Mutation Analysis (MutSig v2.0)
Brain Lower Grade Glioma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
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/C1KK999C
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: LGG-TP

  • Number of patients in set: 289

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:LGG-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 33

  • Mutations seen in COSMIC: 523

  • Significantly mutated genes in COSMIC territory: 20

  • Significantly mutated genesets: 111

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

Mutation Preprocessing
  • Read 289 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 14817

  • After removing 154 mutations outside chr1-24: 14663

  • After removing 1469 blacklisted mutations: 13194

  • After removing 292 noncoding mutations: 12902

Mutation Filtering
  • Number of mutations before filtering: 12902

  • After removing 570 mutations outside gene set: 12332

  • After removing 35 mutations outside category set: 12297

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 11690

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 620
Frame_Shift_Ins 160
In_Frame_Del 311
In_Frame_Ins 17
Missense_Mutation 7404
Nonsense_Mutation 452
Nonstop_Mutation 5
Silent 2858
Splice_Site 470
Total 12297
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 2762 475452123 5.8e-06 5.8 5.2 2.1
*Np(A/C/T)->transit 2277 6731239535 3.4e-07 0.34 0.31 2
*ApG->G 244 1305739676 1.9e-07 0.19 0.17 2.1
transver 2121 8512431334 2.5e-07 0.25 0.22 5
indel+null 2006 8512431334 2.4e-07 0.24 0.21 NaN
double_null 28 8512431334 3.3e-09 0.0033 0.003 NaN
Total 9438 8512431334 1.1e-06 1.1 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: LGG-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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->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_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: 33. 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 947321 28 25 16 0 0 13 2 5 8 0 4.88e-15 0.000218 0.0069 0.0012 0.000052 0.000 0.000
2 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 1142299 21 17 15 0 2 7 0 10 2 0 1.85e-14 0.00258 0.0017 0.00071 0.000064 0.000 0.000
3 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 364906 220 220 2 0 209 0 0 11 0 0 <1.00e-15 <1.00e-15 0 1 0 <1.00e-15 <2.01e-12
4 TP53 tumor protein p53 355375 185 146 90 2 64 45 2 39 30 5 <1.00e-15 <1.00e-15 0 0 0 <1.00e-15 <2.01e-12
5 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 1818866 33 29 27 1 1 6 0 8 16 2 8.77e-15 0.0160 0 0.037 0 <1.00e-15 <2.01e-12
6 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 336981 12 12 3 0 0 7 1 4 0 0 9.99e-15 0.0220 0 1 0 <1.00e-15 <2.01e-12
7 STK19 serine/threonine kinase 19 313876 8 8 1 0 0 0 0 0 8 0 6.97e-10 1.000 0 0.93 0 <1.00e-15 <2.01e-12
8 DYNC1I1 dynein, cytoplasmic 1, intermediate chain 1 557585 2 2 2 0 1 0 0 0 1 0 0.0276 0.467 0.12 0 0 <1.00e-15 <2.01e-12
9 PRCP prolylcarboxypeptidase (angiotensinase C) 457662 2 2 2 0 1 0 0 0 1 0 0.0673 0.490 0.66 0 0 <1.00e-15 <2.01e-12
10 CIC capicua homolog (Drosophila) 1229628 58 54 47 1 20 4 0 6 24 4 5.33e-15 3.94e-05 0.0027 0.31 0.0053 1.11e-15 2.01e-12
