Mutation Analysis (MutSig v2.0)
Prostate Adenocarcinoma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C12N51K5
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C12N51K5
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: PRAD-TP

  • Number of patients in set: 332

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:PRAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 22

  • Mutations seen in COSMIC: 78

  • Significantly mutated genes in COSMIC territory: 8

  • Significantly mutated genesets: 29

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

Mutation Preprocessing

  • Read 332 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 12302

  • After removing 26 mutations outside chr1-24: 12276

  • After removing 14 blacklisted mutations: 12262

  • After removing 427 noncoding mutations: 11835

Mutation Filtering

  • Number of mutations before filtering: 11835

  • After removing 608 mutations outside gene set: 11227

  • After removing 4 mutations outside category set: 11223

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 9
De_novo_Start_OutOfFrame 11
Frame_Shift_Del 297
Frame_Shift_Ins 96
In_Frame_Del 57
In_Frame_Ins 5
Missense_Mutation 7287
Nonsense_Mutation 391
Nonstop_Mutation 7
Silent 2580
Splice_Site 466
Start_Codon_SNP 17
Total 11223
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
Cp*C->A 1900 1395886984 1.4e-06 1.4 1.5 2.4
C->(T/G) 2404 4934634181 4.9e-07 0.49 0.55 2.8
(A/G/T)p*C->A 875 3538747197 2.5e-07 0.25 0.28 6
A->mut 2125 4759038903 4.5e-07 0.45 0.5 3.9
indel+null 1335 9693673084 1.4e-07 0.14 0.15 NaN
double_null 4 9693673084 4.1e-10 0.00041 0.00046 NaN
Total 8643 9693673084 8.9e-07 0.89 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: PRAD-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.

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: Cp*C->A

  • n2 = number of nonsilent mutations of type: C->(T/G)

