Mutation Analysis (MutSig v2.0)
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C11R6PW5
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/C11R6PW5
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: DLBC-TP

  • Number of patients in set: 48

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:DLBC-TP.final_analysis_set.maf

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

  • Significantly mutated genes (q ≤ 0.1): 55

  • Mutations seen in COSMIC: 60

  • Significantly mutated genes in COSMIC territory: 14

  • Significantly mutated genesets: 4

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

Mutation Preprocessing

  • Read 48 MAFs of type "maf1"

  • Total number of mutations in input MAFs: 16918

  • After removing 60 mutations outside chr1-24: 16858

  • After removing 219 blacklisted mutations: 16639

  • After removing 416 noncoding mutations: 16223

  • After collapsing adjacent/redundant mutations: 16219

Mutation Filtering

  • Number of mutations before filtering: 16219

  • After removing 950 mutations outside gene set: 15269

  • After removing 30 mutations outside category set: 15239

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 1
De_novo_Start_OutOfFrame 3
Frame_Shift_Del 175
Frame_Shift_Ins 78
In_Frame_Del 107
In_Frame_Ins 37
Missense_Mutation 8539
Nonsense_Mutation 309
Nonstop_Mutation 14
Silent 5559
Splice_Site 393
Start_Codon_Del 1
Start_Codon_SNP 17
Stop_Codon_Del 4
Stop_Codon_Ins 2
Total 15239
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 2279 89487814 0.000025 25 4.1 2.1
*Cp(A/C/T)->T 1913 705245959 2.7e-06 2.7 0.43 1.7
A->G 1465 750879567 2e-06 2 0.31 2.4
transver 2899 1545613340 1.9e-06 1.9 0.3 5
indel+null 1096 1545613340 7.1e-07 0.71 0.11 NaN
double_null 28 1545613340 1.8e-08 0.018 0.0029 NaN
Total 9680 1545613340 6.3e-06 6.3 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: DLBC-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: 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: 55. 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 IGLL5 immunoglobulin lambda-like polypeptide 5 29626 37 17 31 25 0 13 2 13 8 1 1 0.98 0 0.96 0 <1.00e-15 <3.74e-12
2 BTG2 BTG family, member 2 23234 20 13 17 5 0 4 1 11 4 0 3.4e-12 0.34 0 0.98 0 <1.00e-15 <3.74e-12
3 ZNF814 zinc finger protein 814 123757 13 7 4 1 0 5 0 8 0 0 1.3e-07 0.2 0 0.66 0 <1.00e-15 <3.74e-12
4 OSBPL10 oxysterol binding protein-like 10 106752 9 4 9 3 0 7 0 1 0 1 0.024 0.34 0 0.96 0 <1.00e-15 <3.74e-12
5 SGK1 serum/glucocorticoid regulated kinase 1 94332 24 4 19 4 0 9 0 12 1 2 0.000061 0.12 0 0.054 0 <1.00e-15 <3.74e-12
6 B2M beta-2-microglobulin 17374 15 13 13 0 0 0 4 7 4 0 9.6e-15 0.065 0.037 0.074 0.03 1.07e-14 3.32e-11
7 MYD88 myeloid differentiation primary response gene (88) 44453 7 7 4 0 0 1 1 0 5 0 2.2e-11 0.12 0.01 0.0053 0.0082 5.49e-12 1.47e-08
8 TMSB4X thymosin beta 4, X-linked 6858 7 6 7 0 0 0 0 4 3 0 3.9e-13 0.4 0.81 0.43 0.9 1.05e-11 2.44e-08
9 HIST1H1C histone cluster 1, H1c 31008 9 7 9 1 1 5 0 2 1 0 9.2e-11 0.16 0.019 0.43 0.047 1.18e-10 2.46e-07
