Mutation Analysis (MutSig v2.0)
Rectum Adenocarcinoma (Primary solid tumor)
17 October 2014 | analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1C53JS8
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1C53JS8
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: READ-TP

- Number of patients in set: 69

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:READ-TP.final_analysis_set.maf

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

- Significantly mutated genes (q ≤ 0.1): 14

- Mutations seen in COSMIC: 222

- Significantly mutated genes in COSMIC territory: 10

- Significantly mutated genesets: 33

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

Mutation Preprocessing

- Read 38 MAFs of type "Broad"

- Read 35 MAFs of type "Baylor-SOLiD"

- Total number of mutations in input MAFs: 29413

- After removing 257 invalidated mutations: 29156

- After removing 200 noncoding mutations: 28956

- After collapsing adjacent/redundant mutations: 21679

Mutation Filtering

- Number of mutations before filtering: 21679

- After removing 199 mutations outside gene set: 21480

- After removing 172 mutations outside category set: 21308

- After removing 2 "impossible" mutations in

- gene-patient-category bins of zero coverage: 20935

Results
Breakdown of Mutations by Type

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

type | count
--- | ---
De_novo_Start_InFrame | 4
De_novo_Start_OutOfFrame | 30
Frame_Shift_Del | 151
Frame_Shift_Ins | 155
In_Frame_Del | 27
In_Frame_Ins | 7
Missense_Mutation | 14473
Nonsense_Mutation | 1779
Nonstop_Mutation | 6
Read-through | 10
Silent | 4628
Splice_Site | 38
Total | 21308

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 | 4918 | 99631386 | 0.000049 | 49 | 5.4 | 2.1
*Cp(A/C/T)->mut | 6676 | 831878375 | 8e-06 | 8 | 0.89 | 3.3
A->mut | 2743 | 908606480 | 3e-06 | 3 | 0.33 | 3.9
*CpG->(G/A) | 135 | 99631386 | 1.4e-06 | 1.4 | 0.15 | 2.7
indel+null | 2050 | 1840116241 | 1.1e-06 | 1.1 | 0.12 | NaN
double_null | 157 | 1840116241 | 8.5e-08 | 0.085 | 0.0094 | NaN
Total | 16679 | 1840116241 | 9.1e-06 | 9.1 | 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: READ-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)->mut

- n3 = number of nonsilent mutations of type: A->mut

- n4 = number of nonsilent mutations of type: *CpG->(G/A)

