Mutation Analysis (MutSig v1.5)
Bladder Urothelial Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C13T9G5Q
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/C13T9G5Q
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: BLCA-TP

  • Number of patients in set: 395

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:BLCA-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 53

  • Mutations seen in COSMIC: 749

  • Significantly mutated genes in COSMIC territory: 24

  • Significantly mutated genesets: 23

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

Mutation Preprocessing

  • Read 395 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 138385

  • After removing 10 mutations outside chr1-24: 138375

  • After removing 2579 blacklisted mutations: 135796

  • After removing 3961 noncoding mutations: 131835

  • After collapsing adjacent/redundant mutations: 126949

Mutation Filtering

  • Number of mutations before filtering: 126949

  • After removing 6587 mutations outside gene set: 120362

  • After removing 199 mutations outside category set: 120163

  • After removing 4 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 113373

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1521
Frame_Shift_Ins 584
In_Frame_Del 405
In_Frame_Ins 56
Missense_Mutation 76694
Nonsense_Mutation 7163
Nonstop_Mutation 177
Silent 30062
Splice_Site 3044
Translation_Start_Site 457
Total 120163
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) 45397 1516381424 3e-05 30 3.8 3
Tp*C->A 4263 1516381424 2.8e-06 2.8 0.36 4
(A/C/G)p*C->mut 18068 4291475797 4.2e-06 4.2 0.53 3.2
A->mut 9404 5611559704 1.7e-06 1.7 0.21 3.9
indel+null 12776 11419416925 1.1e-06 1.1 0.14 NaN
double_null 190 11419416925 1.7e-08 0.017 0.0021 NaN
Total 90098 11419416925 7.9e-06 7.9 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: BLCA-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: 53. 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 TP53 tumor protein p53 474723 226 196 118 7 59 3 79 16 67 2 1.2e-15 <1.00e-15 <3.61e-12
2 KDM6A lysine (K)-specific demethylase 6A 1477683 107 103 91 6 9 2 5 6 79 6 0.016 <1.00e-15 <3.61e-12
3 RB1 retinoblastoma 1 (including osteosarcoma) 1017077 73 70 66 1 4 1 0 3 59 6 0.00025 <1.00e-15 <3.61e-12
4 ERCC2 excision repair cross-complementing rodent repair deficiency, complementation group 2 (xeroderma pigmentosum D) 842148 39 38 23 3 15 1 6 17 0 0 0.0028 <1.00e-15 <3.61e-12
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 290850 30 26 22 0 8 3 6 0 13 0 0.0022 <1.00e-15 <3.61e-12
6 TBC1D12 TBC1 domain family, member 12 558145 50 49 4 1 48 0 1 0 1 0 0.0004 1.89e-15 4.77e-12
7 ELF3 E74-like factor 3 (ets domain transcription factor, epithelial-specific ) 441519 58 46 48 0 22 2 7 4 21 2 1e-05 1.89e-15 4.77e-12
