Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1GX48MM
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/C1GX48MM
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: KIRC-TP

  • Number of patients in set: 293

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:KIRC-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 9

  • Mutations seen in COSMIC: 213

  • Significantly mutated genes in COSMIC territory: 5

  • Significantly mutated genesets: 6

Mutation Preprocessing

  • Read 293 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 95839

  • After removing 232 mutations outside chr1-24: 95607

  • After removing 6379 blacklisted mutations: 89228

  • After removing 64591 noncoding mutations: 24637

  • After collapsing adjacent/redundant mutations: 24419

Mutation Filtering

  • Number of mutations before filtering: 24419

  • After removing 659 mutations outside gene set: 23760

  • After removing 11 mutations outside category set: 23749

  • After removing 1 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 23078

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 478
Frame_Shift_Ins 108
In_Frame_Del 48
In_Frame_Ins 8
Missense_Mutation 15594
Nonsense_Mutation 1076
Nonstop_Mutation 21
Silent 5884
Splice_Site 495
Translation_Start_Site 37
Total 23749
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 1722 484078369 3.6e-06 3.6 1.7 2.1
*ApG->G 1172 1342141277 8.7e-07 0.87 0.43 2.1
*Np(A/C/T)->transit 5115 6921093572 7.4e-07 0.74 0.36 2
transver 7620 8747313218 8.7e-07 0.87 0.43 5
indel+null 2226 8747313218 2.5e-07 0.25 0.12 NaN
double_null 10 8747313218 1.1e-09 0.0011 0.00056 NaN
Total 17865 8747313218 2e-06 2 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: KIRC-TP.patients.counts_and_rates.txt

Needs description.

Figure 3.  Needs description.

Figure 4.  Needs description.

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: 9. 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_cons p_joint p_cv p q
1 PBRM1 polybromo 1 1470408 109 107 106 1 0 1 6 15 87 0 0.11 0.071 0 0 0
2 SV2C synaptic vesicle glycoprotein 2C 653960 3 3 3 0 0 1 1 0 1 0 0 0 0.45 0 0
3 VHL von Hippel-Lindau tumor suppressor 123072 139 138 91 5 1 13 9 30 86 0 0.0015 0.0026 1e-15 1.1e-16 6.7e-13
4 BAP1 BRCA1 associated protein-1 (ubiquitin carboxy-terminal hydrolase) 589189 27 27 24 1 0 2 6 4 14 1 0.56 0.23 6.2e-15 5.1e-14 2.3e-10
5 SETD2 SET domain containing 2 1866089 35 34 35 1 2 2 2 7 21 1 0.11 0.27 7e-15 6.6e-14 2.4e-10
6 KDM5C lysine (K)-specific demethylase 5C 1253863 18 18 18 0 0 0 1 5 12 0 0.45 0.017 1.1e-07 4e-08 0.00012
7 TP53 tumor protein p53 372038 7 6 7 1 2 0 3 1 1 0 0.0022 0.000028 0.01 4.6e-06 0.012
8 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 365609 10 9 10 0 0 0 2 2 6 0 0.61 0.35 1.1e-06 6e-06 0.014
9 EBPL emopamil binding protein-like 139558 8 6 4 0 1 0 0 7 0 0 1 0.037 0.000089 0.000045 0.089
10 TOR1A torsin family 1, member A (torsin A) 280456 3 3 1 0 0 0 3 0 0 0 0.0028 0.00017 0.046 0.0001 0.18
11 MTOR mechanistic target of rapamycin (serine/threonine kinase) 2294678 26 24 22 2 1 2 4 19 0 0 0.63 0.016 0.0016 0.0003 0.49
12 UQCRFS1 ubiquinol-cytochrome c reductase, Rieske iron-sulfur polypeptide 1 180195 3 3 1 0 0 0 3 0 0 0 1 0.00096 0.089 0.00089 1
13 CR1 complement component (3b/4b) receptor 1 (Knops blood group) 1444581 10 10 7 0 1 0 0 4 5 0 0.079 0.073 0.0013 0.001 1
14 TP53I3 tumor protein p53 inducible protein 3 298564 4 2 4 0 0 1 1 1 1 0 0.82 0.001 0.12 0.0012 1
15 METTL3 methyltransferase like 3 523510 4 2 4 1 0 0 2 1 1 0 0.048 0.00032 0.6 0.0018 1
16 CYB5B cytochrome b5 type B (outer mitochondrial membrane) 138589 3 1 3 0 0 0 2 1 0 0 0.063 0.0011 0.18 0.0019 1
17 OR5H1 olfactory receptor, family 5, subfamily H, member 1 276592 5 3 3 1 0 0 1 4 0 0 0.68 0.0016 0.15 0.0022 1
18 ADCY8 adenylate cyclase 8 (brain) 1014281 6 5 6 0 1 0 1 4 0 0 0.51 0.00052 0.44 0.0022 1
19 C5orf13 chromosome 5 open reading frame 13 64167 3 3 3 0 0 1 0 0 2 0 0.91 0.87 0.00027 0.0022 1
20 MSN moesin 458269 4 4 4 0 1 0 0 2 1 0 0.052 0.0034 0.076 0.0024 1
21 TSPAN19 tetraspanin 19 144817 4 4 4 0 0 0 1 1 2 0 0.27 0.03 0.0086 0.0024 1
22 SERPINB5 serpin peptidase inhibitor, clade B (ovalbumin), member 5 337536 3 3 3 0 0 0 2 1 0 0 0.074 0.0076 0.059 0.0039 1
23 MEGF10 multiple EGF-like-domains 10 1030929 4 3 4 0 1 1 0 1 1 0 0.51 0.00094 0.68 0.0054 1
24 RPUSD2 RNA pseudouridylate synthase domain containing 2 413507 3 3 3 1 0 0 0 3 0 0 0.057 0.0037 0.17 0.0054 1
25 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 524177 5 5 5 0 0 0 2 3 0 0 0.0078 0.009 0.076 0.0057 1
26 TSGA10IP testis specific, 10 interacting protein 390472 3 3 3 0 0 0 2 0 1 0 0.65 0.17 0.0044 0.0061 1
27 MUC2 mucin 2, oligomeric mucus/gel-forming 1757395 11 10 9 2 2 0 1 7 1 0 0.84 0.043 0.019 0.0067 1
28 PCP4L1 Purkinje cell protein 4 like 1 59064 2 2 2 0 0 0 1 0 1 0 0.97 0.067 0.013 0.0069 1
29 SLC2A14 solute carrier family 2 (facilitated glucose transporter), member 14 442987 3 3 3 0 1 0 1 1 0 0 0.86 0.0052 0.17 0.007 1
30 RARA retinoic acid receptor, alpha 412626 4 4 4 0 0 1 2 1 0 0 0.36 0.031 0.036 0.0087 1
31 ZKSCAN1 zinc finger with KRAB and SCAN domains 1 501610 4 4 4 0 0 0 0 4 0 0 0.0057 0.023 0.05 0.0089 1
32 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 963086 10 10 9 0 0 0 5 4 1 0 0.54 0.022 0.054 0.0093 1
33 ZFAND2B zinc finger, AN1-type domain 2B 235050 3 3 2 2 0 1 2 0 0 0 0.96 0.011 0.11 0.0094 1
34 C2orf62 chromosome 2 open reading frame 62 342797 2 2 2 0 0 0 0 2 0 0 0.008 0.0081 0.15 0.0095 1
35 KIAA1522 KIAA1522 867455 5 5 5 0 1 0 3 0 1 0 0.0079 0.061 0.022 0.01 1
PBRM1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PBRM1 significant gene.

