Mutation Analysis (MutSig v2.0)
Lung Adenocarcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Analysis (MutSig v2.0). Broad Institute of MIT and Harvard. doi:10.7908/C1CF9PJT
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: LUAD-TP

  • Number of patients in set: 545

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:LUAD-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 164

  • Mutations seen in COSMIC: 1117

  • Significantly mutated genes in COSMIC territory: 39

  • Significantly mutated genesets: 17

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

Mutation Preprocessing
  • Read 545 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 255949

  • After removing 114 mutations outside chr1-24: 255835

  • After removing 8884 blacklisted mutations: 246951

  • After removing 19788 noncoding mutations: 227163

  • After collapsing adjacent/redundant mutations: 190718

Mutation Filtering
  • Number of mutations before filtering: 190718

  • After removing 9928 mutations outside gene set: 180790

  • After removing 423 mutations outside category set: 180367

  • After removing 14 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 170002

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 60
De_novo_Start_OutOfFrame 177
Frame_Shift_Del 3844
Frame_Shift_Ins 1608
In_Frame_Del 487
In_Frame_Ins 69
Missense_Mutation 115984
Nonsense_Mutation 9151
Nonstop_Mutation 159
Silent 41254
Splice_Site 7374
Start_Codon_Del 7
Start_Codon_Ins 4
Start_Codon_SNP 189
Total 180367
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->(A/T) 16528 861142629 0.000019 19 2.2 2.1
*Cp(A/C/T)->(A/T) 56880 7163719428 7.9e-06 7.9 0.9 2.7
flip 29781 15791237960 1.9e-06 1.9 0.21 5.3
A->(C/G) 12975 7766375903 1.7e-06 1.7 0.19 3.3
indel+null 22524 15791237960 1.4e-06 1.4 0.16 NaN
double_null 412 15791237960 2.6e-08 0.026 0.003 NaN
Total 139100 15791237960 8.8e-06 8.8 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: LUAD-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->(A/T)

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

  • n3 = number of nonsilent mutations of type: flip

  • n4 = number of nonsilent mutations of type: A->(C/G)

