Prostate Adenocarcinoma: Mutation Analysis (MutSig v2.0)
(primary solid tumor cohort)
Maintained by Dan DiCara (Broad Institute)
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: PRAD-TP

  • Number of patients in set: 83

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:PRAD-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 7

  • Mutations seen in COSMIC: 26

  • Significantly mutated genes in COSMIC territory: 6

  • Genes with clustered mutations (≤ 3 aa apart): 10

  • Significantly mutated genesets: 2

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

Mutation Preprocessing

  • Read 83 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 12281

  • After removing 28 mutations outside chr1-24: 12253

  • After removing 2166 blacklisted mutations: 10087

  • After removing 5009 noncoding mutations: 5078

  • After collapsing adjacent/redundant mutations: 5056

Mutation Filtering

  • Number of mutations before filtering: 5056

  • After removing 133 mutations outside gene set: 4923

  • After removing 4 mutations outside category set: 4919

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 145
Frame_Shift_Ins 65
In_Frame_Del 42
In_Frame_Ins 7
Missense_Mutation 3032
Nonsense_Mutation 171
Nonstop_Mutation 2
Silent 1359
Splice_Site 88
Translation_Start_Site 8
Total 4919
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 815 138713067 5.9e-06 5.9 4.1 2.1
*Np(A/C/T)->transit 826 1965699488 4.2e-07 0.42 0.29 2
*ApG->G 94 381313535 2.5e-07 0.25 0.17 2.1
transver 1302 2485726090 5.2e-07 0.52 0.37 5
indel+null 520 2485726090 2.1e-07 0.21 0.15 NaN
double_null 3 2485726090 1.2e-09 0.0012 0.00084 NaN
Total 3560 2485726090 1.4e-06 1.4 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: PRAD-TP.patients.counts_and_rates.txt

CoMut Plot

Figure 3.  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: *Np(A/C/T)->transit

