Rectum 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: READ-TP

  • Number of patients in set: 69

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:READ-TP.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 26

  • Mutations seen in COSMIC: 222

  • Significantly mutated genes in COSMIC territory: 10

  • Genes with clustered mutations (≤ 3 aa apart): 117

  • Significantly mutated genesets: 111

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

Mutation Preprocessing

  • Read 38 MAFs of type "Broad"

  • Read 35 MAFs of type "Baylor"

  • Total number of mutations in input MAFs: 29413

  • After removing 257 invalidated mutations: 29156

  • After removing 200 noncoding mutations: 28956

  • After collapsing adjacent/redundant mutations: 21678

Mutation Filtering

  • Number of mutations before filtering: 21678

  • After removing 200 mutations outside gene set: 21478

  • After removing 172 mutations outside category set: 21306

  • After removing 2 "impossible" mutations in

  • gene-patient-category bins of zero coverage: 20932

Results
Breakdown of Mutations by Type

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

type count
De_novo_Start_InFrame 4
De_novo_Start_OutOfFrame 30
Frame_Shift_Del 151
Frame_Shift_Ins 155
In_Frame_Del 27
In_Frame_Ins 7
Missense_Mutation 14471
Nonsense_Mutation 1779
Nonstop_Mutation 6
Read-through 10
Silent 4628
Splice_Site 38
Total 21306
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
*CpG->T 4919 99673101 0.000049 49 5.4
*Cp(A/C/T)->mut 6672 832257993 8e-06 8 0.88
A->mut 2743 908854391 3e-06 3 0.33
*CpG->(G/A) 135 99673101 1.4e-06 1.4 0.15
indel+null 2051 1840785523 1.1e-06 1.1 0.12
double_null 157 1840785523 8.5e-08 0.085 0.0094
Total 16677 1840785523 9.1e-06 9.1 1
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: READ-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: *Cp(A/C/T)->mut

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

  • n4 = number of nonsilent mutations of type: *CpG->(G/A)