SV2C

Figure S2.  This figure depicts the distribution of mutations and mutation types across the SV2C significant gene.

VHL

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

BAP1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the BAP1 significant gene.

SETD2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the SETD2 significant gene.

KDM5C

Figure S6.  This figure depicts the distribution of mutations and mutation types across the KDM5C significant gene.

TP53

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

PTEN

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

EBPL

Figure S9.  This figure depicts the distribution of mutations and mutation types across the EBPL 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: 5. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 VHL von Hippel-Lindau tumor suppressor 139 541 139 158513 3495 0 0
2 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 10 220 9 64460 3007 0 0
3 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 10 767 10 224731 76 6.9e-11 1e-07
4 TP53 tumor protein p53 7 356 7 104308 1411 3.3e-09 3.7e-06
5 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 3 52 3 15236 14812 4.9e-06 0.0044
6 SMARCA4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 7 30 2 8790 2 0.00016 0.12
7 NF2 neurofibromin 2 (merlin) 4 550 4 161150 32 0.00038 0.24
8 ONECUT2 one cut homeobox 2 1 1 1 293 1 0.0006 0.25
9 PDLIM4 PDZ and LIM domain 4 2 1 1 293 1 0.0006 0.25
10 PRDX5 peroxiredoxin 5 1 1 1 293 1 0.0006 0.25

