Mutation Analysis (MutSig v2.0)
Kidney Chromophobe (Primary solid tumor)
Due to issues with GAF 3.0, we strongly advise caution in the use of these results.
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1CN727N
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1CN727N
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: KICH-TP

  • Number of patients in set: 66

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:KICH-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 7

  • Mutations seen in COSMIC: 43

  • Significantly mutated genes in COSMIC territory: 2

  • Genes with clustered mutations (≤ 3 aa apart): 13

  • Significantly mutated genesets: 38

  • Significantly mutated genesets: (excluding sig. mutated genes):1

Mutation Preprocessing

  • Read 66 MAFs of type "Broad"

  • Read 65 MAFs of type "Baylor-Illumina"

  • Total number of mutations in input MAFs: 5623

  • After removing 59 mutations outside chr1-24: 5564

  • After removing 79 noncoding mutations: 5485

  • After collapsing adjacent/redundant mutations: 4230

Mutation Filtering

  • Number of mutations before filtering: 4230

  • After removing 176 mutations outside gene set: 4054

  • After removing 17 mutations outside category set: 4037

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 3843

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 207
Frame_Shift_Ins 233
In_Frame_Del 55
In_Frame_Ins 22
Missense_Mutation 2283
Nonsense_Mutation 130
Nonstop_Mutation 3
Silent 958
Splice_Site 146
Total 4037
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 893 114088540 7.8e-06 7.8 5.3 2.1
*ApG->G 165 320373592 5.2e-07 0.52 0.35 2.2
*Np(A/C/T)->transit 630 1646939625 3.8e-07 0.38 0.26 2
transver 595 2081401757 2.9e-07 0.29 0.19 5
indel+null 781 2081401757 3.8e-07 0.38 0.25 NaN
double_null 14 2081401757 6.7e-09 0.0067 0.0045 NaN
Total 3078 2081401757 1.5e-06 1.5 1 3.5
Target Coverage for Each Individual

The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom).

Figure 1. 

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

Figure 2.  Patients counts and rates file used to generate this plot: KICH-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: *ApG->G