11 ATRX alpha thalassemia/mental retardation syndrome X-linked (RAD54 homolog, S. cerevisiae) 2166375 116 114 106 2 1 6 4 4 96 5 3.89e-15 3.13e-05 0.062 0.43 0.083 1.18e-14 1.94e-11
12 FUBP1 far upstream element (FUSE) binding protein 1 570532 26 26 25 1 0 1 0 1 24 0 <1.00e-15 0.149 0.45 0.91 0.61 <2.21e-14 <3.34e-11
13 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 682889 14 13 12 1 1 5 0 0 8 0 9.86e-14 0.323 0.0034 0.77 0.0071 2.50e-14 3.48e-11
14 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 2489012 20 19 19 0 0 2 0 2 9 7 2.54e-14 0.0250 0.2 0.41 0.28 2.35e-13 3.04e-10
15 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 344607 13 13 13 0 1 4 0 5 3 0 9.77e-15 0.0700 0.7 0.6 1 3.25e-13 3.92e-10
16 ZBTB20 zinc finger and BTB domain containing 20 588074 13 13 11 2 1 4 0 3 5 0 9.06e-12 0.281 0.011 0.23 0.014 3.78e-12 4.28e-09
17 EIF1AX eukaryotic translation initiation factor 1A, X-linked 127075 4 4 3 0 1 2 0 1 0 0 4.94e-06 0.271 0.00026 0.046 0.00012 1.35e-08 1.44e-05
18 CREBZF CREB/ATF bZIP transcription factor 301194 5 5 1 0 0 0 0 0 5 0 7.35e-05 1.000 0 0.27 0.000014 2.23e-08 2.25e-05
19 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 1319999 13 13 11 0 3 2 0 4 4 0 1.55e-08 0.0562 0.12 0.43 0.19 6.13e-08 5.84e-05
20 HTRA2 HtrA serine peptidase 2 380083 4 4 1 0 0 0 0 0 4 0 0.000212 1.000 2e-07 0.59 0.000026 1.11e-07 0.000101
21 SPANXE SPANX family, member E 86205 4 4 4 0 0 2 0 2 0 0 5.74e-07 0.336 0.074 0.11 0.014 1.58e-07 0.000137
22 VAV3 vav 3 guanine nucleotide exchange factor 743648 8 8 1 0 0 0 0 0 8 0 3.77e-07 1.000 NaN NaN NaN 3.77e-07 0.000310
23 TCF12 transcription factor 12 (HTF4, helix-loop-helix transcription factors 4) 654788 9 8 8 0 0 0 0 0 9 0 1.04e-07 0.690 0.36 0.46 0.5 9.16e-07 0.000704
24 ARID1A AT rich interactive domain 1A (SWI-like) 1688356 12 12 12 0 0 1 0 0 10 1 1.05e-07 0.0924 0.67 0.23 0.5 9.32e-07 0.000704
25 SLC6A3 solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 504663 8 7 8 0 4 1 0 1 2 0 2.55e-06 0.0330 0.039 0.29 0.084 3.49e-06 0.00253
26 FSTL5 follistatin-like 5 723231 6 5 6 1 0 1 0 1 4 0 0.000302 0.406 0.0013 0.92 0.0024 1.12e-05 0.00780
27 OR5D18 olfactory receptor, family 5, subfamily D, member 18 273088 3 3 3 1 1 1 0 0 1 0 0.000699 0.710 0.0023 0.014 0.0012 1.25e-05 0.00838
28 TMEM216 transmembrane protein 216 92461 3 3 1 0 0 0 0 0 3 0 4.66e-05 0.531 0.0058 1 0.05 3.26e-05 0.0211
29 PTPN11 protein tyrosine phosphatase, non-receptor type 11 (Noonan syndrome 1) 526466 5 5 4 0 0 1 0 4 0 0 8.87e-05 0.366 0.025 0.53 0.052 6.13e-05 0.0383
30 MYH2 myosin, heavy chain 2, skeletal muscle, adult 1725789 9 9 9 0 5 2 0 2 0 0 1.61e-05 0.0588 0.28 0.68 0.36 7.50e-05 0.0453
31 OR5T3 olfactory receptor, family 5, subfamily T, member 3 294615 4 4 4 0 1 1 0 1 1 0 1.65e-05 0.277 0.62 0.22 0.48 0.000101 0.0578
32 LRRC37A2 leucine rich repeat containing 37, member A2 509817 5 5 3 0 0 0 0 4 1 0 0.000102 0.474 NaN NaN NaN 0.000102 0.0578
33 ZNF709 zinc finger protein 709 559891 3 3 1 0 0 3 0 0 0 0 0.00545 0.314 0.000078 0.96 0.0018 0.000125 0.0689
34 CD1B CD1b molecule 296489 2 2 2 1 0 1 0 0 1 0 0.0194 0.821 0.17 0.016 0.0011 0.000243 0.129
35 ZNF292 zinc finger protein 292 1996269 8 8 8 0 0 1 1 1 4 1 0.000122 0.300 0.1 0.78 0.19 0.000276 0.142
PIK3CA

