Mutation Analysis (MutSig v1.5)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1ZK5FND
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1ZK5FND
Overview
Introduction

This report serves to describe the mutational landscape and properties of a given individual set, as well as rank genes and genesets according to mutational significance. MutSig v1.5 was used to generate the results found in this report.

  • Working with individual set: CESC-TP

  • Number of patients in set: 194

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): 16

  • Mutations seen in COSMIC: 191

  • Significantly mutated genes in COSMIC territory: 10

  • Significantly mutated genesets: 32

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

Mutation Preprocessing

  • Read 194 MAFs of type "WashU"

  • Total number of mutations in input MAFs: 46547

  • After removing 120 mutations outside chr1-24: 46427

  • After removing 302 blacklisted mutations: 46125

  • After removing 6065 noncoding mutations: 40060

  • After collapsing adjacent/redundant mutations: 39450

Mutation Filtering

  • Number of mutations before filtering: 39450

  • After removing 2753 mutations outside gene set: 36697

  • After removing 56 mutations outside category set: 36641

  • After removing 6 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 33826

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 168
Frame_Shift_Ins 210
In_Frame_Del 38
In_Frame_Ins 27
Missense_Mutation 24321
Nonsense_Mutation 2403
Nonstop_Mutation 77
Silent 8898
Splice_Site 499
Total 36641
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) 15413 783553866 2e-05 20 4.2 3
Tp*C->A 1244 783553866 1.6e-06 1.6 0.34 4
(A/C/G)p*C->mut 5701 2209833766 2.6e-06 2.6 0.55 3.2
A->mut 1959 2900241563 6.8e-07 0.68 0.14 3.9
indel+null 3373 5893629195 5.7e-07 0.57 0.12 NaN
double_null 49 5893629195 8.3e-09 0.0083 0.0018 NaN
Total 27739 5893629195 4.7e-06 4.7 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: Tp*C->A

  • n3 = number of nonsilent mutations of type: (A/C/G)p*C->mut

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

  • p = p-value (overall)

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

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 16. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).

