integrated studies of breast, esophageal, and gastric cancers using high throughput technologies and...
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Integrated Studies Of Breast, Esophageal, And Gastric Cancers Using High Throughput Technologies And Computational Analyses
Maxwell Lee
National Cancer InstituteCenter for Cancer Research
High-dimension Data Analysis Group
March 19, 2014
Collaborators
CCR Howard Yang Huaitian Liu Mitsutaka Kadota
Lalage Wakefield Kent Hunter Beverly Mock Dinah Singer Kevin Gardner Jing Huang Xin Wang Li YangThomas Ried Stephen Hewitt Paul Meltzer Sean Davis
DCEG Phil Taylor Nan Hu Alisa Goldstein Christian AbnetNeal Freedman Sandy Dawsey Gretchen GierachNeil Caporaso Jonine Figueroa
CBIIT Daoud MeerzamanDCP Mark Sherman Barbara Dunn Ronald Lubet Asad UmarDCTD Jay Ji Jason Lih
UMASS Kathleen ArcaroUNC Melissa TroesterPurdue University Sulma MohammedWindber Research Institute Hai HuToyama University Junya Fukuoka
• Breast cancer1. Delineating genetic alterations for tumor progression in the
MCF10A series of cell lines.2. Identifying novel oncogenes and functional studies3. Predicting clinical outcome using DNA methylation and gene
expression signatures
• Esophageal and gastric cancers1. Microarray data analyses2. Whole genome sequencing data analyses
Outline Of The Talk
1. Delineating genetic alterations for tumor progression in the MCF10A series of cell lines.
2. Identifying novel oncogenes and functional studies3. Predicting clinical outcome using DNA methylation and gene
expression signatures
Part 1 Breast Cancer
Modified Wellings-Jensen Model of Breast Cancer Evolution
Lee el al. Breast Cancer Res. 2006;8(1):R6. Wellings et al. J Natl Cancer Inst. 1975 Aug;55(2):231-73.
Breast Cancer Progression Models Of The MCF10A Series Of Cell Lines
Normal Premalignant Low grade Metastatic carcinoma carcinoma
MCF10AM1
MCF10CA1aM4
HRAS G12V
MCF10CA1hM3
MCF10ATM2
Santner SJ, ..., Miller FR. Breast Cancer Res Treat. 2001 Jan;65(2):101-10.
Role of TGF-b
TumorSuppressor
MetastasisPromoter
Tang B, ..., Wakefield LM. J Clin Invest. 2003 Oct;112(7):1116-24.
DNA Copy Number Alterations In MCF10A Series Of Cells Detected Using The Affymetrix 500K SNP Arrays
Kadota et al PLoS One. 2010 Feb 15;5(2):e9201.
chro
mos
ome
MYC Amplification In MCF10A Series Of Cells Detected By DNA Copy Number Analysis Using SNP Arrays
Kadota et al PLoS One. 2010 Feb 15;5(2):e9201.
MYC
CDKN2A/CDKN2B Deletions In MCF10A Series Of Cells Detected By DNA Copy Number Analysis Using SNP Arrays
CDKN2A/B
PIK3CA Mutation In MCF10CA1h And MCF10CA1a Cells
M1 M2 M3 M4
Chr 3
AG
AG G
G:A = 2:1
DNA Copy Number Alterations In Primary Breast Tumors Detected With SNP Arrays
161 tumors
chro
mos
ome
161 breast tumors
putative novel oncogenes
Affymetrix SNP5 array
1q
8q
traditional approach
my approach
size of focal amplification
multiple genes
1 gene
frequency of tumors with
amplificationcommon
high frequency not required but must occur in ≥
1 tumor
Kadota et al Cancer Res. 2009 Sep 15;69(18):7357-65.
Focal Amplification Detected in Primary Breast Tumors
Focal Amplification Of TBL1XR1 In Breast Tumors
Tumor 1
Tumor 2
Frequent Over-expression Of TBL1XR1 In Primary Breast Tumors Using Tissue Microarray (TMA)
Well-diff poorly-diff
negative 16 4
positive 35 15
negative31%
positive69%
N=84
TBL1XR1 expression associates with poorly differentiated tumors withodds ratio = 1.7
In collaboration with Junya Fukuoka at Toyama University
TBL1XR1-shRNA Knockdown in MCF10CA1h (M3) Suppresses In Vivo Tumor Growth
tum
or v
olum
e (m
m3 )
N=10 N=10 N=14implants
Western Blot
In collaboration with Lalage Wakefield
9 of 10 7 of 10 1 of 14tumor incidence
Day 39
p-value = 0.013
The Polish Breast Cancer Study (PBCS)
• The PBCS included 2386 cases and 2502 controls • They resided in Warsaw, Poland from 2000-2003• Median follow-up: 8 years
• 208 PBCS tumors with Illumina HumanRef-8 v2 Expression data• 226 PBCS tumors with Illumina Human Methylation27 data
In collaboration with Mark Sherman, Jonine Figueroa, Paul Meltzer, Sean Davis, and Melissa Troester
An Algorithm For Methylation And Expression Index (MEI)
Illumina Infinium HumanMethylation27 BeadChip
Illumina HumanRef-8 v2 Expression BeadChip
Differential methylation based on IHC (positive vs. negative for ER, PR, Her2, EGFR, or CK5)
2227 methylation markers in 1162 genes
Top 3% most variable gene expression
541 genes
128 methylation markers in 65 genes
MEI: the weighted sum of the gene expression where the weights are the negative numbers of the Spearman correlations.
Polish dataset: K-M survival based on MEI
p = 0.002
Sur
viva
l Pro
babi
lity
Year
Polish dataset: K-M survival using MEI for ER+ and ER- samples
Sur
viva
l Pro
babi
lity
p = 0.009 p = 0.360
Sur
viva
l Pro
babi
lity
ER+ cases ER- cases
Year Year
Validation: K-M survival using MEI for ER+ samples
TCGA ER+ GSE6532 ER+
NKI ER+ METABRIC ER+
Year Year
Year Year
Sur
viva
l Pro
bab
ility
OS
OS
DM
FS
p = 0.004
p = 0.001 p = 0.001
p = 0.00002
1. Microarray data analyses2. Whole genome sequencing data analyses
Part 2 Esophageal And Gastric Cancers
In collaboration with Phil Taylor, Nan Hu, Alisa Goldstein
Clustering Of ESCC And Gastric Cancers Using The Affymetrix U133 Gene Expression Data
Wang et al. PLoS One. 2013 May 22;8(5):e63826.
54 pairs of ESCC62 pairs of cardia cancer72 pairs of noncardia cancer
t: tumorn: normal
Anatomy Of Esophageal Cancer And Gastric Cancer
cardia
non-cardia
1,898 ESCC cases 2,100 common control
Illumina 660W Quad chip
P-value derived from logistic regressionmodels adjusted for age and sex
esophageal squamous cell carcinoma (ESCC)
Abnet C, ..., Taylor P. Nat Genet 2010;42:764-767
1,625 gastric cancer1,110 gastric cardia cancer515 gastri non-cardia cancer2,100 common control
Analyses of Whole Genome Sequencing (WGS) Data Generated By The Complete Genomics Inc.
• 4 pairs of ESCC and blood • 4 pairs of gastric non-cardia cancer and blood • 7 pairs of gastric cardia cancer and blood
Circos Plot Of WGS data from A Gastric Cardia Cancer: Somatic SVs, CNAs, And SNVs
Somatic Structural Variations (SVs) In ESCC And Gastric Cancer
MACROD2 Exon 6 Was Frequently Deleted in Gastric Cancer
O-acetyl-ADP-ribose deacetylase MACROD2 isoform 1
Mutation Substitution Patterns
Mutation Substitution Patterns
Collaborators
CCR Howard Yang Huaitian Liu Mitsutaka Kadota
Lalage Wakefield Kent Hunter Beverly Mock Dinah Singer Kevin Gardner Jing Huang Xin Wang Li YangThomas Ried Stephen Hewitt Paul Meltzer Sean Davis
DCEG Phil Taylor Nan Hu Alisa Goldstein Christian AbnetNeal Freedman Sandy Dawsey Gretchen GierachNeil Caporaso Jonine Figueroa
CBIIT Daoud MeerzamanDCP Mark Sherman Barbara Dunn Ronald Lubet Asad UmarDCTD Jay Ji Jason Lih
UMASS Kathleen ArcaroUNC Melissa TroesterPurdue University Sulma MohammedWindber Research Institute Hai HuToyama University Junya Fukuoka
Dr. Robert Wiltrout
Dr. Glenn Merlino