My PhD Thesis seminar - April 2007

2,341 views

Published on

I received a PhD in April of 2007 from the Schultz Lab at the Scripps Research Institute in La Jolla, CA. Here is a PowerPoint presentation of my primary work - a use of functional genomics tools to probe cellular disease problems, notably in cancer models.

Published in: Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
2,341
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
40
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

My PhD Thesis seminar - April 2007

  1. 1. Three Functional Genomic Approaches to Biochemical and Screen-Based Analyses of Topics in Cellular Biology Jovana J. Grbi ć Schultz Laboratory April 09, 2007
  2. 2. Talk Outline—Part I <ul><li>Genomic Profiling of Runx3 Downstream Target Genes in a Gastric Cancer Model System </li></ul><ul><li>Generation and Use of a Novel shDNA Library Targeting the Mouse Kinome in the Discovery of Osteogenesis Regulators </li></ul><ul><li>Elucidating the Biological Role of the Protein Interaction Between Bmi1 and Pontin52 </li></ul>
  3. 3. Runx3 <ul><li>Member of the highly conserved Runt domain family of transcription factors </li></ul><ul><li>Thought to be the most ancient of the three genes, both due to its length and regulation of neurogenesis of the monosynaptic reflex arc </li></ul><ul><li>128-amino acid Runt domain regulates binding of Runx proteins to a consensus DNA sequence and mediates interaction with core-binding factor- β </li></ul><ul><li>Cellular Roles: </li></ul><ul><ul><li>Development and survival of dorsal root ganglia neurons (axonal projection) </li></ul></ul><ul><ul><li>CD4 + /CD8 + T cell development </li></ul></ul><ul><ul><li>Myeloid expression/Immune regulation </li></ul></ul><ul><ul><li>Chondrocyte differentiation </li></ul></ul><ul><ul><li>Gastric epithelia differentiation and growth </li></ul></ul>
  4. 4. Runx3 Cellular Mechanism <ul><li>Part of TGF β supersignalig network--directs activation/repression of genes through DNA binding on transcriptional domain </li></ul><ul><li>Downstream signaling targets/mechanisms largely unknown </li></ul>??? ???
  5. 5. Gastric Cancer <ul><li>Most frequent gastrointestinal malignancy </li></ul><ul><li>Second most-common cause of cancer-related death in the world </li></ul><ul><li>Some gene alterations have been associated with gastric cancers (E-cadhedrin, p53, TGF β receptor) </li></ul><ul><li>Many chromosomal loci are lost in gastric cancers (including 1p , 5q, 7q, 12q, 17p, 18q) </li></ul><ul><li>Underlying mechanisms of oncogenesis and tumor progression are still very poorly understood </li></ul>
  6. 6. Causal Link to Gastric Cancer <ul><li>Runx3 loci selectively ablated in GC cell lines (FISH) </li></ul><ul><li>Hemizygous hypermethylation of CpG island </li></ul><ul><li>Runx3 expression able to reverse tumor growth in culture and in vivo </li></ul>
  7. 7. Establishing a Working Cell Line M AGS SNU-1 SNU-16 AZA TSA - - - - - + - + + + - - - + - + + + Runx3 5’-aza-2’- deoxycytidine Demethylation: MS-PCR: runx3 CpG island (~890 bp) F R WT Runx3 sequence AGS (after sodium bisulfite) SNU-1 (after sodium bisulfite) RT-PCR Runx3 1 2 3 4 M