  • 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: 164. 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 STK11 serine/threonine kinase 11 353629 87 80 69 2 1 16 6 5 59 0 2.22e-15 6.73e-08 1.2e-06 0.014 1.8e-06 0.000 0.000
2 TP53 tumor protein p53 667839 309 295 175 4 42 79 33 33 119 3 3.55e-15 <1.00e-15 0 0 0 <1.00e-15 <1.51e-12
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 373039 169 164 11 0 0 141 27 0 1 0 <1.00e-15 4.91e-14 0 0 0 <1.00e-15 <1.51e-12
4 KEAP1 kelch-like ECH-associated protein 1 912683 96 95 85 2 24 28 13 9 22 0 4.66e-15 6.90e-11 0.017 0 0 <1.00e-15 <1.51e-12
5 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 2137011 86 72 38 3 3 13 8 28 34 0 1.44e-15 0.000194 0 0.000014 0 <1.00e-15 <1.51e-12
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 1213204 44 41 21 1 2 18 14 1 8 1 5.77e-15 0.000560 0 0.0065 0 <1.00e-15 <1.51e-12
7 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 451726 22 21 18 3 3 6 4 2 7 0 4.12e-06 0.269 6.8e-06 0 0 <1.00e-15 <1.51e-12
8 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 974172 17 17 17 0 0 5 5 4 3 0 0.000261 0.0351 0.000028 0.00049 0 <1.00e-15 <1.51e-12
9 POTEM POTE ankyrin domain family, member M 312390 13 13 13 2 0 7 4 1 1 0 0.000262 0.452 0 0.72 0 <1.00e-15 <1.51e-12
10 U2AF1 U2 small nuclear RNA auxiliary factor 1 443093 12 12 2 1 0 11 1 0 0 0 0.000337 0.111 0 2e-05 0 <1.00e-15 <1.51e-12
11 EMG1 EMG1 nucleolar protein homolog (S. cerevisiae) 358643 11 11 2 0 0 0 0 0 11 0 3.15e-05 1.000 0 0.94 0 <1.00e-15 <1.51e-12
12 ZNF595 zinc finger protein 595 1009299 7 7 5 6 0 5 0 0 2 0 0.990 0.979 1.4e-06 0.28 0 <1.00e-15 <1.51e-12
13 RBM10 RNA binding motif protein 10 1073502 37 35 35 2 1 5 0 0 31 0 4.77e-13 0.00407 0.4 0.0034 0.034 5.34e-13 7.43e-10
14 FSTL5 follistatin-like 5 1365825 53 45 52 3 3 25 11 6 8 0 1.67e-12 0.00111 0.11 0.74 0.17 8.32e-12 1.07e-08
15 OR4A5 olfactory receptor, family 4, subfamily A, member 5 505448 31 30 31 4 1 16 6 4 4 0 9.30e-12 0.0500 0.15 0.23 0.2 5.11e-11 6.16e-08
16 OR5D13 olfactory receptor, family 5, subfamily D, member 13 515537 35 32 35 4 1 17 10 6 1 0 4.39e-12 0.0210 0.57 0.2 0.54 6.61e-11 7.47e-08
17 RB1 retinoblastoma 1 (including osteosarcoma) 1393625 33 32 32 1 0 1 3 1 28 0 7.92e-11 0.0575 0.012 0.92 0.033 7.27e-11 7.73e-08
18 REG1B regenerating islet-derived 1 beta (pancreatic stone protein, pancreatic thread protein) 283328 23 22 23 2 1 14 2 2 4 0 1.31e-11 0.0230 0.69 0.088 0.25 9.04e-11 9.08e-08
19 LRRIQ3 leucine-rich repeats and IQ motif containing 3 979489 38 32 38 3 2 15 8 5 8 0 6.33e-10 0.0880 0.026 0.91 0.046 7.31e-10 6.95e-07
20 OR4C16 olfactory receptor, family 4, subfamily C, member 16 506644 35 32 34 6 1 15 12 3 4 0 1.09e-09 0.152 0.044 0.6 0.084 2.22e-09 2.01e-06
21 RGS7 regulator of G-protein signaling 7 827433 33 31 32 2 3 17 6 0 6 1 3.01e-10 0.0117 0.31 0.27 0.33 2.39e-09 2.05e-06
22 WDR49 WD repeat domain 49 1162480 37 36 37 3 2 12 13 3 6 1 1.99e-09 0.0438 0.045 0.28 0.074 3.49e-09 2.87e-06
23 POTEG POTE ankyrin domain family, member G 644380 37 36 34 6 3 19 7 2 5 1 6.18e-07 0.174 0.0005 0.98 0.0011 1.45e-08 1.14e-05
24 MUC7 mucin 7, secreted 622300 26 24 26 2 1 13 4 5 3 0 8.21e-09 0.0405 0.084 0.79 0.16 2.90e-08 2.18e-05
25 TAS2R1 taste receptor, type 2, member 1 490760 20 20 20 0 1 11 4 1 3 0 2.75e-09 0.00205 0.55 0.7 0.65 3.81e-08 2.75e-05
26 KIAA0408 KIAA0408 1145889 20 19 8 1 0 4 2 1 13 0 0.000565 0.516 1.2e-06 0.37 9.6e-06 1.09e-07 7.55e-05
27 FERD3L Fer3-like (Drosophila) 273884 21 21 19 3 0 12 3 2 4 0 9.97e-09 0.0456 0.5 0.43 0.6 1.19e-07 7.85e-05
28 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 1306090 20 19 13 0 0 13 4 2 1 0 0.00235 0.0114 2e-07 0.0066 2.6e-06 1.22e-07 7.85e-05
29 OR5W2 olfactory receptor, family 5, subfamily W, member 2 505839 27 26 25 4 1 15 8 2 1 0 4.08e-08 0.0830 0.16 0.35 0.18 1.44e-07 9.01e-05
30 ZNF804A zinc finger protein 804A 1984779 107 90 104 17 4 59 19 6 18 1 7.88e-09 0.0939 0.72 0.68 1 1.55e-07 9.09e-05
31 OR8K5 olfactory receptor, family 8, subfamily K, member 5 504960 21 21 20 2 0 12 5 2 2 0 4.90e-08 0.0472 0.83 0.044 0.16 1.56e-07 9.09e-05
32 LDB2 LIM domain binding 2 630229 23 21 22 1 3 6 7 2 5 0 4.23e-08 0.0186 0.32 0.14 0.28 2.28e-07 0.000129
33 GABRG2 gamma-aminobutyric acid (GABA) A receptor, gamma 2 796777 36 29 36 3 2 16 4 7 7 0 9.63e-08 0.00634 0.14 0.27 0.2 3.61e-07 0.000198
34 COL11A1 collagen, type XI, alpha 1 3066776 138 112 135 17 2 77 20 7 28 4 2.08e-07 0.0370 0.56 0.057 0.099 3.86e-07 0.000205
35 HBG2 hemoglobin, gamma G 201510 10 10 10 2 1 4 2 2 1 0 0.000124 0.280 0.00061 0.026 0.00019 4.40e-07 0.000227
STK11

