Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Adrenocortical Carcinoma (Primary solid tumor)
16 April 2014 | analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1V69H5R
Maintained by Dan DiCara (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result). Broad Institute of MIT and Harvard. doi:10.7908/C1V69H5R
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: ACC-TP

- Number of patients in set: 91

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:ACC-TP.final_analysis_set.maf

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

- Significantly mutated genes (q ≤ 0.1): 146

- Mutations seen in COSMIC: 61

- Significantly mutated genes in COSMIC territory: 4

- Significantly mutated genesets: 19

Mutation Preprocessing

- Read 91 MAFs of type "Baylor-Illumina"

- Total number of mutations in input MAFs: 22072

- After removing 127 mutations outside chr1-24: 21945

- After removing 1384 blacklisted mutations: 20561

- After removing 1399 noncoding mutations: 19162

- After collapsing adjacent/redundant mutations: 19152

Mutation Filtering

- Number of mutations before filtering: 19152

- After removing 1118 mutations outside gene set: 18034

- After removing 67 mutations outside category set: 17967

- After removing 1 "impossible" mutations in

- gene-patient-category bins of zero coverage: 16781

Results
Breakdown of Mutations by Type

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

type | count
--- | ---
Frame_Shift_Del | 514
Frame_Shift_Ins | 186
In_Frame_Del | 265
In_Frame_Ins | 88
Missense_Mutation | 10304
Nonsense_Mutation | 581
Silent | 5784
Splice_Site | 244
Translation_Start_Site | 1
Total | 17967

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 | 2031 | 161241575 | 0.000013 | 13 | 2.9 | 2.1
*CpG->(G/A) | 717 | 161241575 | 4.4e-06 | 4.4 | 1 | 2.7
*Cp(A/C/T)->mut | 4997 | 1299803062 | 3.8e-06 | 3.8 | 0.9 | 3.3
A->mut | 2560 | 1387389109 | 1.8e-06 | 1.8 | 0.43 | 3.9
indel+null | 1814 | 2848433746 | 6.4e-07 | 0.64 | 0.15 | NaN
double_null | 64 | 2848433746 | 2.2e-08 | 0.022 | 0.0053 | NaN
Total | 12183 | 2848433746 | 4.3e-06 | 4.3 | 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: ACC-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: *CpG->(G/A)

