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My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
My PhD Thesis seminar - April 2007
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My PhD Thesis seminar - April 2007

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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 …

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.

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  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Hit Characterization A)
  • 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. 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. 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. 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. 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. 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. 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. 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. 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. Silencing Confers Cancer Cell Death • Loss of Bmi1 established as incurring apoptosis in cancer cells •Parallel effects with Pontin52??? Knockdown Efficiency
  • 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. 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. 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

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