Figure S1.  This figure depicts the distribution of mutations and mutation types across the STK11 significant gene.

TP53

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

KRAS

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

KEAP1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

EGFR

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

BRAF

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

CDKN2A

Figure S7.  This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

NFE2L2

Figure S8.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

POTEM

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

U2AF1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the U2AF1 significant gene.

ZNF595

Figure S11.  This figure depicts the distribution of mutations and mutation types across the ZNF595 significant gene.

RBM10

Figure S12.  This figure depicts the distribution of mutations and mutation types across the RBM10 significant gene.

FSTL5

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FSTL5 significant gene.

OR4A5

Figure S14.  This figure depicts the distribution of mutations and mutation types across the OR4A5 significant gene.

OR5D13

Figure S15.  This figure depicts the distribution of mutations and mutation types across the OR5D13 significant gene.

RB1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

REG1B

Figure S17.  This figure depicts the distribution of mutations and mutation types across the REG1B significant gene.

LRRIQ3

Figure S18.  This figure depicts the distribution of mutations and mutation types across the LRRIQ3 significant gene.

OR4C16

Figure S19.  This figure depicts the distribution of mutations and mutation types across the OR4C16 significant gene.

RGS7

Figure S20.  This figure depicts the distribution of mutations and mutation types across the RGS7 significant gene.

WDR49

Figure S21.  This figure depicts the distribution of mutations and mutation types across the WDR49 significant gene.

POTEG

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

MUC7

Figure S23.  This figure depicts the distribution of mutations and mutation types across the MUC7 significant gene.

TAS2R1

Figure S24.  This figure depicts the distribution of mutations and mutation types across the TAS2R1 significant gene.

KIAA0408

Figure S25.  This figure depicts the distribution of mutations and mutation types across the KIAA0408 significant gene.

FERD3L

Figure S26.  This figure depicts the distribution of mutations and mutation types across the FERD3L significant gene.

CTNNB1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the CTNNB1 significant gene.

OR5W2

Figure S28.  This figure depicts the distribution of mutations and mutation types across the OR5W2 significant gene.

ZNF804A

Figure S29.  This figure depicts the distribution of mutations and mutation types across the ZNF804A significant gene.

OR8K5

Figure S30.  This figure depicts the distribution of mutations and mutation types across the OR8K5 significant gene.

LDB2

Figure S31.  This figure depicts the distribution of mutations and mutation types across the LDB2 significant gene.