  • n3 = number of nonsilent mutations of type: *ApG->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: 7. 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_cons p_joint p q
1 NKX3-1 NK3 homeobox 1 43527 5 5 5 0 0 2 0 2 1 0 2.1e-09 0.26 NaN NaN 2.1e-09 0.000039
2 FRG1 FSHD region gene 1 67208 4 4 2 0 0 0 0 3 1 0 2.9e-07 0.65 NaN NaN 2.9e-07 0.0026
3 TP53 tumor protein p53 105521 5 5 5 0 3 0 0 1 1 0 5.5e-07 0.34 NaN NaN 5.5e-07 0.0033
4 PRR21 proline rich 21 58941 4 4 4 0 1 1 0 2 0 0 2.2e-06 0.26 NaN NaN 2.2e-06 0.01
5 SPOP speckle-type POZ protein 96345 4 4 3 0 0 0 1 3 0 0 3.8e-06 0.39 NaN NaN 3.8e-06 0.014
6 OR4D5 olfactory receptor, family 4, subfamily D, member 5 79763 3 3 3 0 2 0 0 1 0 0 0.000012 0.46 NaN NaN 0.000012 0.032
7 OR6N1 olfactory receptor, family 6, subfamily N, member 1 78146 3 3 2 0 0 0 2 1 0 0 0.000012 0.46 NaN NaN 0.000012 0.032
8 CNTNAP5 contactin associated protein-like 5 309961 5 5 5 0 2 0 0 2 1 0 5e-05 0.2 NaN NaN 5e-05 0.11
9 OR5L2 olfactory receptor, family 5, subfamily L, member 2 78017 3 3 3 0 0 0 0 3 0 0 0.0001 0.55 NaN NaN 0.0001 0.18
10 AIM2 absent in melanoma 2 87306 3 3 3 0 0 1 0 1 1 0 0.00011 0.57 NaN NaN 0.00011 0.18
11 YBX1 Y box binding protein 1 68945 4 3 2 0 0 2 0 2 0 0 0.00012 0.32 NaN NaN 0.00012 0.18
12 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 1228308 8 7 7 0 0 1 0 2 4 1 0.00012 0.23 NaN NaN 0.00012 0.18
13 GGTLC2 gamma-glutamyltransferase light chain 2 47824 2 2 2 1 0 0 1 1 0 0 0.00013 0.81 NaN NaN 0.00013 0.18
14 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 102374 3 3 3 0 0 1 0 1 1 0 0.00016 0.4 NaN NaN 0.00016 0.2
15 OR52A1 olfactory receptor, family 52, subfamily A, member 1 78103 2 2 2 0 2 0 0 0 0 0 0.00017 0.84 NaN NaN 0.00017 0.2
16 GRID2 glutamate receptor, ionotropic, delta 2 256214 4 4 4 1 3 1 0 0 0 0 0.0002 0.62 NaN NaN 0.0002 0.23
17 ZNF98 zinc finger protein 98 (F7175) 122162 3 3 3 0 0 0 0 2 1 0 0.00024 0.67 NaN NaN 0.00024 0.24
18 ZMYM3 zinc finger, MYM-type 3 288038 4 4 4 0 0 0 0 1 3 0 0.00025 0.57 NaN NaN 0.00025 0.24
19 CRIPAK cysteine-rich PAK1 inhibitor 110493 3 3 3 1 0 1 0 2 0 0 0.00026 0.7 NaN NaN 0.00026 0.24
20 TPTE2 transmembrane phosphoinositide 3-phosphatase and tensin homolog 2 136261 3 3 3 0 1 1 0 1 0 0 0.00032 0.42 NaN NaN 0.00032 0.26
21 BANF2 barrier to autointegration factor 2 23572 2 2 2 0 1 0 0 1 0 0 0.00032 0.43 NaN NaN 0.00032 0.26
22 LPHN3 latrophilin 3 311602 4 4 4 1 2 1 0 1 0 0 0.00034 0.61 NaN NaN 0.00034 0.26
23 SLITRK4 SLIT and NTRK-like family, member 4 208728 3 3 2 0 0 0 0 0 3 0 0.00034 0.72 NaN NaN 0.00034 0.26
24 OR2M3 olfactory receptor, family 2, subfamily M, member 3 78186 2 2 2 0 2 0 0 0 0 0 0.00036 0.69 NaN NaN 0.00036 0.26
25 TBX18 T-box 18 132272 3 3 3 0 2 1 0 0 0 0 0.00036 0.29 NaN NaN 0.00036 0.26
26 BBS9 Bardet-Biedl syndrome 9 227840 3 3 2 0 0 1 0 0 2 0 0.00038 0.68 NaN NaN 0.00038 0.26
27 LCE2D late cornified envelope 2D 27971 2 2 2 0 1 0 0 1 0 0 0.00042 0.75 NaN NaN 0.00042 0.27
28 ETV3 ets variant gene 3 36841 2 2 2 0 0 1 0 0 1 0 0.00045 0.65 NaN NaN 0.00045 0.27
29 PCDHB14 protocadherin beta 14 199174 3 3 3 0 1 0 0 1 1 0 0.00046 0.27 NaN NaN 0.00046 0.27
30 KRT25 keratin 25 114954 3 3 3 0 1 0 0 1 1 0 0.00047 0.46 NaN NaN 0.00047 0.27
31 NEUROD6 neurogenic differentiation 6 84494 2 2 2 0 1 0 1 0 0 0 0.00048 0.41 NaN NaN 0.00048 0.27
32 AGT angiotensinogen (serpin peptidase inhibitor, clade A, member 8) 122342 3 3 1 0 0 0 0 3 0 0 0.0005 0.53 NaN NaN 0.0005 0.27
33 B3GNT4 UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 4 94944 2 2 2 0 0 1 0 0 0 1 0.0005 0.63 NaN NaN 0.0005 0.27
34 BCL6 B-cell CLL/lymphoma 6 (zinc finger protein 51) 178187 3 3 3 1 1 2 0 0 0 0 0.00051 0.6 NaN NaN 0.00051 0.27
35 MOCOS molybdenum cofactor sulfurase 214117 3 3 3 0 0 0 0 2 1 0 0.00055 0.57 NaN NaN 0.00055 0.28
NKX3-1

Figure S1.  This figure depicts the distribution of mutations and mutation types across the NKX3-1 significant gene.

FRG1

Figure S2.  This figure depicts the distribution of mutations and mutation types across the FRG1 significant gene.

TP53

Figure S3.  This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

PRR21

Figure S4.  This figure depicts the distribution of mutations and mutation types across the PRR21 significant gene.

SPOP

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

OR4D5

Figure S6.  This figure depicts the distribution of mutations and mutation types across the OR4D5 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: 6. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 TP53 tumor protein p53 5 356 5 29548 1608 1.1e-09 4.9e-06
2 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 3 138 3 11454 1229 7.3e-07 0.0016
3 PTEN phosphatase and tensin homolog (mutated in multiple advanced cancers 1) 3 767 3 63661 15 0.00012 0.09
4 ACSM2B acyl-CoA synthetase medium-chain family member 2B 1 1 1 83 1 0.00012 0.09
5 BRE brain and reproductive organ-expressed (TNFRSF1A modulator) 1 1 1 83 1 0.00012 0.09
6 KCNH1 potassium voltage-gated channel, subfamily H (eag-related), member 1 1 1 1 83 1 0.00012 0.09
7 CHAT choline acetyltransferase 2 2 1 166 1 0.00024 0.13
8 CYP4F2 cytochrome P450, family 4, subfamily F, polypeptide 2 1 2 1 166 2 0.00024 0.13
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 2 220 2 18260 355 0.00034 0.16
10 ACVR2A activin A receptor, type IIA 1 3 1 249 1 0.00036 0.16