- 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: 14. 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 | APC | adenomatous polyposis coli | 576224 | 66 | 57 | 56 | 0 | 1 | 4 | 4 | 0 | 39 | 18 | 3.89e-15 | 0.000014 | 0 | 0.93 | 0 | <1.00e-15 | <5.98e-12
2 | TP53 | tumor protein p53 | 79667 | 45 | 45 | 30 | 1 | 19 | 6 | 6 | 2 | 12 | 0 | 1.67e-15 | 0.00017 | 6e-07 | 0 | 0 | <1.00e-15 | <5.98e-12
3 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 48604 | 38 | 38 | 8 | 0 | 0 | 36 | 1 | 0 | 1 | 0 | <1.00e-15 | 0.0034 | 0 | 0.002 | 0 | <1.00e-15 | <5.98e-12
4 | SMAD4 | SMAD family member 4 | 115264 | 8 | 8 | 6 | 0 | 2 | 3 | 3 | 0 | 0 | 0 | 8.11e-11 | 0.12 | 0.17 | 0.18 | 0.26 | 5.44e-10 | 2.44e-06
5 | KIAA1804 |  | 162266 | 11 | 9 | 9 | 0 | 7 | 3 | 1 | 0 | 0 | 0 | 1.25e-08 | 0.036 | 0.05 | 0.042 | 0.047 | 1.31e-08 | 4.71e-05
6 | FBXW7 | F-box and WD repeat domain containing 7 | 177744 | 12 | 9 | 10 | 0 | 6 | 2 | 2 | 0 | 2 | 0 | 1.95e-08 | 0.075 | 0.077 | 0.063 | 0.057 | 2.40e-08 | 7.19e-05
7 | NRAS | neuroblastoma RAS viral (v-ras) oncogene homolog | 40433 | 5 | 5 | 4 | 0 | 0 | 3 | 2 | 0 | 0 | 0 | 1.06e-07 | 0.32 | 0.013 | 0.44 | 0.026 | 5.76e-08 | 0.000148
8 | TCF7L2 | transcription factor 7-like 2 (T-cell specific, HMG-box) | 119026 | 7 | 7 | 7 | 1 | 2 | 3 | 0 | 0 | 2 | 0 | 1.01e-07 | 0.26 | 0.11 | 0.072 | 0.077 | 1.53e-07 | 0.000343
9 | PIK3CA | phosphoinositide-3-kinase, catalytic, alpha polypeptide | 194975 | 7 | 7 | 7 | 1 | 1 | 3 | 3 | 0 | 0 | 0 | 2.12e-07 | 0.57 | 0.1 | 0.42 | 0.16 | 6.00e-07 | 0.00120
10 | OPCML | opioid binding protein/cell adhesion molecule-like | 73709 | 6 | 6 | 6 | 1 | 1 | 3 | 0 | 0 | 2 | 0 | 2.85e-07 | 0.32 | 0.49 | 0.47 | 0.68 | 3.18e-06 | 0.00570
11 | KRTAP5-5 | keratin associated protein 5-5 | 34487 | 2 | 2 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 2.10e-05 | 0.35 | 0.1 | 0.0062 | 0.013 | 4.51e-06 | 0.00735
12 | SMAD2 | SMAD family member 2 | 98964 | 5 | 5 | 5 | 0 | 0 | 3 | 1 | 0 | 1 | 0 | 2.17e-05 | 0.39 | 0.012 | 0.34 | 0.02 | 6.83e-06 | 0.0102
13 | SPATA8 | spermatogenesis associated 8 | 20140 | 3 | 3 | 3 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 4.19e-06 | 0.45 | 0.1 | 0.45 | 0.16 | 1.00e-05 | 0.0138
14 | ERBB2 | v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) | 227547 | 4 | 4 | 2 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 0.0238 | 0.54 | 0.00017 | 0.026 | 0.00013 | 4.23e-05 | 0.0542
15 | FAM123B | family with sequence similarity 123B | 190503 | 8 | 6 | 8 | 1 | 0 | 2 | 1 | 0 | 5 | 0 | 8.11e-05 | 0.58 | 0.07 | 0.64 | 0.14 | 0.000139 | 0.166
16 | ZIM3 | zinc finger, imprinted 3 | 98103 | 6 | 5 | 6 | 0 | 1 | 1 | 3 | 0 | 1 | 0 | 6.03e-05 | 0.21 | 0.44 | 0.098 | 0.22 | 0.000166 | 0.186
17 | PIK3R1 | phosphoinositide-3-kinase, regulatory subunit 1 (alpha) | 152490 | 5 | 4 | 5 | 0 | 2 | 0 | 0 | 0 | 1 | 2 | 0.000520 | 0.31 | 0.026 | 0.58 | 0.043 | 0.000260 | 0.275
