Mutation Analysis (MutSig v2.0)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C11C1VG5
Maintained by Dan DiCara (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/C11C1VG5
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: CESC-TP

  • Number of patients in set: 39

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:CESC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 10

  • Mutations seen in COSMIC: 35

  • Significantly mutated genes in COSMIC territory: 1

  • Significantly mutated genesets: 0

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

Mutation Preprocessing

  • Read 39 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 10020

  • After removing 5 mutations outside chr1-24: 10015

  • After removing 474 blacklisted mutations: 9541

  • After removing 599 noncoding mutations: 8942

Mutation Filtering

  • Number of mutations before filtering: 8942

  • After removing 116 mutations outside gene set: 8826

  • After removing 17 mutations outside category set: 8809

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 98
Frame_Shift_Ins 62
In_Frame_Del 39
In_Frame_Ins 13
Missense_Mutation 5527
Nonsense_Mutation 473
Nonstop_Mutation 11
Silent 2482
Splice_Site 91
Translation_Start_Site 13
Total 8809
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
Tp*C->(T/G) 3530 150569812 0.000023 23 4.2 3
(A/C/G)p*C->(T/G) 1102 425623126 2.6e-06 2.6 0.46 2.7
C->A 346 576192938 6e-07 0.6 0.11 4.4
A->mut 562 556925266 1e-06 1 0.18 3.9
indel+null 771 1133118204 6.8e-07 0.68 0.12 NaN
double_null 16 1133118204 1.4e-08 0.014 0.0025 NaN
Total 6327 1133118204 5.6e-06 5.6 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). 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: CESC-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: Tp*C->(T/G)

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

  • n3 = number of nonsilent mutations of type: C->A

  • n4 = number of nonsilent mutations of type: A->mut

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

  • n6 = number of nonsilent mutations of type: double_null

  • p_classic = p-value for the observed amount of nonsilent mutations being elevated in this gene

  • p_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene

  • p_cons = p-value for enrichment of mutations at evolutionarily most-conserved sites in gene

