Mutation Analysis (MutSig v2.0)
Thymoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C19K49QC
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/C19K49QC
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: THYM-TP

  • Number of patients in set: 123

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:THYM-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 10

  • Mutations seen in COSMIC: 25

  • Significantly mutated genes in COSMIC territory: 3

  • Significantly mutated genesets: 80

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

Mutation Preprocessing

  • Read 123 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 3057

  • After removing 59 mutations outside chr1-24: 2998

  • After removing 55 blacklisted mutations: 2943

  • After removing 455 noncoding mutations: 2488

Mutation Filtering

  • Number of mutations before filtering: 2488

  • After removing 192 mutations outside gene set: 2296

  • After removing 4 mutations outside category set: 2292

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_OutOfFrame 1
Frame_Shift_Del 137
Frame_Shift_Ins 55
In_Frame_Del 58
In_Frame_Ins 8
Missense_Mutation 1380
Nonsense_Mutation 89
Nonstop_Mutation 5
Silent 478
Splice_Site 78
Start_Codon_SNP 2
Stop_Codon_Del 1
Total 2292
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 451 201268466 2.2e-06 2.2 4.6 2.1
*Cp(A/C/T)->T 254 1676188437 1.5e-07 0.15 0.31 1.7
A->G 201 1820038090 1.1e-07 0.11 0.23 2.3
transver 476 3697494993 1.3e-07 0.13 0.26 5
indel+null 428 3697494993 1.2e-07 0.12 0.24 NaN
double_null 4 3697494993 1.1e-09 0.0011 0.0022 NaN
Total 1814 3697494993 4.9e-07 0.49 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: THYM-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.

