pharmacogenomics – personalized medicine

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PharmacoGenomics personalized medicine. Alina Starovolsky DNA chip Usage DNA chip Usage : :

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DNA chip Usage:. PharmacoGenomics – personalized medicine. Alina Starovolsky. SNP: “ snip ” Single Nucleotide Polymorphisms. One-letter variations in the DNA sequence. SNPs contribute to differences among individuals. - PowerPoint PPT Presentation

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Page 1: PharmacoGenomics  – personalized medicine

PharmacoGenomics – personalized medicine.

Alina Starovolsky

DNA chip UsageDNA chip Usage::

Page 2: PharmacoGenomics  – personalized medicine

SNP: “snip”SNP: “snip”Single Nucleotide PolymorphismsSingle Nucleotide Polymorphisms

One-letter variations in the DNA sequence.SNPs contribute to differences among individuals.The majority have no effect, others cause subtle differences in countless characteristics, including risk for certain diseases.

Page 3: PharmacoGenomics  – personalized medicine

Human genome diversityHuman genome diversity

• 28% of the human genome are coding genes. (all the rest is “junk DNA”).

• 1.4% are the exons.• 30,000 genes.• 40% of then have alterative splicing and

thus there are more genes.

Page 4: PharmacoGenomics  – personalized medicine

• A multi-country effort (Japan, the United Kingdom, Canada, China, Nigeria, and the United States) to identify and catalog genetic similarities and differences in human beings.

• Analyzing DNA from populations with

African, Asian, and European ancestry. Together, these DNA samples should enable HapMap researchers to identify most of the common haplotypes that exist in populations worldwide

Page 5: PharmacoGenomics  – personalized medicine

Polymorphism vs. Polymorphism vs. mutationmutation

• Polymorphism is defined as a variation in more than 1% of the population.

• Mutations Rare differences which occur in less than 1% of the population (usually much less than 1%).

• Typically, mutations have been discovered in coding sequences of genes causing rare inherited diseases.

• In Barley (שעורה): 1 out of 131 nucleotides is different between individuals (was calculated on 75 different genes).

• In 4 types of chickens in comparison to their ancestor it was found that every 200 nucleotides there is an SNP.

Page 6: PharmacoGenomics  – personalized medicine

Polymorphism in humansPolymorphism in humans

• Two random humans are expected to differ at approximately 1 in 1000 nucleotide pairs, whereas two random chimpanzees differ at 1 in 500 nucleotide pairs.

• This is interpreted to mean that the human species is relatively young, perhaps too young to evolve subspecies.

• However, with a geonome of approximate 3 billion nucleotides, on average two humans differ at approximately 3 million nucleotides.

• Most of these SNPs are neutral, but some are functional and influence the phenotypic differences between humans. It is estimated that about 10 million SNPs exist in human populations.

• Amino acid-altering non-synonymous coding-region SNPs would be rare and harder to be found because of expected selection against them in human evolution.

Page 7: PharmacoGenomics  – personalized medicine

PharmacogenomicsPharmacogenomics “Medicine tailored to the individual”“Medicine tailored to the individual”

•The Study of how genetic differences influence variability in patients’ responses to drugs.

•Personalized drugs.

Page 8: PharmacoGenomics  – personalized medicine

• Genetic polymorphisms in drug-metabolizing enzymes, transporters, receptors, and other drug targets have been linked to inter-individual differences in the efficacy and toxicity of many medications.

• Pharmacogenomic studies explain the inherited nature of these differences in drug disposition and effects.

SNPs roolSNPs rool

Page 9: PharmacoGenomics  – personalized medicine

The DNA ChipThe DNA Chip::

Page 10: PharmacoGenomics  – personalized medicine

SNP GenotypingSNP Genotyping

• Using DNA chips, it is possible to measure many thousands of SNPs simultaneously in a small sample from a patient.

• Can compare “genotypes” for SNP markers linked to virtually any trait.

Page 11: PharmacoGenomics  – personalized medicine

Examples traits – complex Examples traits – complex and non complex diseases.and non complex diseases.

• There are a number of classic “genetic diseases” caused by mutations of a single gene.

