Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Thyroid Adenocarcinoma (Primary solid tumor)
16 April 2014 | analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C18P5Z6M
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C18P5Z6M
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 and MutSigCV v0.9 merged result was used to generate the results found in this report.

- Working with individual set: THCA-TP

- Number of patients in set: 401

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:THCA-TP.final_analysis_set.maf

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

- Significantly mutated genes (q ≤ 0.1): 6

- Mutations seen in COSMIC: 312

- Significantly mutated genes in COSMIC territory: 9

- Significantly mutated genesets: 91

Mutation Preprocessing

- Read 401 MAFs of type "Broad"

- Total number of mutations in input MAFs: 7430

- After removing 2 mutations outside chr1-24: 7428

- After removing 23 blacklisted mutations: 7405

- After removing 61 noncoding mutations: 7344

- After collapsing adjacent/redundant mutations: 6975

Mutation Filtering

- Number of mutations before filtering: 6975

- After removing 256 mutations outside gene set: 6719

- After removing 3 mutations outside category set: 6716

Results
Breakdown of Mutations by Type

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

type | count
--- | ---
Frame_Shift_Del | 196
Frame_Shift_Ins | 33
In_Frame_Del | 27
In_Frame_Ins | 6
Missense_Mutation | 4350
Nonsense_Mutation | 240
Nonstop_Mutation | 5
Silent | 1644
Splice_Site | 215
Total | 6716

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 | 810 | 651888269 | 1.2e-06 | 1.2 | 2.9 | 2.1
*Cp(A/C/T)->T | 1012 | 5343350203 | 1.9e-07 | 0.19 | 0.44 | 1.7
A->G | 816 | 5758499319 | 1.4e-07 | 0.14 | 0.33 | 2.3
transver | 1712 | 11753737791 | 1.5e-07 | 0.15 | 0.34 | 5
indel+null | 719 | 11753737791 | 6.1e-08 | 0.061 | 0.14 | NaN
double_null | 3 | 11753737791 | 2.6e-10 | 0.00026 | 0.00059 | NaN
Total | 5072 | 11753737791 | 4.3e-07 | 0.43 | 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: THCA-TP.patients.counts_and_rates.txt

Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 3. Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 4. Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 5. Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

Significantly Mutated Genes

Column Descriptions:

- N = number of sequenced bases in this gene across the individual set

- n = number of (nonsilent) mutations in this gene across the individual set

- npat = number of patients (individuals) with at least one nonsilent mutation

- nsite = number of unique sites having a non-silent mutation

- nsil = number of silent mutations in this gene across the individual set

- n1 = number of nonsilent mutations of type: *CpG->T

- n2 = number of nonsilent mutations of type: *Cp(A/C/T)->T

- n3 = number of nonsilent mutations of type: A->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_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: 6. 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_clust | p_cons | p_joint | p_cv | p | q
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | NRAS | neuroblastoma RAS viral (v-ras) oncogene homolog | 234967 | 34 | 34 | 2 | 0 | 0 | 0 | 27 | 7 | 0 | 0 | 0 | 0.00022 | 0 | 0 | 0 | 0
2 | BRAF | v-raf murine sarcoma viral oncogene homolog B1 | 891836 | 240 | 240 | 6 | 1 | 0 | 1 | 1 | 234 | 4 | 0 | 0 | 0 | 0 | 5.6e-16 | 0 | 0
3 | HRAS | v-Ha-ras Harvey rat sarcoma viral oncogene homolog | 260071 | 14 | 14 | 2 | 0 | 0 | 0 | 11 | 3 | 0 | 0 | 0 | 0.00014 | 0 | 1.1e-09 | 0 | 0
4 | EIF1AX | eukaryotic translation initiation factor 1A, X-linked | 176670 | 6 | 6 | 5 | 0 | 0 | 3 | 0 | 1 | 2 | 0 | 0.028 | 0.033 | 0.016 | 3.2e-07 | 1e-07 | 0.00046
5 | NUP93 | nucleoporin 93kDa | 1019335 | 4 | 4 | 2 | 0 | 0 | 1 | 0 | 0 | 3 | 0 | 3.8e-06 | 0.27 | 0.000012 | 0.011 | 2.1e-06 | 0.0075
6 | NLRP6 | NLR family, pyrin domain containing 6 | 732735 | 3 | 3 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0.00021 | 0.000028 | 4.8e-06 | 0.16 | 0.000012 | 0.036
7 | PPM1D | protein phosphatase 1D magnesium-dependent, delta isoform | 625741 | 5 | 5 | 5 | 0 | 0 | 1 | 0 | 0 | 4 | 0 | 0.026 | 0.89 | 0.066 | 0.00032 | 0.00025 | 0.64
8 | MUC7 | mucin 7, secreted | 457922 | 2 | 2 | 2 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0.44 | 0.011 | 0.014 | 0.051 | 0.006 | 1
9 | OR56A1 | olfactory receptor, family 56, subfamily A, member 1 | 385098 | 2 | 2 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0.16 | 0.0039 | 0.0049 | 0.16 | 0.0064 | 1
10 | C20orf144 | chromosome 20 open reading frame 144 | 53233 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.011 | 0.011 | 1
11 | S100A7 | S100 calcium binding protein A7 | 125914 | 3 | 3 | 3 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0.1 | 0.8 | 0.2 | 0.0081 | 0.012 | 1
12 | PCDHAC2 | protocadherin alpha subfamily C, 2 | 1182850 | 5 | 5 | 5 | 8 | 2 | 0 | 1 | 2 | 0 | 0 | NaN | NaN | NaN | 0.012 | 0.012 | 1
13 | RAB27A | RAB27A, member RAS oncogene family | 273189 | 2 | 2 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0.017 | 0.8 | 0.19 | 0.011 | 0.015 | 1
14 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 275782 | 4 | 4 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 0.036 | 0.0028 | 0.003 | 0.96 | 0.02 | 1
15 | BAGE | B melanoma antigen | 50513 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | NaN | NaN | NaN | 0.021 | 0.021 | 1
16 | WIPF1 | WAS/WASL interacting protein family, member 1 | 613843 | 2 | 2 | 2 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0.75 | 0.0053 | 0.0062 | 0.53 | 0.022 | 1
17 | TMSB15A | thymosin beta 15a | 58475 | 2 | 2 | 2 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0.23 | 0.5 | 1 | 0.0034 | 0.023 | 1
18 | CRH | corticotropin releasing hormone | 79709 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.023 | 0.023 | 1
19 | IARS | isoleucyl-tRNA synthetase | 1564420 | 3 | 3 | 3 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0.24 | 0.0053 | 0.012 | 0.3 | 0.023 | 1
20 | C19orf35 | chromosome 19 open reading frame 35 | 221020 | 2 | 2 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0.19 | 0.033 | 0.048 | 0.079 | 0.025 | 1
21 | ATR | ataxia telangiectasia and Rad3 related | 3219782 | 3 | 3 | 3 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 0.0036 | 0.28 | 0.0042 | 0.99 | 0.027 | 1
22 | MSI1 | musashi homolog 1 (Drosophila) | 314023 | 3 | 3 | 3 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0.37 | 0.69 | 0.63 | 0.0075 | 0.03 | 1
23 | TMEM47 | transmembrane protein 47 | 118810 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.032 | 0.032 | 1
24 | IL11 | interleukin 11 | 72760 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.037 | 0.037 | 1
25 | CST6 | cystatin E/M | 111752 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.037 | 0.037 | 1
26 | TBC1D7 | TBC1 domain family, member 7 | 363943 | 2 | 2 | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0.19 | 0.011 | 0.022 | 0.32 | 0.043 | 1
27 | PDF | peptide deformylase (mitochondrial) | 73258 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.043 | 0.043 | 1
28 | AMDHD1 | amidohydrolase domain containing 1 | 463710 | 2 | 2 | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0.36 | 0.051 | 0.085 | 0.085 | 0.043 | 1
29 | FAM162B | family with sequence similarity 162, member B | 132553 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.046 | 0.046 | 1
30 | ATM | ataxia telangiectasia mutated | 3729176 | 5 | 5 | 5 | 0 | 0 | 1 | 1 | 2 | 1 | 0 | 0.038 | 0.014 | 0.008 | 1 | 0.047 | 1
31 | CXorf61 | chromosome X open reading frame 61 | 140343 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | NaN | NaN | NaN | 0.047 | 0.047 | 1
32 | FUNDC1 | FUN14 domain containing 1 | 168618 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.05 | 0.05 | 1
33 | CACNA1A | calcium channel, voltage-dependent, P/Q type, alpha 1A subunit | 2130097 | 2 | 2 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0.14 | 0.014 | 0.0095 | 0.98 | 0.053 | 1
34 | COMTD1 | catechol-O-methyltransferase domain containing 1 | 106851 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | NaN | NaN | NaN | 0.054 | 0.054 | 1
35 | SLC27A4 | solute carrier family 27 (fatty acid transporter), member 4 | 783281 | 2 | 2 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0.052 | 0.043 | 0.024 | 0.4 | 0.054 | 1