  • n3 = number of nonsilent mutations of type: *Np(A/C/T)->transit

  • 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_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: 7. 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 85638 27 22 25 1 3 0 7 7 9 1 5.9e-15 0.0028 4.8e-06 0.00074 0 <1.00e-15 <1.86e-11
2 MUC4 mucin 4, cell surface associated 233076 13 12 12 3 2 2 5 3 1 0 2.2e-12 0.4 NaN NaN NaN 2.21e-12 2.05e-08
3 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 79333 6 6 6 0 0 0 1 1 4 0 1.9e-10 0.52 0.02 0.44 0.043 2.14e-10 1.33e-06
4 GOLGA6L6 golgin A6 family-like 6 62814 4 4 3 0 0 0 0 3 1 0 7.7e-07 0.78 0.0015 0.93 0.01 1.51e-07 0.000704
5 DSPP dentin sialophosphoprotein 256252 5 5 5 0 0 0 1 2 2 0 4.5e-06 0.57 0.013 0.052 0.0061 5.09e-07 0.00189
6 EBPL emopamil binding protein-like 32228 4 2 2 0 0 0 0 4 0 0 0.00049 0.51 0.00054 0.99 0.0014 1.06e-05 0.0328
7 MUC2 mucin 2, oligomeric mucus/gel-forming 540346 6 6 6 3 1 0 3 1 1 0 0.018 0.79 2.4e-06 0.97 0.000048 1.26e-05 0.0335
8 GFM1 G elongation factor, mitochondrial 1 153540 3 3 2 0 0 0 1 0 2 0 0.00074 0.69 0.0021 0.98 0.006 5.96e-05 0.135
9 MAP1LC3A microtubule-associated protein 1 light chain 3 alpha 21983 2 2 2 0 0 1 1 0 0 0 0.000013 0.55 0.67 0.14 0.38 6.55e-05 0.135
10 DPPA3 developmental pluripotency associated 3 32736 3 3 3 0 0 0 1 0 2 0 7.7e-06 0.69 0.45 0.63 1 9.89e-05 0.184
11 GNPNAT1 glucosamine-phosphate N-acetyltransferase 1 37950 2 2 2 0 0 0 0 0 2 0 0.00013 1 NaN NaN NaN 0.000130 0.220
12 RIPPLY2 ripply2 homolog (zebrafish) 19937 2 2 1 0 0 0 0 1 1 0 0.00025 0.86 0.0096 0.074 0.054 0.000166 0.256
13 RIMBP3 RIMS binding protein 3 244157 2 2 2 0 0 0 0 0 2 0 0.04 1 0.016 0.00014 0.00037 0.000179 0.256
14 PABPC1 poly(A) binding protein, cytoplasmic 1 129710 3 3 3 0 0 0 1 0 0 2 0.000032 0.7 0.44 0.88 0.58 0.000219 0.289
15 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 30155 2 2 2 0 0 0 0 0 2 0 0.00061 0.8 0.49 0.043 0.032 0.000233 0.289
16 AGBL4 ATP/GTP binding protein-like 4 102534 2 2 2 0 1 1 0 0 0 0 0.00039 0.6 NaN NaN NaN 0.000392 0.455
17 OR5M9 olfactory receptor, family 5, subfamily M, member 9 61710 2 2 2 0 0 1 0 1 0 0 0.000094 0.56 0.43 0.25 0.4 0.000426 0.466
18 C7orf25 chromosome 7 open reading frame 25 85206 2 2 1 0 0 0 0 0 2 0 0.0041 1 0.012 0.017 0.01 0.000455 0.470
19 MEF2A myocyte enhancer factor 2A 109974 2 2 2 0 0 1 0 0 1 0 0.00076 0.6 0.15 0.04 0.064 0.000528 0.494
20 RILPL1 Rab interacting lysosomal protein-like 1 71141 2 2 1 0 0 0 0 2 0 0 0.00023 0.72 0.012 0.82 0.21 0.000531 0.494
21 CCDC74A coiled-coil domain containing 74A 70786 3 2 3 0 1 0 0 1 1 0 0.0023 0.57 0.019 0.15 0.023 0.000587 0.520
22 PAX4 paired box 4 68086 2 2 2 0 1 0 0 0 1 0 0.00065 0.92 NaN NaN NaN 0.000652 0.551
23 CBWD6 COBW domain containing 6 55693 2 2 1 0 0 0 0 0 2 0 0.0015 1 0.016 0.1 0.049 0.000768 0.621
24 KCNK10 potassium channel, subfamily K, member 10 115059 3 3 3 0 2 0 1 0 0 0 0.00066 0.29 0.041 0.56 0.13 0.000901 0.692
25 KYNU kynureninase (L-kynurenine hydrolase) 97398 2 2 2 0 0 1 1 0 0 0 0.00038 0.4 0.29 0.28 0.24 0.000930 0.692
26 DTWD1 DTW domain containing 1 61311 2 2 2 0 0 0 0 0 2 0 0.0012 1 0.032 0.3 0.081 0.00102 0.728
27 ZSWIM6 zinc finger, SWIM-type containing 6 206027 2 3 2 0 0 0 1 0 1 0 0.017 0.66 0.0036 0.21 0.0067 0.00117 0.775
28 TBC1D5 TBC1 domain family, member 5 167173 2 2 2 0 0 0 1 0 1 0 0.0024 0.46 0.15 0.017 0.05 0.00120 0.775
29 TAL1 T-cell acute lymphocytic leukemia 1 31628 2 2 2 0 0 0 0 2 0 0 0.00012 0.65 0.48 0.76 1 0.00123 0.775
30 ATP5E ATP synthase, H+ transporting, mitochondrial F1 complex, epsilon subunit 10679 1 1 1 0 0 1 0 0 0 0 0.0012 0.65 NaN NaN NaN 0.00125 0.775
31 MUC5B mucin 5B, oligomeric mucus/gel-forming 1117758 8 8 8 0 0 0 1 2 5 0 0.00029 0.4 0.39 0.43 0.48 0.00135 0.811
32 RAB40A RAB40A, member RAS oncogene family 55264 2 2 2 0 0 0 0 0 2 0 0.0022 1 0.013 0.14 0.09 0.00187 1.000
33 KRTAP5-5 keratin associated protein 5-5 45046 1 1 1 1 1 0 0 0 0 0 0.0021 0.92 NaN NaN NaN 0.00206 1.000
34 AGRN agrin 247748 4 3 3 1 1 0 0 0 3 0 0.007 0.86 0.01 0.94 0.031 0.00207 1.000
35 ORAOV1 oral cancer overexpressed 1 28640 1 1 1 0 0 1 0 0 0 0 0.0022 0.63 NaN NaN NaN 0.00216 1.000
GOLGA6L6

Figure S1.  This figure depicts the distribution of mutations and mutation types across the GOLGA6L6 significant gene.

