Mutation Analysis (MutSig v1.5)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1N87831
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/C1N87831
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: HNSC-TP

  • Number of patients in set: 306

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:HNSC-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 111

  • Mutations seen in COSMIC: 485

  • Significantly mutated genes in COSMIC territory: 9

  • Genes with clustered mutations (≤ 3 aa apart): 574

  • Significantly mutated genesets: 67

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

Mutation Preprocessing

  • Read 306 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 74008

  • After removing 10 mutations outside chr1-24: 73998

  • After removing 5555 noncoding mutations: 68443

  • After collapsing adjacent/redundant mutations: 58338

Mutation Filtering

  • Number of mutations before filtering: 58338

  • After removing 1109 mutations outside gene set: 57229

  • After removing 56 mutations outside category set: 57173

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 1364
Frame_Shift_Ins 636
In_Frame_Del 433
In_Frame_Ins 83
Missense_Mutation 36408
Nonsense_Mutation 2886
Nonstop_Mutation 53
Silent 14249
Splice_Site 960
Translation_Start_Site 101
Total 57173
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 5999 498919062 0.000012 12 2.5 2.1
*Cp(A/C/T)->T 9133 4084447193 2.2e-06 2.2 0.47 1.7
C->(G/A) 14223 4583366255 3.1e-06 3.1 0.65 4.8
A->mut 7136 4404728973 1.6e-06 1.6 0.34 3.9
indel+null 6379 8988095228 7.1e-07 0.71 0.15 NaN
double_null 54 8988095228 6e-09 0.006 0.0013 NaN
Total 42924 8988095228 4.8e-06 4.8 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).

Figure 1. 

Distribution of Mutation Counts, Coverage, and Mutation Rates Across Samples

Figure 2.  Patients counts and rates file used to generate this plot: HNSC-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: C->(G/A)