18 | SGCB | sarcoglycan, beta (43kDa dystrophin-associated glycoprotein) | 64145 | 4 | 4 | 4 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4.60e-05 | 0.51 | 0.32 | 0.73 | 0.7 | 0.000367 | 0.366
19 | LRRTM2 | leucine rich repeat transmembrane neuronal 2 | 59242 | 5 | 4 | 5 | 1 | 1 | 1 | 2 | 1 | 0 | 0 | 3.54e-05 | 0.58 | 0.98 | 0.8 | 1 | 0.000398 | 0.372
20 | OSBPL6 | oxysterol binding protein-like 6 | 208053 | 5 | 5 | 5 | 0 | 1 | 2 | 0 | 2 | 0 | 0 | 0.000295 | 0.25 | 0.22 | 0.069 | 0.13 | 0.000438 | 0.372
21 | CCBP2 | chemokine binding protein 2 | 79700 | 5 | 5 | 5 | 0 | 1 | 2 | 2 | 0 | 0 | 0 | 5.03e-05 | 0.23 | 0.78 | 0.32 | 0.84 | 0.000469 | 0.372
22 | CASP14 | caspase 14, apoptosis-related cysteine peptidase | 51900 | 5 | 4 | 4 | 0 | 4 | 1 | 0 | 0 | 0 | 0 | 0.000185 | 0.2 | 0.14 | 0.68 | 0.23 | 0.000476 | 0.372
23 | GFRA1 | GDNF family receptor alpha 1 | 86296 | 5 | 5 | 5 | 1 | 1 | 0 | 3 | 0 | 1 | 0 | 4.66e-05 | 0.55 | 0.62 | 0.96 | 0.94 | 0.000481 | 0.372
24 | EPYC | epiphycan | 67872 | 4 | 3 | 4 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0.000599 | 0.38 | 0.034 | 0.47 | 0.075 | 0.000497 | 0.372
25 | FAM133A | family with sequence similarity 133, member A | 38160 | 2 | 2 | 2 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0.00121 | 0.98 | 0.54 | 0.034 | 0.041 | 0.000547 | 0.392
26 | SLITRK1 | SLIT and NTRK-like family, member 1 | 134633 | 6 | 5 | 6 | 0 | 2 | 1 | 2 | 0 | 1 | 0 | 0.000291 | 0.18 | 0.13 | 0.58 | 0.2 | 0.000640 | 0.431
27 | MAP2K3 | mitogen-activated protein kinase kinase 3 | 67262 | 4 | 4 | 4 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 6.05e-05 | 0.3 | 0.77 | 0.62 | 1 | 0.000649 | 0.431
28 | PCDHA13 | protocadherin alpha 13 | 162857 | 8 | 6 | 8 | 0 | 3 | 1 | 2 | 1 | 1 | 0 | 9.77e-05 | 0.046 | 0.41 | 0.96 | 0.65 | 0.000676 | 0.433
29 | CACNG7 | calcium channel, voltage-dependent, gamma subunit 7 | 49136 | 3 | 3 | 3 | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0.000572 | 0.28 | 0.51 | 0.0087 | 0.13 | 0.000804 | 0.461
30 | CTNNB1 | catenin (cadherin-associated protein), beta 1, 88kDa | 162026 | 4 | 4 | 4 | 0 | 1 | 2 | 1 | 0 | 0 | 0 | 0.000828 | 0.42 | 0.074 | 0.35 | 0.094 | 0.000814 | 0.461
31 | FBXO15 | F-box protein 15 | 91945 | 3 | 3 | 3 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0.00267 | 0.28 | 0.008 | 0.38 | 0.03 | 0.000830 | 0.461
32 | PRIM2 | primase, DNA, polypeptide 2 (58kDa) | 57190 | 3 | 3 | 3 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0.000842 | 0.97 | NaN | NaN | NaN | 0.000842 | 0.461
33 | EDNRB | endothelin receptor type B | 89905 | 5 | 4 | 5 | 1 | 0 | 2 | 3 | 0 | 0 | 0 | 0.000440 | 0.62 | 0.12 | 0.32 | 0.18 | 0.000848 | 0.461
34 | CFHR5 | complement factor H-related 5 | 116845 | 3 | 3 | 3 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0.000855 | 0.52 | 0.23 | 0.061 | 0.1 | 0.000890 | 0.470
35 | ELF3 | E74-like factor 3 (ets domain transcription factor, epithelial-specific ) | 71547 | 3 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0.000871 | 0.75 | 0.048 | 0.33 | 0.1 | 0.000917 | 0.470