GABRG2

Figure S32.  This figure depicts the distribution of mutations and mutation types across the GABRG2 significant gene.

COL11A1

Figure S33.  This figure depicts the distribution of mutations and mutation types across the COL11A1 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: 39. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 309 356 296 194020 42333 0 0
2 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 86 293 70 159685 25575 0 0
3 LRP1B low density lipoprotein-related protein 1B (deleted in tumors) 333 18 8 9810 8 2e-13 2.7e-10
4 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 169 52 168 28340 2255476 3.2e-13 2.7e-10
5 MET met proto-oncogene (hepatocyte growth factor receptor) 22 34 9 18530 73 4.3e-13 2.7e-10
6 BRAF v-raf murine sarcoma viral oncogene homolog B1 44 89 34 48505 129957 4.6e-13 2.7e-10
7 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 22 332 21 180940 418 5.4e-13 2.7e-10
8 STK11 serine/threonine kinase 11 87 130 56 70850 153 5.6e-13 2.7e-10
9 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 20 138 14 75210 4768 5.9e-13 2.7e-10
10 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 30 220 23 119900 7945 6.1e-13 2.7e-10

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 ATRBRCAPATHWAY BRCA1 and 2 block cell cycle progression in response to DNA damage and promote double-stranded break repair; mutations induce breast cancer susceptibility. ATM, ATR, BRCA1, BRCA2, CHEK1, CHEK2, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, HUS1, MRE11A, NBS1, RAD1, RAD17, RAD50, RAD51, RAD9A, TP53, TREX1 21 ATM(53), ATR(26), BRCA1(22), BRCA2(31), CHEK1(7), CHEK2(10), FANCA(7), FANCC(2), FANCD2(4), FANCE(3), FANCF(4), FANCG(7), HUS1(4), MRE11A(13), RAD1(1), RAD17(6), RAD50(10), RAD51(2), RAD9A(2), TP53(309), TREX1(1) 35575939 524 354 387 37 58 144 83 68 166 5 <1.00e-15 <1.00e-15 <1.23e-13
2 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(9), ATM(53), BRCA1(22), CDKN1A(2), CHEK1(7), CHEK2(10), GADD45A(2), JUN(3), MAPK8(2), MDM2(5), MRE11A(13), NFKB1(6), NFKBIA(4), RAD50(10), RAD51(2), RBBP8(6), RELA(3), TP53(309), TP73(7) 23963460 475 347 337 35 59 126 70 56 159 5 <1.00e-15 <1.00e-15 <1.23e-13
3 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(10), ATM(53), BAX(3), BCL2(5), CCND1(3), CCNE1(7), CDK2(1), CDK4(3), CDKN1A(2), E2F1(3), GADD45A(2), MDM2(5), PCNA(1), RB1(33), TIMP3(4), TP53(309) 14566640 444 342 306 24 53 111 57 50 168 5 <1.00e-15 <1.00e-15 <1.23e-13
4 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(53), ATR(26), CDC25C(8), CHEK1(7), CHEK2(10), TP53(309), YWHAH(1) 12948811 414 334 278 13 51 105 51 52 150 5 <1.00e-15 <1.00e-15 <1.23e-13
5 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(2), IFNG(7), IFNGR1(7), IFNGR2(4), IKBKB(9), JAK2(16), LIN7A(7), NFKB1(6), NFKBIA(4), RB1(33), RELA(3), TNF(2), TNFRSF1B(2), TP53(309), USH1C(13), WT1(16) 14547980 440 329 304 37 54 114 55 41 172 4 <1.00e-15 <1.00e-15 <1.23e-13