  • p_joint = p-value for clustering + conservation

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 10. 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 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 126650 11 9 4 0 10 0 0 1 0 0 3e-08 0.12 8e-06 0.017 0 <1.00e-15 <6.01e-12
2 PRSS48 protease, serine, 48 38982 15 2 8 3 0 2 2 9 2 0 0.0065 0.36 0 0.96 0 <1.00e-15 <6.01e-12
3 UGT2B10 UDP glucuronosyltransferase 2 family, polypeptide B10 122318 19 2 13 3 2 3 1 13 0 0 0.066 0.25 0 0.99 0 <1.00e-15 <6.01e-12
4 TMCC1 transmembrane and coiled-coil domain family 1 77000 4 4 3 0 0 0 1 0 3 0 0.0001 0.82 0.00013 0.086 9e-05 1.83e-07 0.000825
5 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 69545 7 6 6 0 4 0 0 1 2 0 2.4e-06 0.34 0.49 0.041 0.16 5.97e-06 0.0215
6 MAPK1 mitogen-activated protein kinase 1 38660 3 3 1 0 3 0 0 0 0 0 0.001 0.41 0.00032 0.19 0.00065 1.03e-05 0.0309
7 PTH2 parathyroid hormone 2 8040 2 2 2 0 1 0 1 0 0 0 0.000047 0.38 0.7 0.048 0.028 1.90e-05 0.0488
8 UGT3A2 UDP glycosyltransferase 3 family, polypeptide A2 62290 3 3 2 0 1 0 0 0 2 0 0.0029 0.69 0.016 0.0019 0.00059 2.46e-05 0.0554
9 PRB2 proline-rich protein BstNI subfamily 2 49240 5 4 4 0 0 0 0 1 4 0 9e-06 0.52 0.29 0.28 0.33 4.01e-05 0.0803
10 SSX7 synovial sarcoma, X breakpoint 7 23049 5 3 4 0 0 2 1 2 0 0 0.000066 0.34 0.043 1 0.058 5.17e-05 0.0932
11 RAET1L retinoic acid early transcript 1L 25451 5 2 4 0 1 1 0 3 0 0 0.0046 0.28 0.00047 0.45 0.0021 0.000123 0.201
12 OR10G8 olfactory receptor, family 10, subfamily G, member 8 36617 16 2 10 13 0 10 0 5 1 0 1 0.98 2.4e-06 1 0.000017 0.000206 0.309
13 ARID1A AT rich interactive domain 1A (SWI-like) 226053 7 6 6 0 1 1 0 0 3 2 2e-05 0.29 0.77 0.5 1 0.000237 0.329
14 ITGAX integrin, alpha X (complement component 3 receptor 4 subunit) 131027 8 4 6 6 2 2 0 3 1 0 0.19 0.96 0.000038 0.52 0.00012 0.000264 0.341
15 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 45935 3 3 3 0 0 0 0 0 3 0 0.000072 0.59 0.28 0.82 0.39 0.000325 0.390
16 FCRL1 Fc receptor-like 1 53853 3 3 3 0 1 0 0 2 0 0 0.00035 0.45 0.033 0.67 0.092 0.000362 0.400
17 HSD17B4 hydroxysteroid (17-beta) dehydrogenase 4 87517 4 4 4 1 1 2 0 0 1 0 0.00017 0.73 0.54 0.058 0.2 0.000377 0.400
18 PLAC4 placenta-specific 4 7160 2 2 1 0 0 0 0 0 2 0 0.00058 1 0.021 0.31 0.083 0.000525 0.505
19 FAM49A family with sequence similarity 49, member A 39076 2 2 2 0 0 1 0 1 0 0 0.0019 0.61 0.015 0.54 0.026 0.000532 0.505
20 PRG4 proteoglycan 4 166081 8 5 7 0 2 1 1 0 4 0 0.00032 0.46 0.082 0.69 0.17 0.000580 0.518
21 TIE1 tyrosine kinase with immunoglobulin-like and EGF-like domains 1 125328 4 3 4 0 0 2 1 0 1 0 0.0037 0.29 0.066 0.03 0.016 0.000624 0.518
22 ZNF645 zinc finger protein 645 49998 2 2 1 0 0 2 0 0 0 0 0.004 0.65 0.013 0.063 0.015 0.000633 0.518
23 USP26 ubiquitin specific peptidase 26 107055 2 2 2 0 1 0 0 0 1 0 0.024 0.7 0.045 0.0051 0.0026 0.000661 0.518
24 LYZL1 lysozyme-like 1 22057 3 3 3 0 1 1 0 0 1 0 0.00012 0.36 0.68 0.4 0.57 0.000736 0.553
25 CPNE3 copine III 64568 3 2 3 0 2 0 0 0 1 0 0.04 0.51 0.00072 0.97 0.0019 0.000793 0.561
26 GPR153 G protein-coupled receptor 153 40937 2 2 2 0 0 1 0 1 0 0 0.002 0.59 0.21 0.084 0.043 0.000875 0.561
27 FETUB fetuin B 45815 2 2 2 0 1 0 0 1 0 0 0.01 0.6 0.088 0.024 0.0085 0.000881 0.561
28 SSX3 synovial sarcoma, X breakpoint 3 25038 6 2 4 1 0 6 0 0 0 0 0.005 0.51 0.017 0.24 0.018 0.000899 0.561
29 ERP27 endoplasmic reticulum protein 27 kDa 32955 3 3 3 0 0 2 0 1 0 0 0.00018 0.46 0.28 0.64 0.48 0.000902 0.561
30 ZNF43 zinc finger protein 43 95053 4 4 4 0 1 0 1 1 1 0 0.00014 0.58 0.43 0.72 0.67 0.000948 0.570
31 OR5H6 olfactory receptor, family 5, subfamily H, member 6 38003 3 3 3 0 1 0 0 1 1 0 0.00016 0.39 0.77 0.64 0.75 0.00119 0.692
32 SVIP small VCP/p97-interacting protein 7674 1 1 1 0 0 0 0 0 1 0 0.0013 0.91 NaN NaN NaN 0.00126 0.707
33 TMEM51 transmembrane protein 51 29872 3 3 3 0 1 1 0 1 0 0 0.0003 0.4 0.27 0.85 0.47 0.00137 0.749
34 DNAJB1 DnaJ (Hsp40) homolog, subfamily B, member 1 39158 5 3 5 0 3 0 1 0 1 0 0.00037 0.21 0.43 0.15 0.4 0.00145 0.757
35 MAGEC1 melanoma antigen family C, 1 133929 7 5 6 0 2 0 0 2 3 0 0.00086 0.28 0.12 0.98 0.18 0.00147 0.757
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