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)

Clustered Mutations

Table 5.  Get Full Table Genes with Clustered Mutations

num gene desc n mindist nmuts0 nmuts3 nmuts12 npairs0 npairs3 npairs12
88 AGT angiotensinogen (serpin peptidase inhibitor, clade A, member 8) 3 0 3 3 3 3 3 3
447 CCNF cyclin F 3 0 3 3 3 3 3 3
540 CLSTN1 calsyntenin 1 3 0 3 3 3 3 3 3
595 CROCC ciliary rootlet coiled-coil, rootletin 4 0 3 3 3 3 3 3
743 DUSP27 dual specificity phosphatase 27 (putative) 3 0 3 3 3 3 3 3
932 FRG1 FSHD region gene 1 4 0 3 3 3 3 3 3
2724 YBX1 Y box binding protein 1 4 0 2 2 2 2 2 2
2350 SPOP speckle-type POZ protein 4 0 1 3 3 1 3 3
1516 MLL3 myeloid/lymphoid or mixed-lineage leukemia 3 8 0 1 1 3 1 1 3
151 AP4B1 adaptor-related protein complex 4, beta 1 subunit 2 0 1 1 1 1 1 1

Note:

n - number of mutations in this gene in the individual set.

mindist - distance (in aa) between closest pair of mutations in this gene

npairs3 - how many pairs of mutations are within 3 aa of each other.

npairs12 - how many pairs of mutations are within 12 aa of each other.

Geneset Analyses

Table 6.  Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 2. 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 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 CDKN1B(2), PRB1(2), TP53(5) 1062488 9 9 9 0 3 1 0 2 3 0 0.15 2e-05 0.012
2 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(2), AKT1(1), ATM(5), TP53(5) 2602579 13 12 13 0 4 6 0 2 1 0 0.015 0.00015 0.047
3 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), TP53(5) 2266716 11 10 11 0 3 5 0 2 1 0 0.034 0.00079 0.16
4 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 SP1(1), TP53(5) 879118 6 6 6 0 3 1 0 1 1 0 0.16 0.0015 0.23
5 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(5), TP53(5) 2195302 10 9 10 0 3 4 0 2 1 0 0.058 0.0019 0.23
6 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(1), CCNE2(1), CDKN1B(2), PRB1(2) 1130432 6 6 6 0 0 2 0 2 2 0 0.3 0.0026 0.24
7 G1PATHWAY CDK4/6-cyclin D and CDK2-cyclin E phosphorylate Rb, which allows the transcription of genes needed for the G1/S cell cycle transition. ABL1, ATM, ATR, CCNA1, CCND1, CCNE1, CDC2, CDC25A, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, DHFR, E2F1, GSK3B, HDAC1, MADH3, MADH4, RB1, SKP2, TFDP1, TGFB1, TGFB2, TGFB3, TP53 25 ATM(5), CCNA1(1), CDKN1B(2), DHFR(1), TP53(5) 3787641 14 12 14 0 3 5 0 2 4 0 0.032 0.003 0.24
8 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 AKT1(1), APAF1(1), ATM(5), TLN1(1), TP53(5) 3433242 13 12 13 0 3 6 0 3 1 0 0.019 0.0031 0.24
9 SMALL_LIGAND_GPCRS C9orf47, CNR1, CNR2, DNMT1, EDG1, EDG2, EDG5, EDG6, MTNR1A, MTNR1B, PTAFR, PTGDR, PTGER1, PTGER2, PTGER4, PTGFR, PTGIR, TBXA2R 13 DNMT1(3), MTNR1A(1), PTGER2(1), TBXA2R(2) 1410721 7 7 7 1 3 2 0 1 1 0 0.19 0.0075 0.44
10 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 AKT1(1), CDKN1B(2), PIK3CA(2), PTEN(3) 2419782 8 8 8 1 0 3 1 1 3 0 0.36 0.0075 0.44