NRAS

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

BRAF

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

HRAS

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

EIF1AX

Figure S4. This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

NUP93

Figure S5. This figure depicts the distribution of mutations and mutation types across the NUP93 significant gene.

NLRP6

Figure S6. This figure depicts the distribution of mutations and mutation types across the NLRP6 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: 9. Number of genes displayed: 10

rank | gene | description | n | cos | n_cos | N_cos | cos_ev | p | q
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | HRAS | v-Ha-ras Harvey rat sarcoma viral oncogene homolog | 14 | 19 | 14 | 7619 | 2912 | 2.9e-13 | 1.1e-09
2 | NRAS | neuroblastoma RAS viral (v-ras) oncogene homolog | 34 | 33 | 34 | 13233 | 44132 | 5e-13 | 1.1e-09
3 | BRAF | v-raf murine sarcoma viral oncogene homolog B1 | 240 | 89 | 238 | 35689 | 3392099 | 1.3e-12 | 2e-09
4 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 4 | 52 | 4 | 20852 | 15018 | 2.7e-10 | 3.1e-07
5 | C4BPA | complement component 4 binding protein, alpha | 1 | 1 | 1 | 401 | 1 | 0.00017 | 0.087
6 | PCGF2 | polycomb group ring finger 2 | 2 | 1 | 1 | 401 | 1 | 0.00017 | 0.087
7 | SEZ6L | seizure related 6 homolog (mouse)-like | 2 | 1 | 1 | 401 | 1 | 0.00017 | 0.087
8 | SMC3 | structural maintenance of chromosomes 3 | 1 | 1 | 1 | 401 | 1 | 0.00017 | 0.087
9 | TNS1 | tensin 1 | 3 | 1 | 1 | 401 | 1 | 0.00017 | 0.087
10 | DCC | deleted in colorectal carcinoma | 2 | 3 | 1 | 1203 | 1 | 0.00052 | 0.21

