Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Kidney Chromophobe (Primary solid tumor)
Due to issues with GAF 3.0, we strongly advise caution in the use of these results.
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C147485S
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/C147485S
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: KICH-TP

  • Number of patients in set: 66

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:KICH-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 2

  • Mutations seen in COSMIC: 43

  • Significantly mutated genes in COSMIC territory: 2

  • Significantly mutated genesets: 38

Mutation Preprocessing

  • Read 66 MAFs of type "Broad"

  • Read 65 MAFs of type "Baylor-Illumina"

  • Total number of mutations in input MAFs: 5623

  • After removing 59 mutations outside chr1-24: 5564

  • After removing 79 noncoding mutations: 5485

  • After collapsing adjacent/redundant mutations: 4230

Mutation Filtering

  • Number of mutations before filtering: 4230

  • After removing 176 mutations outside gene set: 4054

  • After removing 17 mutations outside category set: 4037

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 3843

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 207
Frame_Shift_Ins 233
In_Frame_Del 55
In_Frame_Ins 22
Missense_Mutation 2283
Nonsense_Mutation 130
Nonstop_Mutation 3
Silent 958
Splice_Site 146
Total 4037
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 893 114088540 7.8e-06 7.8 5.3 2.1
*ApG->G 165 320373592 5.2e-07 0.52 0.35 2.2
*Np(A/C/T)->transit 630 1646939625 3.8e-07 0.38 0.26 2
transver 595 2081401757 2.9e-07 0.29 0.19 5
indel+null 781 2081401757 3.8e-07 0.38 0.25 NaN
double_null 14 2081401757 6.7e-09 0.0067 0.0045 NaN
Total 3078 2081401757 1.5e-06 1.5 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: KICH-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: *ApG->G

  • n3 = number of nonsilent mutations of type: *Np(A/C/T)->transit

  • 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_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: 2. 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 TP53 tumor protein p53 85638 27 22 25 1 3 0 7 7 9 1 4.8e-06 0.00074 0 4e-10 0 0
2 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 79333 6 6 6 0 0 0 1 1 4 0 0.02 0.44 0.043 0.000011 7.6e-06 0.069
3 RIMBP3 RIMS binding protein 3 244157 2 2 2 0 0 0 0 0 2 0 0.016 0.00014 0.00037 0.0093 0.000047 0.28
4 MUC2 mucin 2, oligomeric mucus/gel-forming 540346 6 6 6 3 1 0 3 1 1 0 2.4e-06 0.97 0.000048 0.3 0.00017 0.79
5 EBPL emopamil binding protein-like 32228 4 2 2 0 0 0 0 4 0 0 0.00054 0.99 0.0014 0.043 0.00066 1
6 CDKN1A cyclin-dependent kinase inhibitor 1A (p21, Cip1) 30155 2 2 2 0 0 0 0 0 2 0 0.49 0.043 0.032 0.0026 0.00087 1
7 CBWD6 COBW domain containing 6 55693 2 2 1 0 0 0 0 0 2 0 0.016 0.1 0.049 0.002 0.001 1
8 GNPNAT1 glucosamine-phosphate N-acetyltransferase 1 37950 2 2 2 0 0 0 0 0 2 0 NaN NaN NaN 0.0028 0.0028 1
9 GFM1 G elongation factor, mitochondrial 1 153540 3 3 2 0 0 0 1 0 2 0 0.0021 0.98 0.006 0.079 0.0041 1
10 RAB40A RAB40A, member RAS oncogene family 55264 2 2 2 0 0 0 0 0 2 0 0.013 0.14 0.09 0.0064 0.0049 1
11 RHBDD3 rhomboid domain containing 3 75042 2 2 1 0 0 0 0 0 2 0 0.0097 0.78 0.39 0.0023 0.0072 1
12 GNG7 guanine nucleotide binding protein (G protein), gamma 7 14079 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.0096 0.0096 1
13 TAS2R30 taste receptor, type 2, member 30 63624 2 2 1 0 0 0 0 0 2 0 0.0088 0.8 0.31 0.0045 0.011 1
14 PCDHAC2 protocadherin alpha subfamily C, 2 196181 4 4 4 2 4 0 0 0 0 0 NaN NaN NaN 0.011 0.011 1
15 DTWD1 DTW domain containing 1 61311 2 2 2 0 0 0 0 0 2 0 0.032 0.3 0.081 0.023 0.013 1
16 KLF15 Kruppel-like factor 15 82754 2 2 2 0 0 0 0 0 2 0 NaN NaN NaN 0.018 0.018 1
17 C16orf3 chromosome 16 open reading frame 3 23364 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.019 0.019 1
18 NPTX1 neuronal pentraxin I 58887 2 2 2 0 0 0 0 1 1 0 0.021 0.61 0.1 0.029 0.02 1
19 C16orf54 chromosome 16 open reading frame 54 42357 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.02 0.02 1
20 WASH1 WAS protein family homolog 1 38038 1 1 1 1 0 0 0 0 1 0 NaN NaN NaN 0.021 0.021 1
21 GAL3ST2 galactose-3-O-sulfotransferase 2 58069 2 2 2 0 1 0 0 0 1 0 0.54 0.11 0.2 0.021 0.028 1
22 MEF2A myocyte enhancer factor 2A 109974 2 2 2 0 0 1 0 0 1 0 0.15 0.04 0.064 0.07 0.029 1
23 PPDPF pancreatic progenitor cell differentiation and proliferation factor homolog (zebrafish) 20854 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.029 0.029 1
24 CNTD2 cyclin N-terminal domain containing 2 38276 1 1 1 1 0 0 0 0 1 0 NaN NaN NaN 0.03 0.03 1
25 C10orf114 chromosome 10 open reading frame 114 13656 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.03 0.03 1
26 CHCHD2 coiled-coil-helix-coiled-coil-helix domain containing 2 31152 1 1 1 0 0 0 1 0 0 0 NaN NaN NaN 0.032 0.032 1
27 DSPP dentin sialophosphoprotein 256252 5 5 5 0 0 0 1 2 2 0 0.013 0.052 0.0061 0.91 0.034 1
28 ZNF709 zinc finger protein 709 128172 2 2 2 0 1 0 0 0 1 0 0.66 0.012 0.052 0.12 0.038 1
29 C1orf213 chromosome 1 open reading frame 213 31232 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.039 0.039 1
30 KRTAP17-1 keratin associated protein 17-1 16315 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.044 0.044 1
31 AKT1S1 AKT1 substrate 1 (proline-rich) 35498 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.045 0.045 1
32 OR4F4 olfactory receptor, family 4, subfamily F, member 4 60414 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.045 0.045 1
33 GOLGA8A golgi autoantigen, golgin subfamily a, 8A 113715 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.046 0.046 1
34 SAMD5 sterile alpha motif domain containing 5 19083 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.051 0.051 1
35 KDELR3 KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 47784 2 2 2 0 1 0 0 0 1 0 0.4 0.24 0.24 0.038 0.053 1
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: 2. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 27 356 24 23496 2576 0 0
2 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 6 767 6 50622 35 2.3e-10 5.1e-07
3 KRTAP5-5 keratin associated protein 5-5 1 1 1 66 1 0.000098 0.11
4 RCN1 reticulocalbin 1, EF-hand calcium binding domain 1 1 1 66 1 0.000098 0.11
5 CENPC1 centromere protein C 1 1 2 1 132 1 0.0002 0.18
6 ALPK2 alpha-kinase 2 1 3 1 198 1 0.00029 0.18
7 SMARCC2 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily c, member 2 2 3 1 198 1 0.00029 0.18
8 RB1 retinoblastoma 1 (including osteosarcoma) 2 267 2 17622 4 0.00033 0.18
9 DDR2 discoidin domain receptor tyrosine kinase 2 1 4 1 264 1 0.00039 0.18
10 RHPN2 rhophilin, Rho GTPase binding protein 2 1 4 1 264 1 0.00039 0.18