  • 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_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: 26. 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_cons p_joint p q
1 TP53 tumor protein p53 79667 45 45 30 1 19 6 6 2 12 0 <1.00e-15 NaN NaN <1.00e-15 <1.72e-11
2 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 48604 38 38 8 0 0 36 1 0 1 0 2.78e-15 NaN NaN 2.78e-15 1.72e-11
3 APC adenomatous polyposis coli 576224 66 57 56 0 1 4 4 0 39 18 2.89e-15 NaN NaN 2.89e-15 1.72e-11
4 SMAD4 SMAD family member 4 115264 8 8 6 0 2 3 3 0 0 0 8.09e-11 NaN NaN 8.09e-11 3.62e-07
5 KIAA1804 162266 11 9 9 0 7 3 1 0 0 0 1.25e-08 NaN NaN 1.25e-08 4.48e-05
6 FBXW7 F-box and WD repeat domain containing 7 177744 12 9 10 0 6 2 2 0 2 0 1.94e-08 NaN NaN 1.94e-08 5.80e-05
7 TCF7L2 transcription factor 7-like 2 (T-cell specific, HMG-box) 119026 7 7 7 1 2 3 0 0 2 0 1.00e-07 NaN NaN 1.00e-07 0.000238
8 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 40433 5 5 4 0 0 3 2 0 0 0 1.06e-07 NaN NaN 1.06e-07 0.000238
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 194975 7 7 7 1 1 3 3 0 0 0 2.12e-07 NaN NaN 2.12e-07 0.000421
10 OPCML opioid binding protein/cell adhesion molecule-like 73709 6 6 6 1 1 3 0 0 2 0 2.84e-07 NaN NaN 2.84e-07 0.000509
11 SPATA8 spermatogenesis associated 8 20140 3 3 3 0 0 0 3 0 0 0 4.18e-06 NaN NaN 4.18e-06 0.00681
12 KRTAP5-5 keratin associated protein 5-5 34487 2 2 1 0 0 0 0 2 0 0 2.10e-05 NaN NaN 2.10e-05 0.0280
13 SMAD2 SMAD family member 2 98964 5 5 5 0 0 3 1 0 1 0 2.16e-05 NaN NaN 2.16e-05 0.0280
14 IL1RAPL2 interleukin 1 receptor accessory protein-like 2 139823 5 5 4 2 2 1 0 0 2 0 2.19e-05 NaN NaN 2.19e-05 0.0280
15 CSMD1 CUB and Sushi multiple domains 1 392008 12 9 12 2 4 4 2 0 1 1 2.40e-05 NaN NaN 2.40e-05 0.0287
16 LRRTM2 leucine rich repeat transmembrane neuronal 2 59242 5 4 5 1 1 1 2 1 0 0 3.53e-05 NaN NaN 3.53e-05 0.0395
17 SGCB sarcoglycan, beta (43kDa dystrophin-associated glycoprotein) 64145 4 4 4 0 0 3 0 0 0 1 4.59e-05 NaN NaN 4.59e-05 0.0462
18 GFRA1 GDNF family receptor alpha 1 86296 5 5 5 1 1 0 3 0 1 0 4.65e-05 NaN NaN 4.65e-05 0.0462
19 CCBP2 chemokine binding protein 2 79700 5 5 5 0 1 2 2 0 0 0 5.02e-05 NaN NaN 5.02e-05 0.0473
20 LPHN3 latrophilin 3 147364 7 6 7 3 3 3 1 0 0 0 5.89e-05 NaN NaN 5.89e-05 0.0492
21 ZIM3 zinc finger, imprinted 3 98103 6 5 6 0 1 1 3 0 1 0 6.02e-05 NaN NaN 6.02e-05 0.0492
22 MAP2K3 mitogen-activated protein kinase kinase 3 67262 4 4 4 0 1 1 1 1 0 0 6.05e-05 NaN NaN 6.05e-05 0.0492
23 FAM123B family with sequence similarity 123B 190503 8 6 8 1 0 2 1 0 5 0 8.10e-05 NaN NaN 8.10e-05 0.0630
24 PCDHA13 protocadherin alpha 13 162857 8 6 8 0 3 1 2 1 1 0 9.74e-05 NaN NaN 9.74e-05 0.0727
25 C4BPA complement component 4 binding protein, alpha 126397 5 5 5 1 2 2 0 0 1 0 0.000108 NaN NaN 0.000108 0.0776
26 CSMD3 CUB and Sushi multiple domains 3 787754 11 9 11 6 2 4 2 2 1 0 0.000139 NaN NaN 0.000139 0.0956
27 KCNS2 potassium voltage-gated channel, delayed-rectifier, subfamily S, member 2 80231 5 5 5 0 2 2 1 0 0 0 0.000161 NaN NaN 0.000161 0.107
28 CASP14 caspase 14, apoptosis-related cysteine peptidase 51900 5 4 4 0 4 1 0 0 0 0 0.000185 NaN NaN 0.000185 0.118
29 RBM10 RNA binding motif protein 10 160754 5 5 4 0 0 1 0 0 4 0 0.000212 NaN NaN 0.000212 0.131
30 SLITRK1 SLIT and NTRK-like family, member 1 134633 6 5 6 0 2 1 2 0 1 0 0.000293 NaN NaN 0.000293 0.170
31 OSBPL6 oxysterol binding protein-like 6 208053 5 5 5 0 1 2 0 2 0 0 0.000295 NaN NaN 0.000295 0.170
32 DKK4 dickkopf homolog 4 (Xenopus laevis) 46838 3 3 3 0 1 1 1 0 0 0 0.000316 NaN NaN 0.000316 0.177
33 LIFR leukemia inhibitory factor receptor alpha 228178 5 5 5 2 0 2 1 1 1 0 0.000359 NaN NaN 0.000359 0.195
34 SAMD9L sterile alpha motif domain containing 9-like 327283 9 6 9 1 1 6 1 0 1 0 0.000419 NaN NaN 0.000419 0.216
35 FAT4 FAT tumor suppressor homolog 4 (Drosophila) 968552 17 10 17 5 5 8 3 0 1 0 0.000429 NaN NaN 0.000429 0.216
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: 10. Number of genes displayed: 10