  • n3 = number of nonsilent mutations of type: (A/G/T)p*C->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_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: 22. 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 TP53 tumor protein p53 400419 23 23 21 0 0 5 1 7 10 0 4.9e-15 0.017 0.0004 0.0019 0.00019 0.000 0.000
2 SPOP speckle-type POZ protein 385366 38 37 14 0 1 4 3 28 2 0 1.9e-15 0.00034 0 0.16 0 <1.00e-15 <6.03e-12
3 FOXA1 forkhead box A1 350244 13 13 10 0 0 2 0 5 5 1 8.9e-15 0.27 2e-07 0.006 0 <1.00e-15 <6.03e-12
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 388867 9 9 9 0 0 0 2 1 6 0 2.8e-12 0.45 0.34 0.8 0.43 3.46e-11 1.56e-07
5 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 796491 8 8 7 0 1 2 2 3 0 0 2.5e-07 0.15 0.0018 0.083 0.0014 7.79e-09 2.82e-05
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 740084 8 8 8 0 1 1 1 3 2 0 1.6e-07 0.17 0.52 0.034 0.16 4.60e-07 0.00139
7 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1087905 7 6 7 1 0 1 1 5 0 0 0.0001 0.5 0.00035 0.15 0.0003 5.68e-07 0.00147
8 MED12 mediator complex subunit 12 1765332 6 6 3 0 0 5 1 0 0 0 0.0011 0.18 4.4e-06 0.15 0.000038 7.73e-07 0.00175
9 NKX3-1 NK3 homeobox 1 169068 4 4 4 0 0 1 0 3 0 0 5.7e-06 0.4 0.06 0.0024 0.036 3.36e-06 0.00675
10 IRF4 interferon regulatory factor 4 401399 4 4 4 1 2 0 0 0 2 0 0.00071 0.83 0.00013 0.49 0.00053 5.96e-06 0.0108
11 PCDH18 protocadherin 18 1134275 8 8 8 1 1 3 0 3 1 0 8.6e-06 0.36 0.73 0.0091 0.064 8.48e-06 0.0133
12 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 420799 3 3 2 0 0 3 0 0 0 0 0.0019 0.46 0.00015 0.65 0.00031 8.85e-06 0.0133
13 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 214214 4 4 2 0 0 1 0 3 0 0 6e-06 0.49 0.082 0.21 0.12 1.06e-05 0.0143
14 OR5L2 olfactory receptor, family 5, subfamily L, member 2 311639 5 5 5 0 1 1 2 1 0 0 1.1e-06 0.21 0.65 0.45 0.68 1.10e-05 0.0143
15 PLCB4 phospholipase C, beta 4 1226699 7 7 7 0 0 3 2 1 1 0 0.000014 0.25 0.093 0.17 0.09 1.88e-05 0.0227
16 CDKN1B cyclin-dependent kinase inhibitor 1B (p27, Kip1) 200216 4 4 4 0 0 0 0 0 4 0 2e-06 0.82 0.7 0.74 0.88 2.58e-05 0.0291
17 CSMD3 CUB and Sushi multiple domains 3 3796342 12 12 12 1 2 1 3 2 4 0 0.000013 0.29 0.15 0.24 0.16 2.78e-05 0.0295
18 FAM83B family with sequence similarity 83, member B 1009206 6 6 6 1 1 1 1 3 0 0 0.000061 0.54 0.74 0.012 0.056 4.60e-05 0.0462
19 ATM ataxia telangiectasia mutated 3104760 13 13 13 2 0 5 0 6 2 0 0.00031 0.46 0.066 0.018 0.012 5.14e-05 0.0489
20 ZNF514 zinc finger protein 514 403380 2 2 1 0 2 0 0 0 0 0 0.044 0.54 0.022 0.00013 0.00013 7.37e-05 0.0635
21 LRP1B low density lipoprotein-related protein 1B (deleted in tumors) 4653773 12 12 12 1 0 2 6 2 2 0 0.000012 0.38 0.53 0.23 0.48 7.37e-05 0.0635
22 ETV3 ets variant gene 3 146892 3 3 3 0 0 0 0 1 2 0 0.00011 0.74 0.019 0.44 0.062 8.60e-05 0.0707
23 HIST1H2BG histone cluster 1, H2bg 127820 3 3 3 0 0 0 0 1 2 0 0.000012 0.82 0.51 0.9 1 0.000144 0.114
24 CD48 CD48 molecule 248002 4 4 4 0 1 2 1 0 0 0 0.000042 0.27 0.29 0.71 0.44 0.000219 0.165
25 OR5D18 olfactory receptor, family 5, subfamily D, member 18 313673 4 4 4 0 0 2 1 1 0 0 0.000068 0.28 0.13 0.85 0.28 0.000228 0.165
26 KDM6A lysine (K)-specific demethylase 6A 1243236 6 6 6 1 0 0 0 1 5 0 0.00011 0.83 0.3 0.096 0.22 0.000285 0.198
27 CD5L CD5 molecule-like 352619 4 4 4 0 0 0 1 2 1 0 0.0001 0.41 0.15 0.76 0.27 0.000306 0.198
28 FILIP1 filamin A interacting protein 1 1212371 7 7 7 0 1 3 1 2 0 0 0.000056 0.17 0.38 0.52 0.47 0.000307 0.198
29 FLG2 filaggrin family member 2 2383495 10 9 10 0 1 3 2 3 1 0 0.000043 0.13 0.74 0.41 0.8 0.000387 0.239
30 PCDHA12 protocadherin alpha 12 944112 6 6 6 1 0 5 1 0 0 0 0.000071 0.33 0.33 0.41 0.51 0.000404 0.239
31 LRRIQ3 leucine-rich repeats and IQ motif containing 3 611581 5 5 5 0 1 0 1 2 1 0 0.000046 0.42 0.59 0.74 0.78 0.000409 0.239
32 DCHS2 dachsous 2 (Drosophila) 2852107 9 9 9 1 0 3 3 3 0 0 9e-05 0.37 0.33 0.32 0.44 0.000440 0.243
33 ZMYM3 zinc finger, MYM-type 3 927569 6 6 6 0 0 1 0 1 4 0 0.000058 0.43 0.49 0.83 0.69 0.000445 0.243
34 HSPA8 heat shock 70kDa protein 8 653704 5 5 5 0 1 0 1 3 0 0 0.000061 0.28 0.57 0.85 0.67 0.000457 0.243
35 TLK1 tousled-like kinase 1 770797 4 4 4 1 0 1 2 0 1 0 0.00054 0.82 0.07 0.62 0.084 0.000495 0.256
TP53

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

SPOP

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

FOXA1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

PTEN

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

CTNNB1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

BRAF

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

PIK3CA

Figure S7.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

MED12

Figure S8.  This figure depicts the distribution of mutations and mutation types across the MED12 significant gene.

