Mutation Analysis (MutSig v1.5)
Brain Lower Grade Glioma (Primary solid tumor)
Due to issues with GAF 3.0, we strongly advise caution in the use of these results.
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1T43RC2
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v1.5). Broad Institute of MIT and Harvard. doi:10.7908/C1T43RC2
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: LGG-TP

  • Number of patients in set: 220

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): 44

  • Mutations seen in COSMIC: 431

  • Significantly mutated genes in COSMIC territory: 14

  • Genes with clustered mutations (≤ 3 aa apart): 185

  • Significantly mutated genesets: 95

  • Significantly mutated genesets: (excluding sig. mutated genes):1

Mutation Preprocessing

  • Read 220 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 27315

  • After removing 124 mutations outside chr1-24: 27191

  • After removing 638 noncoding mutations: 26553

Mutation Filtering

  • Number of mutations before filtering: 26553

  • After removing 1159 mutations outside gene set: 25394

  • After removing 142 mutations outside category set: 25252

  • After removing 4 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 23947

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 586
Frame_Shift_Ins 303
In_Frame_Del 339
In_Frame_Ins 23
Missense_Mutation 15782
Nonsense_Mutation 975
Nonstop_Mutation 12
Silent 6253
Splice_Site 974
Translation_Start_Site 5
Total 25252
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 5206 355996191 0.000015 15 5 2.1
*Cp(A/C/T)->T 3430 2925534322 1.2e-06 1.2 0.4 1.7
A->G 2173 3157386047 6.9e-07 0.69 0.23 2.3
transver 4973 6438916560 7.7e-07 0.77 0.26 5
indel+null 3086 6438916560 4.8e-07 0.48 0.16 NaN
double_null 128 6438916560 2e-08 0.02 0.0067 NaN
Total 18996 6438916560 3e-06 3 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).