rank gene description n cos n_cos N_cos cos_ev p q
1 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 38 52 37 3588 363199 1.6e-13 7.2e-10
2 TP53 tumor protein p53 45 824 45 56856 17987 1.6e-12 2.4e-09
3 APC adenomatous polyposis coli 66 839 50 57891 1048 1.6e-12 2.4e-09
4 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 5 33 5 2277 5755 3.1e-11 3.5e-08
5 FBXW7 F-box and WD repeat domain containing 7 12 91 6 6279 329 4.5e-11 4.1e-08
6 SMAD4 SMAD family member 4 8 159 6 10971 39 1.2e-09 9.2e-07
7 KRTAP5-5 keratin associated protein 5-5 2 1 2 69 2 1.9e-07 0.00012
8 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 4 42 3 2898 6 3e-06 0.0017
9 PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 7 220 4 15180 1382 0.000013 0.0067
10 LRP1B low density lipoprotein-related protein 1B (deleted in tumors) 20 18 2 1242 2 0.000063 0.028

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
3872 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 38 0 278 416 445 278 416 445
7547 TP53 tumor protein p53 45 0 37 61 105 37 61 105
392 APC adenomatous polyposis coli 66 0 11 21 47 11 21 47
2614 FBXW7 F-box and WD repeat domain containing 7 12 0 6 6 6 6 6 6
4875 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 5 0 6 6 6 6 6 6
6841 SMAD4 SMAD family member 4 8 0 4 4 6 4 4 6
2361 ERBB2 v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) 4 0 3 3 3 3 3 3
3782 KIAA1804 11 0 2 6 7 2 6 7
3465 IL1RAPL2 interleukin 1 receptor accessory protein-like 2 5 0 1 3 3 1 3 3
2083 DNAH5 dynein, axonemal, heavy chain 5 19 0 1 2 2 1 2 2