  8. 8. Runx3 Profiling Strategy M - + + AGS WT AZA-treated Overexpression AZA treated Over- expression Vector Runx3 β -actin Generate Comprehensive Expression Profile Overlap signatures and Analyze convergent data Extract mRNAs in duplicate Hybridize Onto UA133 Affy Chip Dr. John Walker
  9. 9. Runx3 Upregulated Genes 2.02 2.00 transmembrane 4 superfamily member 1 2.51 2.30 beta tubulin, polypeptide 2.10 2.33 parvulin hPar14 2.24 2.33 neuropilin 1 2.52 2.49 tumor necrosis factor receptor superfamily, member 6 2.15 2.49 lipase protein 2.82 2.62 A kinase (PRKA) anchor protein 2 3.25 2.89 Molecule interacting with Rab13 3.54 3.32 solute carrier family 1, member 3 3.37 3.38 solute carrier family 2, member 3 4.54 4.07 hydroxyprostaglandin dehydrogenase 15-(NAD) 4.49 4.92 Sterile alpha motif domain containing 4 (SAMD4) AGS_runx3 AGS+AZA Gene ID
  10. 10. Anti-Proliferative Capacity of Upregulated Genes <ul><li>Several candidate genes display proliferative inhibition in GC cell line </li></ul><ul><li>AKAP and hP14 both shown to have cell cycle regulatory roles </li></ul><ul><li>None of the upregulated genes could inhibit cell growth beyond 30-50% </li></ul><ul><li>Possible combinatorial effect in tumor suppression </li></ul>
  11. 11. Runx3 Downregulated Genes AGS+AZA Runx3 stable • Tumorigenesis and Cancer Progression • Selectively Overexpressed in Cancer • Other Disease Regulatory Roles -2.11 -2.2 NM_001730 Kruppel-like factor 5 (intestinal) -2.23 -2.6 NM_003667 G protein-coupled receptor 49 -2.28 -2.4 NM_002909 REG1α -2.34 -2.1 NM_139273 cysteinyl-tRNA synthetase -2.37 -2.3 NM_000153 galactosylceramidase -2.64 -2.1 NM_015000 STK38L (NDR2) -2.92 -2.9 X54989 Evi-1 -3.11 -3.1 NM_001536 HRMT1L2 -3.44 -3.0 NM_005194 C/EBPβ -3.55 -3.6 NM_003617 regulator of G-protein signalling 5 -5.41 -5.3 NM_004563 phosphoenolpyruvate carboxykinase 2 AGS_runx3 AGS+AZA Accession # Gene ID
  12. 12. Genomic Analysis <ul><li>Four-gene central network: IL-6, C/EBP β , TNF, NFE2L2 </li></ul><ul><li>All involved with some aspect of cancer progression or tumor viability </li></ul><ul><li>Secondary interactions of downregulated genes: cell proliferation, tumorigenesis, apoptosis, metastasis </li></ul>
  13. 13. Conclusions <ul><li>Runx3 is a master tumor suppressor—regulates combination of genes as an extended network </li></ul><ul><li>More emphasis on downregulation of oncogenes than upregulation of other suppressors </li></ul><ul><li>Data consistent with the established strong causal link between Runx3 silencing and cancer advancement </li></ul>
  14. 14. Talk Outline—Part II <ul><li>Genomic Profiling of Runx3 Downstream Target Genes in a Gastric Cancer Model System </li></ul><ul><li>Generation and Use of a Novel shDNA Library Targeting the Mouse Kinome in the Discovery of Osteogenesis Regulators </li></ul><ul><li>Elucidating the Biological Role of the Protein Interaction Between Bmi1 and Pontin52 </li></ul>
  15. 15. RNAi: Function and Potential <ul><li>RNA shown to interfere with certain native functions of endogenous genes/biological functions </li></ul><ul><li>Can also be introduced exogenously to force gene silencing </li></ul><ul><li>Wide array of current methods for cellular siRNA delivery </li></ul><ul><li>Advent of vector-based hairpin incorporation methods hold promise for medicinal and high-throughput applications </li></ul>
  16. 16. Algorithmic Sequence Design 5 ’ - CUUACGCUGAGUACUUCGA dTdT dTdT GAAUGCGACUCAUGAAGCU -5’ AGGTGGACATAA CTTA CGCTGAGTACT TCGA TTTGTCCGTTCGG 5’ 3’ CDS 0 1 2 3 4 GC 5 0 1 2 3 4 GC 3 0 4 8 9 12 16 19 GC of the oligo AA 5 TA 4 AT 2 TT 2 NA 1 NN 0 TT 5 TA 4 AT 2 AA 2 TN 1 NN 0 F = W 5 ·F 5 + W 3 ·F 3 + W GC ·F GC + W GC5 ·F GC5 + W GC3 ·F GC3 F 5 F 3 Dr. Serge Batalov (Favorability)
  17. 17. Final Sequence Generation 5 unique sequences: Specificity, Fidelity, Ideal Parameters 1) Parameter input 2) Additional algorithm values 3) Putative sequence candidates generated 4) Smith-Waterman similarity search 5) Unique sequences vetted for shDNA cloning
  18. 18. High Throughput Library Construction Dr. Anthony Orth, Dr. Sheng Ding, Alicia Linford, Myleen Medina High-throughput mini-preps, plating into 384-well format Primer PCRs Transfection into E.Coli Ligation into pDONR vector Total library consists of 5 siDNA targets per gene, targeting approximately 500 total murine kinases (Approximately 85-90% sequence fidelity)
  19. 19. Kinases as Targets for Control of Lineage-Specific Differentiation <ul><li>Approximately 518 kinases (1.7% of human genes); mouse orthologs for 510—good model system </li></ul><ul><li>Mediate most signal transduction in cells—involved in a large number of biological processes </li></ul><ul><li>Mesenchymal stem cell differentiation: bone regeneration vs. other lineages (fat, muscle, cartilage) </li></ul>
  20. 20. Osteogenesis Screening Alkaline Phosphatase Fluorescence Assay Cbfa1 Reporter Assay 2 rounds of ALP screening and Cbfa1 confirmation: 87 primary hits validated by both methods Dr. Xu Wu
  21. 21. Hit Characterization A)
  22. 22. Conclusion <ul><li>Successful construction of a vector-encoded shDNA library targeting the murine kinome </li></ul><ul><li>Initial screening efforts have yielded several candidate kinases putatively involved in osteogenesis </li></ul><ul><li>Follow up (in progress) will include other shDNA sequences and genomic characterization of hits </li></ul>
  23. 23. Talk Outline—Part III <ul><li>Genomic Profiling of Runx3 Downstream Target Genes in a Gastric Cancer Model System </li></ul><ul><li>Generation and Use of a Novel shDNA Library Targeting the Mouse Kinome in the Discovery of Osteogenesis Regulators </li></ul><ul><li>Elucidating the Biological Role of the Protein Interaction Between Bmi1 and Pontin52 </li></ul>
  24. 24. Hematopoiesis <ul><li>HCSs give rise to the collective immune system </li></ul><ul><li>Stem cell niche provides essential signaling pathways/factors via MSCs for HCS self-renewal </li></ul><ul><li>Delicate balance between self-renewal and differentiation </li></ul>
  25. 25. Bmi1: Regulation of HSCs <ul><li>Intrinsic factors also contribute to HSC self-renewal </li></ul><ul><li>Polycomb group repressive complex 1 member Bmi1 indispensable to HSC maintenance: forced overexpression and knockout studies </li></ul><ul><li>Direct repression of p14/p16 locus </li></ul><ul><li>Putative links to Wnt, SHH pathways </li></ul><ul><li>Cooperative oncogenic capacity with c-Myc </li></ul>
  26. 26. Bmi1, Stem Cells and Cancer <ul><li>Important role for Bmi1 in self-renewal capacity of hematopoietic and leukemic stem cells </li></ul><ul><li>Prognostic ability for patient survival (prostate cancer) </li></ul><ul><li>Involved in human medulloblastomas </li></ul><ul><li>Identify regulators of BMI-1 (cDNA, siRNA screens; pull-down) </li></ul>
  27. 27. IP-MS Design and Execution FLAGActin FLAGBMI-1 WT FLAGActin FLAGBMI1 64 82 48 Anti-FLAG Ab FLAG-Actin FLAG-BMI-1 293T MALDI-TOF Hit picks, etc. *known Bmi-1 interactor † bait protein
  28. 28. Pontin52 <ul><li>Pontin52 is a AAA+type ATPase </li></ul><ul><li>Essential cofactor for oncogenic transformation by c-Myc </li></ul><ul><li>Regulates beta-catenin-mediated neoplastic transformation and T-cell factor target gene induction via effects on chromatin remodeling </li></ul><ul><li>E2F-dependent histone acetylation and recruitment of the Tip60 acetyltransferase complex to chromatin in late G1 </li></ul><ul><li>Pontin and Reptin regulate cell proliferation in early Xenopus embryos in collaboration with c-Myc and Miz-1 </li></ul><ul><li>Enzyme-dependent activation/regulation (rarity of AAA+ ATPase distribution) lends credibility to drugability/SM targeting </li></ul>Myc/Pontin52-induced Colonies in primary REFs (ablated by null mutant)
  29. 29. SymAtlas Expression Correlation BMI-1 Pontin52 c-Myc HSC Progenitors T and B Cells Almost fingerprint-like degree of expression homology, specifically along blood-related cell lineages
  30. 30. FLAG bead IP; Anti-Pontin52 Antibody Lane 1 (FLAGActin) Lane 2 (blank) Lane 3 (FLAGBMI1) 85 60 50 BMI-1 interacts with Pontin-52 under native conditions Interaction also verified with co-IP (FLAG BMI and HA Pontin) * *positive control 293T cells: B=Bmi1 A=Actin P=Pontin52 B A P B+A B+P
  31. 31. Silencing Confers Cancer Cell Death • Loss of Bmi1 established as incurring apoptosis in cancer cells •Parallel effects with Pontin52??? Knockdown Efficiency
  32. 32. Link to Bmi1 p16 Pathway? <ul><li>WI38 fibroblasts serve as ideal model for senescence (intact p16 expression) </li></ul><ul><li>Bmi1 silencing shown to inversely activate p16 levels </li></ul><ul><li>Similar effect for Pontin52 </li></ul><ul><li>No off-target effects observed </li></ul>
  33. 33. Conclusion <ul><li>Bmi1 complexes with Pontin52 under low-stringency conditions </li></ul><ul><li>Possibly linked via Myc/p16 signaling pathways </li></ul><ul><li>Future efforts towards inhibition and in vivo models of stem cell/tumor regulation </li></ul>
  34. 34. Acknowledgements <ul><li>Schultz Group (TSRI): </li></ul><ul><li>Dr. Qihong Huang </li></ul><ul><li>Dr. Sheng Ding </li></ul><ul><li>Dr. Xu Wu </li></ul><ul><li>Dr. Aaron Willingham </li></ul><ul><li>Functional Genomics Subgroup </li></ul><ul><li>Dr. Lubica Supekova </li></ul><ul><li>Cookie Santamaria, Tanya Gresham, Toni Martin, Emily Remba, Michelle Davis </li></ul>Dr. Peter G. Schultz <ul><li>GNF: </li></ul><ul><li>Dr. John Walker (Profiling) </li></ul><ul><li>Dr. Eric C. Peters (Mass Spec) </li></ul><ul><li>Dr. Markus Warmuth (and Warmuth Group) </li></ul><ul><li>Dr. Serge Batalov </li></ul><ul><li>Dr. Anthony Orth (siDNA library) </li></ul><ul><ul><li>Alicia Linford, Myleen Medina, Brendan Smith, Abel Gutierrez </li></ul></ul><ul><li>Committee: </li></ul><ul><li>Dr. Benjamin Cravatt </li></ul><ul><li>Dr. Peter Vogt </li></ul><ul><li>Dr. Floyd Romesberg </li></ul><ul><li>Graduate Office: </li></ul><ul><li>Marilyn Rinaldi, Stacy Evans, Diane Kreger </li></ul>Family and Friends

×