Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1833QBW
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1833QBW
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 and MutSigCV v0.9 merged result 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): 39

  • Mutations seen in COSMIC: 485

  • Significantly mutated genes in COSMIC territory: 9

  • Significantly mutated genesets: 67

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_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: 39. 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_clust p_cons p_joint p_cv p q
1 POLDIP2 polymerase (DNA-directed), delta interacting protein 2 259479 6 6 2 0 0 0 0 0 6 0 0 1 0 1 0 0
2 NSD1 nuclear receptor binding SET domain protein 1 2490988 36 33 36 1 0 2 8 4 20 2 0.0051 0.041 0.007 0 0 0
3 NUDT11 nudix (nucleoside diphosphate linked moiety X)-type motif 11 123243 6 6 1 1 0 0 0 0 6 0 0 0.99 0 1 0 0
4 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1003706 65 64 24 0 1 40 6 17 1 0 0 0.000073 0 5e-15 0 0
5 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 255389 66 66 32 0 2 2 2 6 53 1 0 0 0 6e-15 0 0
6 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 198292 11 10 6 0 2 2 6 1 0 0 0 0.00082 0 5.6e-07 0 0
7 TP53 tumor protein p53 375773 246 214 153 5 41 27 39 40 92 7 0 0 0 2.4e-15 0 0
8 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 546479 18 17 13 0 0 4 10 4 0 0 0 2e-07 0 5.3e-08 0 0
9 NOTCH1 Notch homolog 1, translocation-associated (Drosophila) 1904576 64 59 64 5 11 10 10 6 27 0 0.00079 0.5 0.002 1.6e-15 1.1e-16 2.2e-13
10 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 4166666 80 72 80 2 1 5 7 6 53 8 0.27 0.012 0.031 1e-15 1.2e-15 2.2e-12
11 CASP8 caspase 8, apoptosis-related cysteine peptidase 533487 27 27 24 0 1 4 2 5 15 0 0.49 0.015 0.078 3.3e-15 9.7e-15 1.6e-11
12 MLL2 myeloid/lymphoid or mixed-lineage leukemia 2 4343439 58 56 58 3 4 7 7 2 35 3 0.31 0.15 0.21 4.8e-15 3.6e-14 5.4e-11
13 JUB jub, ajuba homolog (Xenopus laevis) 357659 19 18 19 1 1 2 0 2 14 0 0.19 0.33 0.28 7.9e-15 7.5e-14 1e-10
14 FBXW7 F-box and WD repeat domain containing 7 757876 16 15 14 1 2 2 5 3 4 0 3.2e-06 0.58 0.000012 1.2e-07 4e-11 5.2e-08
15 EPHA2 EPH receptor A2 868017 16 14 15 0 3 0 1 1 10 1 0.1 0.23 0.085 1.6e-10 3.6e-10 4.4e-07
16 ZNF750 zinc finger protein 750 666533 15 13 14 1 1 2 2 2 8 0 0.00053 0.0097 4e-05 5.5e-07 5.6e-10 6.3e-07
17 FLG filaggrin 3674091 59 48 59 9 8 12 25 6 7 1 0.014 0.22 0.017 1.9e-09 7.8e-10 8.3e-07
18 B2M beta-2-microglobulin 113810 7 7 6 0 0 1 1 1 4 0 0.37 0.21 0.44 2e-09 1.9e-08 0.000019
19 HLA-A major histocompatibility complex, class I, A 335447 14 14 9 4 0 0 0 6 8 0 0.0014 0.64 0.0035 7.7e-07 5.6e-08 0.000053
20 EP300 E1A binding protein p300 2248955 25 25 22 1 3 7 4 5 6 0 0.0018 0.11 0.0024 4.6e-06 2.1e-07 0.00019
21 IL32 interleukin 32 162670 4 4 2 0 0 0 0 0 4 0 0.000023 0.9 0.0002 0.000064 2.4e-07 0.00021
22 RHOA ras homolog gene family, member A 182942 4 4 1 0 0 0 4 0 0 0 1.2e-06 0.058 2.2e-06 0.025 9.7e-07 0.00079
23 CTCF CCCTC-binding factor (zinc finger protein) 679423 13 11 13 1 1 2 5 0 5 0 0.026 0.22 0.035 5.8e-06 3.3e-06 0.0026
24 RB1 retinoblastoma 1 (including osteosarcoma) 790351 10 10 10 2 0 1 1 0 8 0 0.57 0.13 0.45 1.3e-06 9.1e-06 0.0068
25 CSMD3 CUB and Sushi multiple domains 3 3506307 88 70 87 17 6 15 35 18 13 1 0.51 0.71 0.57 1.2e-06 1e-05 0.0075
26 TGFBR2 transforming growth factor, beta receptor II (70/80kDa) 526462 11 10 9 1 1 1 0 2 7 0 0.37 0.55 0.5 1.7e-06 0.000013 0.0091
27 NECAB1 N-terminal EF-hand calcium binding protein 1 176105 6 6 6 2 0 0 2 0 3 1 0.81 0.89 1 1.3e-06 0.000019 0.013
28 MAPK1 mitogen-activated protein kinase 1 303224 4 4 1 0 3 0 0 0 1 0 0.000067 0.22 0.00022 0.0095 0.000029 0.019
29 PLSCR1 phospholipid scramblase 1 302255 5 5 4 0 0 0 2 0 3 0 0.0043 0.96 0.01 0.00031 0.000044 0.027
30 CNPY3 canopy 3 homolog (zebrafish) 204182 3 3 1 0 0 0 0 0 3 0 0.00012 0.64 0.00076 0.006 6e-05 0.036
31 EPB41L3 erythrocyte membrane protein band 4.1-like 3 1022950 16 16 16 5 3 0 6 4 3 0 0.0099 0.94 0.023 0.0002 0.000061 0.036
32 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 0.4 0.3 0.34 0.000015 0.000067 0.038
33 RANGAP1 Ran GTPase activating protein 1 514178 4 4 1 0 0 0 0 4 0 0 1.4e-06 0.94 6.2e-06 1 0.000081 0.044
34 ZCCHC3 zinc finger, CCHC domain containing 3 214314 5 5 1 0 0 0 0 0 5 0 0 1 6.4e-06 1 0.000083 0.044
35 CUL3 cullin 3 703996 10 10 10 1 1 1 3 2 3 0 0.077 0.54 0.12 0.000063 0.000099 0.051
POLDIP2