- n3 = number of nonsilent mutations of type: *Cp(A/C/T)->mut

- 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: 146. 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 | CLIC6 | chloride intracellular channel 6 | 79382 | 11 | 11 | 1 | 15 | 0 | 0 | 11 | 0 | 0 | 0 | 0 | 1 | 0 | 6.1e-06 | 0 | 0
2 | NMU | neuromedin U | 40191 | 10 | 10 | 2 | 0 | 0 | 10 | 0 | 0 | 0 | 0 | 0 | 0.93 | 0 | 5.6e-10 | 0 | 0
3 | LPPR2 |  | 101275 | 6 | 6 | 1 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 0.00031 | 0 | 0.0024 | 0 | 0
4 | CHDH | choline dehydrogenase | 124429 | 6 | 6 | 1 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0.99 | 0 | 0.00074 | 0 | 0
5 | C4orf32 | chromosome 4 open reading frame 32 | 22750 | 9 | 9 | 1 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 1 | 0 | 7.9e-10 | 0 | 0
6 | SYT8 | synaptotagmin VIII | 100867 | 14 | 14 | 3 | 0 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00066 | 0 | 8.3e-09 | 0 | 0
7 | RINL | Ras and Rab interactor-like | 104087 | 19 | 19 | 1 | 0 | 0 | 0 | 19 | 0 | 0 | 0 | 0 | 0.53 | 0 | 1.6e-15 | 0 | 0
8 | OBSCN | obscurin, cytoskeletal calmodulin and titin-interacting RhoGEF | 2188627 | 35 | 29 | 16 | 12 | 25 | 1 | 7 | 1 | 1 | 0 | 0 | 0.99 | 0 | 0.63 | 0 | 0
9 | MAP1S | microtubule-associated protein 1S | 205357 | 9 | 9 | 1 | 4 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0.0095 | 0 | 0.00029 | 0 | 0
10 | GPRIN2 | G protein regulated inducer of neurite outgrowth 2 | 119062 | 11 | 11 | 2 | 1 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 0.3 | 0 | 5.9e-07 | 0 | 0
11 | ATP9B | ATPase, class II, type 9B | 316748 | 5 | 5 | 1 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 0 | 0.33 | 0 | 0
12 | RREB1 | ras responsive element binding protein 1 | 425349 | 11 | 11 | 1 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 0 | 0.75 | 0 | 0.025 | 0 | 0
13 | IDUA | iduronidase, alpha-L- | 117428 | 15 | 15 | 4 | 1 | 2 | 0 | 0 | 13 | 0 | 0 | 0 | 0.0015 | 0 | 6.2e-09 | 0 | 0
14 | RGS9BP | regulator of G protein signaling 9 binding protein | 19133 | 11 | 11 | 1 | 0 | 0 | 11 | 0 | 0 | 0 | 0 | 0 | 0.89 | 0 | 1 | 0 | 0
15 | WDR34 | WD repeat domain 34 | 132945 | 11 | 11 | 1 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 1 | 0 | 0.14 | 0 | 0
16 | NOTCH2 | Notch homolog 2 (Drosophila) | 679200 | 12 | 12 | 1 | 0 | 0 | 12 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0.011 | 0 | 0
17 | TMEM189 | transmembrane protein 189 | 64792 | 12 | 12 | 1 | 0 | 0 | 0 | 0 | 12 | 0 | 0 | 0 | 1 | 0 | 1.7e-10 | 0 | 0
18 | TAF5 | TAF5 RNA polymerase II, TATA box binding protein (TBP)-associated factor, 100kDa | 176695 | 12 | 12 | 1 | 0 | 0 | 0 | 0 | 12 | 0 | 0 | 0 | 1 | 0 | 0.0004 | 0 | 0
19 | LRP11 | low density lipoprotein receptor-related protein 11 | 83134 | 9 | 9 | 1 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 | 0.9 | 0 | 2e-06 | 0 | 0
20 | FPGS | folylpolyglutamate synthase | 137611 | 14 | 14 | 2 | 0 | 0 | 0 | 1 | 13 | 0 | 0 | 0 | 1 | 0 | 2.3e-12 | 0 | 0
21 | BAG1 | BCL2-associated athanogene | 79437 | 6 | 6 | 1 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 0.97 | 0 | 0.0082 | 0 | 0
22 | FZD1 | frizzled homolog 1 (Drosophila) | 146857 | 6 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 0 | 5e-08 | 0 | 0
23 | TOR3A | torsin family 3, member A | 97918 | 25 | 25 | 1 | 0 | 0 | 0 | 0 | 25 | 0 | 0 | 0 | 1 | 0 | 1.3e-14 | 0 | 0
24 | TMEM200C | transmembrane protein 200C | 87981 | 6 | 6 | 2 | 0 | 0 | 0 | 1 | 5 | 0 | 0 | 0 | 0.99 | 0 | 0.00036 | 0 | 0
25 | ZNF517 | zinc finger protein 517 | 113936 | 34 | 33 | 2 | 0 | 0 | 0 | 0 | 34 | 0 | 0 | 0 | 1 | 0 | 6.2e-15 | 0 | 0
26 | DMRT1 | doublesex and mab-3 related transcription factor 1 | 89882 | 5 | 5 | 1 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 0 | 0.00024 | 0 | 0
27 | GLTPD2 | glycolipid transfer protein domain containing 2 | 42681 | 19 | 19 | 1 | 2 | 0 | 19 | 0 | 0 | 0 | 0 | 0 | 0.16 | 0 | 1.4e-14 | 0 | 0
28 | SEMA5B | sema domain, seven thrombospondin repeats (type 1 and type 1-like), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 5B | 278346 | 17 | 16 | 2 | 0 | 0 | 0 | 1 | 16 | 0 | 0 | 0 | 0.99 | 0 | 0.00085 | 0 | 0
29 | TNIP2 | TNFAIP3 interacting protein 2 | 93363 | 7 | 7 | 1 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 0.76 | 0 | 0.00011 | 0 | 0
30 | HHIPL1 | HHIP-like 1 | 140399 | 14 | 14 | 1 | 1 | 0 | 0 | 0 | 14 | 0 | 0 | 0 | 1 | 0 | 5.2e-09 | 0 | 0
31 | HECTD2 | HECT domain containing 2 | 203444 | 7 | 7 | 1 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | 0.97 | 0 | 0
32 | ADAD2 | adenosine deaminase domain containing 2 | 154788 | 15 | 15 | 1 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 1 | 0 | 0.007 | 0 | 0
33 | CTNNB1 | catenin (cadherin-associated protein), beta 1, 88kDa | 218493 | 14 | 14 | 9 | 0 | 0 | 0 | 4 | 6 | 4 | 0 | 0 | 0.33 | 0 | 1.6e-09 | 0 | 0
34 | ZFPM1 | zinc finger protein, multitype 1 | 134629 | 92 | 48 | 5 | 0 | 1 | 0 | 5 | 0 | 65 | 21 | 0 | 1 | 0 | 0 | 0 | 0
35 | CLDN23 | claudin 23 | 31563 | 13 | 13 | 1 | 0 | 0 | 0 | 13 | 0 | 0 | 0 | 0 | 0.99 | 0 | 8.1e-15 | 0 | 0

