Mutation Analysis (MutSig v1.5)
Prostate Adenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1959FXG
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1959FXG
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: PRAD-TP

  • Number of patients in set: 83

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

  • Significantly mutated genes (q ≤ 0.1): 34

  • Mutations seen in COSMIC: 28

  • Significantly mutated genes in COSMIC territory: 7

  • Genes with clustered mutations (≤ 3 aa apart): 24

  • Significantly mutated genesets: 1

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

Mutation Preprocessing

  • Read 83 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 5917

  • After removing 18 mutations outside chr1-24: 5899

  • After removing 304 noncoding mutations: 5595

Mutation Filtering

  • Number of mutations before filtering: 5595

  • After removing 207 mutations outside gene set: 5388

  • After removing 4 mutations outside category set: 5384

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 150
Frame_Shift_Ins 77
In_Frame_Del 51
In_Frame_Ins 13
Missense_Mutation 3294
Nonsense_Mutation 185
Nonstop_Mutation 2
Silent 1497
Splice_Site 102
Translation_Start_Site 13
Total 5384
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 840 138713067 6.1e-06 6.1 3.9 2.1
*Np(A/C/T)->transit 901 1965699488 4.6e-07 0.46 0.29 2
*ApG->G 107 381313535 2.8e-07 0.28 0.18 2.1
transver 1456 2485726090 5.9e-07 0.59 0.37 5
indel+null 580 2485726090 2.3e-07 0.23 0.15 NaN
double_null 3 2485726090 1.2e-09 0.0012 0.00077 NaN
Total 3887 2485726090 1.6e-06 1.6 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: 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.

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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->G

  • n4 = number of nonsilent mutations of type: transver

  • n5 = number of nonsilent mutations of type: indel+null

  • n6 = number of nonsilent mutations of type: double_null

  • p_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: 34. 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 MUC4 mucin 4, cell surface associated 272535 15 13 9 2 3 4 0 8 0 0 0.13 8.9e-13 1.6e-08
2 NKX3-1 NK3 homeobox 1 43527 5 5 5 0 0 2 0 2 1 0 0.26 3.3e-09 3e-05
3 TPTE2 transmembrane phosphoinositide 3-phosphatase and tensin homolog 2 136261 6 6 6 1 1 2 0 2 1 0 0.48 6.1e-09 0.000037
4 FRG1 FSHD region gene 1 67208 6 5 4 0 0 2 0 3 1 0 0.32 1.2e-08 0.000052
5 TP53 tumor protein p53 105521 5 5 5 0 3 0 0 1 1 0 0.34 8.3e-07 0.003
6 ARHGAP11B Rho GTPase activating protein 11B 68637 4 4 2 0 0 0 0 1 3 0 0.25 1.2e-06 0.0035
7 LILRB3 leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 3 120480 4 4 2 1 0 0 3 1 0 0 0.6 1.4e-06 0.0036
8 C9orf150 chromosome 9 open reading frame 150 47265 3 3 1 0 0 0 0 0 3 0 1 2e-06 0.0044
9 SCAI suppressor of cancer cell invasion 157950 5 5 2 0 0 0 0 5 0 0 0.45 3.2e-06 0.0058
10 PRR21 proline rich 21 58941 4 4 4 0 1 1 0 2 0 0 0.26 3.2e-06 0.0058
11 SPOP speckle-type POZ protein 96345 4 4 3 0 0 0 1 3 0 0 0.39 4.8e-06 0.0079
12 ZNF98 zinc finger protein 98 (F7175) 122162 4 4 4 0 0 1 0 2 1 0 0.45 0.000011 0.017
13 OR6N1 olfactory receptor, family 6, subfamily N, member 1 78146 3 3 2 0 0 0 2 1 0 0 0.46 0.000013 0.018
14 LRIT2 leucine-rich repeat, immunoglobulin-like and transmembrane domains 2 138107 4 4 3 0 1 2 0 1 0 0 0.25 0.000014 0.018
15 OR4D5 olfactory receptor, family 4, subfamily D, member 5 79763 3 3 3 0 2 0 0 1 0 0 0.46 0.000017 0.02
16 ZNF492 zinc finger protein 492 123622 4 4 3 0 0 3 0 1 0 0 0.28 2e-05 0.023
17 C17orf63 chromosome 17 open reading frame 63 5972 2 2 1 0 0 0 0 2 0 0 0.65 0.000027 0.028
18 NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4, 18kDa (NADH-coenzyme Q reductase) 45401 3 3 1 0 0 0 0 3 0 0 0.58 0.000043 0.043
19 ZNF285 zinc finger protein 285 148155 4 3 2 1 0 0 2 2 0 0 0.74 0.000059 0.053
20 NOTCH2NL Notch homolog 2 (Drosophila) N-terminal like 60118 3 3 2 0 0 3 0 0 0 0 0.3 0.000059 0.053
21 ZNF814 zinc finger protein 814 168858 4 4 2 0 0 2 0 2 0 0 0.34 0.000061 0.053
22 PRB1 proline-rich protein BstNI subfamily 1 82441 3 3 3 0 0 1 0 2 0 0 0.44 0.000068 0.053
23 CNTNAP5 contactin associated protein-like 5 309961 5 5 5 0 2 0 0 2 1 0 0.2 0.000071 0.053
24 PRIM2 primase, DNA, polypeptide 2 (58kDa) 120943 4 4 2 4 0 0 0 1 3 0 1 0.000073 0.053
25 CROCC ciliary rootlet coiled-coil, rootletin 295882 5 5 3 1 3 1 0 1 0 0 0.42 0.000074 0.053
26 TTLL11 tubulin tyrosine ligase-like family, member 11 83913 3 3 3 0 0 0 0 2 1 0 0.68 0.0001 0.07
27 PDE4DIP phosphodiesterase 4D interacting protein (myomegalin) 720610 6 6 5 1 0 2 3 0 1 0 0.4 0.0001 0.071
28 POTEC POTE ankyrin domain family, member C 130537 3 3 2 0 2 1 0 0 0 0 0.24 0.00011 0.072
29 OR5L2 olfactory receptor, family 5, subfamily L, member 2 78017 3 3 3 0 0 0 0 3 0 0 0.55 0.00013 0.082
30 YBX1 Y box binding protein 1 68945 4 3 2 0 0 2 0 2 0 0 0.32 0.00014 0.087
31 AIM2 absent in melanoma 2 87306 3 3 3 0 0 1 0 1 1 0 0.57 0.00015 0.087
32 FIP1L1 FIP1 like 1 (S. cerevisiae) 152119 3 3 1 0 0 0 0 0 3 0 1 0.00015 0.087
33 GGTLC2 gamma-glutamyltransferase light chain 2 47824 3 2 3 1 0 0 1 2 0 0 0.73 0.00016 0.089
34 ANKRD36 ankyrin repeat domain 36 204931 4 4 2 1 0 0 0 4 0 0 0.71 0.00018 0.096
35 OR52A1 olfactory receptor, family 52, subfamily A, member 1 78103 2 2 2 0 2 0 0 0 0 0 0.84 0.0002 0.1
MUC4