Figure S1.  This figure depicts the distribution of mutations and mutation types across the POLDIP2 significant gene.

NSD1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the NSD1 significant gene.

NUDT11

Figure S3.  This figure depicts the distribution of mutations and mutation types across the NUDT11 significant gene.

PIK3CA

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

CDKN2A

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

HRAS

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

TP53

Figure S7.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NFE2L2

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

NOTCH1

Figure S9.  This figure depicts the distribution of mutations and mutation types across the NOTCH1 significant gene.

FAT1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the FAT1 significant gene.

MLL2

Figure S11.  This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

JUB

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

FBXW7

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

EPHA2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the EPHA2 significant gene.

ZNF750

Figure S15.  This figure depicts the distribution of mutations and mutation types across the ZNF750 significant gene.

FLG

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

B2M

Figure S17.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

HLA-A

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

EP300

Figure S19.  This figure depicts the distribution of mutations and mutation types across the EP300 significant gene.

IL32

Figure S20.  This figure depicts the distribution of mutations and mutation types across the IL32 significant gene.

RHOA

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

CTCF

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

RB1

Figure S23.  This figure depicts the distribution of mutations and mutation types across the RB1 significant gene.

CSMD3

Figure S24.  This figure depicts the distribution of mutations and mutation types across the CSMD3 significant gene.

TGFBR2

Figure S25.  This figure depicts the distribution of mutations and mutation types across the TGFBR2 significant gene.

NECAB1

Figure S26.  This figure depicts the distribution of mutations and mutation types across the NECAB1 significant gene.

MAPK1

Figure S27.  This figure depicts the distribution of mutations and mutation types across the MAPK1 significant gene.

PLSCR1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the PLSCR1 significant gene.

CNPY3

Figure S29.  This figure depicts the distribution of mutations and mutation types across the CNPY3 significant gene.

EPB41L3

Figure S30.  This figure depicts the distribution of mutations and mutation types across the EPB41L3 significant gene.

RAC1

Figure S31.  This figure depicts the distribution of mutations and mutation types across the RAC1 significant gene.

RANGAP1

Figure S32.  This figure depicts the distribution of mutations and mutation types across the RANGAP1 significant gene.

ZCCHC3

Figure S33.  This figure depicts the distribution of mutations and mutation types across the ZCCHC3 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)

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: 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
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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