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Medical Biotechnology Master’s Programmes

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

Beáta Scholtz

Molecular Therapies- Lecture 2

Medical Biotechnology Master’s Programmes

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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1.1 DEFINITIONS

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

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.

FUNCTIONAL GENOMICS 1

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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

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Holly Dressman, IGSP, Genomes 101 2007

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more than 50 genes

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8 Potti et al. Nat Med 2006

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Genomic

signatures for other chemo agents - the same rationale

Potti et al. Nat Med 2006

Gene lists for NCI-60 cell lines

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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

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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

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•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.

Why study DNA in tumors?

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“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.

A Variety of Genetic Alterations Underlie Developmental

Abnormalities and Disease

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Mapping of genetic aberration

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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).

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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

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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

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Alterations to Positions in the Genome

position on sequence

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• 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)

Tumor copy number profiles are a reflection of two processes

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• 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.

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Alignment of Chromosomal and Microarray Based CGH

Amplifications: Activated oncogenic genes

Deletions: Inactivated (tumor suppressor) genes

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Tan DSP et al. Laboratory Investigation 2007.

87:737

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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

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Top-bottom approach to identify novel

therapeutic targets

Tan DSP et al. Pathobiology 2008. 75:63

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Bottom-up approach to identify novel therapeutic targets

Tan DSP et al. Pathobiology 2008. 75:63

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aCGH analysis of multiple myeloma

Carrasco DR et al. Cancer Cell 2006. 9:313

55 MM cell lines, 73 patient samples

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nonhyperdiploid: k3,k4 hyperdiploid: k1, k2

Carrasco DR et al. Cancer Cell 2006. 9:313

Conclusion:

ch11 gain : better outcome ch1q gain: worse

ch13 loss: worse

Prognostic classification

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Carrasco DR et al. Cancer Cell 2006. 9:313

of multiple myeloma

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Boelens MC et al. Lung Cancer 2009. 66:372

PIK3CA

3q26.2-q27.3

A: All samples

B: High CNAs

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aCGH analysis of squamous cell lung cancer:

Correlation of PIK3CA expression levels and gene amplification

Boelens MC et al. Lung Cancer 2009. 66:372

Novel therapeutic target?

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Profiles of PI3K inhibitors in clinical trial

Ihle N T , Powis G Mol Cancer Ther 2009;8:1-9

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