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: *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_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: 44. 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 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 278348 167 167 2 0 157 0 0 10 0 0 <1.00e-15 <1.00e-15 <1.10e-11
2 ATRX alpha thalassemia/mental retardation syndrome X-linked (RAD54 homolog, S. cerevisiae) 1650380 102 97 91 2 2 2 7 7 79 5 0.000299 1.22e-15 1.10e-11
3 TP53 tumor protein p53 270269 154 116 80 2 59 17 20 32 22 4 <1.00e-15 2.33e-15 1.36e-11
4 CIC capicua homolog (Drosophila) 919250 44 39 37 0 16 2 1 5 20 0 5.23e-05 3.00e-15 1.36e-11
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 720586 21 19 13 0 0 4 7 3 7 0 0.00250 5.55e-15 2.01e-11
6 FUBP1 far upstream element (FUSE) binding protein 1 432768 21 21 20 1 0 0 1 0 19 1 0.309 7.44e-15 2.09e-11
7 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 264795 13 13 13 0 1 1 1 6 4 0 0.0959 8.10e-15 2.09e-11
8 IL32 interleukin 32 114597 9 9 1 0 0 0 0 0 9 0 1.000 1.72e-14 3.89e-11
9 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 519451 14 13 13 1 1 2 2 0 9 0 0.356 1.70e-13 3.42e-10
10 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 1897735 20 16 20 1 0 2 1 3 7 7 0.0533 8.59e-12 1.55e-08
11 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 1345769 26 19 23 3 5 3 1 4 10 3 0.0414 2.56e-11 4.21e-08
12 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 256354 8 8 2 0 0 6 0 2 0 0 0.0164 1.89e-10 2.86e-07
13 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 92680 7 7 3 0 2 0 0 0 5 0 0.378 7.12e-10 9.91e-07
14 ARID1A AT rich interactive domain 1A (SWI-like) 1277967 16 14 16 0 1 1 0 1 12 1 0.0331 1.75e-09 2.26e-06
15 ZBTB20 zinc finger and BTB domain containing 20 447654 10 10 10 1 1 0 3 2 4 0 0.297 3.51e-09 4.23e-06
16 NPIP nuclear pore complex interacting protein 80183 5 5 2 0 0 4 0 1 0 0 0.183 3.18e-08 3.60e-05
17 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 865956 13 11 10 2 1 4 0 7 1 0 0.210 4.11e-08 4.37e-05
18 ZNF844 zinc finger protein 844 274312 7 6 3 0 0 0 3 4 0 0 0.156 1.61e-07 0.000162
19 TPTE transmembrane phosphatase with tensin homology 382197 9 8 8 2 0 0 0 2 6 1 0.629 2.81e-07 0.000268
20 MUC7 mucin 7, secreted 251233 9 6 7 0 2 2 5 0 0 0 0.0126 6.02e-07 0.000544
21 TCF12 transcription factor 12 (HTF4, helix-loop-helix transcription factors 4) 498064 7 7 6 0 0 0 0 0 7 0 0.748 7.04e-07 0.000606
22 STAG3L2 stromal antigen 3-like 2 53256 4 4 2 0 0 0 0 1 3 0 0.855 2.62e-06 0.00215
23 TIMD4 T-cell immunoglobulin and mucin domain containing 4 257839 5 5 3 1 0 1 0 1 3 0 0.814 7.01e-06 0.00552
24 OR2T35 olfactory receptor, family 2, subfamily T, member 35 58809 3 3 2 0 1 0 0 0 2 0 0.697 8.70e-06 0.00656
25 PAX4 paired box 4 217042 5 5 5 1 2 1 0 1 1 0 0.610 9.07e-06 0.00656
26 MESP2 mesoderm posterior 2 homolog (mouse) 123791 4 4 2 0 0 0 0 0 4 0 1.000 1.42e-05 0.00989
27 SPANXE SPANX family, member E 65651 3 3 3 0 0 1 1 1 0 0 0.404 1.48e-05 0.00990
28 ZNF57 zinc finger protein 57 368716 7 6 4 0 1 1 1 4 0 0 0.159 2.39e-05 0.0154
29 SERPINB7 serpin peptidase inhibitor, clade B (ovalbumin), member 7 256708 5 5 5 0 1 0 0 2 2 0 0.262 3.12e-05 0.0195
30 ZNF573 zinc finger protein 573 402814 6 6 3 1 0 1 0 0 5 0 0.893 3.24e-05 0.0195
31 UBC ubiquitin C 408518 7 6 5 1 1 0 1 5 0 0 0.518 5.26e-05 0.0305
32 CYP2C19 cytochrome P450, family 2, subfamily C, polypeptide 19 331464 5 5 5 0 3 1 0 0 1 0 0.247 5.40e-05 0.0305
33 NBPF1 neuroblastoma breakpoint family, member 1 697255 7 7 5 1 0 2 1 0 4 0 0.210 5.89e-05 0.0323
34 GAGE2B G antigen 2B 21986 2 4 1 0 0 0 0 0 2 0 1.000 7.92e-05 0.0421
35 PRB2 proline-rich protein BstNI subfamily 2 276407 4 4 3 1 0 0 0 3 1 0 0.631 9.33e-05 0.0482
IDH1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the IDH1 significant gene.

ATRX

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

TP53

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CIC

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

PIK3CA

Figure S5.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

FUBP1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the FUBP1 significant gene.

PTEN

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

IL32

Figure S8.  This figure depicts the distribution of mutations and mutation types across the IL32 significant gene.

PIK3R1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the PIK3R1 significant gene.

NF1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the NF1 significant gene.

NOTCH1

Figure S11.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

IDH2

Figure S12.  This figure depicts the distribution of mutations and mutation types across the IDH2 significant gene.

NUDT11

Figure S13.  This figure depicts the distribution of mutations and mutation types across the NUDT11 significant gene.

ARID1A

Figure S14.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

ZBTB20

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ZBTB20 significant gene.

NPIP

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

EGFR

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

ZNF844

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ZNF844 significant gene.