• There are also many diseases that are the result

of the interactions of many genes:– Athsma, heart disease, cancer.

• Each of these genes may be considered to be a risk factor for the disease.

• Groups of SNP markers may be associated with a disease without determining mechanism.

• Pharmacogenomics – personalized drugs.

Page 12: PharmacoGenomics  – personalized medicine

Soon it will be able to profile variations between individuals’ DNA to predict responses to a particular medicine.

It will provide information on the likelihood of efficacy and safety of a drug for an individual patient

It Will change the practice and economics of medicine (Faster clinical trials. Less drug side effects.)

The FutureThe Future

Page 13: PharmacoGenomics  – personalized medicine

The ‘roots’ of The ‘roots’ of pharmacogeneticspharmacogenetics

Clinical observations of inherited differences in drug effects first documented in the 1950s.

e.g. In African American population it was found that in response to the anti-malarial drug primaquine, they developed hemolyitic anemia due to polymorphic alleles of Glucose-6-phosphate dehydrogenase.

D-glucose 6-phosphate + NADP+ = D-glucono-1,5-lactone 6-phosphate + NADPH (energy).

Without enough normal G6PD to help red blood cells get rid of harmful oxidative substances, they can be damaged or destroyed, leading to a condition known as hemolytic anemia.

Page 14: PharmacoGenomics  – personalized medicine

The molecular genetic basis for the inherited traits began to be revealed in the late 1980s, with the initial cloning and characterization of a polymorphic human gene encoding the drug-metabolizing enzyme debrisoquin hydroxylase (CYP2D6).

Cytochrome P450Cytochrome P450

• Homozygousity for alleles of the Cytochrome P450 gene CYP2D6 (in ~10% of the Caucasian population) lead to dangerous vacular hypotension when receiving the hypertension drug debrisoquine.

Page 15: PharmacoGenomics  – personalized medicine
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Page 18: PharmacoGenomics  – personalized medicine

About schizophreniaAbout schizophrenia• Does not mean split personality!• Afflicts approximately 1% of the world’s

population.• US spends 40 billion $ per year. M=F for rate, onset: male(15-25), female(25-

35).• 10% of the people with the disorder commit

suicide.• Wide spectrum of illness Characterized by

two categories of symptoms: - positive symptoms - negative symptoms

Page 19: PharmacoGenomics  – personalized medicine

Negative symptoms:Negative symptoms:

Flattened emotional response.

Lack of initiative and persistence.

Anhedonia (inability to experience pleasure).

Social withdrawal.

Positive symptoms:Positive symptoms:(more responsive to drug treatment)

Thought disorders. Delusions. Hallucinations. disorganized

speech. (e.g. frequent incoherence)

grossly disorganized or catatonic behavior.

Page 20: PharmacoGenomics  – personalized medicine

What causes schizophreniaWhat causes schizophrenia??

The Genetic Risk – known to “run in the family”

Each of the genetically

identical girls was to become

schizophrenic before the age of

28…

Page 21: PharmacoGenomics  – personalized medicine

What causes schizophreniaWhat causes schizophrenia??

Viral infection in the 2nd trimester of pregnancy

Brain abnormality (enlarged lateral ventricles, low metabolic rate of the prefrontal cortex, abnormal cell arrange in the hippocampus). Usually correlated to negative symptoms

Social influence – highest in poor socioeconomic groups, stressful live events.

Page 22: PharmacoGenomics  – personalized medicine

The Gray matter is the cortex of the brain which contains nerve cells body.

What causes What causes schizophreniaschizophrenia??

parietal lobe logic

hearing

Page 23: PharmacoGenomics  – personalized medicine

What causes schizophreniaWhat causes schizophrenia??

Biochemistry - “dopamine hypothesis” - dopamine levels increase in the brain. (Dopamine is a neurotransmitter that transports signals between nerve endings in the brain).

(antipsychotic drugs = dopamine antagonists, L-dopa, cocaine, amphetamine) – only effective only for the positive symptoms.