10 CARD11 caspase recruitment domain family, member 11 168971 11 10 10 0 1 2 1 7 0 0 1.9e-08 0.041 0.00043 0.14 0.00041 2.04e-10 3.81e-07
11 P2RY8 purinergic receptor P2Y, G-protein coupled, 8 50186 9 8 9 0 1 2 2 4 0 0 2.8e-10 0.044 0.68 0.022 0.084 6.06e-10 1.03e-06
12 CD79B CD79b molecule, immunoglobulin-associated beta 33304 6 5 3 1 0 0 2 3 1 0 3.1e-08 0.74 0.0018 0.047 0.002 1.54e-09 2.40e-06
13 STAT3 signal transducer and activator of transcription 3 (acute-phase response factor) 115316 8 7 8 1 0 1 2 4 1 0 1.6e-07 0.43 0.0014 0.039 0.00088 3.25e-09 4.68e-06
14 HIST1H1E histone cluster 1, H1e 31582 13 9 11 3 0 7 0 5 1 0 2.7e-09 0.23 0.028 0.76 0.072 4.57e-09 6.11e-06
15 KLHL6 kelch-like 6 (Drosophila) 90912 7 7 6 0 1 2 3 1 0 0 5.1e-09 0.074 0.13 0.13 0.11 1.24e-08 1.55e-05
16 MUC2 mucin 2, oligomeric mucus/gel-forming 385696 13 12 12 3 2 3 1 5 2 0 0.00019 0.38 2e-07 1 0.000014 5.59e-08 6.53e-05
17 KRTAP4-5 keratin associated protein 4-5 26164 7 4 5 0 0 1 2 1 3 0 2e-06 0.33 0.00058 0.95 0.002 8.08e-08 8.89e-05
18 RHPN2 rhophilin, Rho GTPase binding protein 2 95835 7 7 3 0 1 5 0 1 0 0 7.4e-07 0.029 0.011 0.048 0.0073 1.08e-07 0.000112
19 IRF4 interferon regulatory factor 4 65761 9 6 9 3 0 2 2 5 0 0 0.00023 0.57 0.000026 0.25 0.000036 1.58e-07 0.000156
20 HRCT1 histidine rich carboxyl terminus 1 13776 4 4 3 0 0 0 0 4 0 0 2.1e-06 0.35 0.0018 0.96 0.0075 3.02e-07 0.000282
21 FAS Fas (TNF receptor superfamily, member 6) 49044 5 5 5 0 1 1 1 0 2 0 2.9e-07 0.24 0.081 0.11 0.061 3.30e-07 0.000294
22 GSTZ1 glutathione transferase zeta 1 (maleylacetoacetate isomerase) 32957 3 3 1 0 0 3 0 0 0 0 0.00067 0.18 0.00024 0.00092 0.000039 4.76e-07 0.000404
23 HIST1H1D histone cluster 1, H1d 32160 7 5 7 1 0 4 0 3 0 0 1.6e-07 0.26 0.11 0.57 0.2 5.90e-07 0.000480
24 TP53 tumor protein p53 62884 5 5 5 0 2 0 1 0 2 0 9.6e-07 0.22 0.11 0.033 0.04 6.97e-07 0.000523
25 HLA-C major histocompatibility complex, class I, C 53860 7 7 5 1 0 4 0 2 1 0 3.9e-08 0.22 0.56 0.99 1 7.00e-07 0.000523
26 IFITM3 interferon induced transmembrane protein 3 (1-8U) 18937 3 3 1 0 0 3 0 0 0 0 4e-05 0.14 0.00037 0.94 0.0012 8.65e-07 0.000622
27 IRF8 interferon regulatory factor 8 57788 6 5 5 1 0 1 2 1 2 0 4.1e-06 0.61 0.098 0.018 0.024 1.74e-06 0.00120
28 UBE2A ubiquitin-conjugating enzyme E2A (RAD6 homolog) 22951 4 4 4 0 0 0 0 0 4 0 2.4e-07 0.41 0.72 0.39 1 3.91e-06 0.00261
29 TNFAIP3 tumor necrosis factor, alpha-induced protein 3 111927 8 7 8 1 0 1 0 1 6 0 2.7e-07 0.75 0.96 0.57 1 4.31e-06 0.00278
30 ACTG1 actin, gamma 1 55101 6 4 6 0 1 0 0 4 1 0 0.00019 0.14 0.001 0.98 0.0021 6.42e-06 0.00400
31 MUC4 mucin 4, cell surface associated 171524 60 15 55 20 10 12 8 29 0 1 7.3e-06 0.34 NaN NaN NaN 7.27e-06 0.00439
32 HLA-A major histocompatibility complex, class I, A 53868 7 5 7 1 0 0 1 2 4 0 9.4e-06 0.5 0.032 0.97 0.07 1.00e-05 0.00584
33 SLC25A37 solute carrier family 25, member 37 48205 3 3 3 0 1 0 0 2 0 0 0.0022 0.42 0.00056 0.18 0.00042 1.37e-05 0.00775
34 ZNF208 zinc finger protein 208 130747 8 6 8 0 0 2 1 5 0 0 0.000017 0.17 0.042 0.42 0.066 1.62e-05 0.00894
35 KLF2 Kruppel-like factor 2 (lung) 21693 5 4 5 1 0 1 0 1 3 0 1.3e-06 0.39 0.79 1 1 1.85e-05 0.00991
BTG2

