Lung Adenocarcinoma: Mutation Analysis (MutSig v2.0)
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: LUAD

  • Number of patients in set: 129

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:LUAD.final_analysis_set.maf

  • Significantly mutated genes (q ≤ 0.1): 124

  • Mutations seen in COSMIC: 266

  • Significantly mutated genes in COSMIC territory: 11

  • Genes with clustered mutations (≤ 3 aa apart): 87

  • Significantly mutated genesets: 11

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

Mutation Preprocessing

  • Read 129 MAFs of type "Broad"

  • Total number of mutations in input MAFs: 132457

  • After removing 11 mutations outside chr1-24: 132446

  • After removing 557 blacklisted mutations: 131889

  • After removing 66504 noncoding mutations: 65385

  • After collapsing adjacent/redundant mutations: 56034

Mutation Filtering

  • Number of mutations before filtering: 56034

  • After removing 675 mutations outside gene set: 55359

  • After removing 318 mutations outside category set: 55041

Results
Breakdown of Mutations by Type

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

type count
Frame_Shift_Del 648
Frame_Shift_Ins 232
In_Frame_Del 93
In_Frame_Ins 10
Missense_Mutation 35707
Nonsense_Mutation 2806
Nonstop_Mutation 30
Silent 14402
Splice_Site 1033
Translation_Start_Site 80
Total 55041
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->A 6856 213659604 0.000032 32 3 2.1
*Cp(A/C/T)->A 13232 1751081217 7.6e-06 7.6 0.72 5
C->(T/G) 10225 1964740821 5.2e-06 5.2 0.49 2.8
A->mut 5448 1889897214 2.9e-06 2.9 0.27 3.9
indel+null 4773 3854638035 1.2e-06 1.2 0.12 NaN
double_null 105 3854638035 2.7e-08 0.027 0.0026 NaN
Total 40639 3854638035 0.000011 11 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: LUAD.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->A

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

  • n3 = number of nonsilent mutations of type: C->(T/G)

  • 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_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_ks = p-value for clustering of mutations (Kolmogorov-Smirnoff test)