Page 24: PharmacoGenomics  – personalized medicine

Dopamine D2 receptor

•Found on chromosome 11q22-23

•Binding site of many psychoactive drugs

Chlorpromazine

Page 25: PharmacoGenomics  – personalized medicine

ANTIPSYCHOTIC DRUGS

TYPICAL ATYPICAL

D2 Receptor Other dopamine receptors and 5HT2 receptor

Treat mainly positive symptom

Efficacy – 60%

Treat negative symptoms too,

Efficacy – 85%(less relapses)

Page 26: PharmacoGenomics  – personalized medicine

THE PHARMACOGENOMIC THE PHARMACOGENOMIC HYPOTHESIS: DRUG EFFICACY RELEATE HYPOTHESIS: DRUG EFFICACY RELEATE

TO GENETIC REASONSTO GENETIC REASONS

Drug mechanism- identify how drug ‘works’ block dopamine receptors

Target – identify those gene products implicated in the mechanism of the drug Dopamine receptor

Candidate gene – identify the gene that have been found to be associated with the disease DRD2 receptor (dopamine

receptor D2 ).Gene variants 141 C Del/Ins, TaqI A

Page 27: PharmacoGenomics  – personalized medicine

141C Del/Ins polymorphism141C Del/Ins polymorphism

• deletion of cytosine 141 in the promoter region upstream from the transcription start site

• Associated with schizophrenia in Japanese, Swedish and Portuguese population

• In vitro – del allele is directly related to DRD2 expression• Individuals with no del allele had lower striatal density of dopamine receptor

Page 28: PharmacoGenomics  – personalized medicine

TaqI polymorphismTaqI polymorphism

• localized 9.5 kb downstream from the DRD2 gene

• restriction fragment length polymorphism creating A1 and A2 allels

• A1 allele -lower density of DRD2 in the caudate nuclei and striaum

• A2 allele - decrease in the binding potential of the D2 receptor

• Controversy about the linkage to schizophrenia

Page 29: PharmacoGenomics  – personalized medicine

Wu S,. Xing Q,. Gao R,. Li X, Gu N,. Feng Wu S,. Xing Q,. Gao R,. Li X, Gu N,. Feng G,.& He L. (2005).Response to G,.& He L. (2005).Response to chlorpromazine treatment may be chlorpromazine treatment may be associated with polymorphisms of the DRD2 associated with polymorphisms of the DRD2 gene in Chinese schizophrenic patients. gene in Chinese schizophrenic patients. Neurosci LettNeurosci Lett. . 376(1)376(1):1-4. :1-4.

Page 30: PharmacoGenomics  – personalized medicine

Purpose of the study: Purpose of the study: examine whether the DRD2 gene contribute to the therapeutic effect of chlorpromazine

in schizophrenia by investigating the potential genetic role of the 141C Ins/Del

and TaqIA polymorphism in the DRD2 gene

Patients :Patients : - Chinese population - Chinese population - mean age – 27.3- mean age – 27.3 - 2 or more characteristic symptoms- 2 or more characteristic symptoms according to the DSM –3R according to the DSM –3R (Diagnostic and Statistical manual of Mental (Diagnostic and Statistical manual of Mental Disorder ).Disorder ).

- first time to be treated with- first time to be treated with chlorpromazinechlorpromazine - 8 weeks of treatment- 8 weeks of treatmentAssessment:Assessment: clinical symptoms were evaluated clinical symptoms were evaluated by BPRS (brief psychiatric rating scale) by by BPRS (brief psychiatric rating scale) by

two psychiatrics (given no information two psychiatrics (given no information about the patient’s genotype).about the patient’s genotype).

Page 31: PharmacoGenomics  – personalized medicine

Results 1 : the frequency of Dell Results 1 : the frequency of Dell allele is higher in non responders allele is higher in non responders than in respondersthan in responders

 141C Ins/Del Genotype

frequencyIns/Ins Ins/Del Del/Del

Responders 61 53) 86.9( 6) 9.8( 2) 3.3(

Non responders 74 53) 71.6( 21) 28.4( 0)0(

P=0.01 

Page 32: PharmacoGenomics  – personalized medicine

Results 2 : no association between Results 2 : no association between A1 allele and the drug responseA1 allele and the drug response

 TaqI A Genotype

frequencyA2/A2 A1/A2 A1/A1

Responders 61 18) 29.5( 27) 44.3( 16 )26.2(

Non responders 74 22) 29.8( 32) 43.2( 20)27(.