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: 91. 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 | HSA04010_MAPK_SIGNALING_PATHWAY | Genes involved in MAPK signaling pathway | ACVR1B, ACVR1C, AKT1, AKT2, AKT3, ARRB1, ARRB2, ATF2, ATF4, BDNF, BRAF, CACNA1A, CACNA1B, CACNA1C, CACNA1D, CACNA1E, CACNA1F, CACNA1G, CACNA1H, CACNA1I, CACNA1S, CACNA2D1, CACNA2D2, CACNA2D3, CACNA2D4, CACNB1, CACNB2, CACNB3, CACNB4, CACNG1, CACNG2, CACNG3, CACNG4, CACNG5, CACNG6, CACNG7, CACNG8, CASP3, CD14, CDC25B, CDC42, CHP, CHUK, CRK, CRKL, DAXX, DDIT3, DUSP1, DUSP10, DUSP14, DUSP16, DUSP2, DUSP3, DUSP4, DUSP5, DUSP6, DUSP7, DUSP8, DUSP9, ECSIT, EGF, EGFR, ELK1, ELK4, EVI1, FAS, FASLG, FGF1, FGF10, FGF11, FGF12, FGF13, FGF14, FGF16, FGF17, FGF18, FGF19, FGF2, FGF20, FGF21, FGF22, FGF23, FGF3, FGF4, FGF5, FGF6, FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FLNA, FLNB, FLNC, FOS, GADD45A, GADD45B, GADD45G, GNA12, GNG12, GRB2, HRAS, IKBKB, IKBKG, IL1A, IL1B, IL1R1, IL1R2, JUN, JUND, KRAS, LOC653852, MAP2K1, MAP2K1IP1, MAP2K2, MAP2K3, MAP2K4, MAP2K5, MAP2K6, MAP2K7, MAP3K1, MAP3K10, MAP3K12, MAP3K13, MAP3K14, MAP3K2, MAP3K3, MAP3K4, MAP3K5, MAP3K6, MAP3K7, MAP3K7IP1, MAP3K7IP2, MAP3K8, MAP4K1, MAP4K2, MAP4K3, MAP4K4, MAPK1, MAPK10, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPK7, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, MAPKAPK2, MAPKAPK3, MAPKAPK5, MAPT, MAX, MEF2C, MKNK1, MKNK2, MOS, MRAS, MYC, NF1, NFATC2, NFATC4, NFKB1, NFKB2, NGFB, NLK, NR4A1, NRAS, NTF3, NTF5, NTRK1, NTRK2, PAK1, PAK2, PDGFA, PDGFB, PDGFRA, PDGFRB, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PPM1A, PPM1B, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PPP5C, PRKACA, PRKACB, PRKACG, PRKCA, PRKCB1, PRKCG, PRKX, PRKY, PTPN5, PTPN7, PTPRR, RAC1, RAC2, RAC3, RAF1, RAP1A, RAP1B, RAPGEF2, RASA1, RASA2, RASGRF1, RASGRF2, RASGRP1, RASGRP2, RASGRP3, RASGRP4, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KA4, RPS6KA5, RPS6KA6, RRAS, RRAS2, SOS1, SOS2, SRF, STK3, STK4, STMN1, TAOK1, TAOK2, TAOK3, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TNF, TNFRSF1A, TP53, TRAF2, TRAF6, ZAK | 247 | AKT1(3), AKT2(2), ARRB1(1), BRAF(240), CACNA1A(2), CACNA1B(2), CACNA1C(1), CACNA1D(2), CACNA1E(5), CACNA1G(3), CACNA1S(1), CACNA2D1(2), CACNA2D3(1), CACNA2D4(2), CACNB3(1), CACNG7(1), CASP3(1), CDC42(1), DUSP5(1), DUSP7(1), ECSIT(1), FGF20(1), FGF5(1), FGF7(1), FGFR2(1), FLNA(1), FLNC(3), HRAS(14), IL1R1(2), JUN(1), KRAS(4), MAP2K6(1), MAP3K1(2), MAP3K3(3), MAP3K6(1), MAP4K4(1), MAPK10(1), MAPK8IP2(1), MAPKAPK3(1), MYC(1), NF1(2), NFATC4(3), NRAS(34), PDGFRB(1), PLA2G2A(1), PLA2G5(1), PPP3R2(1), PTPRR(1), RAP1A(1), RASA1(1), RASGRF2(2), RASGRP1(1), SOS1(1), TGFBR2(1), TP53(3) | 170374057 | 369 | 311 | 89 | 27 | 13 | 23 | 51 | 266 | 16 | 0 | 4.33e-15 | <1.00e-15 | <6.16e-14