Figure S1.  This figure depicts the distribution of mutations and mutation types across the MUC4 significant gene.

NKX3-1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NKX3-1 significant gene.

TPTE2

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TPTE2 significant gene.

FRG1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the FRG1 significant gene.

TP53

Figure S5.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

ARHGAP11B

Figure S6.  This figure depicts the distribution of mutations and mutation types across the ARHGAP11B significant gene.

LILRB3

Figure S7.  This figure depicts the distribution of mutations and mutation types across the LILRB3 significant gene.

C9orf150

Figure S8.  This figure depicts the distribution of mutations and mutation types across the C9orf150 significant gene.

SCAI

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

PRR21

Figure S10.  This figure depicts the distribution of mutations and mutation types across the PRR21 significant gene.

SPOP

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

ZNF98

Figure S12.  This figure depicts the distribution of mutations and mutation types across the ZNF98 significant gene.

OR6N1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the OR6N1 significant gene.

LRIT2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the LRIT2 significant gene.

OR4D5

Figure S15.  This figure depicts the distribution of mutations and mutation types across the OR4D5 significant gene.

ZNF492

Figure S16.  This figure depicts the distribution of mutations and mutation types across the ZNF492 significant gene.

C17orf63

Figure S17.  This figure depicts the distribution of mutations and mutation types across the C17orf63 significant gene.

NDUFS4

Figure S18.  This figure depicts the distribution of mutations and mutation types across the NDUFS4 significant gene.

ZNF285

Figure S19.  This figure depicts the distribution of mutations and mutation types across the ZNF285 significant gene.

NOTCH2NL

Figure S20.  This figure depicts the distribution of mutations and mutation types across the NOTCH2NL significant gene.

ZNF814

Figure S21.  This figure depicts the distribution of mutations and mutation types across the ZNF814 significant gene.

PRB1

Figure S22.  This figure depicts the distribution of mutations and mutation types across the PRB1 significant gene.

CNTNAP5

Figure S23.  This figure depicts the distribution of mutations and mutation types across the CNTNAP5 significant gene.

PRIM2

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PRIM2 significant gene.

CROCC

Figure S25.  This figure depicts the distribution of mutations and mutation types across the CROCC significant gene.

TTLL11

Figure S26.  This figure depicts the distribution of mutations and mutation types across the TTLL11 significant gene.

PDE4DIP

Figure S27.  This figure depicts the distribution of mutations and mutation types across the PDE4DIP significant gene.