  • 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: 111. 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 375773 246 214 153 5 41 27 39 40 92 7 <1.00e-15 <1.00e-15 <6.03e-12
2 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 4166666 80 72 80 2 1 5 7 6 53 8 3.65e-06 <1.00e-15 <6.03e-12
3 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1003706 65 64 24 0 1 40 6 17 1 0 6.29e-09 <1.00e-15 <6.03e-12
4 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 255389 66 66 32 0 2 2 2 6 53 1 6.52e-08 3.00e-15 1.36e-11
5 JUB jub, ajuba homolog (Xenopus laevis) 357659 19 18 19 1 1 2 0 2 14 0 0.0729 4.22e-15 1.53e-11
6 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 1904576 64 59 64 5 11 10 10 6 27 0 1.79e-05 5.44e-15 1.64e-11
7 CASP8 caspase 8, apoptosis-related cysteine peptidase 533487 27 27 24 0 1 4 2 5 15 0 0.000959 1.02e-14 2.64e-11
8 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 4343439 58 56 58 3 4 7 7 2 35 3 0.000398 8.44e-14 1.91e-10
9 POTEC POTE ankyrin domain family, member C 471221 18 18 17 1 4 4 4 5 1 0 0.0235 3.49e-13 7.03e-10
10 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 546479 18 17 13 0 0 4 10 4 0 0 0.0282 5.01e-11 9.06e-08
11 BAGE2 B melanoma antigen family, member 2 105801 12 11 9 2 0 6 2 2 1 1 0.129 4.80e-10 7.90e-07
12 NSD1 nuclear receptor binding SET domain protein 1 2490988 36 33 36 1 0 2 8 4 20 2 0.0169 2.29e-09 3.45e-06
13 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 198292 11 10 6 0 2 2 6 1 0 0 0.0221 2.61e-08 3.63e-05
14 B2M beta-2-microglobulin 113810 7 7 6 0 0 1 1 1 4 0 0.355 5.16e-08 6.67e-05
15 FBXW7 F-box and WD repeat domain containing 7 757876 16 15 14 1 2 2 5 3 4 0 0.179 8.66e-08 0.000104
16 POM121L12 POM121 transmembrane nucleoporin-like 12 264068 15 14 15 2 4 2 4 3 2 0 0.104 9.30e-08 0.000105
17 PRIM2 primase, DNA, polypeptide 2 (58kDa) 381394 12 12 10 1 0 2 3 1 6 0 0.396 1.93e-07 0.000197
18 RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small GTP binding protein Rac1) 189570 10 9 8 0 2 3 2 3 0 0 0.0351 1.96e-07 0.000197
19 NBPF1 neuroblastoma breakpoint family, member 1 1015878 20 19 14 2 0 4 4 3 9 0 0.0335 2.18e-07 0.000208
20 ZNF804B zinc finger protein 804B 1240408 22 21 22 2 4 5 6 5 2 0 0.0640 4.71e-07 0.000426
21 OR2T12 olfactory receptor, family 2, subfamily T, member 12 294908 11 11 11 1 2 2 2 3 2 0 0.104 5.36e-07 0.000462
22 CDH10 cadherin 10, type 2 (T2-cadherin) 736566 24 23 24 4 0 3 12 8 1 0 0.344 1.46e-06 0.00120
23 LCP1 lymphocyte cytosolic protein 1 (L-plastin) 593980 12 12 12 0 3 1 3 4 1 0 0.0391 1.99e-06 0.00157
24 PRAMEF11 PRAME family member 11 390027 10 10 9 1 2 1 5 2 0 0 0.270 2.15e-06 0.00158
25 KCNT2 potassium channel, subfamily T, member 2 1040701 17 17 16 1 2 1 6 3 5 0 0.142 2.18e-06 0.00158
26 EP300 E1A binding protein p300 2248955 25 25 22 1 3 7 4 5 6 0 0.00726 2.40e-06 0.00167
27 RASA1 RAS p21 protein activator (GTPase activating protein) 1 928769 14 14 12 0 2 0 3 2 7 0 0.0560 2.79e-06 0.00187
28 C9orf150 chromosome 9 open reading frame 150 166810 7 7 4 0 0 0 2 1 4 0 0.560 3.04e-06 0.00195
29 PRSS1 protease, serine, 1 (trypsin 1) 233784 8 8 7 1 0 4 1 2 1 0 0.168 3.13e-06 0.00195
30 REG1A regenerating islet-derived 1 alpha (pancreatic stone protein, pancreatic thread protein) 159337 8 8 8 0 0 1 5 2 0 0 0.151 3.72e-06 0.00221
31 FAM155A family with sequence similarity 155, member A 410401 12 12 12 0 2 2 4 2 2 0 0.0293 3.85e-06 0.00221
32 PEG3 paternally expressed 3 1345043 26 23 26 2 0 6 11 6 3 0 0.0764 3.98e-06 0.00221
33 ZNF99 zinc finger protein 99 949165 26 22 26 4 0 4 10 6 6 0 0.461 4.10e-06 0.00221
34 FCRL4 Fc receptor-like 4 485362 14 13 14 1 1 2 7 3 1 0 0.140 4.25e-06 0.00221
35 STEAP4 STEAP family member 4 425992 10 10 10 1 0 4 1 2 3 0 0.174 4.27e-06 0.00221
TP53

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

FAT1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

PIK3CA

Figure S3.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CDKN2A

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

JUB

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

NOTCH1

Figure S6.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

MLL2

Figure S7.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

POTEC

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

NFE2L2

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

NSD1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

HRAS

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

B2M

Figure S12.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

FBXW7

Figure S13.  This figure depicts the distribution of mutations and mutation types across the FBXW7 significant gene.

POM121L12

Figure S14.  This figure depicts the distribution of mutations and mutation types across the POM121L12 significant gene.

PRIM2

Figure S15.  This figure depicts the distribution of mutations and mutation types across the PRIM2 significant gene.

RAC1

Figure S16.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

NBPF1

Figure S17.  This figure depicts the distribution of mutations and mutation types across the NBPF1 significant gene.

ZNF804B

Figure S18.  This figure depicts the distribution of mutations and mutation types across the ZNF804B significant gene.

OR2T12

Figure S19.  This figure depicts the distribution of mutations and mutation types across the OR2T12 significant gene.

CDH10

Figure S20.  This figure depicts the distribution of mutations and mutation types across the CDH10 significant gene.

LCP1

Figure S21.  This figure depicts the distribution of mutations and mutation types across the LCP1 significant gene.

PRAMEF11

Figure S22.  This figure depicts the distribution of mutations and mutation types across the PRAMEF11 significant gene.