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

EGFR

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

IDH1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

TP53

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NOTCH1

Figure S5.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

IDH2

Figure S6.  This figure depicts the distribution of mutations and mutation types across the IDH2 significant gene.

STK19

Figure S7.  This figure depicts the distribution of mutations and mutation types across the STK19 significant gene.

DYNC1I1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the DYNC1I1 significant gene.

PRCP

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PRCP significant gene.

CIC

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CIC significant gene.

ATRX

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ATRX significant gene.

FUBP1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

PIK3R1

Figure S13.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

NF1

Figure S14.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

PTEN

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PTEN significant gene.

ZBTB20

Figure S16.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

EIF1AX

Figure S17.  This figure depicts the distribution of mutations and mutation types across the EIF1AX significant gene.

CREBZF

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CREBZF significant gene.

SMARCA4

Figure S19.  This figure depicts the distribution of mutations and mutation types across the SMARCA4 significant gene.

HTRA2

Figure S20.  This figure depicts the distribution of mutations and mutation types across the HTRA2 significant gene.

SPANXE

Figure S21.  This figure depicts the distribution of mutations and mutation types across the SPANXE significant gene.

TCF12

Figure S22.  This figure depicts the distribution of mutations and mutation types across the TCF12 significant gene.

ARID1A

Figure S23.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

SLC6A3

Figure S24.  This figure depicts the distribution of mutations and mutation types across the SLC6A3 significant gene.

FSTL5

Figure S25.  This figure depicts the distribution of mutations and mutation types across the FSTL5 significant gene.

OR5D18

Figure S26.  This figure depicts the distribution of mutations and mutation types across the OR5D18 significant gene.

TMEM216

Figure S27.  This figure depicts the distribution of mutations and mutation types across the TMEM216 significant gene.

PTPN11

Figure S28.  This figure depicts the distribution of mutations and mutation types across the PTPN11 significant gene.

MYH2

Figure S29.  This figure depicts the distribution of mutations and mutation types across the MYH2 significant gene.

OR5T3

Figure S30.  This figure depicts the distribution of mutations and mutation types across the OR5T3 significant gene.

LRRC37A2

Figure S31.  This figure depicts the distribution of mutations and mutation types across the LRRC37A2 significant gene.

ZNF709

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ZNF709 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: 20. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 185 356 180 102884 61424 0 0
2 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 220 5 220 1445 328240 5.6e-14 1e-10
3 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 12 6 12 1734 996 6.7e-14 1e-10
4 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 14 33 7 9537 14 3.7e-13 4.2e-10
5 PTPN11 protein tyrosine phosphatase, non-receptor type 11 (Noonan syndrome 1) 5 32 5 9248 178 1.3e-12 1.2e-09
6 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 28 220 27 63580 5232 2.3e-12 1.7e-09
7 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 21 293 14 84677 147 3e-12 1.9e-09
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 13 767 12 221663 397 6.8e-12 3.8e-09
9 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 33 292 7 84388 16 1.4e-11 7.3e-09
10 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 13 30 4 8670 1 3.5e-10 1.6e-07

