Insights Into Breast Cancer Etiology: Genomic and Epigenomic Discoveries

1. Investigations into Breast Cancer Etiology: Genomic/Epigenomic Analyses, Novel Oncogenes, and Allele-specific Studies Maxwell Lee National Cancer Institute Center for Cancer Research Laboratory of Population Genetics September 29th, 2010

2. Three Parts • Genomic analysis of breast cancer and functional studies of novel oncogenes. • Deep-sequencing analysis of breast cancer transcriptome. • Large-scale analysis of allele-specific gene expression and epigenetic modifications.

3. Part 1 Our Approach to Understanding the Etiology of Breast Cancer Mits Kadota breast tumors genomics epigenomics cancer-related genes

4. Part 1 A Clinical Information of Our Primary Breast Tumors (CHTN) Numbers refer to tumor counts in each category

5. Part 1 Primary Breast Tumors: DNA Copy Number Variation 1q 161 breast tumors Affymetrix SNP5 array putative novel oncogenes 8q chromosome 161 tumors

6. Part 1 Focal Amplification of TBL1XR1 in Breast Tumors

7. Part 1 Focal Amplification Detected in Primary Breast Tumors

8. Part 1 Gene Amplification and Up-regulation at RNA and Protein Levels of TBL1XR1 in Breast Tumors focal amplification amplification or up-regulation Hypothesis: additional mechanisms for up-regulation genomic alteration RNA over-expression protein over-expression DNA RNA protein

9. Part 1 Primary Breast Tumors: Frequent Over-expression of TBL1XR1 TBL1XR1 staining increases in poorly-differentiated tumors odds ratio = 1.7N=70 negative 31% positive 69% N=84 In collaboration with Dr. Junya Fukuoka

10. Part 1 TBL1XR1-shRNA Knockdown of MCF10CA1h Cells Suppresses In Vitro Cell Migration 0 hour 24 hour Western Blot control TBL1XR1- shRNA cell migration (scratch assay) MCF10A MCF10AT MCF10CA1h HRAS MCF10CA1a In collaboration with Dr. Lalage Wakefield

11. Part 1 TBL1XR1-shRNA Knockdown Suppresses In Vivo Tumor Growth Day 39 Tumor volume (mm3) MCF10CA1h Control-shRNA TBL1XR1-shRNA implants N=10 N=10 N=14 mice N=5 N=5 N=7 Kadota et al. Cancer Research. 2009

12. Part 1 Two Complementary Approaches SNP array 10 kb resolution hundreds of tumors Next-generation sequencing single nucleotide resolution a few samples Functional studies Functional studies

13. Part 2 3 Major Goals of Deep Sequencing Analysis of Breast Cancer Transcriptome • To identify genes with differential expression between tumor and normal tissues. • To identify somatic mutations in breast tumors. • To characterize allele-specific gene expression in tumor and normal tissues.

14. Part 2 Histopathological Data of Tumors

15. Part 2 Summary of Sequence Reads and BWA Mapping hg18 reference sequence mRNA refseq EST combination of any two exons mapping pipeline splicing junction 76 base and 108 base pair-end sequences Assemble bam files 140 120 100 Million reads 80 60 40 20

16. Part 2 The Number of Genes that Showed Differential Expression between Tumor and Normal Tissues

17. Part 2 SOX10 Is Down-regulated in a Tumor chr22:36686044-36722706 normal BN1 tumor BT1 BN2 BT2 BN3 BT3 BN4 BT4

18. Part 2 MMP9 Is Up-regulated in Tumors chr20:44062819-44086029 BN1 BT1 BN2 triple negative BT2 BN3 BT3 BN4 triple negative BT4

19. Part 2 Comparison of Up-regulated Genes between Tumors 2 triple negative tumors HER positive triple negative HER positive triple negative

20. Part 2 An isoform of GNAS Is Down-regulated in Tumors mat pat bi-allelic BN1 BT1 BN2 BT2 BN3 BT3 BN4 BT4

21. Part 2 Somatic Mutation Summary tumor mutant reads > 10 normal mutant read = 0 tumor mutant fraction > 0.1 normal mutant fraction < 0.05 normal reference reads > 10 BT1 BT2 BT3 BT4

22. Part 2 Validation of Somatic Mutations in Genomic DNA P952R normal ESYT1 tumor K217Q normal RYBP tumor

23. Part 2 Summary of Validation Experiments Red highlights deleterious change by SIFT

24. Part 3 Allelic Variation in Gene Expression is Common in the Human Genome normal human fetal tissues 277 genes cDNA > 2-fold difference 326 genes Genomic imprinting 50~100 genes all or none parental origin Allelic gene expression 20%~50% genes quantitative difference sequence, cellular context, etc. Affymetrix HuSNP array Lo et al. Genome Res. 2003

25. Part 3 What Determine Allelic Variation in Gene Expression? • Epigenetic mechanism • Genetic mechanism

26. Part 3 Allele-specific ChIP-on-chip Studies in Lymphoblastoid Cell Lines from CEPH Families

27. Part 3 Allele-specific ChIP-on-chip Studies in Lymphoblastoid Cell Lines from CEPH Families LIT1, an imprinted gene A B 1347 1362 DNA or active chromatin relative allelic signal (RAS) allele A/(allele A + allele B) inactive chromatin 0 0.25 0.5 0.75 1 RAS Pat Mat

28. Part 3 Clustering of Samples Based on Family Using Allele-specific Chromatin Features RAS A /(A+B)

29. Part 3 Inheritance Analysis of Allelic Histone H3 Acetylation at the TMEM16D Locus Informative for SNP interrogated on SNP array (rs938335) L H H H RAS A/ (A + B) L: low H3Ac M: medium H3Ac H: high H3Ac M M Kadota et al. PLoS Genet. 2007

30. Part 3 A Clustering of 42 Primary Breast Tumors by the Degree of Mono-allelic Methylation in Chromosome Arms late stage early stage triple neg. late stage

31. Acknowledgments NCI/CCR Mitsutaka Kadota Howard Yang Beverly Duncan Sheryl Gere Robert Clifford Richard Finney Shuang Cai Chunhua Yan Michael Edmonson Daoud Meerzaman Ken Buetow Misako Sato Akira Ooshima Lalage Wakefield Kent Hunter NCI/DCEG Nan Hu Chaoyu Wang Hua Su Phil Taylor Alisa Goldstein NCI/DCP Barbara Dunn NCI/DCTD Jiuping Ji Japan/Toyama Univ. Shun-Ichiro Kageyama Takuya Nagata Junya Fukuoka Kazuhiro Tsukada