Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
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/C1HX1B3W
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: CESC-TP

  • Number of patients in set: 39

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:CESC-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 5

  • Mutations seen in COSMIC: 35

  • Significantly mutated genes in COSMIC territory: 1

  • Significantly mutated genesets: 0

Mutation Preprocessing
  • Read 39 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 10020

  • After removing 5 mutations outside chr1-24: 10015

  • After removing 474 blacklisted mutations: 9541

  • After removing 599 noncoding mutations: 8942

Mutation Filtering
  • Number of mutations before filtering: 8942

  • After removing 116 mutations outside gene set: 8826

  • After removing 17 mutations outside category set: 8809

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 98
Frame_Shift_Ins 62
In_Frame_Del 39
In_Frame_Ins 13
Missense_Mutation 5527
Nonsense_Mutation 473
Nonstop_Mutation 11
Silent 2482
Splice_Site 91
Translation_Start_Site 13
Total 8809
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
Tp*C->(T/G) 3530 150569812 0.000023 23 4.2 3
(A/C/G)p*C->(T/G) 1102 425623126 2.6e-06 2.6 0.46 2.7
C->A 346 576192938 6e-07 0.6 0.11 4.4
A->mut 562 556925266 1e-06 1 0.18 3.9
indel+null 771 1133118204 6.8e-07 0.68 0.12 NaN
double_null 16 1133118204 1.4e-08 0.014 0.0025 NaN
Total 6327 1133118204 5.6e-06 5.6 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: CESC-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: Tp*C->(T/G)

  • n2 = number of nonsilent mutations of type: (A/C/G)p*C->(T/G)

  • n3 = number of nonsilent mutations of type: C->A

  • 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: 5. 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 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 126650 11 9 4 0 10 0 0 1 0 0 8e-06 0.017 0 0.00038 0 0
2 PRSS48 protease, serine, 48 38982 15 2 8 3 0 2 2 9 2 0 0 0.96 0 0.27 0 0
3 UGT2B10 UDP glucuronosyltransferase 2 family, polypeptide B10 122318 19 2 13 3 2 3 1 13 0 0 0 0.99 0 0.99 0 0
4 TMCC1 transmembrane and coiled-coil domain family 1 77000 4 4 3 0 0 0 1 0 3 0 0.00013 0.086 9e-05 0.00023 3.8e-07 0.0017
5 UGT3A2 UDP glycosyltransferase 3 family, polypeptide A2 62290 3 3 2 0 1 0 0 0 2 0 0.016 0.0019 0.00059 0.0022 0.000019 0.069
6 MAPK1 mitogen-activated protein kinase 1 38660 3 3 1 0 3 0 0 0 0 0 0.00032 0.19 0.00065 0.0046 0.000041 0.12
7 PRB2 proline-rich protein BstNI subfamily 2 49240 5 4 4 0 0 0 0 1 4 0 0.29 0.28 0.33 0.000036 0.00015 0.37
8 PLAC4 placenta-specific 4 7160 2 2 1 0 0 0 0 0 2 0 0.021 0.31 0.083 0.00019 0.00019 0.43
9 OR10G8 olfactory receptor, family 10, subfamily G, member 8 36617 16 2 10 13 0 10 0 5 1 0 2.4e-06 1 0.000017 0.95 0.0002 0.43
10 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 45935 3 3 3 0 0 0 0 0 3 0 0.28 0.82 0.39 0.00015 0.00064 1
11 NFE2L2 nuclear factor (erythroid-derived 2)-like 2 69545 7 6 6 0 4 0 0 1 2 0 0.49 0.041 0.16 0.0004 0.00067 1
12 ITGAX integrin, alpha X (complement component 3 receptor 4 subunit) 131027 8 4 6 6 2 2 0 3 1 0 0.000038 0.52 0.00012 0.74 0.00093 1
13 RAET1L retinoic acid early transcript 1L 25451 5 2 4 0 1 1 0 3 0 0 0.00047 0.45 0.0021 0.084 0.0017 1
14 TREML4 triggering receptor expressed on myeloid cells-like 4 23897 5 2 4 3 0 3 0 1 1 0 0.008 0.83 0.019 0.011 0.0021 1
15 SEH1L SEH1-like (S. cerevisiae) 50533 2 2 1 0 0 0 0 0 2 0 0.0098 0.0074 0.039 0.0059 0.0022 1
16 USP26 ubiquitin specific peptidase 26 107055 2 2 2 0 1 0 0 0 1 0 0.045 0.0051 0.0026 0.12 0.0029 1
17 XAGE5 X antigen family, member 5 13377 3 2 3 0 0 0 0 2 1 0 0.089 0.33 0.12 0.0069 0.0065 1
18 CPNE3 copine III 64568 3 2 3 0 2 0 0 0 1 0 0.00072 0.97 0.0019 0.45 0.0068 1
19 SPANXN5 SPANX family, member N5 8853 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.0069 0.0069 1
20 C20orf134 chromosome 20 open reading frame 134 15064 2 2 2 0 1 0 0 0 1 0 0.081 0.94 0.11 0.0078 0.0071 1
21 PTH2 parathyroid hormone 2 8040 2 2 2 0 1 0 1 0 0 0 0.7 0.048 0.028 0.032 0.0072 1
22 ZNF645 zinc finger protein 645 49998 2 2 1 0 0 2 0 0 0 0 0.013 0.063 0.015 0.066 0.0077 1
23 LCE1C late cornified envelope 1C 14077 4 2 2 9 0 4 0 0 0 0 0.0037 0.98 0.0068 0.16 0.0087 1
24 FETUB fetuin B 45815 2 2 2 0 1 0 0 1 0 0 0.088 0.024 0.0085 0.13 0.0089 1
25 TMEM47 transmembrane protein 47 11233 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.0093 0.0093 1
26 IL13RA1 interleukin 13 receptor, alpha 1 48201 2 2 1 0 0 0 0 0 2 0 0.01 0.62 0.24 0.0051 0.0093 1
27 TCEAL2 transcription elongation factor A (SII)-like 2 26340 3 1 3 1 1 0 0 2 0 0 0.00092 0.94 0.004 0.32 0.0098 1
28 C11orf52 chromosome 11 open reading frame 52 14969 2 2 2 0 1 0 0 0 1 0 0.42 0.56 0.83 0.0019 0.012 1
29 IFNGR2 interferon gamma receptor 2 (interferon gamma transducer 1) 37635 2 2 2 0 0 0 0 0 2 0 0.2 0.59 0.42 0.004 0.012 1
30 WDR44 WD repeat domain 44 109831 2 2 2 0 1 0 0 0 1 0 0.11 0.01 0.019 0.1 0.014 1
31 MTL5 metallothionein-like 5, testis-specific (tesmin) 48655 2 2 2 0 0 0 0 0 2 0 0.45 0.16 0.25 0.0078 0.014 1
32 TIE1 tyrosine kinase with immunoglobulin-like and EGF-like domains 1 125328 4 3 4 0 0 2 1 0 1 0 0.066 0.03 0.016 0.14 0.015 1
33 CTNNBIP1 catenin, beta interacting protein 1 6478 1 1 1 0 0 0 0 0 1 0 NaN NaN NaN 0.017 0.017 1
34 FAM49A family with sequence similarity 49, member A 39076 2 2 2 0 0 1 0 1 0 0 0.015 0.54 0.026 0.11 0.019 1
35 ASH1L ash1 (absent, small, or homeotic)-like (Drosophila) 350984 4 2 4 1 2 0 0 1 1 0 0.00091 0.98 0.0028 0.98 0.019 1
PIK3CA