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: 4. Number of genes displayed: 10

rank | gene | description | n | cos | n_cos | N_cos | cos_ev | p | q
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
1 | CTNNB1 | catenin (cadherin-associated protein), beta 1, 88kDa | 14 | 138 | 14 | 12558 | 6397 | 3.4e-13 | 1.5e-09
2 | TP53 | tumor protein p53 | 18 | 356 | 17 | 32396 | 1628 | 8e-13 | 1.8e-09
3 | MEN1 | multiple endocrine neoplasia I | 8 | 208 | 5 | 18928 | 25 | 2.7e-08 | 0.000041
4 | KRTAP5-5 | keratin associated protein 5-5 | 7 | 1 | 2 | 91 | 0 | 7.5e-08 | 0.000085
5 | ABCA12 | ATP-binding cassette, sub-family A (ABC1), member 12 | 3 | 1 | 1 | 91 | 1 | 0.00039 | 0.22
6 | ANKRD30A | ankyrin repeat domain 30A | 7 | 1 | 1 | 91 | 1 | 0.00039 | 0.22
7 | CCND2 | cyclin D2 | 1 | 1 | 1 | 91 | 1 | 0.00039 | 0.22
8 | LACE1 | lactation elevated 1 | 1 | 1 | 1 | 91 | 1 | 0.00039 | 0.22
9 | GRM3 | glutamate receptor, metabotropic 3 | 4 | 2 | 1 | 182 | 1 | 0.00078 | 0.35
10 | IGFBP3 | insulin-like growth factor binding protein 3 | 1 | 2 | 1 | 182 | 1 | 0.00078 | 0.35

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: 19. 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 | FOLATE_BIOSYNTHESIS |  | ALPI, ALPL, ALPP, ALPP, ALPPL2, ALPPL2, DHFR, FPGS, GCH1, GGH, SPR | 9 | ALPI(1), ALPP(1), ALPPL2(8), FPGS(14), SPR(1) | 931966 | 25 | 23 | 7 | 2 | 0 | 9 | 3 | 13 | 0 | 0 | 0.041 | 2e-13 | 1.3e-10
2 | STILBENE_COUMARINE_AND_LIGNIN_BIOSYNTHESIS |  | EPX, GBA3, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, TPO, TYR | 10 | EPX(1), PRDX1(1), PRDX2(2), TPO(22) | 1351480 | 26 | 25 | 7 | 2 | 3 | 0 | 21 | 0 | 2 | 0 | 0.016 | 4.2e-09 | 1.3e-06
3 | HSA00940_PHENYLPROPANOID_BIOSYNTHESIS | Genes involved in phenylpropanoid biosynthesis | EPX, GBA, GBA3, LPO, MPO, PRDX6, TPO | 7 | EPX(1), TPO(22) | 1167797 | 23 | 22 | 4 | 2 | 2 | 0 | 21 | 0 | 0 | 0 | 0.018 | 5.3e-08 | 0.000011
4 | 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 | ARF3(1), CDKN2A(2), MDM2(2), TP53(18) | 1136927 | 23 | 18 | 23 | 2 | 2 | 0 | 7 | 1 | 12 | 1 | 0.1 | 4.3e-07 | 0.000067
5 | METHANE_METABOLISM |  | ADH5, ATP6V0C, SHMT1, CAT, EPX, LPO, MPO, PRDX1, PRDX2, PRDX5, PRDX6, SHMT1, SHMT2, TPO | 13 | ATP6V0C(1), EPX(1), PRDX1(1), PRDX2(2), SHMT2(1), TPO(22) | 1646854 | 28 | 27 | 9 | 3 | 4 | 0 | 22 | 0 | 2 | 0 | 0.025 | 5.8e-07 | 0.000072
6 | 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 | CREBBP(1), DAXX(4), PML(2), RARA(1), RB1(2), SIRT1(1), TNFRSF1A(1), TP53(18) | 2581860 | 30 | 24 | 30 | 2 | 3 | 1 | 7 | 1 | 17 | 1 | 0.046 | 8.9e-07 | 0.000092
7 | 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 | NFKB1(1), TP53(18) | 1406891 | 19 | 17 | 19 | 1 | 2 | 0 | 5 | 1 | 10 | 1 | 0.12 | 3.1e-06 | 0.00027
8 | 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(5), ATR(3), CHEK2(2), TP53(18) | 2129466 | 28 | 24 | 28 | 4 | 3 | 0 | 6 | 3 | 15 | 1 | 0.48 | 4.1e-06 | 0.00031
9 | P53PATHWAY | p53 induces cell cycle arrest or apoptosis under conditions of DNA damage. | APAF1, ATM, BAX, BCL2, CCND1, CCNE1, CDK2, CDK4, CDKN1A, E2F1, GADD45A, MDM2, PCNA, RB1, TIMP3, TP53 | 16 | APAF1(1), ATM(5), MDM2(2), RB1(2), TIMP3(1), TP53(18) | 2444225 | 29 | 23 | 29 | 3 | 2 | 0 | 6 | 1 | 19 | 1 | 0.21 | 4.5e-06 | 0.00031
10 | 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(1), GNAS(5), GNB1(2), PRKACA(1), PRKAR1A(7) | 931484 | 16 | 15 | 15 | 2 | 1 | 0 | 3 | 2 | 10 | 0 | 0.51 | 0.000059 | 0.0036

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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