2 | HSA04910_INSULIN_SIGNALING_PATHWAY | Genes involved in insulin signaling pathway | ACACA, ACACB, AKT1, AKT2, AKT3, ARAF, BAD, BRAF, CALM1, CALM2, CALM3, CALML3, CALML6, CBL, CBLB, CBLC, CRK, CRKL, EIF4EBP1, ELK1, EXOC7, FASN, FBP1, FBP2, FLOT1, FLOT2, FOXO1, FRAP1, G6PC, G6PC2, GCK, GRB2, GSK3B, GYS1, GYS2, HRAS, IKBKB, INPP5D, INS, INSR, IRS1, IRS2, IRS4, KIAA1303, KRAS, LIPE, MAP2K1, MAP2K2, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MKNK1, MKNK2, NRAS, PCK1, PCK2, PDE3A, PDE3B, PDPK1, PFKL, PFKM, PFKP, PHKA1, PHKA2, PHKB, PHKG1, PHKG2, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PKLR, PKM2, PPARGC1A, PPP1CA, PPP1CB, PPP1CC, PPP1R3A, PPP1R3B, PPP1R3C, PPP1R3D, PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKACA, PRKACB, PRKACG, PRKAG1, PRKAG2, PRKAG3, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, PRKCI, PRKCZ, PRKX, PRKY, PTPN1, PTPRF, PYGB, PYGL, PYGM, RAF1, RAPGEF1, RHEB, RHOQ, RPS6, RPS6KB1, RPS6KB2, SH2B2, SHC1, SHC2, SHC3, SHC4, SKIP, SLC2A4, SOCS1, SOCS2, SOCS3, SOCS4, SORBS1, SOS1, SOS2, SREBF1, TRIP10, TSC1, TSC2 | 131 | ACACA(1), ACACB(1), AKT1(3), AKT2(2), BRAF(240), EXOC7(1), FASN(1), FLOT1(1), FLOT2(1), GYS2(1), HRAS(14), INPP5D(1), IRS1(1), IRS2(1), KRAS(4), MAPK10(1), NRAS(34), PCK2(1), PDE3A(1), PFKP(2), PHKA2(2), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), PPARGC1A(1), PPP1R3B(1), PRKAG2(1), PRKAR2A(1), PYGB(1), RAPGEF1(2), RHOQ(2), RPS6KB2(1), SHC1(1), SOS1(1), SREBF1(1), TRIP10(1) | 95676922 | 337 | 303 | 57 | 19 | 11 | 10 | 46 | 262 | 8 | 0 | 2.11e-15 | <1.00e-15 | <6.16e-14
3 | HSA04650_NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY | Genes involved in natural killer cell mediated cytotoxicity | ARAF, BID, BRAF, CASP3, CD244, CD247, CD48, CHP, CSF2, FAS, FASLG, FCER1G, FCGR3A, FCGR3B, FYN, GRB2, GZMB, HCST, HLA-A, HLA-B, HLA-C, HLA-E, HLA-G, HRAS, ICAM1, ICAM2, IFNA1, IFNA10, IFNA13, IFNA14, IFNA16, IFNA17, IFNA2, IFNA21, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNAR1, IFNAR2, IFNB1, IFNG, IFNGR1, IFNGR2, ITGAL, ITGB2, KIR2DL1, KIR2DL2, KIR2DL3, KIR2DL4, KIR2DL5A, KIR2DS1, KIR2DS2, KIR3DL1, KIR3DL2, KLRC1, KLRC2, KLRC3, KLRD1, KLRK1, KRAS, LAT, LCK, LCP2, LOC652578, MAP2K1, MAP2K2, MAPK1, MAPK3, MICA, MICB, NCR1, NCR2, NCR3, NFAT5, NFATC1, NFATC2, NFATC3, NFATC4, NRAS, PAK1, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLCG1, PLCG2, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRF1, PRKCA, PRKCB1, PRKCG, PTK2B, PTPN11, PTPN6, RAC1, RAC2, RAC3, RAF1, SH2D1A, SH2D1B, SH3BP2, SHC1, SHC2, SHC3, SHC4, SOS1, SOS2, SYK, TNF, TNFRSF10A, TNFRSF10B, TNFRSF10C, TNFRSF10D, TNFSF10, TYROBP, ULBP1, ULBP2, ULBP3, VAV1, VAV2, VAV3, ZAP70 | 126 | BRAF(240), CASP3(1), HLA-E(1), HRAS(14), IFNAR2(1), IFNGR1(1), ITGAL(4), KIR2DL1(1), KIR3DL2(2), KRAS(4), LCK(1), NCR1(1), NFAT5(2), NFATC1(1), NFATC4(3), NRAS(34), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), PPP3R2(1), PTK2B(2), SHC1(1), SOS1(1), SYK(1), ULBP1(1) | 67770272 | 327 | 300 | 48 | 15 | 9 | 9 | 43 | 258 | 8 | 0 | <1.00e-15 | <1.00e-15 | <6.16e-14
4 | HSA04012_ERBB_SIGNALING_PATHWAY | Genes involved in ErbB signaling pathway | ABL1, ABL2, AKT1, AKT2, AKT3, ARAF, AREG, BAD, BRAF, BTC, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CBL, CBLB, CBLC, CDKN1A, CDKN1B, CRK, CRKL, EGF, EGFR, EIF4EBP1, ELK1, ERBB2, ERBB3, ERBB4, EREG, FRAP1, GAB1, GRB2, GSK3B, HBEGF, HRAS, JUN, KRAS, MAP2K1, MAP2K2, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK3, MAPK8, MAPK9, MYC, NCK1, NCK2, NRAS, NRG1, NRG2, NRG3, NRG4, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLCG1, PLCG2, PRKCA, PRKCB1, PRKCG, PTK2, RAF1, RPS6KB1, RPS6KB2, SHC1, SHC2, SHC3, SHC4, SOS1, SOS2, SRC, STAT5A, STAT5B, TGFA | 85 | ABL1(1), ABL2(1), AKT1(3), AKT2(2), BRAF(240), CAMK2A(1), CAMK2B(1), CDKN1A(1), ERBB2(1), ERBB3(1), ERBB4(2), HRAS(14), JUN(1), KRAS(4), MAPK10(1), MYC(1), NCK1(2), NRAS(34), NRG1(1), NRG2(1), PAK3(1), PAK7(2), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), RPS6KB2(1), SHC1(1), SOS1(1), SRC(1), STAT5B(1) | 61538338 | 330 | 298 | 50 | 9 | 8 | 8 | 46 | 258 | 9 | 1 | <1.00e-15 | <1.00e-15 | <6.16e-14
5 | ST_INTEGRIN_SIGNALING_PATHWAY | Integrins are transmembrane receptors that mediate cell growth, survival, and migration by binding to ligands in the extracellular matrix. | ABL1, ACK1, ACTN1, ACTR2, ACTR3, AKT1, AKT2, AKT3, ANGPTL2, ARHGEF6, ARHGEF7, BCAR1, BRAF, CAV1, CDC42, CDKN2A, CRK, CSE1L, DDEF1, DOCK1, EPHB2, FYN, GRAF, GRB2, GRB7, GRF2, GRLF1, ILK, ITGA1, ITGA10, ITGA11, ITGA2, ITGA3, ITGA4, ITGA5, ITGA6, ITGA7, ITGA8, ITGA9, ITGB3BP, MAP2K4, MAP2K7, MAP3K11, MAPK1, MAPK10, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, MRAS, MYLK, MYLK2, P4HB, PAK1, PAK2, PAK3, PAK4, PAK6, PAK7, PIK3CA, PIK3CB, PKLR, PLCG1, PLCG2, PTEN, PTK2, RAF1, RALA, RHO, ROCK1, ROCK2, SHC1, SOS1, SOS2, SRC, TERF2IP, TLN1, TLN2, VASP, WAS, ZYX | 78 | ABL1(1), AKT1(3), AKT2(2), ANGPTL2(1), ARHGEF6(1), ARHGEF7(1), BRAF(240), CDC42(1), GRB7(1), ITGA10(1), ITGA3(2), ITGA7(1), ITGA8(1), MAPK10(1), MAPK8IP2(1), MYLK(3), P4HB(1), PAK3(1), PAK7(2), PIK3CA(2), PIK3CB(1), PTEN(2), SHC1(1), SOS1(1), SRC(1), TLN2(2) | 72966816 | 275 | 251 | 40 | 13 | 8 | 9 | 3 | 248 | 6 | 1 | 2.26e-12 | <1.00e-15 | <6.16e-14
