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FUNCTIONAL GENOMICS 2

Manifestation of Novel Social Challenges of the European Union in the Teaching Material of Medical Biotechnology Master’s P rogrammes at the University of Pécs and at the University of Debrecen Identification number : TÁMOP-4.1.2-08/1/A-2009-0011.

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FUNCTIONAL GENOMICS 2

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  1. Manifestation of Novel Social Challenges of the European Unionin the Teaching Material ofMedical Biotechnology Master’s Programmesat theUniversity of Pécs and at the University of Debrecen Identification number: TÁMOP-4.1.2-08/1/A-2009-0011

  2. Manifestation of Novel Social Challenges of the European Unionin the Teaching Material ofMedical Biotechnology Master’s Programmesat theUniversity of Pécs and at the University of Debrecen Identification number: TÁMOP-4.1.2-08/1/A-2009-0011 Beáta Scholtz Molecular Therapies- Lecture 2 FUNCTIONAL GENOMICS 2

  3. FUNCTIONAL GENOMICS 1 The aim of this chapter is to describe the main goals, tools and techniques of functional genomics. We will discuss its contribution to the advancement of modern medicine through specific examples. 1.1DEFINITIONS 1.2 ABOUT DISEASES 1.3 APPROACHES TO UNDERSTANDING DISEASE MECHANISMS 1.3.1 Gene expression is regulated in several basic ways 1.3.2 Microarrays: functional genomics in cancer research 1.3.3 Genetic Alterations and Disease 1.3.4 Genomic microarrays 1.3.4.1 Array based comparative genome hybridization (aCGH)

  4. TÁMOP-4.1.2-08/1/A-2009-011 Microarrays: Functional genomics to improve cancer therapy • Identify who is at risk (Prognosis) • Identify who will and won’t respond to each agent • Identify alternatives for patients with • chemo-resistant disease • Better utilization of existing and new drugs • Strategies for unique combinations of drugs

  5. TÁMOP-4.1.2-08/1/A-2009-011 Holly Dressman, IGSP, Genomes 101 2007

  6. TÁMOP-4.1.2-08/1/A-2009-011 Holly Dressman, IGSP, Genomes 101 2007

  7. TÁMOP-4.1.2-08/1/A-2009-011 more than 50 genes Holly Dressman, IGSP, Genomes 101 2007 14 cell lines

  8. TÁMOP-4.1.2-08/1/A-2009-011 Potti et al. Nat Med 2006

  9. TÁMOP-4.1.2-08/1/A-2009-011 Genomic signatures for other chemo agents - the same rationale Gene lists for NCI-60 cell lines Potti et al. Nat Med 2006

  10. TÁMOP-4.1.2-08/1/A-2009-011 Data for real patients (ovarian cancer) Pre-existing gene expression data from GEO database Probability score assigned by Potti et al. Sensitivity data from the same study Potti et al. Nat Med 2006

  11. TÁMOP-4.1.2-08/1/A-2009-011 Correlation between oncogenic pathway activation and resistance to chemo drugs: Combination therapy with pathway inhibitors? src: SU6656 PI3K: LY-294002 Potti et al. Nat Med 2006

  12. TÁMOP-4.1.2-08/1/A-2009-011 Why study DNA in tumors? • It is the fundamental repository of information. • If the same DNA aberration occurs repeatedly in • tumors, how can one ignore it? • There are powerful, general methods of assessing certain types of aberrations. • DNA is relatively robust and can be assayed • specimens that have been treated in multiple ways, • including archival tissue from hospital laboratories.

  13. TÁMOP-4.1.2-08/1/A-2009-011 A Variety of Genetic Alterations Underlie Developmental Abnormalities and Disease “Point”mutation – change of one or a few bases -- leads to altered protein or change in expression level. Loss of gene copy reduces expression level. (tumor suppressor loss) Gain of gene copies increases expression level. (oncogene activation) (De)Methylation of gene promoters (increase)decrease expression level. ((oncogene) tumor suppressor) Breaking and abnormal rejoining of DNA makes novel genes.

  14. TÁMOP-4.1.2-08/1/A-2009-011 Mapping of genetic aberration

  15. TÁMOP-4.1.2-08/1/A-2009-011 Genomic microarrays Description: A microarray technology that detects chromosomal abnormalities Uses: Clinical lab: complementary to fluorescence in situ hybridization (FISH) Research lab: discover genetic basis of diseases Significance: Many disorders are likely to be caused by microdeletions and other chromosomal abnormalities that cannot be detected by FISH. SNP arrays may offer even more resolution, and additional information (both genotype and copy number).