rank gene description N n npat nsite nsil n1 n2 n3 n4 n5 n6 p_ns_s p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 636279 58 53 19 0 45 1 5 7 0 0 0.000014 <1.00e-15 <1.83e-11
2 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 239894 17 15 15 0 6 0 0 0 11 0 0.09 5.66e-15 4.28e-11
3 HLA-A major histocompatibility complex, class I, A 155775 17 16 14 1 2 0 1 1 13 0 0.068 7.11e-15 4.28e-11
4 FBXW7 F-box and WD repeat domain containing 7 495633 20 19 14 1 8 0 7 0 5 0 0.067 9.33e-15 4.28e-11
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 136796 11 11 5 0 0 0 10 1 0 0 0.15 1.32e-14 4.85e-11
6 HLA-B major histocompatibility complex, class I, B 171702 11 11 8 0 0 0 2 1 7 1 0.053 8.35e-12 2.55e-08
7 EP300 E1A binding protein p300 1421010 23 21 19 1 9 2 2 0 7 3 0.042 3.20e-11 8.37e-08
8 MUC4 mucin 4, cell surface associated 656842 86 37 84 12 56 2 12 4 10 2 0.000014 1.63e-10 3.73e-07
9 MAPK1 mitogen-activated protein kinase 1 192420 9 9 3 0 9 0 0 0 0 0 0.067 5.94e-09 1.21e-05
10 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 350802 16 12 14 1 11 2 0 1 2 0 0.27 1.34e-08 2.46e-05
11 CASP8 caspase 8, apoptosis-related cysteine peptidase 339514 9 9 8 1 1 0 1 2 5 0 0.34 6.26e-07 0.00104
12 ARID1A AT rich interactive domain 1A (SWI-like) 1119004 14 14 14 1 4 0 1 0 6 3 0.24 2.81e-06 0.00429
13 RB1 retinoblastoma 1 (including osteosarcoma) 528233 9 9 9 1 1 2 1 0 4 1 0.6 4.98e-06 0.00702
14 ZNF720 zinc finger protein 720 71175 4 4 4 0 0 1 0 1 2 0 0.33 9.76e-06 0.0128
15 HIST1H4E histone cluster 1, H4e 61304 4 4 4 0 3 0 1 0 0 0 0.21 4.61e-05 0.0564
16 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 84142 4 4 4 0 3 0 0 1 0 0 0.31 7.59e-05 0.0870
17 SMAD4 SMAD family member 4 330304 7 7 7 0 2 0 3 0 2 0 0.29 0.000106 0.115
18 LIN9 lin-9 homolog (C. elegans) 336749 7 7 6 0 4 0 1 0 2 0 0.27 0.000121 0.122
19 WIZ widely interspaced zinc finger motifs 356294 14 14 14 3 9 0 5 0 0 0 0.29 0.000127 0.122
20 RAB35 RAB35, member RAS oncogene family 111356 4 4 4 0 0 0 1 0 3 0 0.41 0.000151 0.138
21 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 825967 12 11 9 1 5 1 4 2 0 0 0.14 0.000163 0.140
22 ABCD1 ATP-binding cassette, sub-family D (ALD), member 1 347687 7 7 6 1 2 0 3 2 0 0 0.3 0.000168 0.140
23 CACNB4 calcium channel, voltage-dependent, beta 4 subunit 314648 7 7 7 1 2 0 3 1 1 0 0.52 0.000182 0.145
24 HLA-C major histocompatibility complex, class I, C 180752 5 5 5 1 2 0 1 0 1 1 0.58 0.000190 0.145
25 COL19A1 collagen, type XIX, alpha 1 695739 9 9 9 1 4 1 2 1 1 0 0.54 0.000231 0.169
26 PTPRC protein tyrosine phosphatase, receptor type, C 763686 10 10 10 0 4 1 0 1 4 0 0.15 0.000247 0.174
27 HSD17B4 hydroxysteroid (17-beta) dehydrogenase 4 445249 10 9 10 0 6 0 1 2 1 0 0.1 0.000267 0.181
28 USP17L2 ubiquitin specific peptidase 17-like 2 94562 5 4 5 0 3 0 0 1 1 0 0.24 0.000284 0.186
29 DMD dystrophin (muscular dystrophy, Duchenne and Becker types) 2244529 23 20 23 1 10 1 7 2 3 0 0.03 0.000375 0.237
30 MED1 mediator complex subunit 1 933799 14 11 14 0 7 1 2 0 4 0 0.079 0.000394 0.241
31 SLC25A5 solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 5 176461 5 4 4 0 0 0 0 4 1 0 0.27 0.000452 0.253
32 TOMM7 translocase of outer mitochondrial membrane 7 homolog (yeast) 34920 2 2 1 0 0 0 0 0 2 0 1 0.000464 0.253
33 SLC27A5 solute carrier family 27 (fatty acid transporter), member 5 321240 7 7 7 0 2 0 4 0 1 0 0.069 0.000470 0.253
34 ARPP21 cAMP-regulated phosphoprotein, 21kDa 482506 9 8 9 0 1 1 5 1 1 0 0.13 0.000471 0.253
35 PSMB8 proteasome (prosome, macropain) subunit, beta type, 8 (large multifunctional peptidase 7) 91414 4 4 4 0 1 0 3 0 0 0 0.32 0.000482 0.253
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 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 58 220 52 42680 24079 0 0
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 11 52 11 10088 106540 0 0
3 FBXW7 F-box and WD repeat domain containing 7 20 91 14 17654 534 0 0
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 17 767 16 148798 773 0 0
5 TP53 tumor protein p53 12 356 10 69064 707 2.5e-12 2.3e-09
6 ERBB3 v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) 12 6 4 1164 4 3.7e-11 2.8e-08
7 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 11 42 5 8148 11 6.7e-10 4.3e-07
8 RB1 retinoblastoma 1 (including osteosarcoma) 9 267 5 51798 12 5.9e-06 0.0033
9 STK11 serine/threonine kinase 11 8 130 4 25220 7 7.5e-06 0.0038
10 MTOR mechanistic target of rapamycin (serine/threonine kinase) 12 10 2 1940 2 0.000041 0.019