KCNT2

Figure S23.  This figure depicts the distribution of mutations and mutation types across the KCNT2 significant gene.

EP300

Figure S24.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

RASA1

Figure S25.  This figure depicts the distribution of mutations and mutation types across the RASA1 significant gene.

C9orf150

Figure S26.  This figure depicts the distribution of mutations and mutation types across the C9orf150 significant gene.

PRSS1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the PRSS1 significant gene.

REG1A

Figure S28.  This figure depicts the distribution of mutations and mutation types across the REG1A significant gene.

FAM155A

Figure S29.  This figure depicts the distribution of mutations and mutation types across the FAM155A significant gene.

PEG3

Figure S30.  This figure depicts the distribution of mutations and mutation types across the PEG3 significant gene.

FCRL4

Figure S31.  This figure depicts the distribution of mutations and mutation types across the FCRL4 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: 9. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 246 356 224 108936 45925 0 0
2 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 66 332 64 101592 2930 0 0
3 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 11 19 11 5814 2979 1.7e-13 2.5e-10
4 FBXW7 F-box and WD repeat domain containing 7 16 91 10 27846 183 7.2e-13 8.1e-10
5 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 65 220 55 67320 26369 1.4e-12 1.3e-09
6 CHEK2 CHK2 checkpoint homolog (S. pombe) 9 2 4 612 4 3e-12 2.3e-09
7 PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 6 33 4 10098 3 2.2e-07 0.00014
8 PTPN14 protein tyrosine phosphatase, non-receptor type 14 13 3 2 918 2 9.6e-06 0.0054
9 SCN9A sodium channel, voltage-gated, type IX, alpha subunit 10 4 2 1224 2 0.000017 0.0085
10 PTCH1 patched homolog 1 (Drosophila) 11 256 4 78336 5 0.00061 0.19