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: A->G

  • n4 = number of nonsilent mutations of type: transver

  • 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: 10. 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 GTF2I general transcription factor II, i 269255 49 49 2 0 0 0 0 48 1 0 <1.00e-15 0.00028 0 1e-06 0 <1.00e-15 <1.84e-11
2 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 75629 10 10 8 0 0 0 2 7 1 0 6.55e-15 0.2 0.017 0.54 0.035 8.55e-15 7.88e-11
3 UNC93B1 unc-93 homolog B1 (C. elegans) 178091 5 5 2 0 0 5 0 0 0 0 9.72e-10 0.04 0.0011 1 0.0022 6.09e-11 3.74e-07
4 CAPNS1 calpain, small subunit 1 83653 3 3 1 0 0 0 0 0 3 0 4.73e-07 1 0.00011 0.7 0.00053 5.80e-09 2.67e-05
5 MUC4 mucin 4, cell surface associated 406625 5 5 5 1 0 2 0 3 0 0 3.50e-08 0.51 NaN NaN NaN 3.50e-08 0.000129
6 TP53 tumor protein p53 146078 4 4 4 0 1 0 0 2 1 0 5.07e-07 0.5 0.034 0.02 0.015 1.54e-07 0.000473
7 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 72078 3 3 3 0 0 0 1 2 0 0 5.75e-07 0.49 0.14 0.64 0.24 2.30e-06 0.00607
8 BACH1 BTB and CNC homology 1, basic leucine zipper transcription factor 1 258464 9 1 9 0 0 4 0 4 1 0 0.0478 0.11 0.000081 0.0037 0.000011 8.13e-06 0.0187
9 ATRN attractin 483826 3 3 2 0 0 0 0 0 3 0 0.000264 1 0.00063 0.96 0.0031 1.23e-05 0.0252
10 FOXD1 forkhead box D1 75470 2 2 1 0 0 0 0 0 2 0 2.22e-05 1 0.02 0.37 0.082 2.59e-05 0.0478
11 NF1 neurofibromin 1 (neurofibromatosis, von Recklinghausen disease, Watson disease) 1069864 3 3 3 0 0 1 0 1 1 0 0.00363 0.49 0.019 0.054 0.0074 0.000311 0.522
12 OPALIN oligodendrocytic myelin paranodal and inner loop protein 56820 1 1 1 0 1 0 0 0 0 0 0.000386 0.67 NaN NaN NaN 0.000386 0.592
13 REG1A regenerating islet-derived 1 alpha (pancreatic stone protein, pancreatic thread protein) 64043 1 1 1 0 1 0 0 0 0 0 0.000452 0.86 NaN NaN NaN 0.000452 0.641
14 TMEM63B transmembrane protein 63B 283908 2 2 2 0 0 1 0 0 1 0 0.00128 0.52 0.75 0.011 0.034 0.000487 0.641
15 CEBPA CCAAT/enhancer binding protein (C/EBP), alpha 41139 2 2 2 0 0 0 0 0 2 0 5.74e-05 1 0.83 0.79 1 0.000618 0.702
16 LGALS3BP lectin, galactoside-binding, soluble, 3 binding protein 188150 2 2 2 0 0 1 0 1 0 0 0.000199 0.43 0.083 0.57 0.29 0.000624 0.702