  16. TÁMOP-4.1.2-08/1/A-2009-011 Different arrays for different purposes

  17. TÁMOP-4.1.2-08/1/A-2009-011 Array CGH • Array based comparative genome hybridization (CGH) • Measures amount of DNA, not RNA • Comparison between two samples • ‘Test’ sample • ‘Reference’ sample • High resolution • 1-3 Mb (whole genome array CGH), or 10-25 kb (oligo aCGH) vs 5-10 Mb (karyotyping) • Speed : 3-4 days (array CGH) vs 2-4 weeks (karyotyping) • Simple DNA prep for array CGH instead of metaphase synchronization

  18. TÁMOP-4.1.2-08/1/A-2009-011 Array CGH • Detecting genomic rearrangements found in cancer (tumor genome vs normal genome) • Study of genomic copy number variation • Segregating variants found in the population • Pathogenic variants associated with some disease • Compare ‘affected’ vs ‘control’ individuals • Use of known probes linked to genetic markers allows better understanding of disorders

  19. TÁMOP-4.1.2-08/1/A-2009-011 Array CGH Maps DNA Copy Number Alterations to Positions in the Genome position on sequence

  20. TÁMOP-4.1.2-08/1/A-2009-011 Array CGH Analysis of a Tumor Genome

  21. TÁMOP-4.1.2-08/1/A-2009-011 Tumor copy number profiles are a reflection of two processes • Selection for alterations in gene expression that favor • tumor development. Selective advantage to maintain set • of aberrations. • Mechanisms of genetic instability promoting changes in • the genome. (initiating oncogenetic event in murine • models and methotrexate resistance in MMR deficient • and proficient cell lines)

  22. TÁMOP-4.1.2-08/1/A-2009-011 Benefits of aCGH in cancer research • Based on the results better tests can be performed that measure the • DNA copy number of oncogenes and TSGs. • Monitor cancer progression and distinguish between mild and • metastatic cancerous lesions using FISH (Florescence in situ • hybridization) probes on regions of recurrent copy number • aberrations in several tumor types. • It can be used to reveal more regional copy number markers that • can be used for cancer prediction. • Identifying and understanding the genes that are involved in cancer • will help to design therapeutic drugs that target the dysfunction • genes and/or avoid therapies that cause tumor resistance.

  23. Alterations in Cancer Cell Line Genome: Alignment of Chromosomal and Microarray Based CGH TÁMOP-4.1.2-08/1/A-2009-011 Amplifications: Activated oncogenic genes Deletions: Inactivated (tumor suppressor) genes

  24. TÁMOP-4.1.2-08/1/A-2009-011 The power of SNP arrays: Copy number silent LOH discovery Tan DSP et al. Laboratory Investigation 2007. 87:737

  25. TÁMOP-4.1.2-08/1/A-2009-011 SNP repositories dbSNP at NCBI http://www.ncbi.nlm.nih.gov/SNP Human SNP database (Whitehead Institute) http://www.broad.mit.edu/tools/data/genvar.html The SNP Consortium (TSC) http://snp.cshl.org J Pevsner: Bioinformatics and functional genomics

  26. TÁMOP-4.1.2-08/1/A-2009-011

  27. TÁMOP-4.1.2-08/1/A-2009-011 Top-bottom approach to identify novel therapeutic targets Tan DSP et al. Pathobiology 2008. 75:63

  28. TÁMOP-4.1.2-08/1/A-2009-011 Bottom-up approach to identify novel therapeutic targets Tan DSP et al. Pathobiology 2008. 75:63

  29. TÁMOP-4.1.2-08/1/A-2009-011 aCGH analysis of multiple myeloma 55 MM cell lines, 73 patient samples Carrasco DR et al. Cancer Cell 2006. 9:313

  30. TÁMOP-4.1.2-08/1/A-2009-011 aCGH analysis of multiple myeloma: Prognostic classification Carrasco DR et al. Cancer Cell 2006. 9:313 hyperdiploid: k1, k2 nonhyperdiploid: k3,k4 Conclusion: ch11 gain : better outcome ch1q gain: worse ch13 loss: worse

  31. TÁMOP-4.1.2-08/1/A-2009-011 Combined gene expression and aCGH analysis of multiple myeloma Carrasco DR et al. Cancer Cell 2006. 9:313

  32. aCGH analysis of squamous cell lung cancer TÁMOP-4.1.2-08/1/A-2009-011 A: All samples B: High CNAs PIK3CA 3q26.2-q27.3 Boelens MC et al. Lung Cancer 2009. 66:372

  33. TÁMOP-4.1.2-08/1/A-2009-011 aCGH analysis of squamous cell lung cancer: Correlation of PIK3CA expression levels and gene amplification Novel therapeutic target? Boelens MC et al. Lung Cancer 2009. 66:372

  34. TÁMOP-4.1.2-08/1/A-2009-011 The PIK3/Akt/mTOR signalling pathway

  35. TÁMOP-4.1.2-08/1/A-2009-011 Profiles of PI3K inhibitors in clinical trial Ihle N T , Powis G Mol Cancer Ther 2009;8:1-9

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