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
8624 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 65 0 331 628 650 331 628 650
11817 TP53 tumor protein p53 246 0 321 853 2124 321 853 2124
5212 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 11 0 18 45 45 18 45 45
7155 MUC4 mucin 4, cell surface associated 20 0 15 21 28 15 21 28
7457 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 18 0 13 38 60 13 38 60
6125 KRTAP4-11 keratin associated protein 4-11 12 0 8 10 16 8 10 16
4065 FBXW7 F-box and WD repeat domain containing 7 16 0 6 11 20 6 11 20
1577 C3orf59 chromosome 3 open reading frame 59 8 0 6 6 6 6 6 6
6645 MAPK1 mitogen-activated protein kinase 1 4 0 6 6 6 6 6 6
9422 RANGAP1 Ran GTPase activating protein 1 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: 67. 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 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 65 APAF1(9), ATM(9), ATR(19), BAI1(4), BAX(1), BID(2), CASP3(1), CASP8(27), CCNB1(3), CCNB3(5), CCND1(2), CCNE1(3), CCNE2(3), CCNG1(1), CCNG2(2), CDK4(4), CDK6(1), CDKN2A(66), CHEK1(1), CHEK2(9), DDB2(2), EI24(1), FAS(1), GADD45G(1), GTSE1(4), IGFBP3(1), LRDD(3), MDM2(2), MDM4(1), PERP(1), PMAIP1(2), PPM1D(2), PTEN(6), RCHY1(1), RFWD2(1), RRM2(1), RRM2B(1), SERPINE1(4), SESN3(1), SFN(5), SIAH1(1), STEAP3(2), THBS1(7), TNFRSF10B(1), TP53(246), TSC2(3) 29795051 473 249 340 38 57 62 73 90 183 8 <1.00e-15 <1.00e-15 <6.16e-14
2 G2PATHWAY Activated Cdc2-cyclin B kinase regulates the G2/M transition; DNA damage stimulates the DNA-PK/ATM/ATR kinases, which inactivate Cdc2. ATM, ATR, BRCA1, CCNB1, CDC2, CDC25A, CDC25B, CDC25C, CDC34, CDKN1A, CDKN2D, CHEK1, CHEK2, EP300, GADD45A, MDM2, MYT1, PLK, PRKDC, RPS6KA1, TP53, WEE1, YWHAH, YWHAQ 22 ATM(9), ATR(19), BRCA1(9), CCNB1(3), CDC25B(3), CDC34(1), CHEK1(1), CHEK2(9), EP300(25), MDM2(2), MYT1(7), PRKDC(15), RPS6KA1(4), TP53(246), WEE1(1), YWHAH(1), YWHAQ(1) 19102840 356 237 257 25 53 50 66 69 111 7 3.66e-15 <1.00e-15 <6.16e-14
3 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(9), ATR(19), BRCA1(9), BRCA2(11), CHEK1(1), CHEK2(9), FANCA(4), FANCC(2), FANCD2(3), FANCG(2), HUS1(2), MRE11A(1), RAD17(3), RAD50(5), RAD51(1), TP53(246), TREX1(2) 20066645 329 233 233 20 47 50 56 65 104 7 1.93e-14 <1.00e-15 <6.16e-14
4 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 ATM(9), ATR(19), CCNA1(4), CCND1(2), CCNE1(3), CDK4(4), CDK6(1), CDKN1B(2), CDKN2A(66), DHFR(3), GSK3B(1), RB1(10), SKP2(2), TFDP1(3), TGFB1(1), TGFB2(2), TP53(246) 13736583 378 233 251 19 48 43 56 61 162 8 <1.00e-15 <1.00e-15 <6.16e-14
5 ST_JNK_MAPK_PATHWAY JNKs are MAP kinases regulated by several levels of kinases (MAPKK, MAPKKK) and phosphorylate transcription factors and regulatory proteins. AKT1, ATF2, CDC42, DLD, DUSP10, DUSP4, DUSP8, GAB1, GADD45A, GCK, IL1R1, JUN, MAP2K4, MAP2K5, MAP2K7, MAP3K1, MAP3K10, MAP3K11, MAP3K12, MAP3K13, MAP3K2, MAP3K3, MAP3K4, MAP3K5, MAP3K7, MAP3K7IP1, MAP3K7IP2, MAP3K9, MAPK10, MAPK7, MAPK8, MAPK9, MYEF2, NFATC3, NR2C2, PAPPA, SHC1, TP53, TRAF6, ZAK 38 AKT1(2), ATF2(1), CDC42(1), DUSP10(2), DUSP4(1), GAB1(2), GCK(2), IL1R1(2), MAP2K4(1), MAP2K5(2), MAP3K1(3), MAP3K10(4), MAP3K11(1), MAP3K12(6), MAP3K13(8), MAP3K3(1), MAP3K4(6), MAP3K5(5), MAP3K7(4), MAP3K9(3), MAPK10(3), MAPK7(1), MAPK8(4), MAPK9(4), MYEF2(3), NFATC3(6), NR2C2(1), PAPPA(9), SHC1(1), TP53(246), TRAF6(1), ZAK(2) 22997165 338 232 245 30 52 50 70 53 106 7 3.57e-13 <1.00e-15 <6.16e-14
6 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(9), CDC25B(3), CDK4(4), CHEK1(1), MYT1(7), RB1(10), TP53(246), WEE1(1), YWHAH(1) 7991690 282 226 189 12 44 33 49 46 103 7 3.11e-15 <1.00e-15 <6.16e-14
7 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(11), AKT1(2), ATM(9), BAX(1), CPB2(3), CSNK1A1(1), FHL2(1), HIC1(1), HIF1A(2), IGFBP3(1), MAPK8(4), MDM2(2), NFKBIB(1), TP53(246) 9472034 285 220 192 19 45 34 54 47 98 7 6.34e-13 <1.00e-15 <6.16e-14
8 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(1), MYC(4), SP1(1), SP3(1), TP53(246) 3219260 253 214 160 7 41 28 42 42 93 7 <1.00e-15 <1.00e-15 <6.16e-14
9 IGF1RPATHWAY Insulin-like growth factor receptor IGF-1R promotes cell growth and inhibits apoptosis on binding of ligands IGF-1 and 2 via Ras activation and the AKT pathway. AKT1, BAD, GRB2, HRAS, IGF1R, IRS1, MAP2K1, MAPK1, MAPK3, PIK3CA, PIK3R1, RAF1, SHC1, SOS1, YWHAH 15 AKT1(2), BAD(1), HRAS(11), IGF1R(7), IRS1(1), MAP2K1(4), MAPK1(4), PIK3CA(65), PIK3R1(6), RAF1(2), SHC1(1), SOS1(8), YWHAH(1) 8655628 113 94 64 5 11 50 23 23 6 0 1.87e-11 <1.00e-15 <6.16e-14
10 GCRPATHWAY Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. ADRB2, AKT1, ANXA1, CALM1, CALM2, CALM3, CRN, GNAS, GNB1, GNGT1, HSPCA, NFKB1, NOS3, NPPA, NR3C1, PIK3CA, PIK3R1, RELA, SYT1 17 AKT1(2), ANXA1(1), CALM1(1), CALM3(1), GNAS(6), GNB1(2), NFKB1(2), NOS3(4), NPPA(1), NR3C1(5), PIK3CA(65), PIK3R1(6), RELA(1), SYT1(5) 8161012 102 89 61 4 12 48 12 25 5 0 1.42e-10 <1.00e-15 <6.16e-14