TPTE

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

MUC7

Figure S20.  This figure depicts the distribution of mutations and mutation types across the MUC7 significant gene.

TCF12

Figure S21.  This figure depicts the distribution of mutations and mutation types across the TCF12 significant gene.

TIMD4

Figure S22.  This figure depicts the distribution of mutations and mutation types across the TIMD4 significant gene.

OR2T35

Figure S23.  This figure depicts the distribution of mutations and mutation types across the OR2T35 significant gene.

PAX4

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PAX4 significant gene.

MESP2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the MESP2 significant gene.

SPANXE

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

ZNF57

Figure S27.  This figure depicts the distribution of mutations and mutation types across the ZNF57 significant gene.

SERPINB7

Figure S28.  This figure depicts the distribution of mutations and mutation types across the SERPINB7 significant gene.

ZNF573

Figure S29.  This figure depicts the distribution of mutations and mutation types across the ZNF573 significant gene.

CYP2C19

Figure S30.  This figure depicts the distribution of mutations and mutation types across the CYP2C19 significant gene.

NBPF1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the NBPF1 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: 14. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 167 5 167 1100 249164 5.3e-14 1.5e-10
2 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 8 6 8 1320 664 6.4e-14 1.5e-10
3 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 14 33 6 7260 12 4.8e-13 7.2e-10
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 21 220 19 48400 2990 2e-12 2.3e-09
5 TP53 tumor protein p53 154 356 150 78320 53056 3e-12 2.7e-09
6 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 13 767 12 168740 551 5.3e-12 4e-09
7 PTPN11 protein tyrosine phosphatase, non-receptor type 11 (Noonan syndrome 1) 6 32 5 7040 178 3.2e-11 2.1e-08
8 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 13 293 8 64460 71 3.8e-11 2.2e-08
9 CHEK2 CHK2 checkpoint homolog (S. pombe) 6 2 3 440 3 3.6e-10 1.8e-07
10 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 13 30 4 6600 1 5.9e-09 2.7e-06

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)

Clustered Mutations

Table 5.  Get Full Table Genes with Clustered Mutations

num gene desc n mindist nmuts0 nmuts3 nmuts12 npairs0 npairs3 npairs12
3698 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 167 0 13861 13861 13861 13861 13861 13861
8369 TP53 tumor protein p53 154 0 700 1069 1899 700 1069 1899
3699 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 8 0 28 28 28 28 28 28
1636 CIC capicua homolog (Drosophila) 44 0 19 29 54 19 29 54
712 ATRX alpha thalassemia/mental retardation syndrome X-linked (RAD54 homolog, S. cerevisiae) 102 0 15 21 30 15 21 30
2122 DDX11 DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 11 (CHL1-like helicase homolog, S. cerevisiae) 6 0 10 10 10 10 10 10
6052 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 21 0 9 11 17 9 11 17
9373 ZNF844 zinc finger protein 844 7 0 7 7 15 7 7 15
9268 ZNF57 zinc finger protein 57 7 0 6 6 14 6 6 14
2099 DCP1B DCP1 decapping enzyme homolog B (S. cerevisiae) 4 0 6 6 6 6 6 6

Note:

n - number of mutations in this gene in the individual set.

mindist - distance (in aa) between closest pair of mutations in this gene

npairs3 - how many pairs of mutations are within 3 aa of each other.

npairs12 - how many pairs of mutations are within 12 aa of each other.