PRSS48

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PRSS48 significant gene.

UGT2B10

Figure S3.  This figure depicts the distribution of mutations and mutation types across the UGT2B10 significant gene.

TMCC1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TMCC1 significant gene.

NFE2L2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

MAPK1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the MAPK1 significant gene.

UGT3A2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the UGT3A2 significant gene.

SSX7

Figure S8.  This figure depicts the distribution of mutations and mutation types across the SSX7 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: 1. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 11 220 8 8580 3939 0 0
2 ATL2 atlastin GTPase 2 1 1 1 39 1 0.00022 0.16
3 EDA ectodysplasin A 1 1 1 39 1 0.00022 0.16
4 KIAA1024 KIAA1024 2 1 1 39 1 0.00022 0.16
5 MAPK11 mitogen-activated protein kinase 11 1 1 1 39 1 0.00022 0.16
6 SUV39H2 suppressor of variegation 3-9 homolog 2 (Drosophila) 1 1 1 39 2 0.00022 0.16
7 ALS2 amyotrophic lateral sclerosis 2 (juvenile) 2 3 1 117 1 0.00065 0.22
8 EPHA10 EPH receptor A10 1 3 1 117 1 0.00065 0.22
9 IFITM3 interferon induced transmembrane protein 3 (1-8U) 5 3 1 117 1 0.00065 0.22
10 ITIH5L inter-alpha (globulin) inhibitor H5-like 1 3 1 117 1 0.00065 0.22

