
7 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 5 6 2 342 2 1.2e-06 0.00074
8 RB1 retinoblastoma 1 (including osteosarcoma) 6 267 3 15219 10 0.000049 0.028
9 F13A1 coagulation factor XIII, A1 polypeptide 1 1 1 57 1 0.00025 0.088
10 FERD3L Fer3-like (Drosophila) 2 1 1 57 1 0.00025 0.088

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: 104. 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 CHEMICALPATHWAY DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 20 APAF1(2), ATM(3), BCL2L1(1), CASP7(1), EIF2S1(1), PXN(1), STAT1(1), TP53(55) 2302234 65 53 53 2 16 6 14 13 15 1 4.3e-06 <1.00e-15 <8.63e-14
2 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(6), PML(1), RB1(6), SIRT1(1), TP53(55) 1613841 69 52 57 0 18 6 12 14 17 2 5.6e-09 <1.00e-15 <8.63e-14
3 NKCELLSPATHWAY Natural killer (NK) lymphocytes are inhibited by MHC and activated by surface glycoproteins on tumor or virus-infected cells, which undergo perforin-mediated lysis. B2M, HLA-A, IL18, ITGB1, KLRC1, KLRC2, KLRC3, KLRC4, KLRD1, LAT, MAP2K1, MAPK3, PAK1, PIK3CA, PIK3R1, PTK2B, PTPN6, RAC1, SYK, VAV1 20 ITGB1(1), KLRC3(1), PIK3CA(22), PIK3R1(8), PTPN6(1), RAC1(1) 1567278 34 28 25 1 3 6 5 12 8 0 0.004 1.22e-15 8.63e-14
4 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(3), CCNA1(1), CCND1(1), CCND2(1), CCNE2(1), CDKN2A(1), CDKN2B(1), E2F1(1), MCM2(1), MCM3(1), MCM5(1), MCM6(1), MCM7(1), MNAT1(1), MYC(2), NACA(2), POLE(1), POLE2(1), RB1(6), RPA1(1), TNXB(3), TP53(55), WEE1(1) 6583713 88 54 76 6 20 6 21 21 17 3 5.8e-06 1.33e-15 8.63e-14
5 TPOPATHWAY Thrombopoietin binds to its receptor and activates cell growth through the Erk and JNK MAP kinase pathways, protein kinase C, and JAK/STAT activation. CSNK2A1, FOS, GRB2, HRAS, JAK2, JUN, MAP2K1, MAPK3, MPL, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, RAF1, RASA1, SHC1, SOS1, STAT1, STAT3, STAT5A, STAT5B, THPO 22 JAK2(2), PIK3CA(22), PIK3R1(8), RASA1(1), STAT1(1), STAT3(2) 2536692 36 27 27 2 3 7 5 12 9 0 0.011 1.44e-15 8.63e-14
6 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), CASP7(1), CASP8(2), GZMB(1), HELLS(1), IKBKB(1), IRF2(1), IRF6(1), LTA(1), MAP2K4(1), MAP3K1(1), MAPK10(1), MYC(2), TNFRSF21(1), TP53(55), TP73(1) 4903224 77 52 64 5 20 7 12 17 20 1 0.000015 1.55e-15 8.63e-14
7 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(3), ATR(3), BRCA2(5), CHEK2(2), FANCC(1), FANCD2(1), FANCE(1), FANCF(1), FANCG(1), HUS1(1), MRE11A(1), RAD9A(1), TP53(55) 3685680 76 52 64 4 16 7 18 19 15 1 6e-05 1.55e-15 8.63e-14
8 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(6), TEP1(1), TNKS(1), TP53(55) 2390234 67 53 55 2 15 6 11 17 16 2 1e-06 1.89e-15 8.63e-14
9 RASPATHWAY Ras activation stimulates many signaling cascades, including PI3K/AKT activation to inhibit apoptosis. AKT1, ARHA, BAD, BCL2L1, CASP9, CDC42, CHUK, ELK1, H2AFX, HRAS, MAP2K1, MAPK3, MLLT7, NFKB1, PIK3CA, PIK3R1, RAC1, RAF1, RALA, RALBP1, RALGDS, RELA, RHOA 21 BCL2L1(1), PIK3CA(22), PIK3R1(8), RAC1(1), RALGDS(2) 1634536 34 28 25 1 5 7 5 10 7 0 0.0017 1.89e-15 8.63e-14
10 CDC42RACPATHWAY PI3 kinase stimulates cell migration by activating cdc42, which activates ARP2/3, which in turn promotes formation of new actin fibers. ACTR2, ACTR3, ARHA, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, CDC42, PAK1, PDGFRA, PIK3CA, PIK3R1, RAC1, WASL 14 ACTR3(1), PIK3CA(22), PIK3R1(8), RAC1(1), WASL(1) 1132069 33 27 24 1 4 6 5 11 7 0 0.0047 1.89e-15 8.63e-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 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 CD28(1), CD3E(1), CD80(2), CD86(1), HLA-DRA(1), IL2(1), ITK(1), PTPN11(1) 765001 9 7 9 0 3 3 1 2 0 0 0.044 0.001 0.32
2 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 CD28(1), CD80(2), HLA-DRA(1), IL2(1) 337807 5 5 5 0 2 2 1 0 0 0 0.13 0.001 0.32
3 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(3), NTRK1(2), PSMA7(1), RAC1(1), WASF1(1), WASF3(1), WASL(1) 1290167 14 9 14 1 5 1 4 1 3 0 0.074 0.0021 0.42
4 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(2), HLA-DRA(1), IL1B(2), IL5RA(1) 453522 6 5 6 0 2 1 3 0 0 0 0.14 0.0042 0.55
5 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 CD28(1), CD3E(1), IL2(1), IL2RA(1), TGFB1(1), TGFBR3(1), TOB2(1) 897887 7 7 7 0 2 3 0 1 1 0 0.071 0.0045 0.55
6 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(3), SNCAIP(2), UBE2G1(2) 546771 7 5 7 1 2 2 1 1 1 0 0.28 0.016 1
7 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), BCL10(1), BCL2L1(1), BCL2L11(2) 919398 6 6 5 1 2 1 0 0 3 0 0.49 0.018 1
8 BBCELLPATHWAY Fas ligand expression by T cells induces apoptosis in Fas-expressing, inactive B cells. CD28, CD4, HLA-DRA, HLA-DRB1, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 4 CD28(1), HLA-DRA(1) 203680 2 2 2 0 0 2 0 0 0 0 0.33 0.029 1
9 EOSINOPHILSPATHWAY Recruitment of eosinophils in the inflammatory response observed in asthma occurs via the chemoattractant eotaxin binding to the CCR3 receptor. CCL11, CCL5, CCR3, CSF2, HLA-DRA, HLA-DRB1, IL3, IL5 8 CCR3(2), HLA-DRA(1) 259845 3 3 3 0 1 1 1 0 0 0 0.32 0.03 1
10 HSA00232_CAFFEINE_METABOLISM Genes involved in caffeine metabolism CYP1A2, CYP2A13, CYP2A6, CYP2A7, NAT1, NAT2, XDH 7 CYP1A2(2), CYP2A7(2), XDH(1) 677093 5 5 5 1 1 1 2 1 0 0 0.54 0.044 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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