8 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1292933 94 86 35 4 71 3 5 14 1 0 0.000043 2.11e-15 4.77e-12
9 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 191623 38 35 30 1 6 0 2 0 25 5 0.11 3.66e-15 6.82e-12
10 STAG2 stromal antigen 2 1518100 60 56 53 8 11 1 2 3 42 1 0.56 3.77e-15 6.82e-12
11 ARID1A AT rich interactive domain 1A (SWI-like) 2294479 121 97 107 8 28 4 6 3 76 4 0.00038 6.11e-15 1.00e-11
12 ZFP36L1 zinc finger protein 36, C3H type-like 1 400644 33 29 32 2 7 0 5 1 16 4 0.068 6.77e-15 1.02e-11
13 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 720414 64 56 18 6 35 1 13 12 3 0 0.00025 8.10e-15 1.13e-11
14 RHOB ras homolog gene family, member B 234807 30 26 18 0 15 2 11 2 0 0 0.000024 9.44e-15 1.22e-11
15 RHOA ras homolog gene family, member A 236210 19 18 15 1 11 2 4 2 0 0 0.017 3.67e-14 4.43e-11
16 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 249368 21 17 13 1 2 0 12 1 6 0 0.0076 1.67e-13 1.89e-10
17 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 704785 25 24 16 0 14 1 5 4 1 0 0.01 6.55e-12 6.97e-09
18 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 271766 14 14 6 0 1 1 11 1 0 0 0.097 1.47e-10 1.48e-07
19 KLF5 Kruppel-like factor 5 (intestinal) 444131 24 23 21 3 9 4 3 1 7 0 0.28 1.87e-10 1.78e-07
20 EP300 E1A binding protein p300 2895237 77 61 73 7 25 4 8 11 28 1 0.01 5.23e-10 4.73e-07
21 HIST1H3B histone cluster 1, H3b 163925 12 12 9 1 10 2 0 0 0 0 0.054 2.31e-08 1.91e-05
22 C3orf70 chromosome 3 open reading frame 70 289078 17 17 10 0 12 0 2 1 2 0 0.023 2.33e-08 1.91e-05
23 FBXW7 F-box and WD repeat domain containing 7 976750 38 32 28 4 12 0 12 1 13 0 0.096 1.12e-07 8.78e-05
24 PSIP1 PC4 and SFRS1 interacting protein 1 657713 21 20 20 1 7 0 1 0 13 0 0.18 2.59e-07 0.000195
25 FOXQ1 forkhead box Q1 140689 14 14 9 5 4 1 1 0 8 0 0.67 3.23e-07 0.000234
26 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 406737 14 14 13 0 6 1 3 1 3 0 0.043 9.08e-07 0.000631
27 TSC1 tuberous sclerosis 1 1404707 34 33 30 4 4 0 5 1 24 0 0.15 1.06e-06 0.000707
28 CFHR4 complement factor H-related 4 400705 14 13 14 1 7 0 1 4 2 0 0.27 1.78e-06 0.00115
29 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 470985 16 14 15 0 6 0 0 2 8 0 0.087 3.41e-06 0.00213
30 METTL3 methyltransferase like 3 700013 22 18 20 1 11 1 4 3 3 0 0.021 8.54e-06 0.00515
31 ZNF511 zinc finger protein 511 239152 10 10 10 1 4 0 5 0 1 0 0.22 1.33e-05 0.00756
32 FOXA1 forkhead box A1 405482 14 14 13 2 3 1 1 0 9 0 0.7 1.34e-05 0.00756
33 DIAPH2 diaphanous homolog 2 (Drosophila) 1162282 22 21 19 1 10 1 3 5 2 1 0.058 1.56e-05 0.00857
34 ZFP36L2 zinc finger protein 36, C3H type-like 2 281523 20 17 15 4 9 1 2 2 5 1 0.38 2.46e-05 0.0131
35 BTG2 BTG family, member 2 137927 8 8 8 1 3 0 4 0 1 0 0.2 2.63e-05 0.0136
TP53