EBPL

Figure S2.  This figure depicts the distribution of mutations and mutation types across the EBPL 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: 2. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 27 356 24 23496 2576 0 0
2 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 6 767 6 50622 35 2.3e-10 5.1e-07
3 KRTAP5-5 keratin associated protein 5-5 1 1 1 66 1 0.000098 0.11
4 RCN1 reticulocalbin 1, EF-hand calcium binding domain 1 1 1 66 1 0.000098 0.11
5 CENPC1 centromere protein C 1 1 2 1 132 1 0.0002 0.18
6 ALPK2 alpha-kinase 2 1 3 1 198 1 0.00029 0.18
7 SMARCC2 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily c, member 2 2 3 1 198 1 0.00029 0.18
8 RB1 retinoblastoma 1 (including osteosarcoma) 2 267 2 17622 4 0.00033 0.18
9 DDR2 discoidin domain receptor tyrosine kinase 2 1 4 1 264 1 0.00039 0.18
10 RHPN2 rhophilin, Rho GTPase binding protein 2 1 4 1 264 1 0.00039 0.18

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
2309 TP53 tumor protein p53 27 0 3 9 43 3 9 43
664 EBPL emopamil binding protein-like 4 0 2 2 6 2 2 6
1386 MUC4 mucin 4, cell surface associated 13 0 1 1 2 1 1 2
26 ACR acrosin 2 0 1 1 1 1 1 1
180 ATP6V0A4 ATPase, H+ transporting, lysosomal V0 subunit a4 2 0 1 1 1 1 1 1
239 C10orf120 chromosome 10 open reading frame 120 2 0 1 1 1 1 1 1
916 GOLGA6L6 golgin A6 family-like 6 4 0 1 1 1 1 1 1
1093 ITGA5 integrin, alpha 5 (fibronectin receptor, alpha polypeptide) 2 0 1 1 1 1 1 1
1901 RILPL1 Rab interacting lysosomal protein-like 1 2 0 1 1 1 1 1 1
2332 TRRAP transformation/transcription domain-associated protein 4 0 1 1 1 1 1 1

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: 38. 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 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(3), CDC25C(1), MYT1(1), RB1(2), TP53(27), WEE1(1) 1768882 35 25 33 1 5 1 8 9 11 1 0.00078 2e-15 4e-13
2 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 MYC(1), TP53(27) 698258 28 23 26 1 3 0 7 7 10 1 0.0015 2e-15 4e-13
3 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(1), ATM(3), CDKN1A(2), CHEK2(1), TP53(27), TP73(1) 2946230 35 25 33 2 7 0 8 8 11 1 0.0027 2.1e-15 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 PAX3(1), PML(1), RB1(2), SIRT1(2), TP53(27) 1880922 33 25 31 4 4 0 7 7 14 1 0.034 4.1e-15 4e-13
5 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 ATM(3), CDKN1A(2), PCNA(1), RB1(2), TP53(27) 1802829 35 24 33 1 5 0 7 9 13 1 0.0011 4.9e-15 4e-13
6 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 ARF3(1), CDKN1A(2), CDKN1B(1), TP53(27) 807622 31 24 29 2 3 0 7 7 13 1 0.0044 4.9e-15 4e-13
7 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 ATM(3), PTK2(1), PXN(1), TP53(27) 2734647 32 24 30 1 6 0 7 9 9 1 0.00077 5.1e-15 4e-13
8 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 CHUK(1), TP53(27) 1018235 28 22 26 1 3 0 7 7 10 1 0.002 5.4e-15 4e-13
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 IGF1R(1), MYC(1), POLR2A(2), RB1(2), TEP1(1), TERT(2), TP53(27) 2756116 36 24 34 1 5 1 7 8 14 1 0.00034 5.8e-15 4e-13
10 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), MYC(1), PIK3R1(1), POLR1A(1), POLR1C(1), POLR1D(1), RB1(2), TP53(27) 1966199 35 24 33 1 4 0 9 8 13 1 0.00062 7.2e-15 4e-13