Geneset Analyses

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 95. 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 HSA00480_GLUTATHIONE_METABOLISM Genes involved in glutathione metabolism ANPEP, G6PD, GCLC, GCLM, GGT1, GGTL3, GGTL4, GPX1, GPX2, GPX3, GPX4, GPX5, GPX6, GPX7, GSR, GSS, GSTA1, GSTA2, GSTA3, GSTA4, GSTA5, GSTK1, GSTM1, GSTM2, GSTM3, GSTM4, GSTM5, GSTO2, GSTP1, GSTT1, GSTT2, GSTZ1, IDH1, IDH2, MGST1, MGST2, MGST3, OPLAH, TXNDC12 36 ANPEP(2), G6PD(2), GCLC(1), GGT1(4), GPX1(2), GPX4(1), GSTA4(1), GSTA5(3), GSTZ1(2), IDH1(167), IDH2(8), OPLAH(2) 7171644 195 178 23 11 164 11 3 15 2 0 <1.00e-15 <1.00e-15 <4.74e-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(3), ACO1(2), ACO2(2), FH(1), IDH1(167), IDH2(8), IDH3B(1), OGDHL(2), PC(1), PCK1(3), SDHA(1), SDHC(1), SUCLG2(1) 9766691 193 177 22 7 163 10 2 15 3 0 <1.00e-15 <1.00e-15 <4.74e-14
3 REDUCTIVE_CARBOXYLATE_CYCLE_CO2_FIXATION ACO1, ACO2, FH, IDH1, IDH2, MDH1, MDH2, SDHB, SUCLA2 9 ACO1(2), ACO2(2), FH(1), IDH1(167), IDH2(8) 2912395 180 176 9 0 160 7 0 12 1 0 <1.00e-15 <1.00e-15 <4.74e-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 ABL1(4), CDKN2A(2), E2F1(1), MDM2(2), PIK3CA(21), PIK3R1(14), POLR1A(4), POLR1B(2), RAC1(1), RB1(4), TBX2(1), TP53(154) 6628254 210 143 127 9 65 24 32 40 45 4 <1.00e-15 <1.00e-15 <4.74e-14
5 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 APAF1(1), ATM(4), ATR(4), BAI1(2), BAX(1), CCNB2(1), CCNB3(3), CCND1(1), CCNE2(1), CCNG2(1), CDK2(1), CDK4(1), CDKN2A(2), CHEK1(3), CHEK2(6), CYCS(2), DDB2(2), EI24(2), FAS(1), GTSE1(4), IGFBP3(1), MDM2(2), MDM4(1), PPM1D(1), PTEN(13), RFWD2(3), SERPINE1(1), SESN1(1), SESN3(1), SIAH1(1), STEAP3(1), THBS1(1), TP53(154), TSC2(2), ZMAT3(3) 21303520 229 137 152 28 73 27 34 56 35 4 4.51e-10 <1.00e-15 <4.74e-14
6 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(8), DAXX(2), PAX3(1), PML(3), RB1(4), SP100(3), TNFRSF1B(2), TP53(154) 6202031 177 123 103 6 64 19 22 39 29 4 <1.00e-15 <1.00e-15 <4.74e-14
7 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 DNAJA3(3), IFNGR2(1), JAK2(3), NFKB1(1), NFKBIA(1), RB1(4), RELA(1), TNFRSF1B(2), TP53(154), WT1(1) 5925542 171 121 97 10 63 18 21 36 29 4 2.61e-13 <1.00e-15 <4.74e-14
8 APOPTOSIS_GENMAPP APAF1, BAK1, BCL2L7P1, BAX, BCL2, BCL2L1, BID, BIRC2, BIRC3, BIRC4, CASP2, CASP3, CASP6, CASP7, CASP8, CASP9, CYCS, FADD, FAS, FASLG, GZMB, IKBKG, JUN, MAP2K4, MAP3K1, MAP3K14, MAPK10, MCL1, MDM2, MYC, NFKB1, NFKBIA, PARP1, PRF1, RELA, RIPK1, TNF, TNFRSF1A, TNFRSF1B, TNFSF10, TP53, TRADD, TRAF1, TRAF2 41 APAF1(1), BAX(1), BIRC2(1), CYCS(2), FAS(1), MAP3K1(2), MAP3K14(1), MAPK10(1), MDM2(2), NFKB1(1), NFKBIA(1), PARP1(1), PRF1(1), RELA(1), RIPK1(1), TNFRSF1B(2), TP53(154), TRADD(1) 12209034 175 119 101 11 65 19 22 37 28 4 7.62e-14 <1.00e-15 <4.74e-14
9 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ABL1(4), ATM(4), ATR(4), CCNA1(1), CCND1(1), CDC25A(1), CDK2(1), CDK4(1), CDKN1B(1), CDKN2A(2), E2F1(1), RB1(4), SKP2(2), TGFB2(2), TGFB3(1), TP53(154) 9861667 184 119 110 8 67 21 25 39 28 4 1.11e-15 <1.00e-15 <4.74e-14
10 TERTPATHWAY hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 7 MAX(4), SP3(2), TP53(154), WT1(1) 2308742 161 119 86 2 62 18 20 35 22 4 <1.00e-15 <1.00e-15 <4.74e-14