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: 111. 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 q
1 ST_GRANULE_CELL_SURVIVAL_PATHWAY The survival and differentiation of granule cells in the brain is controlled by pro-growth PACAP and pro-apoptotic ceramides. ADPRT, APC, ASAH1, CAMP, CASP3, CERK, CREB1, CREB3, CREB5, CXCL2, DAG1, EPHB2, FOS, GNAQ, IL8RB, ITPKA, ITPKB, JUN, MAP2K4, MAP2K7, MAPK1, MAPK10, MAPK8, MAPK8IP1, MAPK8IP2, MAPK8IP3, MAPK9, PACAP 25 APC(66), CASP3(1), CREB3(1), CREB5(2), DAG1(1), EPHB2(1), FOS(1), GNAQ(1), MAP2K4(2), MAPK10(4), MAPK8(5), MAPK8IP3(1), MAPK9(2) 2754563 88 58 78 3 7 9 7 2 45 18 <1.00e-15 <8.74e-14
2 ST_MYOCYTE_AD_PATHWAY Cardiac myocytes have a variety of adrenergic receptors that induce subtype-specific signaling effects. ADRB1, AKT1, APC, ASAH1, BF, CAMP, CAV3, DAG1, DLG4, EPHB2, GAS, GNAI1, GNAQ, HTATIP, ITPR1, ITPR2, ITPR3, KCNJ3, KCNJ5, KCNJ9, MAPK1, PITX2, PLB, PTX1, PTX3, RAC1, RHO, RYR1 23 ADRB1(1), APC(66), CAV3(1), DAG1(1), DLG4(1), EPHB2(1), GNAI1(1), GNAQ(1), ITPR1(8), ITPR2(6), ITPR3(1), KCNJ5(1), KCNJ9(1), RHO(1), RYR1(6) 4224359 97 57 87 9 14 15 6 0 43 19 <1.00e-15 <8.74e-14
3 TGFBPATHWAY The TGF-beta receptor responds to ligand binding by activating the SMAD family of transcriptional regulations, commonly blocking cell growth. APC, CDH1, CREBBP, EP300, MADH2, MADH3, MADH4, MADH7, MADHIP, MAP2K1, MAP3K7, MAP3K7IP1, MAPK3, SKIL, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2 13 APC(66), CDH1(1), CREBBP(4), EP300(2), MAP2K1(1), MAP3K7(2), MAPK3(1), SKIL(1), TGFB2(4), TGFBR1(3) 2554178 85 57 75 4 5 10 8 0 44 18 <1.00e-15 <8.74e-14
4 HSA04370_VEGF_SIGNALING_PATHWAY Genes involved in VEGF signaling pathway AKT1, AKT2, AKT3, BAD, CASP9, CDC42, CHP, HRAS, KDR, KRAS, MAP2K1, MAP2K2, MAPK1, MAPK11, MAPK12, MAPK13, MAPK14, MAPK3, MAPKAPK2, MAPKAPK3, NFAT5, NFATC1, NFATC2, NFATC3, NFATC4, NOS3, NRAS, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIK3R5, PLA2G10, PLA2G12A, PLA2G12B, PLA2G1B, PLA2G2A, PLA2G2D, PLA2G2E, PLA2G2F, PLA2G3, PLA2G4A, PLA2G5, PLA2G6, PLCG1, PLCG2, PPP3CA, PPP3CB, PPP3CC, PPP3R1, PPP3R2, PRKCA, PRKCB1, PRKCG, PTGS2, PTK2, PXN, RAC1, RAC2, RAC3, RAF1, SH2D2A, SHC2, SPHK1, SPHK2, SRC, VEGFA 69 