Mutation Analysis (MutSig v2.0)
Lung Squamous Cell Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C13R0RHD
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/C13R0RHD
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: LUSC-TP

  • Number of patients in set: 178

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:LUSC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 101

  • Mutations seen in COSMIC: 352

  • Significantly mutated genes in COSMIC territory: 11

  • Significantly mutated genesets: 17

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

Mutation Preprocessing

  • Read 178 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 65305

  • After removing 2 mutations outside chr1-24: 65303

  • After removing 595 blacklisted mutations: 64708

  • After removing 583 noncoding mutations: 64125

Mutation Filtering

  • Number of mutations before filtering: 64125

  • After removing 343 mutations outside gene set: 63782

  • After removing 47 mutations outside category set: 63735

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 63343

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 510
Frame_Shift_Ins 115
In_Frame_Del 44
In_Frame_Ins 3
Missense_Mutation 42416
Nonsense_Mutation 3678
Nonstop_Mutation 55
Silent 15702
Splice_Site 1191
Translation_Start_Site 21
Total 63735
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->mut 12963 692977947 0.000019 19 2 3.3
(A/C/G)p*C->(A/T) 17392 1964339776 8.9e-06 8.9 0.96 2.6
(A/C/G)p*C->G 3301 1964339776 1.7e-06 1.7 0.18 4.9
A->mut 8779 2561387954 3.4e-06 3.4 0.37 3.9
indel+null 5552 5218705677 1.1e-06 1.1 0.12 NaN
double_null 45 5218705677 8.6e-09 0.0086 0.00094 NaN
Total 48032 5218705677 9.2e-06 9.2 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: LUSC-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->mut

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

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

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

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

  • n6 = number of nonsilent mutations of type: double_null

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

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

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

  • p_joint = p-value for clustering + conservation

  • p = p-value (overall)