 NO SIGNIFICANT RESULTS!

Page 33: PharmacoGenomics  – personalized medicine

conclusionconclusion::

Del allele of the 141C Ins/Del polymorphism might predict therapeutic response to chlorpromazine in schizophrenia probably due to alteration of the D2 receptor density but that the A1 allele of the TaqI A polymorphism have no such effect

Del alleleDel allelelow therapeuticlow therapeutic

response to response to chlorpromazinechlorpromazine

Higher density of the D2 receptor

Page 34: PharmacoGenomics  – personalized medicine

Other studies:Other studies:- (Suzuki A, Kondo T, Mihara K, Yasui-Furukori N, Ishida M, Furukori H, Kaneko S, Inoue Y, (Suzuki A, Kondo T, Mihara K, Yasui-Furukori N, Ishida M, Furukori H, Kaneko S, Inoue Y,

Otani K.(2001).Otani K.(2001).The -141C Ins/DelThe -141C Ins/Del polymorphism in the polymorphism in the dopamine D2 receptor gene promoter region is dopamine D2 receptor gene promoter region is associated with anxiolytic and antidepressiveassociated with anxiolytic and antidepressive effects effects during treatment with during treatment with dopamine antagonistsdopamine antagonists in in schizophrenic patientsschizophrenic patients. . PharmacogeneticsPharmacogenetics. 11(6):545-50). 11(6):545-50)

- Arranz, M.J., Li, T., Liu, X., Murray, R. Collier, D.A. Kerwin, R.W.(1998). Arranz, M.J., Li, T., Liu, X., Murray, R. Collier, D.A. Kerwin, R.W.(1998). Lack of Lack of associationassociation between a polymorphism in the promoter between a polymorphism in the promoter region of the dopamine-2 receptor gene and region of the dopamine-2 receptor gene and clozapine clozapine responseresponse. . Pharmacogenetics. 8(6):481-4.Pharmacogenetics. 8(6):481-4.

Page 35: PharmacoGenomics  – personalized medicine

AdvantagesAdvantages DisadvantagesDisadvantages

• Diagnosis-systematized

• investigators blinded to the patient genotype

• Prior medical treatment

• Don’t separate positive from negative symptoms

Page 36: PharmacoGenomics  – personalized medicine

Non small cell lung cancer Non small cell lung cancer - NSCLC- NSCLC

Lung carcinoma is theLeading cause of cancer deths in the USA and worldwide for both men and women.

Page 37: PharmacoGenomics  – personalized medicine

Rationale: EGFR (epidermal growth factor receptor) over-expressed in lung cancers (and other). EGFR inhibitors block signal transduction and cell proliferationGefitinib : A drug that targets the ATP cleft within the EGFR.

Design:•210 patients from Europe, Australia, South Africa, Japan• Objective tumor response in 19% of patients - mean survival 8 months• Response better among Japanese vs non-Japanese pts

(27.5% vs. 10.4% response; P = 0.002)• Response also better among female pts, adenocarcinoma pts, pts with prior hormonal/immuno treatment, pts with less morbidity

•What is molecular basis of the differential response?

Multi-center trial of EGFR inhibitor to treat Multi-center trial of EGFR inhibitor to treat advanced lung cancer (NSCLC)advanced lung cancer (NSCLC)

Page 38: PharmacoGenomics  – personalized medicine

Paez JG, Janne PA, Lee JC, Tracy S, Greulich H, Gabriel S, Herman P, Kaye FJ, Lindeman N, Boggon TJ, Naoki K, Sasaki H, Fujii Y, Eck MJ, Sellers WR, Johnson BE, Meyerson M.

EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy.

Science 304:1497-500, 2004

Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN, Christiani DC, Settleman J, Haber DA.

Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib.