17 MUC21 mucin 21, cell surface associated 207776 2 2 1 1 0 0 2 0 0 0 0.000181 0.79 0.0099 0.94 0.35 0.000675 0.702
18 KRTAP4-8 keratin associated protein 4-8 69125 2 2 2 0 0 0 0 1 1 0 0.000119 0.86 0.14 0.58 0.54 0.000685 0.702
19 CCL25 chemokine (C-C motif) ligand 25 57624 1 1 1 0 0 0 1 0 0 0 0.000816 0.79 NaN NaN NaN 0.000816 0.792
20 GAGE13 G antigen 13 16895 1 1 1 0 0 0 0 0 1 0 0.00105 1 NaN NaN NaN 0.00105 0.967
21 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 86652 1 1 1 0 0 1 0 0 0 0 0.00135 0.73 NaN NaN NaN 0.00135 1.000
22 OR2D2 olfactory receptor, family 2, subfamily D, member 2 112327 1 1 1 0 1 0 0 0 0 0 0.00148 0.76 NaN NaN NaN 0.00148 1.000
23 CCDC3 coiled-coil domain containing 3 79577 1 1 1 0 0 0 0 1 0 0 0.00149 0.84 NaN NaN NaN 0.00149 1.000
24 FNBP4 formin binding protein 4 356486 2 2 1 0 0 0 0 0 2 0 0.000868 1 0.01 0.11 0.19 0.00157 1.000
25 BCOR BCL6 co-repressor 575158 3 3 3 1 0 0 0 1 1 1 0.000261 0.79 0.91 0.26 0.67 0.00169 1.000
26 MED6 mediator complex subunit 6 94787 1 1 1 0 0 1 0 0 0 0 0.00185 0.72 NaN NaN NaN 0.00185 1.000
27 OCIAD2 OCIA domain containing 2 60147 1 1 1 0 0 0 0 1 0 0 0.00186 0.86 NaN NaN NaN 0.00186 1.000
28 EIF1AX eukaryotic translation initiation factor 1A, X-linked 56920 1 1 1 0 0 0 1 0 0 0 0.00197 0.64 NaN NaN NaN 0.00197 1.000
29 NUDCD2 NudC domain containing 2 59811 1 1 1 0 0 0 0 0 1 0 0.00213 1 NaN NaN NaN 0.00213 1.000
30 SF3B1 splicing factor 3b, subunit 1, 155kDa 494214 2 2 1 1 0 0 2 0 0 0 0.00188 0.73 0.01 0.17 0.12 0.00214 1.000
31 OR4C3 olfactory receptor, family 4, subfamily C, member 3 122004 1 1 1 0 0 1 0 0 0 0 0.00215 0.6 NaN NaN NaN 0.00215 1.000
32 LBH limb bud and heart development homolog (mouse) 39703 1 1 1 0 0 0 1 0 0 0 0.00215 0.82 NaN NaN NaN 0.00215 1.000
33 RPL23A ribosomal protein L23a 59582 1 1 1 0 0 0 1 0 0 0 0.00222 0.73 NaN NaN NaN 0.00222 1.000
34 CIRBP cold inducible RNA binding protein 56211 1 1 1 0 0 1 0 0 0 0 0.00225 0.64 NaN NaN NaN 0.00225 1.000
35 PRB2 proline-rich protein BstNI subfamily 2 155338 1 1 1 0 1 0 0 0 0 0 0.00229 1 NaN NaN NaN 0.00229 1.000
GTF2I

Figure S1.  This figure depicts the distribution of mutations and mutation types across the GTF2I significant gene.

HRAS

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

UNC93B1

Figure S3.  This figure depicts the distribution of mutations and mutation types across the UNC93B1 significant gene.

CAPNS1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the CAPNS1 significant gene.

MUC4

Figure S5.  This figure depicts the distribution of mutations and mutation types across the MUC4 significant gene.

TP53

Figure S6.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

NRAS

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

BACH1

Figure S8.  This figure depicts the distribution of mutations and mutation types across the BACH1 significant gene.

ATRN

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

FOXD1

Figure S10.  This figure depicts the distribution of mutations and mutation types across the FOXD1 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: 3. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 10 19 9 2337 887 0 0
2 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 3 33 3 4059 2597 1.3e-09 3e-06
3 TP53 tumor protein p53 4 356 4 43788 2290 8.7e-09 0.000013
4 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 1 5 1 615 1492 0.0003 0.34
5 AXL AXL receptor tyrosine kinase 2 7 1 861 1 0.00042 0.38
6 CYLD cylindromatosis (turban tumor syndrome) 2 18 1 2214 1 0.0011 0.82
7 PRKDC protein kinase, DNA-activated, catalytic polypeptide 1 22 1 2706 1 0.0013 0.86
8 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 1 52 1 6396 14604 0.0031 1
9 KIT v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 1 240 1 29520 467 0.014 1
10 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 1 332 1 40836 24 0.02 1

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: 80. 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 HSA03022_BASAL_TRANSCRIPTION_FACTORS Genes involved in basal transcription factors GTF2A1, GTF2A1L, GTF2A2, GTF2B, GTF2E1, GTF2E2, GTF2F1, GTF2F2, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2I, GTF2IRD1, LOC391764, STON1, TAF1, TAF10, TAF12, TAF13, TAF1L, TAF2, TAF4, TAF4B, TAF5, TAF5L, TAF6, TAF6L, TAF7, TAF7L, TAF9, TAF9B, TBPL1, TBPL2 33 GTF2B(1), GTF2F1(1), GTF2I(49), TAF1L(1) 6593929 52 51 5 0 1 0 1 49 1 0 0.000085 4.9e-15 3e-12
2 RASPATHWAY Ras activation stimulates many signaling cascades, including PI3K/AKT activation to inhibit apoptosis. AKT1, ARHA, BAD, BCL2L1, CASP9, CDC42, CHUK, ELK1, H2AFX, HRAS, MAP2K1, MAPK3, MLLT7, NFKB1, PIK3CA, PIK3R1, RAC1, RAF1, RALA, RALBP1, RALGDS, RELA, RHOA 21 AKT1(1), HRAS(10), MAP2K1(1), PIK3R1(2), RALA(1) 3578670 15 15 13 1 0 1 3 8 3 0 0.14 3.7e-12 1.1e-09
3 LONGEVITYPATHWAY Caloric restriction in animals often increases lifespan, which may occur via decreased IGF receptor expression and consequent expression of stress-resistance proteins. AKT1, CAT, FOXO3A, GH1, GHR, HRAS, IGF1, IGF1R, PIK3CA, PIK3R1, SHC1, SOD1, SOD2, SOD3 12 AKT1(1), HRAS(10), PIK3R1(2) 2360634 13 13 11 0 0 1 2 7 3 0 0.06 6.4e-12 1.3e-09
4 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(1), HRAS(10), IRS1(1), MAP2K1(1), PIK3R1(2) 3422142 15 15 13 0 0 1 2 8 4 0 0.047 2e-11 3.1e-09
5 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 12 AKT1(1), HRAS(10), PIK3R1(2) 2748870 13 13 11 0 0 1 2 7 3 0 0.059 3.6e-11 4.3e-09
6 CDK5PATHWAY Cdk5, a regulatory kinase implicated in neuronal development, represses Mek1, which downregulates the MAP kinase pathway. CDK5, CDK5R1, DPM2, EGR1, HRAS, KLK2, MAP2K1, MAP2K2, MAPK1, MAPK3, NGFB, NGFR, RAF1 12 HRAS(10), MAP2K1(1) 1503463 11 11 9 0 0 0 2 8 1 0 0.13 4.2e-11 4.3e-09
7 RACCYCDPATHWAY Ras, Rac, and Rho coordinate to induce cyclin D1 expression and activate cdk2 to promote the G1/S transition. AKT1, ARHA, CCND1, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, E2F1, HRAS, MAPK1, MAPK3, NFKB1, NFKBIA, PAK1, PIK3CA, PIK3R1, RAC1, RAF1, RB1, RELA, TFDP1 22 AKT1(1), CDK6(1), HRAS(10), PIK3R1(2) 3678499 14 14 12 0 0 2 2 7 3 0 0.035 5.6e-11 5e-09
8 RECKPATHWAY RECK is a membrane-anchored inhibitor of matrix metalloproteinases, which are expressed by tumor cells and promote metastasis. HRAS, MMP14, MMP2, MMP9, RECK, TIMP1, TIMP2, TIMP3, TIMP4 9 HRAS(10), TIMP3(1) 1366578 11 11 9 0 0 0 2 7 2 0 0.11 6.5e-11 5e-09
9 GLEEVECPATHWAY The drug Gleevec specifically targets the abnormal bcr-abl protein, an apoptosis inhibitor present in chronic myeloid leukemia. AKT1, BCL2, BCR, CRKL, FOS, GRB2, HRAS, JAK2, JUN, MAP2K1, MAP2K4, MAP3K1, MAPK3, MAPK8, MYC, PIK3CA, PIK3R1, RAF1, SOS1, STAT1, STAT5A, STAT5B 22 AKT1(1), HRAS(10), MAP2K1(1), MAP3K1(1), PIK3R1(2), STAT5B(1) 5136298 16 16 14 0 0 1 3 9 3 0 0.03 1.8e-10 1.2e-08
10 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 HRAS(10), TP53(4) 3285463 14 14 12 0 1 0 2 9 2 0 0.065 2e-10 1.3e-08

