FUNCTIONAL GENOMICS 2

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

FUNCTIONAL GENOMICS 2

Beáta ScholtzMolecular Therapies- Lecture 2

Manifestation of Novel Social Challenges of the European Unionin the Teaching Material ofMedical Biotechnology Master’s Programmesat the University of Pécs and at the University of DebrecenIdentification 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 ways1.3.2 Microarrays: functional genomics in cancer research1.3.3 Genetic Alterations and Disease1.3.4 Genomic microarrays

1.3.4.1 Array based comparative genome hybridization (aCGH)

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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5Holly Dressman, IGSP, Genomes 101 2007

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6Holly Dressman, IGSP, Genomes 101 2007

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714 cell lines

more than 50 genes

Holly Dressman, IGSP, Genomes 101 2007

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8Potti et al. Nat Med 2006

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Genomic signatures for other chemoagents - thesame rationale

Potti et al. Nat Med 2006

Gene lists forNCI-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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Correlationbetween oncogenicpathway activationand resistanceto chemo drugs:

Combination therapywith pathway inhibitors?

src: SU6656PI3K: 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 assayedspecimens that have been treated in multiple ways,including archival tissue from hospital laboratories.

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“Point”mutation – change of one or a few bases -- leads to alteredprotein 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 expressionlevel. ((oncogene) tumor suppressor)

Breaking and abnormal rejoining of DNA makes novel genes.

A Variety of Genetic Alterations Underlie DevelopmentalAbnormalities and Disease

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Mapping of genetic aberrationTÁMOP-4.1.2-08/1/A-2009-011

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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 microdeletionsand other chromosomal abnormalities that cannot bedetected by FISH. SNP arrays may offer even more resolution,and additional information (both genotype and copy number).

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Different arrays for different purposesTÁMOP-4.1.2-08/1/A-2009-011

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Array CGH

Array based comparative genome hybridization (CGH)Measures amount of DNA, not RNAComparison between two samples

‘Test’ sample‘Reference’ sample

High resolution1-3 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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Array CGH

Detecting genomic rearrangements found in cancer (tumor genome vs normal genome)

Study of genomic copy number variationSegregating variants found in the populationPathogenic variants associated with some disease

Compare ‘affected’ vs ‘control’ individualsUse of known probes linked to genetic markers allows better

understanding of disorders

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Array CGH Maps DNA Copy NumberAlterations to Positions in the Genome

position on sequence

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Array CGH Analysis of a Tumor GenomeTÁMOP-4.1.2-08/1/A-2009-011

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• Selection for alterations in gene expression that favortumor development. Selective advantage to maintain setof aberrations.

• Mechanisms of genetic instability promoting changes inthe genome. (initiating oncogenetic event in murinemodels and methotrexate resistance in MMR deficientand 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 theDNA copy number of oncogenes and TSGs.

• Monitor cancer progression and distinguish between mild andmetastatic cancerous lesions using FISH (Florescence in situhybridization) probes on regions of recurrent copy numberaberrations in several tumor types.

• It can be used to reveal more regional copy number markers thatcan be used for cancer prediction.

• Identifying and understanding the genes that are involved in cancerwill help to design therapeutic drugs that target the dysfunctiongenes and/or avoid therapies that cause tumor resistance.

Benefits of aCGH in cancer researchTÁMOP-4.1.2-08/1/A-2009-011

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Alterations in Cancer Cell Line Genome:Alignment of Chromosomal and Microarray Based CGH

Amplifications: Activated oncogenic genesDeletions: Inactivated (tumor suppressor) genes

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The power of SNP arrays: Copy number silent LOH discovery

Tan DSP et al. Laboratory Investigation 2007. 87:737

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SNP repositories

dbSNP at NCBIhttp://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 approachto identify novel therapeutic targets

Tan DSP et al. Pathobiology 2008. 75:63

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Bottom-up approachto 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 outcomech1q gain: worsech13 loss: worse

aCGH analysis of multiple myeloma: Prognostic classification

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

Combined gene expression and aCGH analysis of multiple myeloma

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aCGH analysis of squamous cell lung cancer

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

PIK3CA3q26.2-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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The PIK3/Akt/mTOR signalling pathwayTÁMOP-4.1.2-08/1/A-2009-011

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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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