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: 32. 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 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 16 AKT1(3), ITGB1(2), MAPK1(9), MAPK3(1), PDK2(1), PDPK1(2), PIK3CA(58), PIK3R1(10), PTEN(17), PTK2(2), SOS1(5) 5594594 110 76 62 6 73 5 10 9 13 0 2e-06 <1.00e-15 <3.93e-13
2 SA_PTEN_PATHWAY PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. AKT1, AKT2, AKT3, BPNT1, GRB2, ILK, MAPK1, MAPK3, PDK1, PIK3CA, PIK3CD, PIP3-E, PTEN, PTK2B, RBL2, SHC1, SOS1 16 AKT1(3), AKT2(1), AKT3(3), MAPK1(9), MAPK3(1), PDK1(3), PIK3CA(58), PIK3CD(1), PTEN(17), PTK2B(3), RBL2(2), SOS1(5) 5880977 106 74 58 6 74 2 8 8 14 0 4.3e-07 1.78e-15 3.93e-13
3 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 AKT1(3), BAD(2), CHRNB1(1), CHRNG(1), MUSK(3), PIK3CA(58), PIK3R1(10), PTK2(2), PTK2B(3), RAPSN(1), TERT(1) 4886895 85 69 45 5 55 3 11 10 6 0 7.8e-07 2.66e-15 3.93e-13
4 HCMVPATHWAY Cytomegalovirus activates MAP kinase pathways in the host cell, inducing transcription of viral genes. AKT1, CREB1, MAP2K1, MAP2K2, MAP2K3, MAP2K6, MAP3K1, MAPK1, MAPK14, MAPK3, NFKB1, PIK3CA, PIK3R1, RB1, RELA, SP1 16 AKT1(3), CREB1(2), MAP2K1(2), MAP2K3(2), MAP3K1(4), MAPK1(9), MAPK3(1), NFKB1(2), PIK3CA(58), PIK3R1(10), RB1(9), RELA(7), SP1(3) 5748570 112 75 66 7 76 5 13 10 7 1 3.1e-06 3.22e-15 3.93e-13
5 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 20 B2M(3), HLA-A(17), ITGB1(2), KLRC4(1), KLRD1(2), LAT(1), MAP2K1(2), MAPK3(1), PAK1(1), PIK3CA(58), PIK3R1(10), PTK2B(3), RAC1(1), SYK(1), VAV1(2) 5484583 105 78 63 7 60 2 13 10 20 0 4.4e-06 4.66e-15 3.93e-13
6 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 AKT1(3), CREB1(2), HRAS(1), MAPK1(9), MAPK3(1), MAPK7(2), MEF2A(1), MEF2B(1), MEF2C(1), MEF2D(3), PIK3CA(58), PIK3R1(10), PLCG1(3), RPS6KA1(1) 5735427 96 73 50 5 67 4 12 9 4 0 1.7e-07 4.66e-15 3.93e-13
7 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 CD3D(2), HLA-DRA(1), HLA-DRB1(1), ITK(1), PIK3CA(58), PIK3R1(10) 3581149 73 60 34 1 51 4 8 8 2 0 1.3e-07 5.00e-15 3.93e-13
8 CDC42RACPATHWAY PI3 kinase stimulates cell migration by activating cdc42, which activates ARP2/3, which in turn promotes formation of new actin fibers. ACTR2, ACTR3, ARHA, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, CDC42, PAK1, PDGFRA, PIK3CA, PIK3R1, RAC1, WASL 14 ACTR2(1), ARPC1A(2), ARPC2(3), CDC42(1), PAK1(1), PDGFRA(2), PIK3CA(58), PIK3R1(10), RAC1(1), WASL(4) 3919913 83 66 44 4 58 2 9 9 5 0 0.000011 5.11e-15 3.93e-13
9 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 AKT1(3), PIK3CA(58), PIK3R1(10), PLCB1(10), PLCG1(3), PRKCA(3), VAV1(2) 3764925 89 70 49 5 65 2 9 9 4 0 3.8e-06 6.88e-15 4.71e-13