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

Table 3.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 101. 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 583734 29 27 16 1 20 4 0 5 0 0 2.06e-12 0.021 8e-05 0.0016 3.4e-06 3.33e-16 4.50e-12
2 TP53 tumor protein p53 218677 147 141 98 7 9 42 17 32 47 0 <1.00e-15 4e-09 0 0 0 <1.00e-15 <4.50e-12
3 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 318204 28 27 15 0 19 4 0 4 1 0 6.99e-15 0.007 0 0 0 <1.00e-15 <4.50e-12
4 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 134387 26 26 23 1 5 5 2 2 12 0 1.55e-15 0.016 0.0065 2.4e-06 0 <1.00e-15 <4.50e-12
5 TPTE transmembrane phosphatase with tensin homology 308873 30 24 29 2 10 4 2 9 5 0 <1.00e-15 0.034 0.61 0.34 0.6 <2.14e-14 <7.72e-11
6 KEAP1 kelch-like ECH-associated protein 1 312991 24 22 21 0 9 9 2 2 2 0 4.09e-13 0.00021 0.036 0.18 0.047 6.30e-13 1.89e-09
7 SI sucrase-isomaltase (alpha-glucosidase) 995567 46 36 46 2 10 21 2 8 5 0 6.82e-12 0.0066 0.77 0.82 1 1.82e-10 4.67e-07
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 214719 16 14 15 0 4 1 0 3 8 0 1.04e-10 0.1 0.044 0.46 0.075 2.07e-10 4.67e-07
9 TRIM58 tripartite motif-containing 58 195196 15 15 15 1 2 8 1 1 3 0 1.41e-09 0.052 0.058 0.62 0.16 5.25e-09 1.05e-05
10 OR5L2 olfactory receptor, family 5, subfamily L, member 2 167267 15 13 15 1 0 6 3 5 1 0 1.00e-09 0.068 0.42 0.41 0.69 1.52e-08 2.74e-05
11 LRRC4C leucine rich repeat containing 4C 342685 19 17 19 1 5 8 1 4 1 0 1.87e-08 0.021 0.073 0.19 0.063 2.54e-08 4.15e-05
12 FAM5C family with sequence similarity 5, member C 412431 28 27 28 3 3 15 1 9 0 0 1.71e-09 0.043 0.98 0.98 1 3.63e-08 5.45e-05
13 ZBBX zinc finger, B-box domain containing 437517 17 17 17 1 4 4 1 5 3 0 7.02e-08 0.13 0.025 0.68 0.05 7.13e-08 9.87e-05
14 DPPA4 developmental pluripotency associated 4 167827 12 12 12 0 4 3 1 0 4 0 1.23e-08 0.057 0.31 0.48 0.43 1.06e-07 0.000136
15 PDYN prodynorphin 137367 11 10 11 1 2 6 2 1 0 0 5.45e-07 0.1 0.015 0.23 0.017 1.83e-07 0.000208
16 ASB5 ankyrin repeat and SOCS box-containing 5 180540 9 9 9 0 3 1 3 2 0 0 6.80e-06 0.14 0.013 0.0042 0.0014 1.85e-07 0.000208
17 REG1B regenerating islet-derived 1 beta (pancreatic stone protein, pancreatic thread protein) 92608 13 11 11 2 6 4 0 2 1 0 1.29e-07 0.29 0.24 0.053 0.12 2.93e-07 0.000311
18 CYP11B1 cytochrome P450, family 11, subfamily B, polypeptide 1 272922 15 15 15 0 0 11 1 3 0 0 1.71e-07 0.0059 0.094 0.92 0.18 5.65e-07 0.000565
19 CRB1 crumbs homolog 1 (Drosophila) 759065 27 23 27 2 8 6 1 9 3 0 1.83e-07 0.043 0.14 0.82 0.22 7.12e-07 0.000675
20 OR6F1 olfactory receptor, family 6, subfamily F, member 1 165718 13 13 13 2 2 6 1 4 0 0 3.39e-07 0.19 0.33 0.14 0.22 1.29e-06 0.00116
21 OR2G6 olfactory receptor, family 2, subfamily G, member 6 169883 17 16 17 4 3 6 1 7 0 0 2.54e-06 0.27 0.12 0.093 0.074 3.11e-06 0.00264
22 OR2T33 olfactory receptor, family 2, subfamily T, member 33 171450 15 14 15 3 2 7 1 4 1 0 2.44e-07 0.22 0.99 0.39 0.81 3.24e-06 0.00264
23 ESRRG estrogen-related receptor gamma 250009 12 12 12 1 2 5 1 2 2 0 1.38e-06 0.13 0.09 0.57 0.15 3.37e-06 0.00264
24 REG3A regenerating islet-derived 3 alpha 97465 14 11 14 2 1 8 3 1 1 0 1.55e-06 0.16 0.085 0.73 0.14 3.67e-06 0.00275
25 PNLIPRP3 pancreatic lipase-related protein 3 257837 12 12 12 1 1 6 2 1 2 0 6.71e-07 0.33 0.44 0.21 0.38 4.18e-06 0.00301
26 SPHKAP SPHK1 interactor, AKAP domain containing 911279 36 27 36 3 5 17 5 8 1 0 4.19e-07 0.012 0.76 0.82 0.82 5.46e-06 0.00378
27 MAGEB2 melanoma antigen family B, 2 133192 9 9 9 1 2 4 2 1 0 0 5.27e-07 0.26 0.63 0.56 0.78 6.50e-06 0.00424
28 CFHR4 complement factor H-related 4 180409 10 10 10 1 0 4 1 3 2 0 8.85e-07 0.35 0.41 0.36 0.48 6.60e-06 0.00424
29 OR51B2 olfactory receptor, family 51, subfamily B, member 2 166648 12 10 11 0 2 4 1 3 2 0 1.17e-06 0.045 0.3 0.47 0.41 7.51e-06 0.00456
30 OR4M2 olfactory receptor, family 4, subfamily M, member 2 168054 15 14 15 3 1 7 0 6 1 0 6.67e-07 0.31 0.81 0.41 0.73 7.59e-06 0.00456
31 CPS1 carbamoyl-phosphate synthetase 1, mitochondrial 828677 30 25 29 3 4 17 1 6 2 0 5.31e-06 0.038 0.057 0.82 0.096 7.86e-06 0.00457
32 ELTD1 EGF, latrophilin and seven transmembrane domain containing 1 365327 18 18 18 2 4 3 1 4 6 0 9.07e-07 0.2 0.5 0.8 0.67 9.31e-06 0.00511
33 SLC13A1 solute carrier family 13 (sodium/sulfate symporters), member 1 326098 12 12 12 1 4 2 1 4 1 0 4.11e-06 0.15 0.072 0.52 0.15 9.36e-06 0.00511
34 TGIF2LX TGFB-induced factor homeobox 2-like, X-linked 129265 12 9 12 1 2 2 0 6 2 0 1.34e-06 0.21 0.37 0.47 0.52 1.05e-05 0.00557
35 REG3G regenerating islet-derived 3 gamma 97540 8 8 8 1 1 3 0 0 4 0 1.64e-06 0.26 0.46 0.43 0.57 1.40e-05 0.00717
PIK3CA

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

TP53

Figure S2.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NFE2L2

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

CDKN2A

Figure S4.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

TPTE

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

KEAP1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

SI

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

PTEN

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

TRIM58

Figure S9.  This figure depicts the distribution of mutations and mutation types across the TRIM58 significant gene.