NKX3-1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NKX3-1 significant gene.

IRF4

Figure S10.  This figure depicts the distribution of mutations and mutation types across the IRF4 significant gene.

PCDH18

Figure S11.  This figure depicts the distribution of mutations and mutation types across the PCDH18 significant gene.

IDH1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

HRAS

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

OR5L2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the OR5L2 significant gene.

PLCB4

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PLCB4 significant gene.

CDKN1B

Figure S16.  This figure depicts the distribution of mutations and mutation types across the CDKN1B significant gene.

CSMD3

Figure S17.  This figure depicts the distribution of mutations and mutation types across the CSMD3 significant gene.

FAM83B

Figure S18.  This figure depicts the distribution of mutations and mutation types across the FAM83B significant gene.

ATM

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

ZNF514

Figure S20.  This figure depicts the distribution of mutations and mutation types across the ZNF514 significant gene.

LRP1B

Figure S21.  This figure depicts the distribution of mutations and mutation types across the LRP1B significant gene.

ETV3

Figure S22.  This figure depicts the distribution of mutations and mutation types across the ETV3 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: 8. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 23 356 21 118192 1670 0 0
2 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 9 767 9 254644 96 0 0
3 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 8 138 6 45816 2207 3.9e-12 5.9e-09
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 7 220 6 73040 1262 9.7e-11 9.2e-08
5 BRAF v-raf murine sarcoma viral oncogene homolog B1 8 89 5 29548 14375 1e-10 9.2e-08
6 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 3 5 3 1660 4476 5.4e-10 4.1e-07
7 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 4 19 3 6308 624 3e-08 0.000019
8 SMAD4 SMAD family member 4 4 159 4 52788 19 2e-07 0.00011
9 ACSM2B acyl-CoA synthetase medium-chain family member 2B 2 1 1 332 1 0.0003 0.12
10 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 2 1 1 332 1 0.0003 0.12

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: 29. 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 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 AKT1(3), ATM(13), HSPA1A(1), NFKBIB(1), TP53(23) 10237566 41 39 38 2 1 13 2 13 12 0 0.012 2.8e-15 9.4e-13
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(1), ATM(13), RB1(2), TP53(23) 8943084 39 37 37 2 1 11 1 14 12 0 0.016 5.9e-15 9.4e-13
3 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(1), PIK3CA(7), POLR1A(2), POLR1B(1), POLR1C(1), RAC1(1), RB1(2), TP53(23) 10023689 38 37 36 1 3 6 3 16 10 0 0.0035 8.2e-15 9.4e-13
4 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(2), DAXX(1), HRAS(4), PAX3(1), RB1(2), SIRT1(1), SP100(1), TP53(23) 9353517 35 35 31 1 2 6 2 15 10 0 0.0068 8.9e-15 9.4e-13
5 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 CDKN1B(4), CFL1(1), TP53(23) 4146431 28 28 26 1 0 5 1 7 15 0 0.06 9e-15 9.4e-13
6 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 SP1(2), SP3(3), TP53(23) 3469530 28 28 26 0 0 7 2 7 12 0 0.0053 9.1e-15 9.4e-13
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 NFKB1(2), RELA(2), TP53(23) 4782176 27 27 25 1 2 6 1 8 10 0 0.031 1.1e-14 9.6e-13
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 AKT1(3), EGFR(4), IGF1R(2), PRKCA(1), RB1(2), TEP1(4), TNKS(2), TP53(23), XRCC5(1) 13842900 42 41 39 1 6 9 4 13 10 0 0.00076 6.8e-14 5.3e-12
9 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(13), MYT1(1), RB1(2), TP53(23) 8673699 39 37 37 3 2 10 1 14 12 0 0.044 4e-13 2.7e-11
10 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 AKT1(3), APAF1(1), ATM(13), BAD(1), PRKCA(1), STAT1(1), TLN1(2), TP53(23) 13528093 45 43 42 3 1 13 3 15 13 0 0.017 7.2e-13 4.4e-11