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 BADPATHWAY When phosphorylated, BAD is inhibited by sequestration; when non-phosphorylated, it promotes apoptosis by inactivating pro-survival BCL-XL and BCL-2. ADCY1, AKT1, BAD, BAX, BCL2, BCL2L1, CSF2RB, IGF1, IGF1R, IL3, IL3RA, KIT, KITLG, PIK3CA, PIK3R1, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, YWHAH 22 AKT1(1), CSF2RB(1), KIT(1), PIK3R1(2), PRKAR2B(1) 3947301 6 6 6 0 1 1 0 2 2 0 0.17 0.002 0.5
2 RASPATHWAY Ras activation stimulates many signaling cascades, including PI3K/AKT activation to inhibit apoptosis. AKT1, ARHA, BAD, BCL2L1, CASP9, CDC42, CHUK, ELK1, H2AFX, HRAS, MAP2K1, MAPK3, MLLT7, NFKB1, PIK3CA, PIK3R1, RAC1, RAF1, RALA, RALBP1, RALGDS, RELA, RHOA 20 AKT1(1), MAP2K1(1), PIK3R1(2), RALA(1) 3503041 5 5 5 1 0 1 1 1 2 0 0.58 0.0026 0.5
3 HCMVPATHWAY Cytomegalovirus activates MAP kinase pathways in the host cell, inducing transcription of viral genes. AKT1, CREB1, MAP2K1, MAP2K2, MAP2K3, MAP2K6, MAP3K1, MAPK1, MAPK14, MAPK3, NFKB1, PIK3CA, PIK3R1, RB1, RELA, SP1 16 AKT1(1), MAP2K1(1), MAP3K1(1), PIK3R1(2) 3586945 5 5 5 0 0 1 1 1 2 0 0.24 0.0027 0.5
4 NFATPATHWAY Cardiac hypertrophy is induced by NF-ATc4 and GATA4, which are stimulated through calcineurin activated by CaMK. ACTA1, AGT, AKT1, CALM1, CALM2, CALM3, CALR, CAMK1, CAMK1G, CAMK4, CREBBP, CSNK1A1, CTF1, DTR, EDN1, ELSPBP1, F2, FGF2, FKBP1A, GATA4, GSK3B, HAND1, HAND2, HRAS, IGF1, LIF, MAP2K1, MAPK1, MAPK14, MAPK3, MAPK8, MEF2C, MYH2, NFATC1, NFATC2, NFATC3, NFATC4, NKX2-5, NPPA, PIK3CA, PIK3R1, PPP3CA, PPP3CB, PPP3CC, PRKACB, PRKACG, PRKAR1A, PRKAR1B, PRKAR2A, PRKAR2B, RAF1, RPS6KB1, SYT1 51 AKT1(1), CALM3(1), HAND2(1), MAP2K1(1), NFATC1(1), NFATC4(1), NKX2-5(1), PIK3R1(2), PRKAR2B(1) 8869101 10 9 10 0 2 2 0 2 4 0 0.078 0.0033 0.5
5 CTLA4PATHWAY T cell activation requires interaction with an antigen-MHC-I complex on an antigen-presenting cell (APC), as well as CD28 interaction with the APC's CD80 or 86. CD28, CD3D, CD3E, CD3G, CD3Z, CD80, CD86, CTLA4, GRB2, HLA-DRA, HLA-DRB1, ICOS, ICOSL, IL2, ITK, LCK, PIK3CA, PIK3R1, PTPN11, TRA@, TRB@ 17 CD3E(1), HLA-DRB1(1), PIK3R1(2) 2330360 4 4 4 0 0 0 0 1 3 0 0.54 0.004 0.5
6 MTORPATHWAY Mammalian target of rapamycin (mTOR) senses mitogenic factors and nutrients, including ATP, and induces cell proliferation. AKT1, EIF3S10, EIF4A1, EIF4A2, EIF4B, EIF4E, EIF4EBP1, EIF4G1, EIF4G2, EIF4G3, FKBP1A, FRAP1, MKNK1, PDK2, PDPK1, PIK3CA, PIK3R1, PPP2CA, PTEN, RPS6, RPS6KB1, TSC1, TSC2 21 AKT1(1), EIF4G3(1), MKNK1(1), PIK3R1(2), TSC2(1) 5043319 6 6 6 0 0 2 0 0 4 0 0.22 0.0067 0.59
7 GLEEVECPATHWAY The drug Gleevec specifically targets the abnormal bcr-abl protein, an apoptosis inhibitor present in chronic myeloid leukemia. AKT1, BCL2, BCR, CRKL, FOS, GRB2, HRAS, JAK2, JUN, MAP2K1, MAP2K4, MAP3K1, MAPK3, MAPK8, MYC, PIK3CA, PIK3R1, RAF1, SOS1, STAT1, STAT5A, STAT5B 21 AKT1(1), MAP2K1(1), MAP3K1(1), PIK3R1(2), STAT5B(1) 5060669 6 6 6 0 0 1 1 2 2 0 0.2 0.0068 0.59
8 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 14 AKT1(1), IRS1(1), MAP2K1(1), PIK3R1(2) 3346513 5 5 5 0 0 1 0 1 3 0 0.33 0.0087 0.67
9 BBCELLPATHWAY Fas ligand expression by T cells induces apoptosis in Fas-expressing, inactive B cells. CD28, CD4, HLA-DRA, HLA-DRB1, TNFRSF5, TNFRSF6, TNFSF5, TNFSF6 4 CD4(1), HLA-DRB1(1) 427975 2 2 2 0 0 0 0 0 2 0 1 0.011 0.69
10 RACCYCDPATHWAY Ras, Rac, and Rho coordinate to induce cyclin D1 expression and activate cdk2 to promote the G1/S transition. AKT1, ARHA, CCND1, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, E2F1, HRAS, MAPK1, MAPK3, NFKB1, NFKBIA, PAK1, PIK3CA, PIK3R1, RAC1, RAF1, RB1, RELA, TFDP1 21 AKT1(1), CDK6(1), PIK3R1(2) 3602870 4 4 4 0 0 2 0 0 2 0 0.25 0.012 0.69
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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