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: 111. 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 HSA00720_REDUCTIVE_CARBOXYLATE_CYCLE Genes involved in reductive carboxylate cycle (CO2 fixation) ACLY, ACO1, ACO2, ACSS1, ACSS2, FH, IDH1, IDH2, LOC441996, MDH1, MDH2, SUCLA2 11 ACLY(2), ACO1(1), ACSS1(2), IDH1(220), IDH2(12) 5724551 237 235 10 1 210 8 1 17 1 0 <1.00e-15 <1.00e-15 <5.13e-14
2 HSA00020_CITRATE_CYCLE Genes involved in citrate cycle (TCA cycle) ACLY, ACO1, ACO2, CLYBL, CS, DLD, DLST, FH, IDH1, IDH2, IDH3A, IDH3B, IDH3G, LOC283398, LOC441996, MDH1, MDH2, OGDH, OGDHL, PC, PCK1, PCK2, SDHA, SDHB, SDHC, SDHD, SUCLA2, SUCLG1, SUCLG2 27 ACLY(2), ACO1(1), IDH1(220), IDH2(12), IDH3B(1), OGDHL(1), PC(1), PCK1(1), SDHA(3), SDHC(1) 12856133 243 233 15 1 212 12 1 16 2 0 <1.00e-15 <1.00e-15 <5.13e-14
3 CITRATE_CYCLE_TCA_CYCLE ACO1, ACO2, CS, DLD, DLST, DLSTP, FH, IDH1, IDH2, IDH3A, IDH3B, IDH3G, MDH1, MDH2, PC, PCK1, SDHA, SDHA, SDHAL2, SDHB, SUCLA2, SUCLG1, SUCLG2 20 ACO1(1), IDH1(220), IDH2(12), IDH3B(1), PC(1), PCK1(1), SDHA(3) 8868606 239 232 11 0 210 12 1 15 1 0 <1.00e-15 <1.00e-15 <5.13e-14
4 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 CDKN2A(1), MDM2(2), PIK3CA(28), PIK3R1(14), POLR1A(1), RB1(3), TBX2(1), TP53(185) 8752049 235 178 126 5 65 65 4 46 50 5 <1.00e-15 <1.00e-15 <5.13e-14
5 HSA04110_CELL_CYCLE Genes involved in cell cycle ABL1, ANAPC1, ANAPC10, ANAPC11, ANAPC2, ANAPC4, ANAPC5, ANAPC7, ATM, ATR, BUB1, BUB1B, BUB3, CCNA1, CCNA2, CCNB1, CCNB2, CCNB3, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNH, CDC14A, CDC14B, CDC16, CDC2, CDC20, CDC23, CDC25A, CDC25B, CDC25C, CDC26, CDC27, CDC45L, CDC6, CDC7, CDK2, CDK4, CDK6, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CHEK1, CHEK2, CREBBP, CUL1, DBF4, E2F1, E2F2, E2F3, EP300, ESPL1, FZR1, GADD45A, GADD45B, GADD45G, GSK3B, hCG_1982709, HDAC1, HDAC2, LOC440917, LOC728919, MAD1L1, MAD2L1, MAD2L2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, ORC1L, ORC2L, ORC3L, ORC4L, ORC5L, ORC6L, PCNA, PKMYT1, PLK1, PRKDC, PTTG1, PTTG2, RB1, RBL1, RBL2, RBX1, SFN, SKP1, SKP2, SMAD2, SMAD3, SMAD4, SMC1A, SMC1B, TFDP1, TGFB1, TGFB2, TGFB3, TP53, WEE1, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 