6 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(53), ATR(26), CCNA1(7), CCND1(3), CCNE1(7), CDC25A(4), CDK2(1), CDK4(3), CDK6(5), CDKN1A(2), CDKN1B(5), CDKN2A(22), DHFR(2), E2F1(3), GSK3B(4), HDAC1(4), RB1(33), SKP2(3), TFDP1(10), TGFB1(3), TGFB2(10), TP53(309) 24262756 528 351 385 42 63 138 71 57 194 5 <1.00e-15 1.33e-15 1.37e-13
7 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), MAX(8), MYC(4), SP1(6), SP3(6), TP53(309), WT1(16) 5699587 353 306 218 16 48 95 38 36 133 3 <1.00e-15 1.89e-15 1.66e-13
8 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(7), DNAJC3(5), EIF2S2(3), NFKB1(6), NFKBIA(4), RELA(3), TP53(309) 7863806 337 303 203 17 43 87 37 38 129 3 <1.00e-15 2.22e-15 1.67e-13
9 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 AKT1(3), BCL2(5), EGFR(86), IGF1R(8), MYC(4), POLR2A(11), PPP2CA(1), PRKCA(10), RB1(33), TEP1(39), TERF1(4), TERT(7), TNKS(11), TP53(309), XRCC5(9) 22681635 540 351 356 50 62 137 64 70 204 3 <1.00e-15 2.44e-15 1.67e-13
10 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), ARF3(1), CCND1(3), CDK2(1), CDK4(3), CDKN1A(2), CDKN1B(5), CDKN2A(22), E2F1(3), E2F2(5), MDM2(5), NXT1(2), PRB1(5), TP53(309) 6739941 367 307 228 15 50 100 42 38 134 3 <1.00e-15 2.89e-15 1.77e-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 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(8), GOT1(3), GOT2(6), TAT(9), TYR(29) 3808360 55 53 55 9 8 22 11 6 8 0 0.033 0.6 1
2 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(3), GOT2(6), TAT(9) 2128311 18 18 18 2 5 7 3 2 1 0 0.076 0.62 1
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(8), IFNG(7), IL12A(2), IL12B(3), IL2(7) 2403481 27 26 27 5 1 16 0 1 8 1 0.2 0.73 1
4 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 6 ATM(53), ATR(26), CDC25C(8), CHEK1(7), CHEK2(10), YWHAH(1) 12280972 105 90 103 9 9 26 18 19 31 2 0.00048 0.79 1
5 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(7) 584333 7 7 7 3 2 1 0 2 2 0 0.74 0.93 1
6 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(6), SLPI(1) 1382720 7 7 6 1 1 2 1 1 2 0 0.35 0.93 1
7 HSA00031_INOSITOL_METABOLISM Genes involved in inositol metabolism ALDH6A1, TPI1 2 ALDH6A1(2), TPI1(9) 1324024 11 10 11 3 1 3 5 0 2 0 0.59 0.96 1
8 SULFUR_METABOLISM BPNT1, PAPSS1, PAPSS2, SULT1A2, SULT1A3, SULT1A3, SULT1A4, SULT1E1, SULT2A1, SUOX 7 BPNT1(7), PAPSS1(5), PAPSS2(10), SULT1A2(5), SULT1E1(11), SULT2A1(6), SUOX(5) 4954097 49 45 49 7 3 21 9 7 9 0 0.037 0.98 1
9 HSA00471_D_GLUTAMINE_AND_D_GLUTAMATE_METABOLISM Genes involved in D-glutamine and D-glutamate metabolism GLS, GLS2, GLUD1, GLUD2 4 GLS(8), GLS2(6), GLUD1(4), GLUD2(15) 3672284 33 31 33 5 0 17 9 2 5 0 0.13 0.98 1
10 ASBCELLPATHWAY B cells require interaction with helper T cells to produce antigen-specific immunoglobulins as a key element of the human immune response. CD28, CD4, CD80, HLA-DRA, HLA-DRB1, IL10, IL2, IL4, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 8 CD28(4), CD4(8), CD80(3), HLA-DRA(3), HLA-DRB1(5), IL10(2), IL2(7), IL4(1) 3223968 33 29 29 7 1 14 1 3 14 0 0.42 0.99 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)