POTEC

Figure S28.  This figure depicts the distribution of mutations and mutation types across the POTEC significant gene.

OR5L2

Figure S29.  This figure depicts the distribution of mutations and mutation types across the OR5L2 significant gene.

YBX1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the YBX1 significant gene.

AIM2

Figure S31.  This figure depicts the distribution of mutations and mutation types across the AIM2 significant gene.

FIP1L1

Figure S32.  This figure depicts the distribution of mutations and mutation types across the FIP1L1 significant gene.

GGTLC2

Figure S33.  This figure depicts the distribution of mutations and mutation types across the GGTLC2 significant gene.

ANKRD36

Figure S34.  This figure depicts the distribution of mutations and mutation types across the ANKRD36 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: 7. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 5 356 5 29548 1608 1.7e-09 7.6e-06
2 CHEK2 CHK2 checkpoint homolog (S. pombe) 2 2 2 166 2 3.3e-08 0.000076
3 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 3 138 3 11454 1229 9.4e-07 0.0014
4 ACSM2B acyl-CoA synthetase medium-chain family member 2B 1 1 1 83 1 0.00013 0.098
5 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 1 1 1 83 1 0.00013 0.098
6 KCNH1 potassium voltage-gated channel, subfamily H (eag-related), member 1 1 1 1 83 1 0.00013 0.098
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 3 767 3 63661 15 0.00015 0.099
8 CHAT choline acetyltransferase 2 2 1 166 1 0.00026 0.13
9 CYP4F2 cytochrome P450, family 4, subfamily F, polypeptide 2 1 2 1 166 2 0.00026 0.13
10 ACVR2A activin A receptor, type IIA 1 3 1 249 1 0.00039 0.16

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)

Clustered Mutations

Table 5.  Get Full Table Genes with Clustered Mutations

num gene desc n mindist nmuts0 nmuts3 nmuts12 npairs0 npairs3 npairs12
1657 MUC4 mucin 4, cell surface associated 15 0 13 23 23 13 23 23
480 CDC27 cell division cycle 27 homolog (S. cerevisiae) 10 0 6 8 9 6 8 9
2274 SCAI suppressor of cancer cell invasion 5 0 6 6 6 6 6 6
92 AGT angiotensinogen (serpin peptidase inhibitor, clade A, member 8) 3 0 3 3 3 3 3 3
144 ANKRD36 ankyrin repeat domain 36 4 0 3 3 3 3 3 3
464 CCNF cyclin F 3 0 3 3 3 3 3 3
563 CLSTN1 calsyntenin 1 3 0 3 3 3 3 3 3
624 CROCC ciliary rootlet coiled-coil, rootletin 5 0 3 3 3 3 3 3
665 CYP2D6 cytochrome P450, family 2, subfamily D, polypeptide 6 4 0 3 3 3 3 3 3
779 DUSP27 dual specificity phosphatase 27 (putative) 3 0 3 3 3 3 3 3

Note:

n - number of mutations in this gene in the individual set.

mindist - distance (in aa) between closest pair of mutations in this gene

npairs3 - how many pairs of mutations are within 3 aa of each other.

npairs12 - how many pairs of mutations are within 12 aa of each other.

Geneset Analyses

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 1. 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 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(2), PRB1(3), TP53(5) 1062488 10 10 10 0 3 1 0 3 3 0 0.12 6.4e-06 0.0039
2 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 ABCB1(2), AKT1(1), ATM(5), TP53(5) 2602579 13 12 13 0 4 6 0 2 1 0 0.015 0.00034 0.1
3 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(1), CCNE2(1), CDKN1B(2), PRB1(3) 1130432 7 7 7 0 0 2 0 3 2 0 0.25 0.00099 0.2
4 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(5), TP53(5) 2266716 11 10 11 0 3 5 0 2 1 0 0.034 0.0014 0.22
5 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(1), TP53(5) 879118 6 6 6 0 3 1 0 1 1 0 0.16 0.0022 0.23
6 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(5), CHEK2(2), TP53(5) 1994178 12 11 11 2 3 6 0 2 1 0 0.26 0.0022 0.23
7 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(5), TP53(5) 2195302 10 9 10 1 3 4 0 2 1 0 0.18 0.0032 0.28
8 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ATM(5), CCNA1(1), CDKN1B(2), DHFR(1), TP53(5) 3787641 14 12 14 0 3 5 0 2 4 0 0.032 0.0056 0.4
9 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(1), APAF1(1), ATM(5), TLN1(1), TP53(5) 3433242 13 12 13 0 3 6 0 3 1 0 0.019 0.0058 0.4
10 SMALL_LIGAND_GPCRS C9orf47, CNR1, CNR2, DNMT1, EDG1, EDG2, EDG5, EDG6, MTNR1A, MTNR1B, PTAFR, PTGDR, PTGER1, PTGER2, PTGER4, PTGFR, PTGIR, TBXA2R 13 DNMT1(3), MTNR1A(1), PTGER2(1), TBXA2R(2) 1410721 7 7 7 1 3 2 0 1 1 0 0.19 0.011 0.65

