Lung Squamous Cell Carcinoma: Mutation Analysis (MutSig)

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 vS2N was used to generate the results found in this report.

Working with individual set: LUSC

Input

The input for this pipeline is a set of individuals with the following files associated for each:

An annotated .maf file describing the mutations called for the respective individual, and their properties.
A .wig file that contains information about the coverage of the sample.

Summary

MAF used for this analysis:LUSC.final_analysis_set.maf
Significantly mutated genes (q ≤ 0.1): 9

Results

Significantly Mutated Genes

Column Descriptions:

N = number of sequenced bases in this gene across the individual set
nnon = number of (nonsilent) mutations in this gene across the individual set
nnull = number of (nonsilent) null mutations in this gene across the individual set
nflank = number of noncoding mutations from this gene's flanking region, across the individual set
nsil = number of silent mutations in this gene across the individual set
p = p-value (overall)
q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 1. 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).

gene	N	nflank	nsil	nnon	nnull	p	q
TP53	22428	0	5	146	47	1.5e-144	2.8e-140
CDKN2A	10020	3	1	26	12	1.2e-61	1.1e-57
PIK3CA	74998	1	1	29	0	5.1e-29	3.2e-25
HLA-A	19194	0	0	7	6	8.3e-16	3.9e-12
KEAP1	32842	0	0	23	2	1.8e-13	6.7e-10
PTEN	28478	1	0	16	8	1.9e-12	6.1e-09
NFE2L2	38270	1	0	28	1	2.9e-12	7.9e-09
MLL2	221958	3	6	40	18	1.3e-11	3e-08
SCN1A	141098	2	9	34	3	4e-05	0.084
PRR23B	9552	0	2	9	0	0.000086	0.16
FSCB	40910	0	2	19	1	0.0002	0.34
WHSC1L1	93628	2	1	16	2	0.00026	0.4
COL19A1	56664	6	4	19	2	0.00028	0.4
AHNAK	358404	0	8	25	1	0.00035	0.45
ASCL4	3234	0	0	6	2	0.00036	0.45
NOTCH1	94148	2	3	17	7	0.00044	0.51
TRIOBP	96658	2	1	20	1	0.00059	0.6
ZNF208	84566	1	6	27	1	0.0006	0.6
AKAP13	169872	3	4	19	0	0.00061	0.6
MAGEB2	15514	0	1	9	0	0.00064	0.6
TAS2R60	21004	0	0	8	0	0.00071	0.62
SPHKAP	103032	2	3	34	1	0.00072	0.62
OR2G6	20648	0	4	16	0	0.00086	0.68
MAGEA6	16198	0	2	9	1	0.00087	0.68
CPS1	99740	10	3	27	2	0.00094	0.71
REG3A	10858	2	2	13	1	0.00098	0.71
CYP11B1	29548	2	0	15	0	0.0011	0.73
MYPN	78468	1	4	15	0	0.0011	0.73
TPTE	40970	10	2	30	5	0.0012	0.77
MYH2	131572	2	6	33	3	0.0012	0.77
FAM47C	50224	0	5	21	1	0.0013	0.77
DNAH6	28928	1	1	5	1	0.0014	0.85
EBF1	33494	1	1	8	1	0.0016	0.93
ZIC1	23436	0	5	20	2	0.0019	1
CD109	99058	3	1	8	0	0.0019	1

TP53

Figure S1. This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.

CDKN2A

Figure S2. This figure depicts the distribution of mutations and mutation types across the CDKN2A significant gene.

PIK3CA

Figure S3. This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.

HLA-A

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

KEAP1

Figure S5. This figure depicts the distribution of mutations and mutation types across the KEAP1 significant gene.

PTEN

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

NFE2L2

Figure S7. This figure depicts the distribution of mutations and mutation types across the NFE2L2 significant gene.

MLL2

Figure S8. This figure depicts the distribution of mutations and mutation types across the MLL2 significant gene.

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)