6 | 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 | AKT1(3), APC(2), BRAF(240), ITPR1(2), ITPR2(5), MAPK10(1), PHKA2(2), PIK3CA(2), PIK3CD(1), PIK3R1(1), PITX2(2), SRC(1) | 31888074 | 262 | 246 | 27 | 6 | 5 | 5 | 1 | 244 | 7 | 0 | 9.66e-15 | <1.00e-15 | <6.16e-14
7 | HSA04150_MTOR_SIGNALING_PATHWAY | Genes involved in mTOR signaling pathway | AKT1, AKT2, AKT3, BRAF, CAB39, DDIT4, EIF4B, EIF4EBP1, FIGF, FRAP1, GBL, HIF1A, IGF1, INS, KIAA1303, LYK5, MAPK1, MAPK3, PDPK1, PGF, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PRKAA1, PRKAA2, RHEB, RICTOR, RPS6, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KA6, RPS6KB1, RPS6KB2, STK11, TSC1, TSC2, ULK1, ULK2, ULK3, VEGFA, VEGFB, VEGFC | 44 | AKT1(3), AKT2(2), BRAF(240), FIGF(1), HIF1A(1), PIK3CA(2), PIK3CB(1), PIK3CD(1), PIK3CG(1), PIK3R1(1), PIK3R5(3), RPS6KB2(1), ULK3(1), VEGFA(1) | 31724050 | 259 | 242 | 24 | 4 | 3 | 4 | 5 | 240 | 7 | 0 | <1.00e-15 | <1.00e-15 | <6.16e-14
8 | ST_DIFFERENTIATION_PATHWAY_IN_PC12_CELLS | Rat-derived PC12 cells respond to nerve growth factor (NGF) and PACAP to differentiate into neuronal cells. | AKT1, ASAH1, ATF1, BRAF, CAMP, CREB1, CREB3, CREB5, CREBBP, CRKL, DAG1, EGR1, EGR2, EGR3, EGR4, ELK1, FRS2, GAS, GNAQ, GRF2, JUN, MAP1B, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK3, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, NTRK1, OPN1LW, PACAP, PIK3C2G, PIK3CA, PIK3CD, PIK3R1, PTPN11, RPS6KA3, SH2B, SHC1, SRC, TERF2IP, TH, TUBA3 | 42 | AKT1(3), BRAF(240), CREBBP(1), JUN(1), MAP1B(3), MAPK10(1), MAPK8IP2(1), PIK3C2G(1), PIK3CA(2), PIK3CD(1), PIK3R1(1), SHC1(1), SRC(1) | 30662299 | 257 | 242 | 22 | 5 | 4 | 6 | 1 | 240 | 6 | 0 | 2.00e-15 | <1.00e-15 | <6.16e-14
9 | ST_ERK1_ERK2_MAPK_PATHWAY | The Erk1 and Erk2 MAP kinase pathways are regulated by Raf, Mos, and Tpl-2. | ARAF1, ATF1, BAD, BRAF, COPEB, CREB1, CREB3, CREB5, DUSP4, DUSP6, DUSP9, EEF2K, EIF4E, GRB2, HTATIP, MAP2K1, MAP2K2, MAP3K8, MAPK1, MAPK3, MKNK1, MKNK2, MOS, NFKB1, RAP1A, RPS6KA1, RPS6KA2, RPS6KA3, SHC1, SOS1, SOS2, TRAF3 | 29 | BRAF(240), EEF2K(1), RAP1A(1), SHC1(1), SOS1(1) | 17612692 | 244 | 241 | 10 | 3 | 1 | 3 | 1 | 235 | 4 | 0 | 1.33e-15 | <1.00e-15 | <6.16e-14
10 | ST_G_ALPHA_S_PATHWAY | The G-alpha-s protein activates adenylyl cyclases, which catalyze cAMP formation. | ASAH1, BF, BFAR, BRAF, CAMP, CREB1, CREB3, CREB5, EPAC, GAS, GRF2, MAPK1, RAF1, SNX13, SRC, TERF2IP | 12 | BRAF(240), SNX13(1), SRC(1) | 6581484 | 242 | 240 | 8 | 2 | 0 | 1 | 1 | 235 | 5 | 0 | <1.00e-15 | <1.00e-15 | <6.16e-14

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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle