Exploring the role of DNA Methylation in the development of drug resistance in ovarian cancer cells

1. Exploring the role of DNA Methylation in the development of drug resistance in ovarian cancer cells Meng Li School of Informatics Interdisciplinary Program of Biochemistry Indiana University Advisors: Dr. Sun Kim, Dr. Kenneth Nephew 4/25/2008

2. Overview • Biology background and experimental model • Objective • High-throughput data and data analysis • Combinatorial study and data mining • Conclusions

3. Objective Data Results Conclusion Background Experimental Model Ovarian cancer and drug resistance • Ovarian cancer • Most deadly gynecological malignancy • Cisplatin • Widely used chemotherapeutic drug • DNA intercalating agent • Cisplatin resistance • 70% to 80% of patients develop resistance after 2-year treatment

4. Objective Data Results Conclusion Background Experimental Model DNA methylation CpGdinucleotides: 5’- AATACGCCACGA

5. Objective Data Results Conclusion Background Experimental Model DNA methylation CpG island MCG CG CG MCG CG CG CG CG CG CG Normal Cancer 1 1 2 2 3 3 4 4 MCG MCG MCG MCG X C: cytosine mC: methylcytosine De novomethylation: acquired methylation

6. Objective Experimental Model Data Results Conclusion Background Objective • Does de novo DNA methylation plays a role in the development of chemotherapeutic drug resistance in ovarian cancer cells? • How does de novo DNA methylation affect drug resistance development?

7. Objective Experimental Model Data Results Conclusion Background IC50 (uM) Rounds of Cisplatin treatment In vitro drug resistance system Cisplatin Cisplatin Drug-sensitive parental cellsA2780 R- Drug-resistant CellsA2780 R+ Development of drug resistance

8. Objective Data Results Conclusion Background Experimental Model High-throughput data and data analysis • Global promoter methylation data • Global gene expression data Louis Staudt, The nation’s investment in cancer research (NCI)

9. Objective Data Results Conclusion Background Experimental Model Global promoter methylation profiling A2780 R- A2780 R+ • Differential Methylation Hybridization (DMH) • 44,000 probes representing 10,000 genes • Two-color microarray analysis • Data processing • Estimate methylation level CpG Island Microarray (44K)

10. Objective Data Results Conclusion Background Experimental Model Raw Data Normalized Data M = Global promoter methylation profiling • Loess normalization: correcting technical bias • Fold-change analysis: extracting gene methylation level

11. Objective Data Results Conclusion Background Experimental Model Global gene expression profiling • Affymetrix U133 plus 2.0 microarray • 54,675 probes representing 20,606 genes • Single-color microarray analysis • Data processing • Estimate gene expression levels mRNA cRNA U133 plus 2.0 array

12. Objective Data Results Conclusion Background Experimental Model Global gene expression profiling • Clustering • Fold change • A2780R+ expression • A2780R- expression • Welch’s t-test p-values A2780 R+ A2780 R- • Cutoffs: • p-value < 0.01 • fold change >= 1.5

13. Objective Experimental Model Data Results Conclusion Background Combinatorial study and data mining • Does de novo DNA methylation plays a role in the development of chemotherapeutic drug resistance in ovarian cancer cells? • How does de novo DNA methylation affect drug resistance development?

14. Objective Experimental Model Data Results Conclusion Background The number of hypermethylated genes positively correlated with the increase of IC50

15. Objective Experimental Model Data Results Conclusion Background DNA methyl-transferases (DNMT) are up_regulated in resistant cells DNMT1: maintain genomic DNA methylation DNMT3B: de novo methylation

16. Objective Experimental Model Data Results Conclusion Background Resistant cells re-establish cisplatin sensitivity after methylation inhibitor treatment

17. Objective Experimental Model Data Results Conclusion Background Key questions • Does de novo DNA methylation plays a role in the development of chemotherapeutic drug resistance? Yes • How does de novo DNA methylation affect drug resistance development? • Does de novo methylation selectively blocking transcription factor binding? x

18. Objective Experimental Model Data Results Conclusion Background Surveying Transcription Factor Binding Sites (TFBS) on differentially methylated regions • Scan TFBS on hypermethylation (S+), hypomethylation (S-), or hypermethylated CGI (SCpG) regions with match program against TRANSFAC database * * * * . . . . . . . . . . . . . . . * * S+ S- SCpG

19. Objective Experimental Model Data Results Conclusion Background Methylation selectively occurs at certain TFBS

20. Objective Experimental Model Data Results Conclusion Background Statistical scoring • Fisher exact test • Multiple test correction – False discovery rate (FDR)

21. Objective Experimental Model Data Results Conclusion Background Key questions • Does de novo DNA methylation plays a role in the development of chemotherapeutic drug resistance? Yes • How does de novo DNA methylation affect drug resistance development? • Does de novo methylation selectively blocking transcription factor binding? Yes • Does de novo methylation selectively regulates certain pathways?

22. Objective Experimental Model Data Results Conclusion Background Methylation regulated pathways • Hypomethylation up-regulated pathways • All are human cancer related pathways

23. Objective Experimental Model Data Results Conclusion Background Hypomethylated and up-regulated pathways • Genes involved for each pathway: PIK3R3, PDGFRA, E2F1, TGFBR2 E2F Smad2/3 Smad4

24. Objective Experimental Model Data Results Conclusion Background Methylation regulated pathways • Hypermethylation down-regulated pathways • Cell adhesion molecules (CAMs): Environmental information processing • Tight junction: Experimental processes -> Cell communication • PPAR signaling pathway: Experimental processes -> Endocrine system

25. Objective Experimental Model Data Results Conclusion Background Hypermethylated and down-regulated pathways • Genes involved for each pathway: CAMs (ITGAV, CLDN11, NEO1, CDH2) Tight junction (CLDN11, PPP2R4, INADL) PPAR signaling (CPT1A, SLC27A6)

26. Objective Experimental Model Data Results Conclusion Background Key questions • Does de novo DNA methylation plays a role in the development of chemotherapeutic drug resistance? Yes • How does de novo DNA methylation affect drug resistance development? • Does de novo methylation selectively blocking transcription factor binding? Yes • Does de novo methylation selectively regulates certain pathways? Yes

27. Objective Experimental Model Data Results Conclusion Background Conclusion • Promoter CpG island methylation • Participates in the development of drug resistance of ovarian cancer cells • Regulates gene expression alteration through drug resistance development by selectively occurring at certain TFBS • Regulates cellular functions by methylating key players in certain pathways

28. Acknowledgements • Colleagues • Fang Fang • Shu Zhang • Henry Paik • John Montgomery • Mikyoung Jeong • Fuxiao Xin • Nicolas Berry • Xinghua Long • Nicole Nickerson • Xi Rao • Cori Hartiman-Frey • Funding Agencies • NCI U54 CA11300 • NCI R01 CA85289 • Advisors Sun Kim Kenneth Nephew • Committee Curt Balch Haixu Tang • OSU ICBP center Dustin Potter Pearlly Yan Tim H-M. Huang • IUPUI Lang Li Jeanette McClintick

29. F. Coste, J. M. Malinge, L. Serre, W. Shepard, M. Roth, M. Leng and C. Zelwer, "Crystal structure of a double-stranded DNA containing a cisplatin interstrand cross-link at 1.63 A resolution: hydration at the platinated site", Nucleic Acids Res, 1999, 27, 1837.