N Engl J Med 350:2129-2139, 2004

Lung cancer - EGFR inhibitors – Lung cancer - EGFR inhibitors – EGFR somatic mutationEGFR somatic mutation

Page 39: PharmacoGenomics  – personalized medicine

Activating mutations in EGFR underlying Activating mutations in EGFR underlying responsiveness of lung cancer to gefitinibresponsiveness of lung cancer to gefitinib

•EGFR sequenced in pre-treatment tumor tissue from: •9 responders (tumors that were available), 7 non-responders, 25 untreated patients

Example of improvement after 6 weeks treatment

Page 40: PharmacoGenomics  – personalized medicine

Most of them were women, had never smoked, and had bronchoalveolar tumors

Page 41: PharmacoGenomics  – personalized medicine

(9 tumors available from 25 responders)

(25 untreated tumors evaluated)

OverlapAA 747-750

8 out of the 9 patients that were checked for mutations in the tumors and responded to gefitinib had deletions in the tumor cells.And in 7 patients with no response no mutations were observed. (p<0.001)

Page 42: PharmacoGenomics  – personalized medicine

OverlapOverlap

Page 43: PharmacoGenomics  – personalized medicine

EGFR mutations in lung cancer: Correlation with EGFR mutations in lung cancer: Correlation with clinical response to gefitinib therapy. Science clinical response to gefitinib therapy. Science

304:1497, 2004304:1497, 2004119 primary lung tumors (58 Japan, 61 US), none treated before, EGFR somatic mutations in 15/58 (26%) of Japanese pts vs 1/61 (2%) of US

pts. Among adenocarcinomas only, mutations in 14/41 (32%) of Japanese pts vs. 1/29 (3%) of US pts

Page 44: PharmacoGenomics  – personalized medicine

EGFR mutations in lung cancer: Correlation with EGFR mutations in lung cancer: Correlation with clinical response to gefitinib therapy. clinical response to gefitinib therapy.

Science 304:1497, 2004Science 304:1497, 2004Pre-treatment tumors from treated patients: 6 responders, 4 non-responders

Page 45: PharmacoGenomics  – personalized medicine

EGFR mutations in lung cancer: Correlation with EGFR mutations in lung cancer: Correlation with clinical response to gefitinib therapy. clinical response to gefitinib therapy.

Science 304:1497, 2004Science 304:1497, 2004

exon 21

exon 18

exon 19

Sequence and substitutions alterations at kinase active site.

Page 46: PharmacoGenomics  – personalized medicine

EGFR mutations in lung cancer: EGFR mutations in lung cancer: Correlation with clinical response to Correlation with clinical response to

gefitinib therapy. gefitinib therapy. Science 304:1497, 2004Science 304:1497, 2004

Page 47: PharmacoGenomics  – personalized medicine

Mutations may stabilize interaction of EGFR with both ATP (enhancing phosphorylation) and with competitive inhibitor geftinib -> both enhanced inhibition by drug.

EGFR mutations in lung cancer: EGFR mutations in lung cancer: Correlation with clinical response to Correlation with clinical response to

gefitinib therapy. gefitinib therapy. Science 304:1497, 2004Science 304:1497, 2004

Page 48: PharmacoGenomics  – personalized medicine

• These drug response phenotypes are associated with a set of specific gene alleles.

• Identify populations of people who show specific responses to a drug.

• In early clinical trials, it is possible to identify people who react well and react poorly.

In general :In general :Collect Drug Response DataCollect Drug Response Data

Page 49: PharmacoGenomics  – personalized medicine

• Scan these populations with a large number of SNP markers.

• Find markers linked to drug response phenotypes.

• It is interesting, but not necessary, to identify the exact genes involved.

Make Genetic Profiles

Page 50: PharmacoGenomics  – personalized medicine

ProfilesProfiles

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Use the Profiles - SummaryUse the Profiles - Summary

• Genetic profiles of new patients can then be used to prescribe drugs more effectively & avoid adverse reactions.

• Can also speed clinical trials by testing on those who are likely to respond well.

Page 52: PharmacoGenomics  – personalized medicine

Impact on BioinformaticsImpact on Bioinformatics

• Genomics produces high-throughput, high-quality data, and bioinformatics provides the analysis and interpretation of these massive data sets.

• It is impossible to separate genomics laboratory technologies from the computational tools required for data analysis.

Page 53: PharmacoGenomics  – personalized medicine

DebateDebate

Will it be economical to develop medications and dosages for only a subset of the population?