10 AKTPATHWAY Second messenger PIP3 promotes cell survival by activating the anti-apoptotic kinase AKT. AKT1, BAD, CASP9, CHUK, FOXO1A, FOXO3A, GH1, GHR, HSPCA, MLLT7, NFKB1, NFKBIA, PDPK1, PIK3CA, PIK3R1, PPP2CA, RELA, TNFSF6, YWHAH 14 AKT1(3), BAD(2), CASP9(1), CHUK(2), GHR(6), NFKB1(2), NFKBIA(2), PDPK1(2), PIK3CA(58), PIK3R1(10), RELA(7) 4124019 95 71 55 7 64 4 11 10 6 0 0.000065 9.66e-15 5.95e-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 PEPIPATHWAY Proepithelin (PEPI) induces epithelial cells to secrete IL-8, which promotes elastase secretion by neutrophils. ELA1, ELA2, ELA2A, ELA2B, ELA3B, GRN, IL8, SLPI 3 GRN(3), IL8(2) 496037 5 5 5 0 1 1 2 0 1 0 0.35 0.013 1
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), GNAS(6), GNB1(1), GNGT1(1), PRKACA(2) 1769339 14 14 14 1 7 1 4 1 1 0 0.076 0.051 1
3 TCRAPATHWAY The kinases Lck and Fyn phosphorylate and activate the T cell receptor, which recognizes antigen-bound MHCII and leads to T cell activation. CD3D, CD3E, CD3G, CD3Z, CD4, FYN, HLA-DRA, HLA-DRB1, LCK, PTPRC, TRA@, TRB@, ZAP70 10 CD3D(2), CD4(1), FYN(3), HLA-DRA(1), HLA-DRB1(1), PTPRC(10), ZAP70(2) 2462474 20 19 20 3 9 3 3 1 4 0 0.17 0.062 1
4 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 7 CHRM1(1), GNAQ(2), GNB1(1), GNGT1(1), HTR2C(2), PLCB1(10), TUB(3) 2066687 20 18 20 3 11 1 3 4 1 0 0.14 0.066 1
5 TERCPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. NFYA, NFYB, NFYC, RB1, SP1, SP3 5 NFYA(3), NFYB(1), NFYC(1), SP1(3), SP3(2) 1417365 10 10 10 0 8 0 2 0 0 0 0.076 0.07 1
6 HSA00643_STYRENE_DEGRADATION Genes involved in styrene degradation FAH, GSTZ1, HGD 3 FAH(3), GSTZ1(1), HGD(2) 656562 6 6 6 0 5 0 0 1 0 0 0.14 0.078 1
7 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNG(1), IFNGR1(6), IFNGR2(3), JAK1(1), JAK2(6), STAT1(2) 2394449 19 18 18 3 9 2 0 0 7 1 0.32 0.085 1
8 STEROID_BIOSYNTHESIS CYP17A1, F13B, HSD17B1, HSD17B2, HSD17B3, HSD17B4, HSD17B7, HSD3B1, HSD3B2 9 CYP17A1(2), F13B(2), HSD17B4(10), HSD17B7(2), HSD3B1(2), HSD3B2(1) 2356166 19 14 19 2 10 0 4 3 2 0 0.074 0.11 1
9 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 ACAA2(1), HADH(1), HSD17B10(1), HSD17B4(10), MECR(1), PPT1(1), PPT2(1) 2402078 16 13 16 1 7 2 3 2 2 0 0.062 0.12 1
10 IL17PATHWAY Activated T cells secrete IL-17, which stimulates fibroblasts and other cells to secrete inflammatory and hematopoietic cytokines. CD2, CD34, CD3D, CD3E, CD3G, CD3Z, CD4, CD58, CD8A, CSF3, IL17, IL3, IL6, IL8, KITLG, TRA@, TRB@ 13 CD34(2), CD3D(2), CD4(1), CD58(2), CD8A(2), IL6(1), IL8(2), KITLG(1) 1811898 13 10 13 2 5 2 3 0 3 0 0.32 0.16 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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