  • 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: 124. 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_ks p_cons p_joint p q
1 STK11 serine/threonine kinase 11 112230 18 17 17 0 0 4 1 4 9 0 3.2e-15 0.018 0.00013 0.0027 0.000052 0.000 0.000
2 TP53 tumor protein p53 162282 65 58 55 2 4 12 16 10 23 0 4.3e-15 0.000023 2e-07 2e-07 0 <1.00e-15 <3.62e-12
3 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 91203 35 35 3 0 0 31 3 1 0 0 2.3e-15 0.042 2e-07 2e-07 0 <1.00e-15 <3.62e-12
4 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 517161 24 19 14 5 2 4 3 9 6 0 0.00014 0.57 2e-07 0.0013 0 <1.00e-15 <3.62e-12
5 OR6C4 olfactory receptor, family 6, subfamily C, member 4 120228 2 2 2 0 0 0 1 0 1 0 0.13 0.4 0.06 0.0076 0 <1.00e-15 <3.62e-12
6 KEAP1 kelch-like ECH-associated protein 1 235941 24 24 23 0 2 3 11 6 2 0 7.7e-15 0.00076 0.081 0.15 0.082 2.28e-14 6.86e-11
7 BRAF v-raf murine sarcoma viral oncogene homolog B1 287799 13 13 9 1 1 4 2 4 2 0 9.6e-08 0.17 0.0036 0.097 0.0054 1.16e-08 3.00e-05
8 NAV3 neuron navigator 3 934992 36 27 36 2 3 22 5 5 0 1 1.3e-09 0.022 0.39 0.52 0.48 1.35e-08 3.06e-05
9 CD5L CD5 molecule-like 137772 11 11 11 1 3 2 0 3 3 0 4.1e-08 0.2 0.17 0.01 0.018 1.57e-08 3.15e-05
10 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 127323 7 7 7 1 0 1 1 2 3 0 8.7e-06 0.64 0.013 0.00038 0.00027 4.89e-08 8.84e-05
11 REG3A regenerating islet-derived 3 alpha 70692 11 10 11 1 0 3 5 1 2 0 8.4e-09 0.24 0.23 0.66 0.47 8.04e-08 0.000132
12 RIMS2 regulating synaptic membrane exocytosis 2 560118 27 22 27 2 2 10 6 4 5 0 3e-08 0.12 0.23 0.095 0.17 1.04e-07 0.000157
13 U2AF1 U2 small nuclear RNA auxiliary factor 1 106425 4 4 1 0 0 0 4 0 0 0 0.0071 0.32 4e-07 1e-05 1.2e-06 1.67e-07 0.000233
14 DCAF4L2 DDB1 and CUL4 associated factor 4-like 2 153768 11 10 11 1 1 4 2 2 2 0 1.2e-07 0.2 0.07 0.86 0.18 3.99e-07 0.000515
15 MAGEC1 melanoma antigen family C, 1 436020 21 19 21 2 1 10 5 4 1 0 4.7e-08 0.14 0.32 0.67 0.56 4.84e-07 0.000584
16 IL1RAPL1 interleukin 1 receptor accessory protein-like 1 273222 11 11 10 0 1 3 4 2 1 0 2.1e-06 0.083 0.054 0.024 0.017 6.31e-07 0.000713
17 CDH8 cadherin 8, type 2 315276 13 13 12 0 1 5 3 1 3 0 1.4e-06 0.062 0.041 0.12 0.044 1.11e-06 0.00118
18 OR2T33 olfactory receptor, family 2, subfamily T, member 33 124614 10 9 10 1 3 3 1 2 1 0 2.3e-07 0.18 0.18 0.6 0.3 1.21e-06 0.00122
19 TMTC1 transmembrane and tetratricopeptide repeat containing 1 306117 17 13 16 2 2 9 3 1 2 0 9.2e-07 0.24 0.57 0.038 0.12 1.95e-06 0.00186
20 HGF hepatocyte growth factor (hepapoietin A; scatter factor) 285993 18 14 18 1 0 10 3 4 1 0 2.2e-07 0.21 0.77 0.31 0.63 2.35e-06 0.00212
21 SNTG1 syntrophin, gamma 1 209238 15 14 15 2 2 4 3 4 2 0 2.9e-07 0.26 0.52 0.24 0.54 2.60e-06 0.00224
22 MUC7 mucin 7, secreted 147318 12 10 12 0 0 5 2 3 2 0 7.3e-07 0.078 0.14 0.55 0.27 3.26e-06 0.00268
23 OR2T4 olfactory receptor, family 2, subfamily T, member 4 135579 11 10 11 1 0 4 5 2 0 0 9.7e-07 0.14 0.12 0.81 0.25 3.95e-06 0.00311
24 OR2W3 olfactory receptor, family 2, subfamily W, member 3 122163 11 10 11 1 2 4 2 2 1 0 4.1e-07 0.11 0.39 0.89 0.64 4.23e-06 0.00319
25 EPHA6 EPH receptor A6 425442 18 15 18 3 1 10 4 2 1 0 0.000069 0.45 0.03 0.011 0.0045 4.93e-06 0.00357
26 CARM1 coactivator-associated arginine methyltransferase 1 203949 3 3 2 0 0 0 3 0 0 0 0.17 0.3 1.8e-06 0.26 2.2e-06 6.05e-06 0.00405
27 RBM10 RNA binding motif protein 10 251034 10 10 10 1 1 0 1 0 8 0 9.8e-06 0.085 0.091 0.1 0.041 6.26e-06 0.00405
28 CDH10 cadherin 10, type 2 (T2-cadherin) 311019 30 24 30 6 3 15 8 1 3 0 4.9e-07 0.49 0.67 0.46 0.81 6.26e-06 0.00405
29 OR2L3 olfactory receptor, family 2, subfamily L, member 3 121647 10 9 10 1 0 5 2 3 0 0 8.6e-07 0.26 0.36 0.6 0.51 6.85e-06 0.00428
30 REG1B regenerating islet-derived 1 beta (pancreatic stone protein, pancreatic thread protein) 67209 6 6 6 0 0 3 1 2 0 0 0.000013 0.28 0.045 0.14 0.049 9.98e-06 0.00602
31 PDE10A phosphodiesterase 10A 313212 9 9 9 1 2 2 3 2 0 0 0.0014 0.3 0.00031 0.54 0.0005 1.10e-05 0.00641
32 SEC14L1 SEC14-like 1 (S. cerevisiae) 287412 4 4 4 2 2 0 1 1 0 0 0.55 0.84 0.073 2e-07 1.4e-06 1.15e-05 0.00651
33 CDH18 cadherin 18, type 2 311793 14 13 14 1 0 9 2 3 0 0 5.3e-06 0.25 0.3 0.088 0.16 1.27e-05 0.00668
34 SETD2 SET domain containing 2 823407 16 13 16 0 0 3 1 2 9 1 0.00052 0.055 0.00085 0.25 0.0016 1.29e-05 0.00668
35 OR4C46 olfactory receptor, family 4, subfamily C, member 46 120228 9 9 8 1 0 4 1 3 1 0 1e-06 0.3 0.64 0.56 0.87 1.32e-05 0.00668
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: 11. 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 35 51 35 6579 491694 0 0
2 TP53 tumor protein p53 65 308 61 39732 8260 0 0
3 BRAF v-raf murine sarcoma viral oncogene homolog B1 13 88 10 11352 21196 0 0
4 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 24 218 21 28122 8076 0 0
5 STK11 serine/threonine kinase 11 18 130 12 16770 26 0 0
6 MET met proto-oncogene (hepatocyte growth factor receptor) 10 33 5 4257 60 1.5e-09 1.1e-06
7 CDKN2A cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) 7 315 7 40635 126 3.6e-07 0.00023
8 CTNNB1 catenin (cadherin-associated protein), beta 1, 88kDa 9 101 4 13029 1911 0.000013 0.0074
9 SMC2 structural maintenance of chromosomes 2 4 4 2 516 2 0.000015 0.0074
10 SMAD4 SMAD family member 4 6 159 4 20511 17 0.000077 0.035