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: 38. 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 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(3), CDC25C(1), MYT1(1), RB1(2), TP53(27), WEE1(1) 1768882 35 25 33 1 5 1 8 9 11 1 0.00078 2e-15 4e-13
2 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 MYC(1), TP53(27) 698258 28 23 26 1 3 0 7 7 10 1 0.0015 2e-15 4e-13
3 ATMPATHWAY The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 19 ABL1(1), ATM(3), CDKN1A(2), CHEK2(1), TP53(27), TP73(1) 2946230 35 25 33 2 7 0 8 8 11 1 0.0027 2.1e-15 4e-13
4 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 PAX3(1), PML(1), RB1(2), SIRT1(2), TP53(27) 1880922 33 25 31 4 4 0 7 7 14 1 0.034 4.1e-15 4e-13
5 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 ATM(3), CDKN1A(2), PCNA(1), RB1(2), TP53(27) 1802829 35 24 33 1 5 0 7 9 13 1 0.0011 4.9e-15 4e-13
6 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), CDKN1A(2), CDKN1B(1), TP53(27) 807622 31 24 29 2 3 0 7 7 13 1 0.0044 4.9e-15 4e-13
7 CHEMICALPATHWAY DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 20 ATM(3), PTK2(1), PXN(1), TP53(27) 2734647 32 24 30 1 6 0 7 9 9 1 0.00077 5.1e-15 4e-13
8 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 CHUK(1), TP53(27) 1018235 28 22 26 1 3 0 7 7 10 1 0.002 5.4e-15 4e-13
9 TELPATHWAY Telomerase is a ribonucleotide protein that adds telomeric repeats to the 3' ends of chromosomes. AKT1, BCL2, EGFR, G22P1, HSPCA, IGF1R, KRAS2, MYC, POLR2A, PPP2CA, PRKCA, RB1, TEP1, TERF1, TERT, TNKS, TP53, XRCC5 15 IGF1R(1), MYC(1), POLR2A(2), RB1(2), TEP1(1), TERT(2), TP53(27) 2756116 36 24 34 1 5 1 7 8 14 1 0.00034 5.8e-15 4e-13
10 ARFPATHWAY Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 16 ABL1(1), MYC(1), PIK3R1(1), POLR1A(1), POLR1C(1), POLR1D(1), RB1(2), TP53(27) 1966199 35 24 33 1 4 0 9 8 13 1 0.00062 7.2e-15 4e-13
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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