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: 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 PAR1PATHWAY Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. ADCY1, ARHA, ARHGEF1, F2, F2R, F2RL3, GNA12, GNA13, GNAI1, GNAQ, GNB1, GNGT1, MAP3K7, PIK3CA, PIK3R1, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2B, ROCK1 19 ADCY1(1), ARHGEF1(1), F2R(1), F2RL3(2), GNA13(1), PIK3CA(11), PIK3R1(1), PPP1R12B(1), PRKCA(1), ROCK1(3) 1478575 23 13 16 1 16 3 1 2 0 1 0.011 0.00041 0.12
2 ACHPATHWAY Nicotinic acetylcholine receptors are ligand-gated ion channels that primarily mediate neuromuscular signaling and may inhibit neuronal apoptosis via the AKT pathway. AKT1, BAD, CHRNB1, CHRNG, FOXO3A, MUSK, PIK3CA, PIK3R1, PTK2, PTK2B, RAPSN, SRC, TERT, TNFSF6, YWHAH 13 CHRNG(1), MUSK(1), PIK3CA(11), PIK3R1(1), PTK2(1) 935251 15 11 8 1 11 0 1 2 1 0 0.053 0.00044 0.12
3 ERK5PATHWAY Signaling between a tissue and its innervating axon stimulates retrograde transport via Trk receptors, which activate Erk5, which induces transcription of anti-apoptotic factors. AKT1, CREB1, GRB2, HRAS, MAPK1, MAPK3, MAPK7, MEF2A, MEF2B, MEF2C, MEF2D, NTRK1, PIK3CA, PIK3R1, PLCG1, RPS6KA1, SHC1 17 MAPK1(3), MAPK7(1), MEF2C(1), PIK3CA(11), PIK3R1(1), RPS6KA1(2) 1088110 19 11 10 1 14 1 0 3 1 0 0.03 0.00069 0.12
4 GCRPATHWAY Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. ADRB2, AKT1, ANXA1, CALM1, CALM2, CALM3, CRN, GNAS, GNB1, GNGT1, HSPCA, NFKB1, NOS3, NPPA, NR3C1, PIK3CA, PIK3R1, RELA, SYT1 17 CALM1(1), CALM3(1), NPPA(1), PIK3CA(11), PIK3R1(1), SYT1(1) 1019231 16 11 9 0 12 1 1 2 0 0 0.018 0.00078 0.12
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 16 MAPK1(3), PIK3CA(11), PIK3R1(1), PTEN(3), PTK2(1), SOS1(1) 1108069 20 11 11 0 15 0 0 2 3 0 0.0079 0.0014 0.15
6 CTLA4PATHWAY T cell activation requires interaction with an antigen-MHC-I complex on an antigen-presenting cell (APC), as well as CD28 interaction with the APC's CD80 or 86. CD28, CD3D, CD3E, CD3G, CD3Z, CD80, CD86, CTLA4, GRB2, HLA-DRA, HLA-DRB1, ICOS, ICOSL, IL2, ITK, LCK, PIK3CA, PIK3R1, PTPN11, TRA@, TRB@ 17 CD86(1), ITK(1), PIK3CA(11), PIK3R1(1), PTPN11(1) 739491 15 9 8 0 12 1 0 2 0 0 0.018 0.0014 0.15
7 ST_TYPE_I_INTERFERON_PATHWAY Type I interferon is an antiviral cytokine that induces a JAK-STAT type pathway leading to ISGF3 activation and a cellular antiviral response. IFNAR1, IFNB1, ISGF3G, JAK1, PTPRU, REG1A, STAT1, STAT2, TYK2 8 IFNAR1(2), PTPRU(1), REG1A(1), STAT1(3), TYK2(3) 723179 10 10 10 1 7 3 0 0 0 0 0.12 0.0018 0.16
8 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNGR1(2), IFNGR2(2), JAK2(1), STAT1(3) 473117 8 7 8 1 4 1 0 0 3 0 0.48 0.0021 0.16
9 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(1), PIK3CA(11), PIK3R1(1), POLR1A(2), POLR1C(2), TP53(2) 1168503 19 14 12 2 13 0 0 4 2 0 0.13 0.0027 0.18
10 PLCPATHWAY Phospholipase C hydrolyzes the membrane lipid PIP2 to DAG, which activates protein kinase C, and IP3, which causes calcium influx. AKT1, PIK3CA, PIK3R1, PLCB1, PLCG1, PRKCA, PRKCB1, VAV1 7 PIK3CA(11), PIK3R1(1), PRKCA(1) 739813 13 9 6 1 11 0 0 2 0 0 0.13 0.0029 0.18