Figure S1.  This figure depicts the distribution of mutations and mutation types across the BTG2 significant gene.

ZNF814

Figure S2.  This figure depicts the distribution of mutations and mutation types across the ZNF814 significant gene.

OSBPL10

Figure S3.  This figure depicts the distribution of mutations and mutation types across the OSBPL10 significant gene.

SGK1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the SGK1 significant gene.

B2M

Figure S5.  This figure depicts the distribution of mutations and mutation types across the B2M significant gene.

MYD88

Figure S6.  This figure depicts the distribution of mutations and mutation types across the MYD88 significant gene.

HIST1H1C

Figure S7.  This figure depicts the distribution of mutations and mutation types across the HIST1H1C significant gene.

CARD11

Figure S8.  This figure depicts the distribution of mutations and mutation types across the CARD11 significant gene.

P2RY8

Figure S9.  This figure depicts the distribution of mutations and mutation types across the P2RY8 significant gene.

CD79B

Figure S10.  This figure depicts the distribution of mutations and mutation types across the CD79B significant gene.

STAT3

Figure S11.  This figure depicts the distribution of mutations and mutation types across the STAT3 significant gene.

HIST1H1E

Figure S12.  This figure depicts the distribution of mutations and mutation types across the HIST1H1E significant gene.

KLHL6

Figure S13.  This figure depicts the distribution of mutations and mutation types across the KLHL6 significant gene.

MUC2

Figure S14.  This figure depicts the distribution of mutations and mutation types across the MUC2 significant gene.

KRTAP4-5

Figure S15.  This figure depicts the distribution of mutations and mutation types across the KRTAP4-5 significant gene.

RHPN2

Figure S16.  This figure depicts the distribution of mutations and mutation types across the RHPN2 significant gene.

IRF4

Figure S17.  This figure depicts the distribution of mutations and mutation types across the IRF4 significant gene.

HRCT1

Figure S18.  This figure depicts the distribution of mutations and mutation types across the HRCT1 significant gene.

FAS

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

GSTZ1

Figure S20.  This figure depicts the distribution of mutations and mutation types across the GSTZ1 significant gene.

HIST1H1D

Figure S21.  This figure depicts the distribution of mutations and mutation types across the HIST1H1D significant gene.

TP53

Figure S22.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

HLA-C

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

IFITM3

Figure S24.  This figure depicts the distribution of mutations and mutation types across the IFITM3 significant gene.

IRF8

Figure S25.  This figure depicts the distribution of mutations and mutation types across the IRF8 significant gene.

UBE2A

Figure S26.  This figure depicts the distribution of mutations and mutation types across the UBE2A significant gene.

TNFAIP3

Figure S27.  This figure depicts the distribution of mutations and mutation types across the TNFAIP3 significant gene.

ACTG1

Figure S28.  This figure depicts the distribution of mutations and mutation types across the ACTG1 significant gene.

MUC4

Figure S29.  This figure depicts the distribution of mutations and mutation types across the MUC4 significant gene.

HLA-A

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

SLC25A37

Figure S31.  This figure depicts the distribution of mutations and mutation types across the SLC25A37 significant gene.