Table 7.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). 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 OXIDATIVE_PHOSPHORYLATION ATP12A, ATP4B, ATP5E, ATP5O, ATP6AP1, ATP6V0A1, ATP6V0A4, ATP6V0B, ATP6V0C, ATP6V0C, SHMT1, ATP6V0D1, ATP6V0E, ATP6V1A, ATP6V1B1, ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1D, ATP6V1E1, ATP6V1F, ATP6V1G1, ATP6V1G2, ATP6V1G3, ATP6V1H, ATP7A, ATP7B, COX10, COX4I1, COX5A, COX5B, COX6A1, COX6A2, COX6B1, COX6C, COX7A1, COX7A2, COX7B, COX7C, COX8A, NDUFA1, NDUFA10, NDUFA11, NDUFA4, NDUFA5, NDUFA8, NDUFB2, NDUFB4, NDUFB5, NDUFB6, NDUFB7, NDUFS1, NDUFS2, NDUFV1, NDUFV2, PP, PPA2, SDHA, SDHA, SDHAL2, SDHB, UQCRB, UQCRC1, UQCRFS1, UQCRH 60 ATP12A(1), ATP5E(1), ATP6AP1(1), ATP6V0A4(2), ATP6V1A(1), ATP6V1B1(1), ATP6V1B2(1), ATP7A(1), COX7A1(1), NDUFB5(1), NDUFS1(2), SDHA(1), UQCRFS1(1) 3815499 15 14 15 0 2 1 5 5 2 0 0.011 0.00012 0.073
2 CELL2CELLPATHWAY Epithelial cell adhesion proteins such as cadherins transduce signals into the cell via catenins, which alter cell shape and motility. ACTN1, ACTN2, ACTN3, BCAR1, CSK, CTNNA1, CTNNA2, CTNNB1, PECAM1, PTK2, PXN, SRC, VCL 13 BCAR1(2), CSK(1), CTNNA2(2), CTNNB1(1), PTK2(1), PXN(1), SRC(1) 1938296 9 8 9 0 3 1 1 2 1 1 0.087 0.0014 0.39
3 GLYCOSAMINOGLYCAN_DEGRADATION ARSB, GALNS, GLB1, GNS, GUSB, HEXA, HEXB, IDS, IDUA, LCT, NAGLU 11 GALNS(2), GNS(2), HEXA(1), LCT(2) 1447206 7 7 7 1 1 1 3 0 2 0 0.36 0.0022 0.39
4 SRCRPTPPATHWAY Activation of Src by Protein-tyrosine phosphatase alpha CCNB1, CDC2, CDC25A, CDC25B, CDC25C, CSK, GRB2, PRKCA, PRKCB1, PTPRA, SRC 9 CDC25C(1), CSK(1), PTPRA(1), SRC(1) 924906 4 4 4 0 0 3 1 0 0 0 0.24 0.0033 0.39
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 15 BCAR1(2), CDKN1B(1), ITGB1(1), MAPK3(1), PDK2(1), PIK3R1(1), PTK2(1), SHC1(1) 1879520 9 8 9 0 3 0 2 1 2 1 0.091 0.0037 0.39
6 IL3PATHWAY IL-3 promotes proliferation and differentiation of hematopoietic cells via a heterodimeric receptor that activates the Stat5 and MAP kinase pathways. CSF2RB, FOS, GRB2, HRAS, IL3, IL3RA, JAK2, MAP2K1, MAPK3, PTPN6, RAF1, SHC1, SOS1, STAT5A, STAT5B 15 CSF2RB(3), MAPK3(1), RAF1(1), SHC1(1), STAT5B(1) 1807897 7 7 7 0 2 0 3 2 0 0 0.092 0.0042 0.39
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 11 ATM(3), CDC25C(1), MYT1(1), RB1(2), WEE1(1) 1683244 8 7 8 0 2 1 1 2 2 0 0.17 0.0044 0.39
8 CDC25PATHWAY The protein phosphatase Cdc25 is phosphorylated by Chk1 and activates Cdc2 to stimulate eukaryotic cells into M phase. ATM, CDC2, CDC25A, CDC25B, CDC25C, CHEK1, MYT1, WEE1, YWHAH 8 ATM(3), CDC25C(1), MYT1(1), WEE1(1) 1381283 6 6 6 0 2 1 1 2 0 0 0.16 0.0066 0.44
9 ATP_SYNTHESIS ATP5E, ATP5O, ATP6AP1, ATP6V0A1, ATP6V0A4, ATP6V0B, ATP6V0C, ATP6V0C, SHMT1, ATP6V0D1, ATP6V0E, ATP6V1A, ATP6V1B1, ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1D, ATP6V1E1, ATP6V1F, ATP6V1G1, ATP6V1G2, ATP6V1G3, ATP6V1H 21 ATP5E(1), ATP6AP1(1), ATP6V0A4(2), ATP6V1A(1), ATP6V1B1(1), ATP6V1B2(1) 1502206 7 6 7 0 2 1 1 2 1 0 0.15 0.0082 0.44
10 FLAGELLAR_ASSEMBLY ATP5E, ATP5O, ATP6AP1, ATP6V0A1, ATP6V0A4, ATP6V0B, ATP6V0C, ATP6V0C, SHMT1, ATP6V0D1, ATP6V0E, ATP6V1A, ATP6V1B1, ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1D, ATP6V1E1, ATP6V1F, ATP6V1G1, ATP6V1G2, ATP6V1G3, ATP6V1H 21 ATP5E(1), ATP6AP1(1), ATP6V0A4(2), ATP6V1A(1), ATP6V1B1(1), ATP6V1B2(1) 1502206 7 6 7 0 2 1 1 2 1 0 0.15 0.0082 0.44
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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle