Download GWAS_CN_alterations_20090528gscTalk

Genome–wide Scan of Genetic Variants
Associated with DNA Copy Number Alterations
in Lung Cancer (Adenocarcinoma)
Qunyuan Zhang
Division of Statistical Genomics
The CGS Research Talk, May 28,2009
Genetic Abnormalities & Cancers
Normal
Genome
(Genotypes)
Non-genetic Factors
Chemical carcinogens
Radiation
Viral or bacterial infection
Hormonal imbalances
…
Random
Mutations
Cancers
Hypothesis to be tested:
DNA polymorphisms (genotypes)
in normal cells may associate with
genomic abnormalities in tumor
cells.
Abnormal
Genome
Genetic Alterations
Mutation
Copy number alteration
LOH
Methylation
…
Previous Work
Smith AG, Worrillow LJ, Allan JM. A common genetic variant in XPD associates with
risk of 5q- and 7q-deleted acute myeloid leukemia. Blood. 2007 Feb 1;109(3):1233-6.
Gao Q, Horwitz M, Roulston D, et al. Susceptibility gene for familial acute myeloid
leukemia associated with loss of 5q and/or 7q is not localized on the commonly deleted
portion of 5q. Genes Chromosomes Cancer. 2000;28:164-172.
Stern MC, Conway K, Li Y, Mistry K, Taylor JA. DNA repair gene polymorphisms and
probability of p53 mutation in bladder cancer. Mol Carcinog. 2006;45:715-719.
Mechanic LE, Marrogi AJ, Welsh JA, et al. Polymorphisms in XPD and TP53 and
mutation in human lung cancer. Carcinogenesis. 2005;26:597-604.
Our Goal
Genome-wide scan to identify genetic variants (polymorphisms) in normal cells that
associate with DNA copy number alterations (CNA) in tumor cells.
Data
From Tumor Sequencing Project (TSP)
Nature. 2007 Dec 6;450(7171):893-8.
Nature. 2008 Oct 23;455(7216):1069-75.
383 lung cancer patients
383 pairs (tumor & normal) of samples
357 pairs after QC
Affymetrix Human Mapping 250K Sty SNP Array
357 CEL files (normal samples) => Affymetrix GeneChip®
Genotyping Analysis Software (GTYPE 4.0)
=> genotypes of 250K SNPs
2*357=714 CEL files => (background correction, normalization,
summarization using diChip) => intensities for 250K SNPs
=> log2(tumor/normal) ratios for 250K SNPs
Intensity Log2 Ratio Changes on Chromosome
(Subject ID: 101, Chr. 14)
Genome-wide Pattern of Copy Number (Log2 Ratio) Changes in Lung Cancer
(Smoothed and Averaged over 357 Patients)
Indentifying Reccurent CN Alterations
( CMDS: correlation matrix diagonal segmentation)
RCNA region
RCNA region
RCNA region
CN Alteration Regions/Genes in Lung Cancer
EGFR
CCND1
MYC
MDM1, MDM2
KRAS
TITF1,MBIP
CN Alteration Frequencies of Selected Genes
(in 357 tumor samples)
Gene(SNP#)
Amp. Freq.
Del. Freq.
EGFR(73)
0.176
0.000
MYC(6)
0.168
0.008
MBIP(59)
0.148
0.022
TITF1(21)
0.126
0.017
KRAS(44)
0.090
0.022
MDM1(46)
0.090
0.011
MDM2(6)
0.084
0.022
CCND1(56)
0.081
0.011
CN alteration status of each gene is defined as log2 ratio > 2 SD
CN Distributions of 4 Genes
(in 357 tumor samples)
EGFR
TITF1
1.6
2
1.4
1.2
1.5
1
1
0.8
0.6
0.5
0.4
0.2
0
0
0
-0.2 0
50
100
150
200
250
300
350
400
-0.4
50
100
150
200
250
300
350
400
250
300
350
400
-0.5
-1
MDM1
KRAS
2.5
2.5
2
2
1.5
1.5
1
1
0.5
0.5
0
0
50
100
150
200
250
300
350
400
0
-0.5
-1
0
-0.5
50
100
150
200
(based on the data of 357 samples from normal tissue)
(250K SNPs)
-Log(P) Values from GWAS test of EGFR’s Copy Number Alteration
-Log(FDR) Values from GWAS test of EGFR’s Copy Number Alteration
Minor Allelic Freq.
(MAF) of 124
Significant SNPs
-Log(P) Values of 15 Significant SNPs
(FDR<0.05 and MAF>0.03, test of EGFR)
-Log(P) Values of 121 Significant SNPs
(FDR<0.05 and MAF>0.03, test for all 8 genes)
CCNE1 EGFR KRAS MBIP MDM1 TITF1
3
15
34
40
18
28
Total 121 SNPs
TITF1 Copy Number
An Example of Association
AA
AB
BB
Genotype of SNP-1948204
(MAF=0.45, P=0.00005)
Genes at Significant Loci
CNA
Region
Sig.
SNP#
Sig.
Gene#
Gene list
CCNE1
3
4
EGFR
15
24
ADPGK C10orf38 C10orf76 CKLFSF8 CPEB2 FAM44A FGFR2 GAGE4 GAGE5 GAGE6 GAGE7
GAGE7B GPD1L GRIN2A IL1A IL1B LOC92345 MUM1 NDUFA12 NEO1 NPY5R PPP1R3F
PTHB1 WBSCR17
KRAS
34
41
BCOR BICD1 C16orf47 CAPZB CLSTN2 CNBD1 COX17 CYP4F12 DDI1 EDN1 EN1
EN2
FLJ33708 FOXG1B HIVEP1 INSIG1 NSIG2 ITGA9 ITPKB KIAA0574 KIAA0934 LY86
MAGI3 MGC14798 MICAL-L2 MID1IP1 NISCH NOVA1 PARP1 PDGFD PKIA POPDC2
PXMP3 RBBP7 REPS2 RREB1 SGEF ST6GAL2 TLE2 TU3A WDR21C
MBIP
40
47
AFAP
AP1S3 ATXN1 C10orf108 C15orf15 CDH11 CDH8 CMKLR1 CPAMD8 CRB2
CXorf36 DENND1A DTNBP1 FANCB FLJ10996 FLJ33708 FLJ33814 GLRA2 GPC6
GPR110
GTF3A HMGA2 HTR4 INSIG2 KCTD12 KIAA0460 KIAA0934 KIAA1505 LHX2
LRP1B
MFHAS1 MTIF3 MYLIP PGRMC2 PHF17 RASL11A RPN2 SEMA5A SLC25A21 THEX1
TLK1
TNFRSF21 UTX
WWOX
ZMYND11 ZNF516 ZNF673
MDM1
18
30
APOA4 APOA5 ATP8A1
BARD1
C1orf190 DKFZP 586H2123 FLJ10159 FLJ10803 GAS2L3
GFRA2 GGTL4
GLRA1
GNAZ
HRMT1L4
IER3IP1 LPHN2
LZTS1
MGC4266
MSI2
NMUR2 PRAME
RAD54L
RTDR1
SCML4
SUHW1
SUHW2
TCERG1L
TMEM16D
TXNL2
ZNF638
TITF1
28
29
AP1S3 CDH11 CDH8 CMKLR1 CPAMD8 CXorf36 DBC1 DTNBP1 FANCB FLJ10094
FLJ31846 GLRA2 IBRDC2 ID4
KCTD12 KIAA0460 LRP1B MFHAS1 MYLIP NBL1 PROX1
RPN2 RYR2 SEMA5A SLC6A5 THEX1 TLK1 UTX ZNF673
Total
121
152
API5 GNAQ ITGA7 LRRC4C
Level 1 Pathways (1-5)
01100 Metabolism
01200 Genetic Information Processing
56
5
01300 Environmental Information Processing
43
01400 Cellular Processes
56
01500 Human Diseases
13
Level 2 Pathways (1-27)
01330 Signaling Molecules and Interaction
01320 Signal Transduction
01430 Cell Communication
01150 Amino Acid Metabolism
01130 Lipid Metabolism
01440 Development
01110 Carbohydrate Metabolism
01480 Endocrine System
01160 Metabolism of Other Amino Acids
01196 Xenobiotics Biodegradation and Metabolism
01410 Cell Motility
01540 Cancers
01420 Cell Growth and Death
01460 Immune System
01120 Energy Metabolism
01470 Nervous System
01530 Metabolic Disorders
01170 Glycan Biosynthesis and Metabolism
01310 Membrane Transport
01510 Neurodegenerative Disorders
01190 Metabolism of Cofactors and Vitamins
01195 Biosynthesis of Secondary Metabolites
01210 Transcription
01140 Nucleotide Metabolism
01220 Translation
01230 Folding, Sorting and Degradation
01240 Replication and Repair
22
18
18
13
9
9
8
8
7
7
7
6
5
5
4
4
4
3
3
3
2
2
2
1
1
1
1
Level 3 Pathways (1-20)
04510 Focal adhesion [PATH:ko04510]
04080 Neuroactive ligand-receptor interaction [PATH:ko04080]
04512 ECM-receptor interaction [PATH:ko04512]
04020 Calcium signaling pathway [PATH:ko04020]
04810 Regulation of actin cytoskeleton [PATH:ko04810]
00380 Tryptophan metabolism [PATH:ko00380]
04360 Axon guidance [PATH:ko04360]
00500 Starch and sucrose metabolism [PATH:ko00500]
04010 MAPK signaling pathway [PATH:ko04010]
04060 Cytokine-cytokine receptor interaction [PATH:ko04060]
04320 Dorso-ventral axis formation [PATH:ko04320]
00071 Fatty acid metabolism [PATH:ko00071]
00190 Oxidative phosphorylation [PATH:ko00190]
00450 Selenoamino acid metabolism [PATH:ko00450]
04111 Cell cycle - yeast [PATH:ko04111]
04530 Tight junction [PATH:ko04530]
05010 Alzheimer s disease [PATH:ko05010]
05220 Chronic myeloid leukemia [PATH:ko05220]
00310 Lysine degradation [PATH:ko00310]
00340 Histidine metabolism [PATH:ko00340]
12
8
8
7
7
5
5
4
4
4
4
3
3
3
3
3
3
3
2
2
Level 3 Pathways (21-40)
00350 Tyrosine metabolism [PATH:ko00350]
00510 N-Glycan biosynthesis [PATH:ko00510]
00564 Glycerophospholipid metabolism [PATH:ko00564]
02082 Other transporters [:ko]
03022 Basal transcription factors [PATH:ko03022]
03320 PPAR signaling pathway [PATH:ko03320]
04210 Apoptosis [PATH:ko04210]
04330 Notch signaling pathway [PATH:ko04330]
04514 Cell adhesion molecules (CAMs) [PATH:ko04514]
04540 Gap junction [PATH:ko04540]
04640 Hematopoietic cell lineage [PATH:ko04640]
04720 Long-term potentiation [PATH:ko04720]
04730 Long-term depression [PATH:ko04730]
04920 Adipocytokine signaling pathway [PATH:ko04920]
04940 Type I diabetes mellitus [PATH:ko04940]
04950 Maturity onset diabetes of the young [PATH:ko04950]
05215 Prostate cancer [PATH:ko05215]
00051 Fructose and mannose metabolism [PATH:ko00051]
00052 Galactose metabolism [PATH:ko00052]
00120 Bile acid biosynthesis [PATH:ko00120]
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
1
Level 3 Pathways (41-60)
00130 Ubiquinone biosynthesis [PATH:ko00130]
00150 Androgen and estrogen metabolism [PATH:ko00150]
00230 Purine metabolism [PATH:ko00230]
00260 Glycine serine and threonine metabolism [PATH:ko00260]
00360 Phenylalanine metabolism [PATH:ko00360]
00361 gamma-Hexachlorocyclohexane degradation [PATH:ko00361]
00363 Bisphenol A degradation [PATH:ko00363]
00430 Taurine and hypotaurine metabolism [PATH:ko00430]
00440 Aminophosphonate metabolism [PATH:ko00440]
00460 Cyanoamino acid metabolism [PATH:ko00460]
00480 Glutathione metabolism [PATH:ko00480]
00512 O-Glycan biosynthesis [PATH:ko00512]
00562 Inositol phosphate metabolism [PATH:ko00562]
00590 Arachidonic acid metabolism [PATH:ko00590]
00591 Linoleic acid metabolism [PATH:ko00591]
00624 1- and 2-Methylnaphthalene degradation [PATH:ko00624]
00625 Tetrachloroethene degradation [PATH:ko00625]
00626 Naphthalene and anthracene degradation [PATH:ko00626]
00632 Benzoate degradation via CoA ligation [PATH:ko00632]
00642 Ethylbenzene degradation [PATH:ko00642]
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Level 3 Pathways (61-83)
00650 Butanoate metabolism [PATH:ko00650]
00790 Folate biosynthesis [PATH:ko00790]
00903 Limonene and pinene degradation [PATH:ko00903]
00920 Sulfur metabolism [PATH:ko00920]
00960 Alkaloid biosynthesis II [PATH:ko00960]
02052 Other ion-coupled transporters [:ko]
03010 Ribosome [PATH:ko03010]
03034 Other replication recombination and repair proteins [:ko]
04012 ErbB signaling pathway [PATH:ko04012]
04070 Phosphatidylinositol signaling system [PATH:ko04070]
04120 Ubiquitin mediated proteolysis [PATH:ko04120]
04310 Wnt signaling pathway [PATH:ko04310]
04350 TGF-beta signaling pathway [PATH:ko04350]
04520 Adherens junction [PATH:ko04520]
04610 Complement and coagulation cascades [PATH:ko04610]
04620 Toll-like receptor signaling pathway [PATH:ko04620]
04630 Jak-STAT signaling pathway [PATH:ko04630]
04660 T cell receptor signaling pathway [PATH:ko04660]
04910 Insulin signaling pathway [PATH:ko04910]
04912 GnRH signaling pathway [PATH:ko04912]
04914 Progesterone-mediated oocyte maturation [PATH:ko04914]
04916 Melanogenesis [PATH:ko04916]
05218 Melanoma [PATH:ko05218]
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Ongoing Work …
•Biological analysis
•Integration analysis (genotypes, mutations, expression,
interactions )
•Validation using independent data sets (TCGA: brain
cancer & ovarian cancer data)
•Combining the results from regular GWAS of cancers
Acknowledgments
•Li Ding, John Osborne, Ling Lin
(Medical Genomics Group, GSC)
•Aldi Kraja, Ingrid Boreki, Michael Province
(Division of Statistical Genomics)