Table 7.  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 SMALL_LIGAND_GPCRS C9orf47, CNR1, CNR2, DNMT1, EDG1, EDG2, EDG5, EDG6, MTNR1A, MTNR1B, PTAFR, PTGDR, PTGER1, PTGER2, PTGER4, PTGFR, PTGIR, TBXA2R 13 DNMT1(3), MTNR1A(1), PTGER2(1), TBXA2R(2) 1410721 7 7 7 1 3 2 0 1 1 0 0.19 0.011 1
2 HSA00830_RETINOL_METABOLISM Genes involved in retinol metabolism ALDH1A1, ALDH1A2, BCMO1, RDH5 4 ALDH1A2(1), BCMO1(2) 483292 3 3 2 0 0 2 0 1 0 0 0.37 0.012 1
3 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 AKT1(1), CDKN1B(2), PIK3CA(2), PTEN(3) 2419782 8 8 8 1 0 3 1 1 3 0 0.36 0.013 1
4 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 18 ABCB1(2), AKT1(1), ATM(5) 2497058 8 8 8 0 1 6 0 1 0 0 0.053 0.02 1
5 HSA00670_ONE_CARBON_POOL_BY_FOLATE Genes involved in one carbon pool by folate ALDH1L1, AMT, ATIC, DHFR, FTCD, GART, MTFMT, MTHFD1, MTHFD1L, MTHFD2, MTHFR, MTHFS, MTR, SHMT1, SHMT2, TYMS 16 DHFR(1), FTCD(2), GART(1), MTHFD1(1), MTHFD1L(1), MTHFR(1) 2365631 7 7 7 0 0 2 0 2 3 0 0.21 0.022 1
6 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 13 AKT1(1), GHR(1), IGF1R(1), PIK3CA(2), SOD3(1) 1657357 6 6 6 0 0 4 1 1 0 0 0.12 0.023 1
7 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 12 AKT1(1), KLK2(1), NTRK1(2), PIK3CA(2) 1940556 6 6 6 0 0 4 1 0 1 0 0.13 0.031 1
8 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM Genes involved in glycerophospholipid metabolism ACHE, AGPAT1, AGPAT2, AGPAT3, AGPAT4, AGPAT6, ARD1A, CDIPT, CDS1, CDS2, CHAT, CHKA, CHKB, CHPT1, CRLS1, DGKA, DGKB, DGKD, DGKE, DGKG, DGKH, DGKI, DGKQ, DGKZ, ESCO1, ESCO2, ETNK1, ETNK2, GNPAT, GPAM, GPD1, GPD1L, GPD2, LCAT, LYCAT, LYPLA1, LYPLA2, LYPLA3, MYST3, MYST4, NAT5, NAT6, PCYT1A, PCYT1B, PEMT, PHOSPHO1, PISD, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLD1, PLD2, PNPLA3, PPAP2A, PPAP2B, PPAP2C, PTDSS1, PTDSS2, SH3GLB1 64 AGPAT2(1), AGPAT3(1), CHAT(2), DGKD(1), DGKH(1), DGKI(1), DGKQ(2), ESCO1(3), GNPAT(1), MYST3(1), PEMT(1), PLA2G2A(1), PLA2G4A(1), PLA2G5(1), PLD1(1), PTDSS1(1) 8241571 20 19 20 2 2 4 1 9 4 0 0.11 0.032 1
9 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY The phosphoinositide-3 kinase pathway produces the lipid second messenger PIP3 and regulates cell growth, survival, and movement. A1BG, AKT1, AKT2, AKT3, BAD, BTK, CDKN2A, CSL4, DAF, DAPP1, FOXO1A, GRB2, GSK3A, GSK3B, IARS, IGFBP1, INPP5D, P14, PDK1, PIK3CA, PPP1R13B, PSCD3, PTEN, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KB1, SFN, SHC1, SOS1, SOS2, TEC, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 33 A1BG(1), AKT1(1), BTK(1), GSK3A(1), PDK1(1), PIK3CA(2), PPP1R13B(1), PTEN(3) 4518736 11 11 11 1 1 3 1 4 2 0 0.16 0.04 1
10 HSA00592_ALPHA_LINOLENIC_ACID_METABOLISM Genes involved in alpha-Linolenic acid metabolism ACOX1, ACOX3, FADS2, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6 15 ACOX3(1), FADS2(1), PLA2G2A(1), PLA2G4A(1), PLA2G5(1) 1273374 5 5 5 1 2 1 0 2 0 0 0.46 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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