Table 7.  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 SA_REG_CASCADE_OF_CYCLIN_EXPR Expression of cyclins regulates progression through the cell cycle by activating cyclin-dependent kinases. CCNA1, CCNA2, CCND1, CCNE1, CCNE2, CDK2, CDK4, CDKN1B, CDKN2A, E2F1, E2F2, E2F4, PRB1 13 CCNA1(1), CCNE2(1), CDKN1B(2), PRB1(2) 1130432 6 6 6 0 0 2 0 2 2 0 0.3 0.0026 1
2 SMALL_LIGAND_GPCRS C9orf47, CNR1, CNR2, DNMT1, EDG1, EDG2, EDG5, EDG6, MTNR1A, MTNR1B, PTAFR, PTGDR, PTGER1, PTGER2, PTGER4, PTGFR, PTGIR, TBXA2R 13 DNMT1(3), MTNR1A(1), PTGER2(1), TBXA2R(2) 1410721 7 7 7 1 3 2 0 1 1 0 0.19 0.0075 1
3 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 AKT1(1), CDKN1B(2), PIK3CA(2), PTEN(3) 2419782 8 8 8 1 0 3 1 1 3 0 0.36 0.0075 1
4 HSA00830_RETINOL_METABOLISM Genes involved in retinol metabolism ALDH1A1, ALDH1A2, BCMO1, RDH5 4 ALDH1A2(1), BCMO1(2) 483292 3 3 2 0 0 2 0 1 0 0 0.37 0.0079 1
5 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 18 ABCB1(2), AKT1(1), ATM(5) 2497058 8 8 8 0 1 6 0 1 0 0 0.053 0.012 1
6 HSA00564_GLYCEROPHOSPHOLIPID_METABOLISM Genes involved in glycerophospholipid metabolism ACHE, AGPAT1, AGPAT2, AGPAT3, AGPAT4, AGPAT6, ARD1A, CDIPT, CDS1, CDS2, CHAT, CHKA, CHKB, CHPT1, CRLS1, DGKA, DGKB, DGKD, DGKE, DGKG, DGKH, DGKI, DGKQ, DGKZ, ESCO1, ESCO2, ETNK1, ETNK2, GNPAT, GPAM, GPD1, GPD1L, GPD2, LCAT, LYCAT, LYPLA1, LYPLA2, LYPLA3, MYST3, MYST4, NAT5, NAT6, PCYT1A, PCYT1B, PEMT, PHOSPHO1, PISD, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLD1, PLD2, PNPLA3, PPAP2A, PPAP2B, PPAP2C, PTDSS1, PTDSS2, SH3GLB1 64 AGPAT2(1), AGPAT3(1), CHAT(2), DGKD(1), DGKH(1), DGKI(1), DGKQ(2), ESCO1(3), GNPAT(1), MYST3(1), PEMT(1), PLA2G2A(1), PLA2G4A(1), PLA2G5(1), PLD1(1), PTDSS1(1) 8241571 20 19 20 2 2 4 1 9 4 0 0.11 0.014 1
7 LONGEVITYPATHWAY Caloric restriction in animals often increases lifespan, which may occur via decreased IGF receptor expression and consequent expression of stress-resistance proteins. AKT1, CAT, FOXO3A, GH1, GHR, HRAS, IGF1, IGF1R, PIK3CA, PIK3R1, SHC1, SOD1, SOD2, SOD3 13 AKT1(1), GHR(1), IGF1R(1), PIK3CA(2), SOD3(1) 1657357 6 6 6 0 0 4 1 1 0 0 0.12 0.016 1
8 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 14 CDKN1B(2), PRB1(2) 956967 4 4 4 0 0 1 0 1 2 0 0.54 0.019 1
9 TRKAPATHWAY Nerve growth factor (NGF) promotes neuronal survival and proliferation by binding its receptor TrkA, which activates PI3K/AKT, Ras, and the MAP kinase pathway. AKT1, DPM2, GRB2, HRAS, KLK2, NGFB, NTRK1, PIK3CA, PIK3R1, PLCG1, PRKCA, PRKCB1, SHC1, SOS1 12 AKT1(1), KLK2(1), NTRK1(2), PIK3CA(2) 1940556 6 6 6 0 0 4 1 0 1 0 0.13 0.021 1
10 ST_PHOSPHOINOSITIDE_3_KINASE_PATHWAY The phosphoinositide-3 kinase pathway produces the lipid second messenger PIP3 and regulates cell growth, survival, and movement. A1BG, AKT1, AKT2, AKT3, BAD, BTK, CDKN2A, CSL4, DAF, DAPP1, FOXO1A, GRB2, GSK3A, GSK3B, IARS, IGFBP1, INPP5D, P14, PDK1, PIK3CA, PPP1R13B, PSCD3, PTEN, RPS6KA1, RPS6KA2, RPS6KA3, RPS6KB1, SFN, SHC1, SOS1, SOS2, TEC, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ 33 A1BG(1), AKT1(1), BTK(1), GSK3A(1), PDK1(1), PIK3CA(2), PPP1R13B(1), PTEN(3) 4518736 11 11 11 1 1 3 1 4 2 0 0.16 0.022 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

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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