OR5L2

Figure S10.  This figure depicts the distribution of mutations and mutation types across the OR5L2 significant gene.

LRRC4C

Figure S11.  This figure depicts the distribution of mutations and mutation types across the LRRC4C significant gene.

FAM5C

Figure S12.  This figure depicts the distribution of mutations and mutation types across the FAM5C significant gene.

ZBBX

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

DPPA4

Figure S14.  This figure depicts the distribution of mutations and mutation types across the DPPA4 significant gene.

ASB5

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ASB5 significant gene.

REG1B

Figure S16.  This figure depicts the distribution of mutations and mutation types across the REG1B significant gene.

CYP11B1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the CYP11B1 significant gene.

CRB1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the CRB1 significant gene.

OR6F1

Figure S19.  This figure depicts the distribution of mutations and mutation types across the OR6F1 significant gene.

OR2G6

Figure S20.  This figure depicts the distribution of mutations and mutation types across the OR2G6 significant gene.

OR2T33

Figure S21.  This figure depicts the distribution of mutations and mutation types across the OR2T33 significant gene.

ESRRG

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

REG3A

Figure S23.  This figure depicts the distribution of mutations and mutation types across the REG3A significant gene.

PNLIPRP3

Figure S24.  This figure depicts the distribution of mutations and mutation types across the PNLIPRP3 significant gene.

SPHKAP

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

MAGEB2

Figure S26.  This figure depicts the distribution of mutations and mutation types across the MAGEB2 significant gene.

CFHR4

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CFHR4 significant gene.

OR51B2

Figure S28.  This figure depicts the distribution of mutations and mutation types across the OR51B2 significant gene.

OR4M2

Figure S29.  This figure depicts the distribution of mutations and mutation types across the OR4M2 significant gene.

CPS1

Figure S30.  This figure depicts the distribution of mutations and mutation types across the CPS1 significant gene.

ELTD1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the ELTD1 significant gene.

SLC13A1

Figure S32.  This figure depicts the distribution of mutations and mutation types across the SLC13A1 significant gene.

TGIF2LX

Figure S33.  This figure depicts the distribution of mutations and mutation types across the TGIF2LX 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: 11. 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 29 220 24 39160 9572 1.3e-12 2.6e-09
2 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 26 332 25 59096 559 1.7e-12 2.6e-09
3 TP53 tumor protein p53 147 356 144 63368 25865 1.7e-12 2.6e-09
4 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 16 767 16 136526 579 2.5e-12 2.8e-09
5 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 5 19 5 3382 1133 2.4e-10 2.1e-07
6 RB1 retinoblastoma 1 (including osteosarcoma) 12 267 7 47526 17 4.1e-07 0.00031
7 FBXW7 F-box and WD repeat domain containing 7 10 91 5 16198 217 5.4e-07 0.00035
8 HEPACAM2 HEPACAM family member 2 4 1 2 178 2 1.3e-06 0.00075
9 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 22 285 6 50730 21 9.7e-06 0.0049
10 BRAF v-raf murine sarcoma viral oncogene homolog B1 8 89 4 15842 77 0.000017 0.0076