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: 10. Number of genes displayed: 10

rank | gene | description | n | cos | n_cos | N_cos | cos_ev | p | q
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 38 | 52 | 37 | 3588 | 363199 | 1.8e-13 | 8e-10
2 | TP53 | tumor protein p53 | 45 | 824 | 45 | 56856 | 17987 | 1.7e-12 | 2.6e-09
3 | APC | adenomatous polyposis coli | 66 | 839 | 50 | 57891 | 1048 | 1.7e-12 | 2.6e-09
4 | NRAS | neuroblastoma RAS viral (v-ras) oncogene homolog | 5 | 33 | 5 | 2277 | 5755 | 3.1e-11 | 3.5e-08
5 | FBXW7 | F-box and WD repeat domain containing 7 | 12 | 91 | 6 | 6279 | 329 | 4.5e-11 | 4.1e-08
6 | SMAD4 | SMAD family member 4 | 8 | 159 | 6 | 10971 | 39 | 1.2e-09 | 9.3e-07
7 | KRTAP5-5 | keratin associated protein 5-5 | 2 | 1 | 2 | 69 | 2 | 1.9e-07 | 0.00012
8 | ERBB2 | v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) | 4 | 42 | 3 | 2898 | 6 | 3e-06 | 0.0017
9 | PIK3CA | phosphoinositide-3-kinase, catalytic, alpha polypeptide | 7 | 220 | 4 | 15180 | 1382 | 0.000013 | 0.0067
10 | LRP1B | low density lipoprotein-related protein 1B (deleted in tumors) | 20 | 18 | 2 | 1242 | 2 | 0.000063 | 0.028