ZNF208

Figure S32.  This figure depicts the distribution of mutations and mutation types across the ZNF208 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: 14. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 ATM ataxia telangiectasia mutated 8 245 6 11760 32 2.1e-10 9.4e-07
2 TNFAIP3 tumor necrosis factor, alpha-induced protein 3 8 138 5 6624 9 9.9e-10 2.2e-06
3 SOCS1 suppressor of cytokine signaling 1 9 67 4 3216 14 6.7e-09 1e-05
4 TP53 tumor protein p53 5 356 5 17088 1887 1.1e-07 0.00012
5 RADIL Ras association and DIL domains 6 2 2 96 2 1.8e-07 0.00016
6 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 3 52 3 2496 14621 6.3e-07 0.00048
7 EZH2 enhancer of zeste homolog 2 (Drosophila) 6 6 2 288 116 1.6e-06 0.0011
8 JAK3 Janus kinase 3 (a protein tyrosine kinase, leukocyte) 2 18 2 864 5 0.000015 0.0083
9 MLH1 mutL homolog 1, colon cancer, nonpolyposis type 2 (E. coli) 5 49 2 2352 8 0.00011 0.054
10 ATP2A3 ATPase, Ca++ transporting, ubiquitous 2 1 1 48 1 0.0003 0.098

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: 4. 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 NKCELLSPATHWAY Natural killer (NK) lymphocytes are inhibited by MHC and activated by surface glycoproteins on tumor or virus-infected cells, which undergo perforin-mediated lysis. B2M, HLA-A, IL18, ITGB1, KLRC1, KLRC2, KLRC3, KLRC4, KLRD1, LAT, MAP2K1, MAPK3, PAK1, PIK3CA, PIK3R1, PTK2B, PTPN6, RAC1, SYK, VAV1 20 B2M(15), HLA-A(7), KLRC4(1), MAP2K1(2), PIK3CA(2), PTPN6(4) 1386527 31 21 29 2 2 1 7 11 10 0 0.03 5.9e-07 0.00036
2 CTLPATHWAY Cytotoxic T lymphocytes induce apoptosis in infected cells presenting antigen-MHC-I complexes via the perforin and Fas/Fas ligand pathways. B2M, CD3D, CD3E, CD3G, CD3Z, GZMB, HLA-A, ICAM1, ITGAL, ITGB2, PRF1, TNFRSF6, TNFSF6, TRA@, TRB@ 10 B2M(15), CD3D(1), CD3G(1), HLA-A(7), PRF1(2) 627337 26 17 24 5 2 1 5 9 9 0 0.29 0.000026 0.0079
3 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 CDKN1A(2), CDKN2A(1), E2F1(2), E2F2(1), PRB1(1), TP53(5) 608381 12 11 12 2 4 2 2 0 4 0 0.2 0.00031 0.063
4 NTHIPATHWAY Hemophilus influenzae infections activate NF-kB via several pathways, inducing the inflammatory response. CHUK, CREBBP, DUSP1, EP300, IKBKB, IL1B, IL8, MADH3, MADH4, MAP2K3, MAP2K6, MAP3K14, MAP3K7, MAPK11, MAPK14, MYD88, NFKB1, NFKBIA, NR3C1, RELA, TGFBR1, TGFBR2, TLR2, TNF 22 CREBBP(6), EP300(3), IKBKB(2), MAP2K3(2), MAPK11(1), MYD88(7), NFKB1(1), NFKBIA(3), TLR2(2), TNF(3) 2183744 30 26 27 6 4 2 5 8 11 0 0.1 0.00049 0.076
5 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 EIF2S2(1), NFKB1(1), NFKBIA(3), TP53(5) 751321 10 9 10 2 4 0 2 1 3 0 0.29 0.0032 0.4
6 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(8), ATR(2), CDC25C(2), CHEK2(2), TP53(5) 1143073 19 14 17 3 3 3 6 4 2 1 0.13 0.0045 0.42
7 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 7 GNGT1(1), PLCB1(5), TUB(2) 517190 8 7 8 0 2 0 1 2 3 0 0.17 0.0053 0.42
8 PKCPATHWAY Gq-coupled receptors promote hydrolysis of PIP2 to DAG and IP3, which causes calcium influx and activates protein kinase C. GNAQ, NFKB1, NFKBIA, PLCB1, PRKCA, PRKCB1, RELA 6 NFKB1(1), NFKBIA(3), PLCB1(5) 608492 9 8 9 2 1 0 1 3 4 0 0.53 0.0055 0.42
9 PPARGPATHWAY PPAR-gamma is a nuclear hormone receptor that is activated by fatty acids and regulates transcription through co-activations like Src-1 and Tif2. CREBBP, EP300, LPL, NCOA1, NCOA2, PPARBP, PPARG, PPARGC1, RXRA 7 CREBBP(6), EP300(3), NCOA1(1), NCOA2(1), PPARG(1) 1337157 12 11 12 1 1 1 3 5 2 0 0.14 0.0072 0.49
10 SA_DIACYLGLYCEROL_SIGNALING DAG (diacylglycerol) signaling activity ESR1, ESR2, ITPKA, PDE1A, PDE1B, PLCB1, PLCB2, PRL, TRH, VIP 10 ESR2(1), ITPKA(1), PDE1B(1), PLCB1(5) 818032 8 8 8 1 0 2 1 2 3 0 0.33 0.0088 0.54