109 ANAPC2(1), ANAPC7(1), ATR(1), BUB1(1), BUB3(1), CCNA1(2), CCNB1(1), CCNB2(1), CCNB3(1), CCNE2(1), CDC14B(2), CDC16(1), CDC25B(1), CDKN1B(1), CDKN2A(1), CDKN2C(1), CHEK2(1), CREBBP(4), CUL1(1), FZR1(1), HDAC2(3), MCM6(1), MCM7(1), MDM2(2), PLK1(1), PRKDC(3), RB1(3), SKP2(1), SMAD2(1), SMAD3(1), SMC1B(1), TP53(185), WEE1(1), YWHAE(1), YWHAH(1) 58395004 231 167 136 17 69 59 3 51 44 5 3.99e-13 <1.00e-15 <5.13e-14
6 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(21), IGF1R(2), POLR2A(1), PRKCA(1), RB1(3), TEP1(2), TERT(1), TP53(185) 12161005 216 167 115 6 71 53 2 49 36 5 <1.00e-15 <1.00e-15 <5.13e-14
7 HSA04115_P53_SIGNALING_PATHWAY Genes involved in p53 signaling pathway APAF1, ATM, ATR, BAI1, BAX, BBC3, BID, CASP3, CASP8, CASP9, CCNB1, CCNB2, CCNB3, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNG1, CCNG2, CD82, CDC2, CDK2, CDK4, CDK6, CDKN1A, CDKN2A, CHEK1, CHEK2, CYCS, DDB2, EI24, FAS, GADD45A, GADD45B, GADD45G, GTSE1, IGF1, IGFBP3, LRDD, MDM2, MDM4, P53AIP1, PERP, PMAIP1, PPM1D, PTEN, RCHY1, RFWD2, RPRM, RRM2, RRM2B, SCOTIN, SERPINB5, SERPINE1, SESN1, SESN2, SESN3, SFN, SIAH1, STEAP3, THBS1, TNFRSF10B, TP53, TP53I3, TP73, TSC2, ZMAT3 64 ATR(1), BAI1(1), BAX(1), CCNB1(1), CCNB2(1), CCNB3(1), CCNE2(1), CCNG2(1), CDKN2A(1), CHEK2(1), CYCS(1), DDB2(1), GTSE1(1), MDM2(2), MDM4(1), PTEN(13), RFWD2(2), SESN3(1), SIAH1(1), THBS1(1), TP53(185), TSC2(2), ZMAT3(1) 28129770 222 166 127 9 69 56 2 51 39 5 <1.00e-15 <1.00e-15 <5.13e-14
8 PMLPATHWAY Ring-shaped PML nuclear bodies regulate transcription and are required co-activators in p53- and DAXX-mediated apoptosis. CREBBP, DAXX, HRAS, PAX3, PML, PRAM-1, RARA, RB1, SIRT1, SP100, TNF, TNFRSF1A, TNFRSF1B, TNFRSF6, TNFSF6, TP53, UBL1 13 CREBBP(4), PML(1), RB1(3), SP100(2), TNF(1), TP53(185) 8197018 196 156 101 6 67 47 2 41 34 5 <1.00e-15 <1.00e-15 <5.13e-14
9 CHEMICALPATHWAY DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 20 BAX(1), CYCS(1), PRKCA(1), TLN1(3), TP53(185) 11792561 191 149 96 4 66 45 2 42 31 5 <1.00e-15 <1.00e-15 <5.13e-14
10 RNAPATHWAY dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 9 EIF2S2(1), NFKBIA(1), TP53(185) 4219956 187 147 92 3 64 45 2 40 31 5 <1.00e-15 <1.00e-15 <5.13e-14