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: 33. 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 | ST_ADRENERGIC | Adrenergic receptors respond to epinephrine and norepinephrine signaling. | AKT1, APC, AR, ASAH1, BF, BRAF, CAMP, CCL13, CCL15, CCL16, DAG1, EGFR, GAS, GNA11, GNA15, GNAI1, GNAQ, ITPKA, ITPKB, ITPR1, ITPR2, ITPR3, KCNJ3, KCNJ5, KCNJ9, MAPK1, MAPK10, MAPK14, PHKA2, PIK3CA, PIK3CD, PIK3R1, PITX2, PTX1, PTX3, RAF1, SRC | 34 | APC(66), AR(2), BRAF(2), DAG1(1), EGFR(1), GNAI1(1), GNAQ(1), ITPR1(8), ITPR2(6), ITPR3(1), KCNJ5(1), KCNJ9(1), MAPK10(4), PHKA2(1), PIK3CA(7), PIK3CD(1), PIK3R1(5), RAF1(2) | 5018319 | 111 | 60 | 101 | 7 | 18 | 15 | 11 | 0 | 46 | 21 | 4.9e-08 | <1.00e-15 | <1.07e-13
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 | 18 | ABCB1(5), ATM(10), CPB2(1), CSNK1D(1), FHL2(1), HIF1A(2), IGFBP3(2), MAPK8(5), TP53(45) | 2001688 | 72 | 50 | 57 | 4 | 26 | 18 | 9 | 3 | 15 | 1 | 0.000018 | <1.00e-15 | <1.07e-13
3 | 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(10), ATR(4), CDC25C(1), TP53(45), YWHAH(1) | 1621418 | 61 | 49 | 46 | 6 | 22 | 16 | 7 | 2 | 13 | 1 | 0.015 | <1.00e-15 | <1.07e-13
4 | 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 | EGFR(1), IGF1R(1), PRKCA(2), RB1(3), TERF1(1), TP53(45), XRCC5(2) | 2767314 | 55 | 48 | 40 | 6 | 22 | 9 | 9 | 2 | 13 | 0 | 0.0014 | <1.00e-15 | <1.07e-13
5 | TGFBPATHWAY | The TGF-beta receptor responds to ligand binding by activating the SMAD family of transcriptional regulations, commonly blocking cell growth. | APC, CDH1, CREBBP, EP300, MADH2, MADH3, MADH4, MADH7, MADHIP, MAP2K1, MAP3K7, MAP3K7IP1, MAPK3, SKIL, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2 | 13 | APC(66), CDH1(1), CREBBP(4), EP300(2), MAP2K1(1), MAP3K7(2), MAPK3(1), SKIL(1), TGFB2(4), TGFBR1(3) | 2554178 | 85 | 57 | 75 | 4 | 5 | 10 | 8 | 0 | 44 | 18 | 5.2e-06 | 1.11e-15 | 1.07e-13
6 | PITX2PATHWAY | The bicoid-related transcription factor Pitx2 is activated by Wnt binding to the Frizzled receptor and induces tissue-specific cell proliferation. | APC, AXIN1, CREBBP, CTNNB1, DVL1, EP300, FZD1, GSK3B, HDAC1, HTATIP, LDB1, LEF1, PITX2, PPARBP, TRRAP, WNT1 | 13 | APC(66), AXIN1(1), CREBBP(4), CTNNB1(4), EP300(2), FZD1(1), GSK3B(1), LDB1(2), TRRAP(4) | 3136901 | 85 | 58 | 75 | 4 | 8 | 12 | 6 | 0 | 41 | 18 | 1e-06 | 1.22e-15 | 1.07e-13
7 | WNTPATHWAY | The Wnt glycoprotein binds to membrane-bound receptors such as Frizzled to activate a number of signaling pathways, including that of beta-catenin. | APC, AXIN1, BTRC, CCND1, CREBBP, CSNK1A1, CSNK1D, CSNK2A1, CTBP1, CTNNB1, DVL1, FRAT1, FZD1, GSK3B, HDAC1, MADH4, MAP3K7, MAP3K7IP1, MYC, NLK, PPARD, PPP2CA, TCF1, TLE1, WIF1, WNT1 | 21 | APC(66), AXIN1(1), BTRC(3), CREBBP(4), CSNK1D(1), CTNNB1(4), FZD1(1), GSK3B(1), MAP3K7(2), PPARD(1) | 2701685 | 84 | 58 | 74 | 4 | 8 | 9 | 8 | 0 | 41 | 18 | 1.8e-06 | 1.22e-15 | 1.07e-13
8 | WNT_SIGNALING | Wnt signaling genes | APC, ARHA, AXIN1, C2orf31, CCND1, CCND2, CCND3, CSNK1E, CSNK1E, LOC400927, CTNNB1, DIPA, DVL1, DVL2, DVL3, FBXW2, FOSL1, FRAT1, FZD1, FZD10, FZD2, FZD3, FZD5, FZD6, FZD7, FZD8, FZD9, GSK3B, JUN, LDLR, MAPK10, MAPK9, MYC, PAFAH1B1, PLAU, PPP2R5C, PPP2R5E, PRKCA, PRKCB1, PRKCD, PRKCE, PRKCG, PRKCH, PRKCI, PRKCM, PRKCQ, PRKCZ, PRKD1, RAC1, RHOA, SFRP4, TCF7, WNT1, WNT10A, WNT10B, WNT11, WNT16, WNT2, WNT2B, WNT3, WNT4, WNT5A, WNT5B, WNT6, WNT7A, WNT7B | 57 | APC(66), AXIN1(1), CTNNB1(4), DVL2(1), DVL3(2), FBXW2(1), FZD1(1), FZD10(2), FZD3(3), FZD6(3), GSK3B(1), LDLR(1), MAPK10(4), MAPK9(2), PLAU(1), PPP2R5C(1), PRKCA(2), PRKCE(2), PRKCG(2), PRKCH(1), PRKCQ(1), PRKD1(5), RHOA(1), SFRP4(1), TCF7(3), WNT10B(1), WNT2(1), WNT2B(2), WNT6(1) | 5514820 | 117 | 58 | 107 | 13 | 15 | 27 | 8 | 0 | 49 | 18 | 6.7e-06 | 1.44e-15 | 1.09e-13
9 | 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(10), CDK4(1), PCNA(1), RB1(3), TIMP3(1), TP53(45) | 1820960 | 62 | 50 | 47 | 6 | 21 | 14 | 9 | 2 | 15 | 1 | 0.002 | 1.67e-15 | 1.09e-13
10 | ALKPATHWAY | Activin receptor-like kinase 3 (ALK3) is required during gestation for cardiac muscle development. | ACVR1, APC, ATF2, AXIN1, BMP10, BMP2, BMP4, BMP5, BMP7, BMPR1A, BMPR2, CHRD, CTNNB1, DVL1, FZD1, GATA4, GSK3B, MADH1, MADH4, MADH5, MADH6, MAP3K7, MEF2C, MYL2, NKX2-5, NOG, NPPA, NPPB, RFC1, TCF1, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, WNT1 | 31 | ACVR1(1), APC(66), ATF2(1), AXIN1(1), BMP10(1), BMP2(1), BMP4(1), BMP5(1), BMP7(1), BMPR2(3), CTNNB1(4), FZD1(1), GSK3B(1), MAP3K7(2), MEF2C(2), NPPB(1), RFC1(4), TGFB2(4), TGFBR1(3), TGFBR3(3) | 3414527 | 102 | 59 | 92 | 3 | 13 | 19 | 9 | 0 | 43 | 18 | 6.1e-09 | 1.78e-15 | 1.09e-13