Table 7.  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 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(3), CYP2C9(5) 922599 8 8 8 0 0 3 4 1 0 0 0.087 0.057 1
2 HSA00627_1,4_DICHLOROBENZENE_DEGRADATION Genes involved in 1,4-dichlorobenzene degradation CMBL 1 CMBL(2) 231812 2 2 2 0 0 0 0 0 2 0 0.66 0.12 1
3 GSPATHWAY Activated G-protein coupled receptors stimulate cAMP production and thus activate protein kinase A, involved in a number of signal transduction pathways. ADCY1, GNAS, GNB1, GNGT1, PRKACA, PRKAR1A 6 ADCY1(12), GNAS(6), GNB1(2), PRKACA(4), PRKAR1A(2) 2991458 26 23 26 2 10 3 9 4 0 0 0.019 0.17 1
4 BLOOD_GROUP_GLYCOLIPID_BIOSYNTHESIS_NEOLACTOSERIES ABO, B3GNT1, FUT1, FUT2, FUT9, GCNT2, ST8SIA1 7 ABO(2), B3GNT1(1), FUT1(1), FUT2(2), FUT9(10), GCNT2(4), ST8SIA1(2) 2797416 22 21 22 4 2 7 10 2 1 0 0.12 0.2 1
5 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 7 CCNE1(3), CDC34(1), CUL1(6), RB1(10), TFDP1(3) 2976526 23 22 23 4 3 4 2 2 12 0 0.16 0.25 1
6 ACETAMINOPHENPATHWAY Acetaminophen selectively inhibits Cox-3, which is localized to the brain, and yields the toxic metabolite NAPQI when processed by CAR in the liver. CYP1A2, CYP2E1, CYP3A, NR1I3, PTGS1, PTGS2 5 CYP1A2(4), CYP2E1(5), PTGS1(6), PTGS2(2) 2433197 17 15 17 2 2 1 9 0 5 0 0.16 0.28 1
7 HSA00550_PEPTIDOGLYCAN_BIOSYNTHESIS Genes involved in peptidoglycan biosynthesis GLUL, PGLYRP2 2 GLUL(2), PGLYRP2(3) 829283 5 5 5 1 1 2 0 1 1 0 0.39 0.33 1
8 BETAOXIDATIONPATHWAY Beta-Oxidation of Fatty Acids ACADL, ACADM, ACADS, ACAT1, ECHS1, HADHA 6 ACADL(2), ACADM(3), ACADS(2), ECHS1(2), HADHA(3) 2467452 12 12 12 1 2 2 4 3 1 0 0.13 0.36 1
9 NUCLEOTIDE_SUGARS_METABOLISM GALE, GALT, TGDS, UGDH, UXS1 5 GALT(1), TGDS(2), UGDH(3), UXS1(2) 1758796 8 8 8 0 0 1 3 3 1 0 0.19 0.4 1
10 FXRPATHWAY The nuclear receptor transcription factors FXR and LXR are activated by cholesterol metabolites and regulate cholesterol homeostasis. FABP6, LDLR, NR0B2, NR1H3, NR1H4, RXRA 6 FABP6(2), LDLR(3), NR0B2(1), NR1H4(5), RXRA(4) 2480469 15 15 15 1 2 2 6 1 4 0 0.1 0.42 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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