Figure S1.  This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

PRSS48

Figure S2.  This figure depicts the distribution of mutations and mutation types across the PRSS48 significant gene.

UGT2B10

Figure S3.  This figure depicts the distribution of mutations and mutation types across the UGT2B10 significant gene.

TMCC1

Figure S4.  This figure depicts the distribution of mutations and mutation types across the TMCC1 significant gene.

UGT3A2

Figure S5.  This figure depicts the distribution of mutations and mutation types across the UGT3A2 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: 1. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 11 220 8 8580 3939 0 0
2 ATL2 atlastin GTPase 2 1 1 1 39 1 0.00022 0.16
3 EDA ectodysplasin A 1 1 1 39 1 0.00022 0.16
4 KIAA1024 KIAA1024 2 1 1 39 1 0.00022 0.16
5 MAPK11 mitogen-activated protein kinase 11 1 1 1 39 1 0.00022 0.16
6 SUV39H2 suppressor of variegation 3-9 homolog 2 (Drosophila) 1 1 1 39 2 0.00022 0.16
7 ALS2 amyotrophic lateral sclerosis 2 (juvenile) 2 3 1 117 1 0.00065 0.22
8 EPHA10 EPH receptor A10 1 3 1 117 1 0.00065 0.22
9 IFITM3 interferon induced transmembrane protein 3 (1-8U) 5 3 1 117 1 0.00065 0.22
10 ITIH5L inter-alpha (globulin) inhibitor H5-like 1 3 1 117 1 0.00065 0.22