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 TUBBYPATHWAY Tubby is activated by phospholipase C activity and hydrolysis of PIP2, after which it enters the nucleus and regulates transcription. CHRM1, GNAQ, GNB1, GNGT1, HTR2C, PLCB1, TUB 7 GNGT1(1), PLCB1(5), TUB(2) 517190 8 7 8 0 2 0 1 2 3 0 0.17 0.0053 1
2 PKCPATHWAY Gq-coupled receptors promote hydrolysis of PIP2 to DAG and IP3, which causes calcium influx and activates protein kinase C. GNAQ, NFKB1, NFKBIA, PLCB1, PRKCA, PRKCB1, RELA 6 NFKB1(1), NFKBIA(3), PLCB1(5) 608492 9 8 9 2 1 0 1 3 4 0 0.53 0.0055 1
3 PPARGPATHWAY PPAR-gamma is a nuclear hormone receptor that is activated by fatty acids and regulates transcription through co-activations like Src-1 and Tif2. CREBBP, EP300, LPL, NCOA1, NCOA2, PPARBP, PPARG, PPARGC1, RXRA 7 CREBBP(6), EP300(3), NCOA1(1), NCOA2(1), PPARG(1) 1337157 12 11 12 1 1 1 3 5 2 0 0.14 0.0072 1
4 SA_DIACYLGLYCEROL_SIGNALING DAG (diacylglycerol) signaling activity ESR1, ESR2, ITPKA, PDE1A, PDE1B, PLCB1, PLCB2, PRL, TRH, VIP 10 ESR2(1), ITPKA(1), PDE1B(1), PLCB1(5) 818032 8 8 8 1 0 2 1 2 3 0 0.33 0.0088 1
5 SETPATHWAY Cytotoxic T cells release perforin, which to allow entry into target cells of granzyme B, which activates caspases, and granzyme A, which induces caspase-independent apoptosis. ANP32A, APEX1, CREBBP, DFFA, DFFB, GZMA, GZMB, HMGB2, NME1, PRF1, SET 11 CREBBP(6), DFFA(1), HMGB2(1), PRF1(2) 788678 10 10 10 2 3 0 2 3 2 0 0.36 0.013 1
6 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(2) 51556 2 2 2 0 1 0 0 1 0 0 0.59 0.016 1
7 TCRMOLECULE T Cell Receptor and CD3 Complex CD3D, CD3E, CD3G, CD3Z, TRA@, TRB@ 3 CD3D(1), CD3G(1) 84242 2 2 2 0 0 1 0 0 1 0 0.41 0.022 1
8 IL17PATHWAY Activated T cells secrete IL-17, which stimulates fibroblasts and other cells to secrete inflammatory and hematopoietic cytokines. CD2, CD34, CD3D, CD3E, CD3G, CD3Z, CD4, CD58, CD8A, CSF3, IL17, IL3, IL6, IL8, KITLG, TRA@, TRB@ 13 CD3D(1), CD3G(1), CD58(1), IL6(2), KITLG(1) 460709 6 5 6 1 1 1 1 1 2 0 0.37 0.025 1
9 IL18PATHWAY Pro-inflammatory IL-18 is activated in macrophages by caspase-1 cleavage and, in conjunction with IL-12, stimulates Th1 cell differentiation. CASP1, IFNG, IL12A, IL12B, IL18, IL2 6 CASP1(1), IL12B(2) 222942 3 3 2 0 2 0 0 0 1 0 0.3 0.049 1
10 HSA00300_LYSINE_BIOSYNTHESIS Genes involved in lysine biosynthesis AADAT, AASDHPPT, AASS, KARS 4 AASDHPPT(2), AASS(2) 342070 4 4 4 0 0 1 1 1 1 0 0.38 0.05 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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