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: 17. 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 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(3), ATM(8), ATR(13), CCNA1(1), CCND1(1), CCNE1(3), CDKN1A(2), CDKN2A(26), CDKN2B(1), E2F1(2), HDAC1(2), RB1(12), SKP2(2), TFDP1(3), TGFB1(1), TGFB2(3), TP53(147) 7994705 230 156 178 17 29 69 22 40 70 0 2.6e-09 <1.00e-15 <2.05e-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(4), ATM(8), BAX(1), CCND1(1), CCNE1(3), CDKN1A(2), E2F1(2), GADD45A(1), MDM2(2), RB1(12), TP53(147) 4817072 183 149 134 8 17 53 18 38 57 0 4.3e-10 <1.00e-15 <2.05e-13
3 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 CHUK(2), EIF2S2(1), MAP3K14(1), NFKB1(2), RELA(3), TP53(147) 2611540 156 141 107 10 11 43 18 34 50 0 1.7e-07 <1.00e-15 <2.05e-13
4 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(2), MYC(1), SP1(2), SP3(1), TP53(147), WT1(4) 1863398 157 146 108 12 10 45 19 36 47 0 8.6e-07 1.67e-15 2.19e-13
5 SA_G1_AND_S_PHASES Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 15 ARF1(1), CCND1(1), CDKN1A(2), CDKN2A(26), CFL1(2), E2F1(2), MDM2(2), NXT1(1), PRB1(5), TP53(147) 2143952 189 149 137 12 18 56 19 37 59 0 2.5e-10 1.78e-15 2.19e-13
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(17), DAXX(3), HRAS(5), PAX3(4), RARA(1), RB1(12), SIRT1(1), SP100(3), TNF(1), TNFRSF1A(2), TNFRSF1B(1), TP53(147) 5020302 197 147 147 17 17 59 21 42 58 0 7.7e-08 2.44e-15 2.51e-13
7 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(8), ATR(13), CDC25C(1), CHEK1(5), CHEK2(3), TP53(147) 4260894 177 146 128 10 18 52 20 37 50 0 2.2e-07 3.11e-15 2.74e-13
8 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(8), CDC25B(2), CDC25C(1), CHEK1(5), MYT1(4), RB1(12), TP53(147), WEE1(4) 4677103 183 146 134 10 18 53 19 36 57 0 9.3e-09 3.89e-15 2.94e-13
9 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 IFNG(1), IFNGR1(4), IFNGR2(1), IKBKB(2), JAK2(4), LIN7A(1), NFKB1(2), RB1(12), RELA(3), TNF(1), TNFRSF1A(2), TNFRSF1B(1), TP53(147), USH1C(7), WT1(4) 4825619 192 144 143 16 19 51 21 43 58 0 1.1e-07 4.66e-15 2.94e-13
10 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(3), CDKN2A(26), E2F1(2), MDM2(2), MYC(1), PIK3CA(29), PIK3R1(2), POLR1A(3), POLR1B(2), POLR1D(1), RAC1(1), RB1(12), TBX2(3), TP53(147), TWIST1(1) 5361306 235 155 170 19 43 60 19 44 69 0 1.7e-09 4.77e-15 2.94e-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 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(3) 134908 3 3 3 1 0 1 0 2 0 0 0.81 0.04 1
2 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(9), CYP2C9(3) 536360 12 10 12 3 5 4 0 2 1 0 0.48 0.098 1
3 SA_G2_AND_M_PHASES Cdc25 activates the cdc2/cyclin B complex to induce the G2/M transition. CDC2, CDC25A, CDC25B, CDK7, CDKN1A, CHEK1, NEK1, WEE1 7 CDC25B(2), CDK7(1), CDKN1A(2), CHEK1(5), NEK1(3), WEE1(4) 1849805 17 17 17 1 7 5 1 3 1 0 0.1 0.23 1
4 HSA00750_VITAMIN_B6_METABOLISM Genes involved in vitamin B6 metabolism AOX1, PDXK, PDXP, PNPO, PSAT1 5 AOX1(13), PDXP(1), PSAT1(3) 1279971 17 16 17 2 6 5 0 5 1 0 0.13 0.27 1
5 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(2) 191569 2 2 2 0 0 1 0 0 1 0 0.5 0.35 1
6 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(4), PGLYRP2(2) 477868 6 5 6 0 1 4 1 0 0 0 0.15 0.37 1
7 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 11 CCNE1(3), CKS1B(1), CUL1(4), E2F1(2), RBX1(1), SKP2(2), TFDP1(3), UBE2M(1) 1813849 17 16 17 1 5 8 0 2 2 0 0.05 0.46 1
8 HSA00780_BIOTIN_METABOLISM Genes involved in biotin metabolism BTD, HLCS, SPCS1, SPCS3 4 BTD(2), HLCS(5), SPCS1(1), SPCS3(2) 816418 10 9 10 2 2 2 2 0 4 0 0.4 0.48 1
9 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(6), GOT2(3), TAT(1), TYR(10) 1245159 20 18 20 4 2 12 0 3 3 0 0.22 0.52 1
10 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), IFNG(1), IL12A(1), IL12B(3) 791855 6 6 6 1 3 1 0 0 2 0 0.52 0.53 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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