AKT2(1), AKT3(1), CDC42(1), KDR(2), KRAS(38), MAP2K1(1), MAP2K2(1), MAPK13(1), MAPK3(1), NFATC1(1), NFATC2(2), NFATC3(1), NFATC4(1), NRAS(5), PIK3CA(7), PIK3CD(1), PIK3CG(2), PIK3R1(5), PIK3R3(4), PLA2G4A(3), PLA2G6(2), PLCG2(4), PPP3CA(2), PPP3CB(1), PPP3CC(1), PRKCA(2), PRKCG(2), PTGS2(1), RAF1(2), SH2D2A(1), SHC2(1), SPHK1(1) 6915053 99 50 68 19 27 50 10 0 10 2 <1.00e-15 <8.74e-14
5 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(4), DAXX(1), PAX3(2), PML(1), RB1(3), SIRT1(1), TP53(45) 1828212 57 49 42 5 26 7 8 2 14 0 <1.00e-15 <8.74e-14
6 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(2), MAP3K14(1), NFKB1(3), TP53(45) 924291 51 47 36 3 22 7 8 2 12 0 1.11e-15 8.74e-14
7 G1_TO_S_CELL_CYCLE_REACTOME ATM, CCNA1, CCNB1, CCND1, CCND2, CCND3, CCNE1, CCNE2, CCNG2, CCNH, CDC25A, CDC45L, CDK2, CDK4, CDK7, CDKN1A, CDKN1B, CDKN1C, CDKN2A, CDKN2B, CDKN2C, CDKN2D, CREB3, CREB3L1, CREB3L3, CREB3L4, CREBL1, CREBL1, TNXB, E2F1, E2F2, E2F3, E2F4, E2F5, E2F6, FLJ14001, GADD45A, GBA2, MCM2, MCM3, MCM4, MCM5, MCM6, MCM7, MDM2, MNAT1, MYC, MYT1, NACA, NACA, FKSG17, ORC1L, ORC2L, ORC3L, ORC4L, ORC5L, ORC6L, PCNA, POLA2, POLE, POLE2, PRIM1, PRIM2A, RB1, RBL1, RPA1, RPA2, RPA3, TFDP1, TFDP2, TP53, WEE1 63 ATM(10), CCNA1(2), CCNE2(1), CDK4(1), CDKN1B(2), CREB3(1), CREB3L3(2), E2F3(1), MCM3(2), MCM5(3), MCM6(1), MCM7(1), MYT1(5), PCNA(1), POLE(4), POLE2(1), RB1(3), RBL1(2), TNXB(3), TP53(45) 7068990 91 53 75 16 31 25 12 3 19 1 1.22e-15 8.74e-14
8 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(5), ATM(10), CPB2(1), CSNK1D(1), FHL2(1), HIF1A(2), IGFBP3(2), MAPK8(5), TP53(45) 2001688 72 50 57 4 26 18 9 3 15 1 1.33e-15 8.74e-14
9 WNTPATHWAY The Wnt glycoprotein binds to membrane-bound receptors such as Frizzled to activate a number of signaling pathways, including that of beta-catenin. APC, AXIN1, BTRC, CCND1, CREBBP, CSNK1A1, CSNK1D, CSNK2A1, CTBP1, CTNNB1, DVL1, FRAT1, FZD1, GSK3B, HDAC1, MADH4, MAP3K7, MAP3K7IP1, MYC, NLK, PPARD, PPP2CA, TCF1, TLE1, WIF1, WNT1 21 APC(66), AXIN1(1), BTRC(3), CREBBP(4), CSNK1D(1), CTNNB1(4), FZD1(1), GSK3B(1), MAP3K7(2), PPARD(1) 2701685 84 58 74 4 8 9 8 0 41 18 1.44e-15 8.74e-14
10 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(10), CDK4(1), PCNA(1), RB1(3), TIMP3(1), TP53(45) 1820960 62 50 47 6 21 14 9 2 15 1 1.67e-15 8.74e-14