Table 7.  Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 1. 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(7), GABRA3(1), GABRA4(4), GABRA5(1), GABRA6(4), GPX1(2) 2578270 19 13 18 4 5 4 1 5 4 0 0.25 0.00013 0.083
2 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 ACOX1(1), ACOX3(3), FADS2(2), PLA2G12B(1), PLA2G2D(1), PLA2G3(3), PLA2G4A(4), PLA2G5(1), PLA2G6(2) 3315078 18 10 18 2 3 3 3 6 3 0 0.078 0.0055 1
3 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 CSF1R(3), EGF(3), MET(6), PDGFRA(8), PRKCA(3), SH3GLB1(3), SH3KBP1(3) 5489512 29 13 29 7 9 4 4 6 5 1 0.17 0.021 1
4 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 BGN(2), DCN(1), FMOD(1), KERA(2), LUM(2) 1186959 8 7 8 3 1 1 2 4 0 0 0.7 0.025 1
5 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 AGPAT3(1), AGPS(2), ENPP2(3), ENPP6(1), PAFAH1B1(4), PAFAH1B3(1), PAFAH2(2), PLA2G12B(1), PLA2G2D(1), PLA2G3(3), PLA2G4A(4), PLA2G5(1), PLA2G6(2), PLD1(5), PPAP2A(2), PPAP2C(1) 7574393 34 16 34 6 6 5 6 12 5 0 0.066 0.03 1
6 P27PATHWAY p27 blocks the G1/S transition by inhibiting the checkpoint kinase cdk2/cyclin E and is inhibited by cdk2-mediated ubiquitination. CCNE1, CDK2, CDKN1B, CKS1B, CUL1, E2F1, NEDD8, RB1, RBX1, SKP1A, SKP2, TFDP1, UBE2M 12 CDK2(1), CDKN1B(1), CUL1(1), E2F1(1), RB1(4), SKP2(2), UBE2M(1) 2798648 11 8 11 1 1 1 4 1 4 0 0.17 0.034 1
7 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(1), CDC34(1), CDK2(1), CUL1(1), E2F1(1), RB1(4), SKP2(2) 2788860 11 8 11 1 1 1 4 1 4 0 0.19 0.035 1
8 HSA00430_TAURINE_AND_HYPOTAURINE_METABOLISM Genes involved in taurine and hypotaurine metabolism BAAT, CDO1, CSAD, GAD1, GAD2, GGT1, GGTL3, GGTL4 6 GAD1(2), GAD2(1), GGT1(4) 1879746 7 6 7 0 2 1 2 2 0 0 0.098 0.039 1
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 5 AKT1(1), PLCB1(2), PLCG1(6), PRKCA(3), VAV1(4) 2959480 16 11 15 3 4 3 2 5 1 1 0.24 0.047 1
10 CYANOAMINO_ACID_METABOLISM ATP6V0C, SHMT1, GBA3, GGT1, SHMT1, SHMT2 5 ATP6V0C(1), GGT1(4), SHMT1(1) 1356911 6 5 6 1 2 1 2 1 0 0 0.3 0.061 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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