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 | ERBB4PATHWAY | ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. | ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 | 6 | ADAM17(1), ERBB4(5), NRG2(2), NRG3(4), PRKCA(2) | 908762 | 14 | 9 | 14 | 1 | 4 | 5 | 1 | 1 | 3 | 0 | 0.073 | 0.0014 | 0.9
2 | GSPATHWAY | Activated G-protein coupled receptors stimulate cAMP production and thus activate protein kinase A, involved in a number of signal transduction pathways. | ADCY1, GNAS, GNB1, GNGT1, PRKACA, PRKAR1A | 6 | ADCY1(4), GNGT1(1), PRKACA(1), PRKAR1A(4) | 607553 | 10 | 8 | 10 | 1 | 3 | 4 | 1 | 0 | 2 | 0 | 0.2 | 0.0071 | 1
3 | HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM | Genes involved in D-arginine and D-ornithine metabolism | DAO | 1 | DAO(4) | 73821 | 4 | 3 | 4 | 0 | 3 | 1 | 0 | 0 | 0 | 0 | 0.28 | 0.012 | 1
4 | C21_STEROID_HORMONE_METABOLISM |  | AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 | 11 | AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) | 837086 | 11 | 10 | 11 | 2 | 3 | 5 | 1 | 0 | 2 | 0 | 0.31 | 0.017 | 1
5 | HSA00140_C21_STEROID_HORMONE_METABOLISM | Genes involved in C21-steroid hormone metabolism | AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 | 11 | AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) | 837086 | 11 | 10 | 11 | 2 | 3 | 5 | 1 | 0 | 2 | 0 | 0.31 | 0.017 | 1
6 | NUCLEOTIDE_GPCRS |  | ADORA1, ADORA2A, ADORA2B, ADORA3, GPR23, LTB4R, P2RY1, P2RY2, P2RY5, P2RY6 | 8 | ADORA1(3), ADORA2A(2), LTB4R(1), P2RY1(3), P2RY2(1), P2RY6(1) | 524943 | 11 | 6 | 11 | 0 | 5 | 5 | 1 | 0 | 0 | 0 | 0.014 | 0.032 | 1
7 | 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 | 19 | B2M(3), HLA-A(2), KLRC3(1), LAT(1), MAP2K1(1), MAPK3(1), PAK1(1), PIK3R1(5), SYK(3), VAV1(2) | 1594854 | 20 | 8 | 20 | 1 | 4 | 5 | 4 | 0 | 4 | 3 | 0.034 | 0.035 | 1
8 | PS1PATHWAY | Presenilin is required for gamma-secretase activity to activate Notch signaling; presenilin also inhibits beta-catenin in the Wnt/Frizzled pathway. | ADAM17, APC, AXIN1, BTRC, CTNNB1, DLL1, DVL1, FZD1, GSK3B, NOTCH1, PSEN1, RBPSUH, TCF1, WNT1 | 10 | ADAM17(1), AXIN1(1), BTRC(3), CTNNB1(4), DLL1(3), FZD1(1), GSK3B(1) | 1369199 | 14 | 9 | 14 | 1 | 5 | 4 | 2 | 0 | 3 | 0 | 0.041 | 0.05 | 1
9 | HSA00643_STYRENE_DEGRADATION | Genes involved in styrene degradation | FAH, GSTZ1, HGD | 3 | FAH(1), HGD(1) | 179749 | 2 | 2 | 2 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0.78 | 0.073 | 1
10 | 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 | CDKN1B(2), GRB2(1), MAPK3(1), PDK2(1), PIK3R1(5), PTEN(4), SOS1(2) | 1658685 | 16 | 7 | 16 | 1 | 3 | 4 | 2 | 0 | 5 | 2 | 0.073 | 0.089 | 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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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