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 FLUMAZENILPATHWAY Flumazenil is a benzodiazepine receptor antagonist that may induce protective preconditioning in ischemic cardiomyocytes. GABRA1, GABRA2, GABRA3, GABRA4, GABRA5, GABRA6, GPX1, PRKCE, SOD1 9 GABRA1(3), GABRA3(2), GABRA4(3), GABRA5(1), GABRA6(3) 3395416 12 12 12 2 5 3 0 4 0 0 0.21 0.00072 0.44
2 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(5) 870909 5 5 5 0 3 1 0 0 1 0 0.27 0.0015 0.46
3 IL18PATHWAY Pro-inflammatory IL-18 is activated in macrophages by caspase-1 cleavage and, in conjunction with IL-12, stimulates Th1 cell differentiation. CASP1, IFNG, IL12A, IL12B, IL18, IL2 6 CASP1(1), IL12B(1), IL18(2) 1280747 4 4 4 1 1 0 1 2 0 0 0.62 0.011 1
4 HSA00565_ETHER_LIPID_METABOLISM Genes involved in ether lipid metabolism AGPAT1, AGPAT2, AGPAT3, AGPAT4, AGPAT6, AGPS, CHPT1, ENPP2, ENPP6, LYCAT, PAFAH1B1, PAFAH1B2, PAFAH1B3, PAFAH2, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLD1, PLD2, PPAP2A, PPAP2B, PPAP2C 30 AGPAT2(1), AGPAT3(1), AGPS(1), ENPP2(2), PAFAH1B1(2), PAFAH1B3(1), PAFAH2(1), PLA2G12B(1), PLA2G2D(1), PLA2G3(1), PLA2G4A(4), PLD1(3) 9987119 19 18 19 1 3 5 2 7 2 0 0.032 0.012 1
5 RIBOFLAVIN_METABOLISM ACP1, ACP2, ACP5, ACPP, ACPT, ENPP1, ENPP3, FLAD1, RFK, TYR 10 ACPP(3), ENPP1(1), ENPP3(2), FLAD1(1), TYR(2) 4172365 9 9 9 1 3 3 0 1 2 0 0.21 0.017 1
6 FOLATE_BIOSYNTHESIS ALPI, ALPL, ALPP, ALPP, ALPPL2, ALPPL2, DHFR, FPGS, GCH1, GGH, SPR 9 ALPP(4), ALPPL2(2), FPGS(2), SPR(1) 2821312 9 8 9 2 3 2 1 1 2 0 0.43 0.019 1
7 HSA00592_ALPHA_LINOLENIC_ACID_METABOLISM Genes involved in alpha-Linolenic acid metabolism ACOX1, ACOX3, FADS2, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6 15 ACOX3(1), FADS2(1), PLA2G12B(1), PLA2G2D(1), PLA2G3(1), PLA2G4A(4) 4369144 9 9 9 0 1 3 0 3 2 0 0.074 0.019 1
8 RAC1PATHWAY Rac-1 is a Rho family G protein that stimulates formation of actin-dependent structures such as filopodia and lamellopodia. ARFIP2, CDK5, CDK5R1, CFL1, CHN1, LIMK1, MAP3K1, MYL2, MYLK, NCF2, PAK1, PDGFRA, PIK3CA, PIK3R1, PLD1, PPP1R12B, RAC1, RALBP1, RPS6KB1, TRIO, VAV1, WASF1 20 CFL1(1), LIMK1(3), MAP3K1(2), MYLK(1), NCF2(1), PAK1(1), PDGFRA(7), PLD1(3), TRIO(2), VAV1(3) 13426396 24 23 24 2 7 6 1 4 6 0 0.022 0.026 1
9 SKP2E2FPATHWAY E2F-1, a transcription factor that promotes the G1/S transition, is repressed by Rb and activated by cdk2/cyclin E. CCNA1, CCNE1, CDC34, CDK2, CUL1, E2F1, RB1, SKP1A, SKP2, TFDP1 9 CCNA1(2), CDC34(1), CUL1(1), RB1(3), SKP2(1) 3677825 8 8 8 0 0 2 0 1 5 0 0.25 0.032 1
10 CBLPATHWAY Activated EGF receptors undergo endocytosis into clathrin-coated vesicles, where they are recycled to the membrane or ubiquitinated by Cbl. CBL, CSF1R, EGF, EGFR, GRB2, MET, PDGFRA, PRKCA, PRKCB1, SH3GLB1, SH3GLB2, SH3KBP1, SRC 11 EGF(3), MET(4), PDGFRA(7), PRKCA(1), SH3KBP1(1) 7227860 16 14 16 2 2 5 0 4 5 0 0.17 0.042 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)