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: 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 PAR1PATHWAY Activated extracellular thrombin cleaves and activates the G-protein coupled receptors PAR1 and PAR4, which activate platelets. ADCY1, ARHA, ARHGEF1, F2, F2R, F2RL3, GNA12, GNA13, GNAI1, GNAQ, GNB1, GNGT1, MAP3K7, PIK3CA, PIK3R1, PLCB1, PPP1R12B, PRKCA, PRKCB1, PTK2B, ROCK1 19 ADCY1(1), ARHGEF1(1), F2R(1), F2RL3(2), GNA13(1), PIK3CA(11), PIK3R1(1), PPP1R12B(1), PRKCA(1), ROCK1(3) 1478575 23 13 16 1 16 3 1 2 0 1 0.011 0.00041 0.12
2 ACHPATHWAY Nicotinic acetylcholine receptors are ligand-gated ion channels that primarily mediate neuromuscular signaling and may inhibit neuronal apoptosis via the AKT pathway. AKT1, BAD, CHRNB1, CHRNG, FOXO3A, MUSK, PIK3CA, PIK3R1, PTK2, PTK2B, RAPSN, SRC, TERT, TNFSF6, YWHAH 13 CHRNG(1), MUSK(1), PIK3CA(11), PIK3R1(1), PTK2(1) 935251 15 11 8 1 11 0 1 2 1 0 0.053 0.00044 0.12
3 ERK5PATHWAY Signaling between a tissue and its innervating axon stimulates retrograde transport via Trk receptors, which activate Erk5, which induces transcription of anti-apoptotic factors. AKT1, CREB1, GRB2, HRAS, MAPK1, MAPK3, MAPK7, MEF2A, MEF2B, MEF2C, MEF2D, NTRK1, PIK3CA, PIK3R1, PLCG1, RPS6KA1, SHC1 17 MAPK1(3), MAPK7(1), MEF2C(1), PIK3CA(11), PIK3R1(1), RPS6KA1(2) 1088110 19 11 10 1 14 1 0 3 1 0 0.03 0.00069 0.12
4 GCRPATHWAY Corticosteroids activate the glucocorticoid receptor (GR), which inhibits NF-kB and activates Annexin-1, thus inhibiting the inflammatory response. ADRB2, AKT1, ANXA1, CALM1, CALM2, CALM3, CRN, GNAS, GNB1, GNGT1, HSPCA, NFKB1, NOS3, NPPA, NR3C1, PIK3CA, PIK3R1, RELA, SYT1 17 CALM1(1), CALM3(1), NPPA(1), PIK3CA(11), PIK3R1(1), SYT1(1) 1019231 16 11 9 0 12 1 1 2 0 0 0.018 0.00078 0.12
5 PTENPATHWAY PTEN suppresses AKT-induced cell proliferation and antagonizes the action of PI3K. AKT1, BCAR1, CDKN1B, FOXO3A, GRB2, ILK, ITGB1, MAPK1, MAPK3, PDK2, PDPK1, PIK3CA, PIK3R1, PTEN, PTK2, SHC1, SOS1, TNFSF6 16 MAPK1(3), PIK3CA(11), PIK3R1(1), PTEN(3), PTK2(1), SOS1(1) 1108069 20 11 11 0 15 0 0 2 3 0 0.0079 0.0014 0.15
6 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 CD86(1), ITK(1), PIK3CA(11), PIK3R1(1), PTPN11(1) 739491 15 9 8 0 12 1 0 2 0 0 0.018 0.0014 0.15
7 ST_TYPE_I_INTERFERON_PATHWAY Type I interferon is an antiviral cytokine that induces a JAK-STAT type pathway leading to ISGF3 activation and a cellular antiviral response. IFNAR1, IFNB1, ISGF3G, JAK1, PTPRU, REG1A, STAT1, STAT2, TYK2 8 IFNAR1(2), PTPRU(1), REG1A(1), STAT1(3), TYK2(3) 723179 10 10 10 1 7 3 0 0 0 0 0.12 0.0018 0.16
8 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNGR1(2), IFNGR2(2), JAK2(1), STAT1(3) 473117 8 7 8 1 4 1 0 0 3 0 0.48 0.0021 0.16
9 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), PIK3CA(11), PIK3R1(1), POLR1A(2), POLR1C(2), TP53(2) 1168503 19 14 12 2 13 0 0 4 2 0 0.13 0.0027 0.18
10 PLCPATHWAY Phospholipase C hydrolyzes the membrane lipid PIP2 to DAG, which activates protein kinase C, and IP3, which causes calcium influx. AKT1, PIK3CA, PIK3R1, PLCB1, PLCG1, PRKCA, PRKCB1, VAV1 7 PIK3CA(11), PIK3R1(1), PRKCA(1) 739813 13 9 6 1 11 0 0 2 0 0 0.13 0.0029 0.18
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)