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 ST_TYPE_I_INTERFERON_PATHWAY Type I interferon is an antiviral cytokine that induces a JAK-STAT type pathway leading to ISGF3 activation and a cellular antiviral response. IFNAR1, IFNB1, ISGF3G, JAK1, PTPRU, REG1A, STAT1, STAT2, TYK2 8 IFNAR1(2), PTPRU(1), REG1A(1), STAT1(3), TYK2(3) 723179 10 10 10 1 7 3 0 0 0 0 0.12 0.0018 0.64
2 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNGR1(2), IFNGR2(2), JAK2(1), STAT1(3) 473117 8 7 8 1 4 1 0 0 3 0 0.48 0.0021 0.64
3 IFNAPATHWAY Interferon alpha, active in the immune response, binds to the IFN receptor and activates Jak1 and Tyk2, which phosphorylate Stat1 and Stat2. IFNA1, IFNAR1, IFNAR2, IFNB1, ISGF3G, JAK1, STAT1, STAT2, TYK2 8 IFNA1(1), IFNAR1(2), IFNAR2(1), STAT1(3), TYK2(3) 627650 10 9 10 1 9 1 0 0 0 0 0.14 0.01 1
4 HSA00062_FATTY_ACID_ELONGATION_IN_MITOCHONDRIA Genes involved in fatty acid elongation in mitochondria ACAA2, ECHS1, HADH, HADHA, HADHB, HSD17B10, HSD17B4, MECR, PPT1, PPT2 10 HADH(2), HSD17B4(4) 492055 6 6 6 1 3 2 0 0 1 0 0.45 0.014 1
5 FIBRINOLYSISPATHWAY Thrombin cleavage of fibrinogen results in rapid formation of fibrin threads that form a mesh to capture platelets and other blood cells into a clot. CPB2, F13A1, F2, F2R, FGA, FGB, FGG, PLAT, PLAU, PLG, SERPINB2, SERPINE1 12 CPB2(2), F2R(1), FGA(1), PLAU(1), PLG(2) 774038 7 7 7 1 3 1 1 2 0 0 0.43 0.017 1
6 ST_INTERFERON_GAMMA_PATHWAY The interferon gamma pathway resembles the JAK-STAT pathway and activates STAT transcription factors. CISH, IFNG, IFNGR1, JAK1, JAK2, PLA2G2A, PTPRU, REG1A, STAT1, STATIP1 9 IFNGR1(2), JAK2(1), PTPRU(1), REG1A(1), STAT1(3) 661911 8 7 8 1 4 3 0 0 1 0 0.27 0.018 1
7 STEROID_BIOSYNTHESIS CYP17A1, F13B, HSD17B1, HSD17B2, HSD17B3, HSD17B4, HSD17B7, HSD3B1, HSD3B2 9 F13B(1), HSD17B4(4), HSD3B1(1) 465186 6 5 6 1 3 2 0 0 1 0 0.43 0.021 1
8 NKTPATHWAY T cell differentiation into Th1 and Th2 cells occurs by differential chemokine receptor expression, which mediates tissue localization and immune response. CCL3, CCL4, CCR1, CCR2, CCR3, CCR4, CCR5, CCR7, CD28, CD4, CSF2, CXCR3, CXCR4, IFNG, IFNGR1, IFNGR2, IL12A, IL12B, IL12RB1, IL12RB2, IL18R1, IL2, IL4, IL4R, IL5, TGFB1, TGFB2, TGFB3, TNFSF5 28 CCL4(1), CCR7(1), IFNGR1(2), IFNGR2(2), IL12B(1), IL12RB1(1), TGFB3(2) 1166496 10 9 10 1 5 0 1 0 4 0 0.2 0.026 1
9 HSA00130_UBIQUINONE_BIOSYNTHESIS Genes involved in ubiquinone biosynthesis COQ2, COQ3, COQ5, COQ6, COQ7, ND1, ND2, ND3, ND4, ND4L, ND5, ND6, NDUFA12, NDUFA13, NDUFB11 8 COQ3(1), COQ5(1), COQ6(1) 232317 3 3 3 0 2 1 0 0 0 0 0.44 0.034 1
10 PAR1PATHWAY Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. ADCY1, ARHA, ARHGEF1, F2, F2R, F2RL3, GNA12, GNA13, GNAI1, GNAQ, GNB1, GNGT1, MAP3K7, PIK3CA, PIK3R1, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2B, ROCK1 18 ADCY1(1), ARHGEF1(1), F2R(1), F2RL3(2), GNA13(1), PIK3R1(1), PPP1R12B(1), PRKCA(1), ROCK1(3) 1351925 12 9 12 1 6 3 1 1 0 1 0.13 0.035 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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