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 q
1 C21_STEROID_HORMONE_METABOLISM AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 11 AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) 837086 11 10 11 2 3 5 1 0 2 0 0.0014 0.3
2 HSA00140_C21_STEROID_HORMONE_METABOLISM Genes involved in C21-steroid hormone metabolism AKR1C4, AKR1D1, CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD11B1, HSD11B2, HSD3B1, HSD3B2 11 AKR1C4(1), AKR1D1(1), CYP11A1(2), CYP11B1(4), CYP21A2(1), HSD3B1(1), HSD3B2(1) 837086 11 10 11 2 3 5 1 0 2 0 0.0014 0.3
3 ERBB4PATHWAY ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 6 ADAM17(1), ERBB4(5), NRG2(2), NRG3(4), PRKCA(2) 908762 14 9 14 1 4 5 1 1 3 0 0.0014 0.3
4 HSA00240_PYRIMIDINE_METABOLISM Genes involved in pyrimidine metabolism AICDA, AK3, CAD, CANT1, CDA, CMPK, CTPS, CTPS2, DCK, DCTD, DHODH, DPYD, DPYS, DTYMK, DUT, ECGF1, ENTPD1, ENTPD3, ENTPD4, ENTPD5, ENTPD6, ENTPD8, ITPA, NME1, NME2, NME4, NME6, NME7, NP, NT5C, NT5C1A, NT5C1B, NT5C2, NT5C3, NT5E, NT5M, NUDT2, PNPT1, POLA1, POLA2, POLD1, POLD2, POLD3, POLD4, POLE, POLE2, POLE3, POLE4, POLR1A, POLR1B, POLR1C, POLR1D, POLR2A, POLR2B, POLR2C, POLR2D, POLR2E, POLR2F, POLR2G, POLR2H, POLR2I, POLR2J, POLR2K, POLR2L, POLR3A, POLR3B, POLR3G, POLR3GL, POLR3H, POLR3K, PRIM1, PRIM2, RFC5, RRM1, RRM2, RRM2B, TK1, TK2, TXNRD1, TXNRD2, TYMS, UCK1, UCK2, UMPS, UPB1, UPP1, UPP2, UPRT, ZNRD1 86 AICDA(1), CAD(1), CTPS(1), DCK(1), DHODH(1), DPYD(6), DPYS(1), DTYMK(1), ENTPD5(1), ENTPD6(1), NME6(1), NME7(2), NT5C1B(1), NT5C2(1), NT5E(1), PNPT1(5), POLA1(3), POLE(4), POLE2(1), POLR1A(3), POLR1B(2), POLR2B(3), POLR2K(1), POLR3A(4), POLR3B(5), POLR3K(1), PRIM2(3), RFC5(1), RRM1(1), TK2(1), TXNRD1(1), TXNRD2(1), TYMS(1), UMPS(1), UPB1(2), UPP2(1), UPRT(1) 7933506 67 28 65 15 18 26 10 0 13 0 0.0046 0.65
5 CREMPATHWAY The transcription factor CREM activates a post-meiotic transcriptional cascade culminating in spermatogenesis. ADCY1, CREM, FHL5, FSHB, FSHR, GNAS, XPO1 7 ADCY1(4), FHL5(3), FSHB(1), FSHR(1), XPO1(1) 917313 10 9 10 4 4 1 3 1 1 0 0.0053 0.65
6 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(4), GNGT1(1), PRKACA(1), PRKAR1A(4) 607553 10 8 10 1 3 4 1 0 2 0 0.0071 0.7
7 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 18 ADCY1(4), ARHGEF1(1), F2(1), GNAI1(1), GNAQ(1), GNGT1(1), MAP3K7(2), PIK3R1(5), PPP1R12B(4), PRKCA(2), ROCK1(7) 2322908 29 13 29 7 8 7 5 0 7 2 0.008 0.7
8 NEUROTRANSMITTERSPATHWAY Biosynthesis of neurotransmitters DBH, GAD1, HDC, PNMT, TH, TPH1 6 DBH(1), GAD1(2), HDC(5), TPH1(2) 572489 10 7 10 2 3 5 1 0 1 0 0.01 0.77
9 HSA00150_ANDROGEN_AND_ESTROGEN_METABOLISM Genes involved in androgen and estrogen metabolism AKR1C4, AKR1D1, ARSD, ARSE, CARM1, CYP11B1, CYP11B2, CYP19A1, HEMK1, HSD11B1, HSD11B2, HSD17B1, HSD17B12, HSD17B2, HSD17B3, HSD17B7, HSD17B8, HSD3B1, HSD3B2, LCMT1, LCMT2, METTL2B, METTL6, PRMT2, PRMT3, PRMT5, PRMT6, PRMT7, PRMT8, SRD5A1, SRD5A2, STS, SULT1E1, SULT2A1, SULT2B1, UGT1A1, UGT1A10, UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT2A1, UGT2A3, UGT2B10, UGT2B11, UGT2B15, UGT2B17, UGT2B28, UGT2B4, UGT2B7, WBSCR22 53 AKR1C4(1), AKR1D1(1), CYP11B1(4), CYP19A1(3), HSD17B2(1), HSD17B3(1), HSD3B1(1), HSD3B2(1), LCMT1(2), METTL2B(1), METTL6(3), PRMT3(1), PRMT7(1), PRMT8(2), SRD5A2(1), STS(1), SULT1E1(1), SULT2A1(1), UGT1A4(1), UGT1A6(1), UGT1A8(1), UGT1A9(1), UGT2A3(2), UGT2B11(2), UGT2B17(3), UGT2B28(1), UGT2B4(1), UGT2B7(2) 4462401 42 18 42 9 9 19 6 1 7 0 0.012 0.77
10 HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM Genes involved in D-arginine and D-ornithine metabolism DAO 1 DAO(4) 73821 4 3 4 0 3 1 0 0 0 0 0.012 0.77
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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