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
5758 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 35 0 528 528 528 528 528 528
3336 EGFR epidermal growth factor receptor (erythroblastic leukemia viral (v-erb-b) oncogene homolog, avian) 24 0 22 31 31 22 31 31
11252 TP53 tumor protein p53 65 0 16 74 202 16 74 202
1083 BRAF v-raf murine sarcoma viral oncogene homolog B1 13 0 4 6 10 4 6 10
10430 SPTA1 spectrin, alpha, erythrocytic 1 (elliptocytosis 2) 49 0 3 5 13 3 5 13
12412 ZNF536 zinc finger protein 536 30 0 3 4 8 3 4 8
5525 KEAP1 kelch-like ECH-associated protein 1 24 0 2 6 18 2 6 18
2045 CDH10 cadherin 10, type 2 (T2-cadherin) 30 0 2 6 12 2 6 12
10549 STK11 serine/threonine kinase 11 18 0 2 5 19 2 5 19
11427 TSHZ3 teashirt zinc finger homeobox 3 20 0 2 2 5 2 2 5

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: 11. 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 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 HDAC1(1), MAX(1), SP3(1), TP53(65), WT1(7) 1367658 75 60 65 8 5 18 17 10 25 0 0.0048 <1.00e-15 <4.10e-13
2 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), DNAJC3(2), MAP3K14(1), NFKB1(2), TP53(65) 1900041 71 59 61 7 5 13 19 10 24 0 0.0043 1.33e-15 4.10e-13
3 PLK3PATHWAY Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH 7 ATM(14), ATR(9), CHEK1(6), CHEK2(2), TP53(65) 3108126 96 68 85 7 5 21 24 15 31 0 0.0011 2.55e-15 5.24e-13
4 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), CCND1(2), CDK2(4), CDK4(2), CDKN1B(2), CDKN2A(7), MDM2(1), PRB1(3), TP53(65) 1666809 87 62 77 7 11 17 18 13 28 0 0.00011 4.22e-15 6.50e-13
5 TIDPATHWAY On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 18 IFNG(3), IFNGR1(3), IFNGR2(2), IKBKB(2), JAK2(2), LIN7A(1), NFKB1(2), RB1(5), TNFRSF1B(1), TP53(65), USH1C(3), WT1(7) 3567108 96 68 86 9 9 22 23 12 30 0 0.00022 8.88e-15 1.09e-12
6 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(2), DAXX(2), HRAS(1), PAX3(3), PML(4), RARA(2), RB1(5), SIRT1(1), SP100(4), TNFRSF1B(1), TP53(65) 3730422 90 64 80 7 7 17 23 14 29 0 0.000091 4.23e-14 4.34e-12
7 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(4), ATM(14), BAX(1), BCL2(1), CCND1(2), CCNE1(3), CDK2(4), CDK4(2), GADD45A(1), MDM2(1), RB1(5), TP53(65) 3530085 103 73 92 12 11 22 22 16 32 0 0.0032 1.11e-12 9.79e-11
8 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(14), CDC25A(2), CDC25B(1), CDK2(4), CDK4(2), CHEK1(6), MYT1(5), RB1(5), TP53(65), WEE1(1) 3419532 105 72 94 12 9 24 22 16 34 0 0.0042 1.73e-11 1.33e-09
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), CDKN2A(7), MDM2(1), PIK3CA(5), PIK3R1(1), POLR1A(5), POLR1B(8), POLR1D(1), RB1(5), TP53(65), TWIST1(1) 3965073 100 66 88 11 11 18 24 16 31 0 0.00078 2.33e-08 1.60e-06
10 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(10), ATM(14), BAX(1), CSNK1A1(1), CSNK1D(1), GADD45A(1), HIF1A(1), IGFBP3(2), MAPK8(3), MDM2(1), NQO1(3), TP53(65) 4040280 103 69 92 13 11 24 22 13 33 0 0.0072 1.62e-06 0.000100