Figure S1.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

KDM6A

Figure S2.  This figure depicts the distribution of mutations and mutation types across the KDM6A significant gene.

RB1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

ERCC2

Figure S4.  This figure depicts the distribution of mutations and mutation types across the ERCC2 significant gene.

CDKN2A

Figure S5.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

TBC1D12

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TBC1D12 significant gene.

ELF3

Figure S7.  This figure depicts the distribution of mutations and mutation types across the ELF3 significant gene.

PIK3CA

Figure S8.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CDKN1A

Figure S9.  This figure depicts the distribution of mutations and mutation types across the CDKN1A significant gene.

STAG2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the STAG2 significant gene.

ARID1A

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.

ZFP36L1

Figure S12.  This figure depicts the distribution of mutations and mutation types across the ZFP36L1 significant gene.

FGFR3

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FGFR3 significant gene.

RHOB

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

RHOA

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

HRAS

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

NFE2L2

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

KRAS

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

KLF5

Figure S19.  This figure depicts the distribution of mutations and mutation types across the KLF5 significant gene.

EP300

Figure S20.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

HIST1H3B

Figure S21.  This figure depicts the distribution of mutations and mutation types across the HIST1H3B significant gene.

C3orf70

Figure S22.  This figure depicts the distribution of mutations and mutation types across the C3orf70 significant gene.

FBXW7

Figure S23.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

PSIP1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PSIP1 significant gene.

FOXQ1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the FOXQ1 significant gene.

RUNX1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the RUNX1 significant gene.

TSC1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the TSC1 significant gene.

PTEN

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

METTL3

Figure S29.  This figure depicts the distribution of mutations and mutation types across the METTL3 significant gene.

ZNF511

Figure S30.  This figure depicts the distribution of mutations and mutation types across the ZNF511 significant gene.

FOXA1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the FOXA1 significant gene.

DIAPH2

Figure S32.  This figure depicts the distribution of mutations and mutation types across the DIAPH2 significant gene.

ZFP36L2

Figure S33.  This figure depicts the distribution of mutations and mutation types across the ZFP36L2 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: 24. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 FGFR3 fibroblast growth factor receptor 3 (achondroplasia, thanatophoric dwarfism) 64 62 51 24490 34265 0 0
2 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 54 42 31 16590 150 0 0
3 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 21 19 13 7505 2748 0 0
4 TP53 tumor protein p53 226 356 210 140620 46180 0 0
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 94 220 74 86900 35681 0 0
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 14 52 13 20540 147785 0 0
7 FBXW7 F-box and WD repeat domain containing 7 38 91 20 35945 549 0 0
8 RB1 retinoblastoma 1 (including osteosarcoma) 73 267 43 105465 114 0 0
9 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 30 332 30 131140 772 0 0
10 ATM ataxia telangiectasia mutated 65 245 16 96775 23 0 0