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 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(1), PGLYRP2(3) 890560 4 4 4 0 1 1 1 0 1 0 0.33 0.0022 0.82
2 TERCPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. NFYA, NFYB, NFYC, RB1, SP1, SP3 6 NFYC(1), RB1(2), SP1(2), SP3(3) 3297294 8 8 8 0 1 3 1 1 2 0 0.17 0.0027 0.82
3 HSA00130_UBIQUINONE_BIOSYNTHESIS Genes involved in ubiquinone biosynthesis COQ2, COQ3, COQ5, COQ6, COQ7, ND1, ND2, ND3, ND4, ND4L, ND5, ND6, NDUFA12, NDUFA13, NDUFB11 8 COQ3(2), COQ5(1), COQ7(1), NDUFA13(1) 1961734 5 5 5 0 0 2 0 2 1 0 0.27 0.008 1
4 LONGEVITYPATHWAY Caloric restriction in animals often increases lifespan, which may occur via decreased IGF receptor expression and consequent expression of stress-resistance proteins. AKT1, CAT, FOXO3A, GH1, GHR, HRAS, IGF1, IGF1R, PIK3CA, PIK3R1, SHC1, SOD1, SOD2, SOD3 11 AKT1(3), GH1(1), GHR(2), IGF1R(2), SHC1(1), SOD3(1) 5269377 10 10 9 0 2 4 2 2 0 0 0.07 0.0083 1
5 ETCPATHWAY Energy is extracted from carbohydrates via oxidation and transferred to the mitochondrial electron transport chain, which couples ATP synthesis to the reduction of oxygen to water. ATP5A1, CYCS, GPD2, MTCO1, NDUFA1, SDHA, SDHB, SDHC, SDHD, UQCRC1 9 ATP5A1(2), SDHA(1), SDHB(1), SDHC(2), UQCRC1(1) 3258606 7 7 7 0 1 2 0 1 3 0 0.19 0.016 1
6 EEA1PATHWAY The FYVE-finger proteins EEA1 and HRS are localized to endosome membranes and regulate sorting and ubiquitination in the vesicle transport system. EEA1, EGF, EGFR, HGS, RAB5A, TF, TFRC 7 EEA1(2), EGF(2), EGFR(4), TF(2) 6338332 10 10 10 1 4 2 1 3 0 0 0.27 0.016 1
7 ERBB3PATHWAY Neuregulins bind to the receptor tyrosine kinases ErbB3 and ErbB4, surface-localized receptors whose overexpression induces tumor formation. EGF, EGFR, ERBB3, NRG1, UBE2D1 5 EGF(2), EGFR(4), ERBB3(2), UBE2D1(1) 5068951 9 9 9 1 3 0 1 4 1 0 0.3 0.017 1
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 14 AKT1(3), EGFR(4), IGF1R(2), PRKCA(1), RB1(2), TEP1(4), TNKS(2), XRCC5(1) 13442481 19 19 18 1 6 4 3 6 0 0 0.027 0.019 1
9 FATTY_ACID_BIOSYNTHESIS_PATH_2 ACAA1, ACAA2, ACAT1, ACAT2, ECHS1, EHHADH, HADHA, HADHB, SDS 9 ACAA1(3), ACAA2(1), ACAT1(1), EHHADH(5) 4121609 10 8 10 1 3 1 1 2 3 0 0.27 0.02 1
10 HSA00534_HEPARAN_SULFATE_BIOSYNTHESIS Genes involved in heparan sulfate biosynthesis EXT1, EXT2, EXTL1, EXTL2, EXTL3, GLCE, HS2ST1, HS3ST1, HS3ST2, HS3ST3A1, HS3ST3B1, HS3ST5, HS6ST1, HS6ST2, HS6ST3, LOC728969, NDST1, NDST2, NDST3, NDST4 19 EXT1(1), EXT2(4), EXTL1(1), EXTL3(1), HS6ST1(1), HS6ST2(1), NDST2(2), NDST4(4) 10133977 15 15 15 1 1 7 0 5 2 0 0.083 0.022 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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