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 P27PATHWAY p27 blocks the G1/S transition by inhibiting the checkpoint kinase cdk2/cyclin E and is inhibited by cdk2-mediated ubiquitination. CCNE1, CDK2, CDKN1B, CKS1B, CUL1, E2F1, NEDD8, RB1, RBX1, SKP1A, SKP2, TFDP1, UBE2M 12 CCNE1(3), CDK2(4), CDKN1B(2), CUL1(3), NEDD8(2), RB1(5), SKP2(3), TFDP1(2), UBE2M(1) 1678032 25 19 25 3 5 4 8 4 4 0 0.084 0.018 1
2 SKP2E2FPATHWAY E2F-1, a transcription factor that promotes the G1/S transition, is repressed by Rb and activated by cdk2/cyclin E. CCNA1, CCNE1, CDC34, CDK2, CUL1, E2F1, RB1, SKP1A, SKP2, TFDP1 9 CCNA1(2), CCNE1(3), CDC34(1), CDK2(4), CUL1(3), RB1(5), SKP2(3), TFDP1(2) 1675581 23 18 23 2 6 5 6 3 3 0 0.056 0.048 1
3 ST_INTERFERON_GAMMA_PATHWAY The interferon gamma pathway resembles the JAK-STAT pathway and activates STAT transcription factors. CISH, IFNG, IFNGR1, JAK1, JAK2, PLA2G2A, PTPRU, REG1A, STAT1, STATIP1 9 IFNG(3), IFNGR1(3), JAK1(5), JAK2(2), PLA2G2A(3), PTPRU(6), REG1A(5), STAT1(2) 2243697 29 22 29 3 5 6 6 5 7 0 0.043 0.1 1
4 IL18PATHWAY Pro-inflammatory IL-18 is activated in macrophages by caspase-1 cleavage and, in conjunction with IL-12, stimulates Th1 cell differentiation. CASP1, IFNG, IL12A, IL12B, IL18, IL2 6 CASP1(2), IFNG(3), IL12A(2), IL2(3) 581919 10 8 10 1 2 5 2 0 1 0 0.26 0.14 1
5 IFNGPATHWAY IFN gamma signaling pathway IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1 6 IFNG(3), IFNGR1(3), IFNGR2(2), JAK1(5), JAK2(2), STAT1(2) 1595988 17 14 17 2 3 1 6 3 4 0 0.12 0.17 1
6 FBW7PATHWAY Cyclin E interacts with cell cycle checkpoint kinase cdk2 to allow transcription of genes required for S phase, including transcription of additional cyclin E. CCNE1, CDC34, CDK2, CUL1, E2F1, FBXW7, RB1, SKP1A, TFDP1 8 CCNE1(3), CDC34(1), CDK2(4), CUL1(3), FBXW7(2), RB1(5), TFDP1(2) 1630818 20 15 20 2 5 4 5 3 3 0 0.11 0.17 1
7 RECKPATHWAY RECK is a membrane-anchored inhibitor of matrix metalloproteinases, which are expressed by tumor cells and promote metastasis. HRAS, MMP14, MMP2, MMP9, RECK, TIMP1, TIMP2, TIMP3, TIMP4 9 HRAS(1), MMP14(2), MMP2(6), MMP9(8), RECK(5), TIMP4(1) 1454862 23 16 23 4 3 4 7 4 5 0 0.24 0.21 1
8 NUCLEOTIDE_SUGARS_METABOLISM GALE, GALT, TGDS, UGDH, UXS1 5 GALT(1), TGDS(2), UGDH(3), UXS1(4) 755037 10 9 10 2 1 2 4 0 3 0 0.56 0.22 1
9 SLRPPATHWAY Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. BGN, DCN, DSPG3, FMOD, KERA, LUM 5 BGN(4), DCN(1), FMOD(2), KERA(3), LUM(3) 700083 13 11 13 3 2 4 3 3 1 0 0.46 0.23 1
10 HSA00902_MONOTERPENOID_BIOSYNTHESIS Genes involved in monoterpenoid biosynthesis CYP2C19, CYP2C9 2 CYP2C19(5), CYP2C9(2) 389193 7 6 7 2 2 2 0 1 2 0 0.68 0.24 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)
Copyright © 2012 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
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