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: 23. 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 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(9), CDKN2A(30), E2F1(3), MDM2(6), MYC(2), PIK3CA(94), PIK3R1(7), POLR1A(18), POLR1B(5), POLR1C(5), POLR1D(4), RAC1(4), RB1(73), TBX2(7), TP53(226) 11787713 493 271 310 38 182 13 102 37 151 8 <1.00e-15 <1.00e-15 <1.48e-13
2 P53PATHWAY p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 16 APAF1(7), ATM(65), BAX(2), CCND1(4), CCNE1(3), CDK2(1), CDK4(6), CDKN1A(38), E2F1(3), GADD45A(1), MDM2(6), PCNA(4), RB1(73), TP53(226) 10569238 439 266 312 31 118 9 95 30 173 14 1.07e-12 <1.00e-15 <1.48e-13
3 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(4), CCNE1(3), CDC34(1), CDK2(1), CUL1(19), E2F1(3), RB1(73), SKP2(5), TFDP1(2) 4966858 111 101 99 9 29 1 8 5 62 6 0.000161 <1.00e-15 <1.48e-13
4 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), HSPA1A(3), IFNG(2), IFNGR1(1), IFNGR2(6), IKBKB(11), JAK2(8), LIN7A(3), NFKB1(3), NFKBIA(6), RB1(73), RELA(6), TNF(4), TNFRSF1A(5), TNFRSF1B(6), TP53(226), USH1C(10), WT1(4) 10415274 380 237 263 31 112 7 91 22 140 8 6.85e-14 1.33e-15 1.48e-13
5 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 HDAC1(4), MYC(2), SP1(10), SP3(3), TP53(226), WT1(4) 4101874 249 205 141 21 69 6 80 21 71 2 3.73e-09 1.33e-15 1.48e-13
6 P53HYPOXIAPATHWAY Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 19 ABCB1(16), AKT1(3), ATM(65), BAX(2), CDKN1A(38), CPB2(5), CSNK1A1(6), CSNK1D(3), FHL2(4), GADD45A(1), HIF1A(6), HSPA1A(3), IGFBP3(1), MAPK8(5), MDM2(6), NFKBIB(6), TP53(226) 12077203 396 261 276 37 124 11 102 32 119 8 2.30e-09 1.44e-15 1.48e-13
7 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(50), DAXX(9), HRAS(21), PAX3(11), PML(14), RARA(6), RB1(73), SIRT1(9), SP100(13), TNF(4), TNFRSF1A(5), TNFRSF1B(6), TP53(226) 10972480 447 258 318 32 119 5 124 30 160 9 <1.00e-15 2.11e-15 1.86e-13
8 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(65), ATR(32), CDC25C(2), CHEK1(3), CHEK2(11), TP53(226), YWHAH(2) 9369284 341 240 229 22 113 10 92 34 88 4 1.12e-10 3.00e-15 2.13e-13
9 RBPATHWAY The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH 12 ATM(65), CDC25A(5), CDC25B(2), CDC25C(2), CDK2(1), CDK4(6), CHEK1(3), MYT1(10), RB1(73), TP53(226), WEE1(10), YWHAH(2) 10260649 405 252 287 31 112 10 93 32 149 9 8.30e-12 3.11e-15 2.13e-13
10 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(9), ATM(65), ATR(32), CCNA1(4), CCND1(4), CCNE1(3), CDC25A(5), CDK2(1), CDK4(6), CDK6(5), CDKN1A(38), CDKN1B(6), CDKN2A(30), CDKN2B(3), E2F1(3), GSK3B(5), HDAC1(4), RB1(73), SKP2(5), TFDP1(2), TGFB1(3), TGFB3(1), TP53(226) 17514723 533 279 396 42 158 15 113 39 193 15 2.11e-15 4.22e-15 2.45e-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(8) 1005449 8 8 8 0 3 0 3 0 2 0 0.13 0.49 1
2 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(7), CYP2C9(3) 1188571 10 10 10 2 3 0 6 0 1 0 0.37 0.59 1
3 HSA00785_LIPOIC_ACID_METABOLISM Genes involved in lipoic acid metabolism LIAS, LIPT1, LOC387787 2 LIAS(5), LIPT1(1) 897135 6 5 6 0 4 1 1 0 0 0 0.29 0.74 1
4 HSA00730_THIAMINE_METABOLISM Genes involved in thiamine metabolism LHPP, MTMR1, MTMR2, MTMR6, NFS1, PHPT1, THTPA, TPK1 8 LHPP(2), MTMR1(8), MTMR2(6), MTMR6(8), NFS1(5), THTPA(2), TPK1(4) 3725882 35 32 35 4 20 0 5 5 5 0 0.07 0.75 1
5 1_AND_2_METHYLNAPHTHALENE_DEGRADATION ADH1A, ADH1A, ADH1B, ADH1C, ADH1B, ADH1C, ADH4, ADH6, ADH7, ADHFE1 7 ADH1A(5), ADH1B(3), ADH4(2), ADH6(7), ADH7(4), ADHFE1(4) 3308380 25 24 25 3 11 1 6 2 5 0 0.065 0.78 1
6 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(1) 299386 1 1 1 0 1 0 0 0 0 0 0.75 0.79 1
7 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(3), FMOD(3), KERA(7), LUM(2) 2112006 17 16 17 2 9 0 5 2 1 0 0.085 0.8 1
8 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(9), IFNG(2), IL12A(1), IL12B(3), IL2(1) 1737741 16 16 16 3 9 0 4 1 2 0 0.33 0.84 1
9 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(8), GOT1(2), TAT(5), TYR(12) 2741084 27 23 27 4 12 1 9 1 4 0 0.086 0.85 1
10 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(2), GNAQ(3), GNB1(7), HTR2C(1), PLCB1(17), TUB(4) 4164702 34 31 33 4 19 2 9 3 1 0 0.022 0.88 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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