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: 6. 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 VEGFPATHWAY Vascular endothelial growth factor (VEGF) is upregulated by hypoxic conditions and promotes normal blood vessel formation and angiogenesis related to tumor growth or cardiac disease. ARNT, EIF1, EIF1A, EIF2B1, EIF2B2, EIF2B3, EIF2B4, EIF2B5, EIF2S1, EIF2S2, EIF2S3, ELAVL1, FLT1, FLT4, HIF1A, HRAS, KDR, NOS3, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, PTK2, PXN, SHC1, VEGF, VHL 25 EIF1(1), EIF2B1(3), EIF2B2(1), EIF2B5(2), EIF2S1(1), EIF2S2(1), ELAVL1(1), FLT1(3), FLT4(4), HIF1A(3), KDR(5), NOS3(1), PIK3CA(10), PIK3R1(1), PTK2(1), PXN(2), SHC1(2), VHL(139) 14983008 181 157 132 14 6 15 19 50 91 0 8.7e-06 <1.00e-15 <3.08e-13
2 HIFPATHWAY Under normal conditions, hypoxia inducible factor HIF-1 is degraded; under hypoxic conditions, it activates transcription of genes controlled by hpoxic response elements (HREs). ARNT, ASPH, COPS5, CREB1, EDN1, EP300, EPO, HIF1A, HSPCA, JUN, LDHA, NOS3, P4HB, VEGF, VHL 13 EP300(6), HIF1A(3), JUN(1), NOS3(1), VHL(139) 7504580 150 143 102 11 1 14 11 36 88 0 0.000073 <1.00e-15 <3.08e-13
3 HSA04120_UBIQUITIN_MEDIATED_PROTEOLYSIS Genes involved in ubiquitin mediated proteolysis ANAPC1, ANAPC10, ANAPC11, ANAPC2, ANAPC4, ANAPC5, ANAPC7, BTRC, CDC16, CDC20, CDC23, CDC26, CDC27, CUL1, CUL2, CUL3, FBXW11, FBXW7, FZR1, ITCH, LOC728919, RBX1, SKP1, SKP2, SMURF1, SMURF2, TCEB1, TCEB2, UBA1, UBE2C, UBE2D1, UBE2D2, UBE2D3, UBE2D4, UBE2E1, UBE2E2, UBE2E3, VHL, WWP1, WWP2 39 ANAPC1(4), ANAPC2(1), ANAPC4(2), ANAPC5(2), ANAPC7(1), CDC16(2), CDC20(1), CDC23(2), CDC27(5), CUL1(3), CUL2(1), CUL3(2), FBXW11(1), FBXW7(2), FZR1(1), SKP2(1), SMURF1(1), SMURF2(2), TCEB1(3), UBA1(1), UBE2D1(2), UBE2D2(1), UBE2D3(1), UBE2E2(1), VHL(139), WWP2(1) 17820449 183 157 135 18 2 18 23 45 95 0 9e-05 2.66e-15 5.47e-13
4 SA_PTEN_PATHWAY PTEN is a tumor suppressor that dephosphorylates the lipid messenger phosphatidylinositol triphosphate. AKT1, AKT2, AKT3, BPNT1, GRB2, ILK, MAPK1, MAPK3, PDK1, PIK3CA, PIK3CD, PIP3-E, PTEN, PTK2B, RBL2, SHC1, SOS1 16 AKT1(1), AKT2(2), AKT3(2), MAPK1(1), MAPK3(1), PDK1(1), PIK3CA(10), PIK3CD(1), PTEN(10), PTK2B(2), RBL2(3), SHC1(2), SOS1(4) 8973555 40 38 39 2 3 2 15 12 8 0 0.00042 8.75e-06 0.00135
5 CDC42RACPATHWAY PI3 kinase stimulates cell migration by activating cdc42, which activates ARP2/3, which in turn promotes formation of new actin fibers. ACTR2, ACTR3, ARHA, ARPC1A, ARPC1B, ARPC2, ARPC3, ARPC4, CDC42, PAK1, PDGFRA, PIK3CA, PIK3R1, RAC1, WASL 14 ACTR2(2), ACTR3(1), ARPC2(1), CDC42(2), PAK1(1), PDGFRA(6), PIK3CA(10), PIK3R1(1), WASL(5) 5877261 29 28 28 2 0 1 11 15 2 0 0.016 0.000292 0.0360
6 SA_TRKA_RECEPTOR The TrkA receptor binds nerve growth factor to activate MAP kinase pathways and promote cell growth. AKT1, AKT2, AKT3, ARHA, CDKN1A, ELK1, GRB2, HRAS, MAP2K1, MAP2K2, NGFB, NGFR, NTRK1, PIK3CA, PIK3CD, SHC1, SOS1 15 AKT1(1), AKT2(2), AKT3(2), CDKN1A(1), ELK1(1), MAP2K1(1), NGFR(1), NTRK1(2), PIK3CA(10), PIK3CD(1), SHC1(2), SOS1(4) 7184719 28 28 27 1 2 1 12 12 1 0 0.002 0.000881 0.0905
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(9), AKT1(1), ATM(13), CDKN1A(1), CSNK1A1(1), FHL2(1), HIC1(1), HIF1A(3), MAPK8(1), TP53(7) 9166900 38 33 38 2 2 0 14 10 12 0 0.0018 0.00171 0.150
8 HSA00950_ALKALOID_BIOSYNTHESIS_I Genes involved in alkaloid biosynthesis I DDC, GOT1, GOT2, TAT, TYR 5 DDC(3), GOT1(2), GOT2(3), TAT(1), TYR(1) 2063429 10 10 10 1 1 0 5 1 3 0 0.2 0.00475 0.366
9 HSA00401_NOVOBIOCIN_BIOSYNTHESIS Genes involved in novobiocin biosynthesis GOT1, GOT2, TAT 3 GOT1(2), GOT2(3), TAT(1) 1153972 6 6 6 1 1 0 3 0 2 0 0.42 0.0142 0.972
10 CYSTEINE_METABOLISM CARS, CTH, GOT1, GOT2, LDHA, LDHB, LDHC, MPST 8 CARS(2), CTH(1), GOT1(2), GOT2(3), LDHB(1), LDHC(2), MPST(2) 3003190 13 13 13 2 2 0 4 3 4 0 0.33 0.0181 1.000
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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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