Genomics and personalized medicine are changing the field of pharmacogenomics by two ways:

by optimizing drug therapies and by reducing adverse drug

reactions.

In the near future, personalized medicine will allow physicians to predict which diseases you will develop, which therapeutics will work for you, and which drug dosages are appropriate.

Genomics, personalized medicine and pharmacogenomics

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Today, the phrase personalized medicine is used to describe the application of information from a patient’s unique genetic profile in order to select effective treatments that have minimal side-effects and to detect disease susceptibility prior to development of the disease.

Pharmacogenomics is the study of how an individual’s entire genetic makeup determines the body’s response to drugs. The term pharmacogenomics is used interchangeably with pharmacogenetics, which refers to the study of how sequence variation within specific candidate genes affects an individual’s drug responses.

In pharmacogenomics, scientists take into account many aspects of drug metabolism and how genetic traits affect these aspects.

Definition

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When a drug enters the body, it interacts with various proteins including carriers, cell-surface receptors, transpor-ters, and metabolizing enzymes. These proteins affect a drug’s target site of action, absorption, pharmacological response, breakdown, and excretion. Because there are so many interactions that occur between a drug and proteins within the patient, many genes and many different genetic polymorphisms can affect a person’s response to a drug.Figure: A

general summary of the percentages ofpatients for which a particular class of drugs is effective.

Variations in patient response to drugs

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Optimizing drug therapies On average, a drug will be effective in only about 50%

of patients who take it (see Fig. in previous slide), which means that physicians often must switch their patients from one drug to another until they find one that is effective.

Not only does this waste time and resources, but also it may be dangerous to the patient who is exposed to a variety of different pharmaceuticals and who may not receive appropriate treatment in time to combat a progressive illness.

One of the most common current applications of personalized pharmacogenomics is in the diagnosis and treatment of cancers.

Large-scale sequencing studies show that each tumor is genetically unique, even though it may fall into a broad category based on cytological analysis or knowledge of its tissue origin.

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One of the first success stories in personalized medicine was that of the human epidermal growth factor receptor 2 (HER-2) gene and the use of the drug Herceptin® in breast cancer.

Because Herceptin will only act on breast cancer cells that have amplified HER-2 genes, it is important to know the HER-2 phenotype of each cancer. In addition, Herceptin has potentially serious side-effects. Hence, its use must be limited to those who could benefit from the treatment.

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Determining the gene and protein status of breast cancer cells

A number of molecular assays have been developed to determine the gene and protein status of breast cancer cells. Two of the most commonly used tests are based on immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH).

In IHC assays, an antibody that binds to HER-2 protein molecules is added to fixed tissue on a slide. The antibody is bound to another molecule that reacts to produce a visual stain.

After washing and staining, the tissues are observed under a microscope. The level of HER-2 staining is assessed from “0” (fewer than 20,000 HER-2 molecules per cell) to “+3” (approx. 2 million molecules per cell).

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IHC is a method to stain the tissue sections/cells and is perhaps the most commonly applied immunostaining technique. While the first cases of IHC staining used fluorescent dyes, other non-fluorescent methods using enzymes such as peroxidase and alkaline phosphatase are now used.

Immunohistochemistry (IHC)

These enzymes are capable of catalysing reactions that give a coloured product that is easily detectable by light microscopy. Alternatively, radioactive elements can be used as labels, and the immuno-reaction can be visualized by autoradiography.

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ELISA is a diagnostic method for quantitatively or semi-quantitatively determining protein concentrations from blood plasma, serum or cell/tissue extracts in a multi-well plate format (usually 96-wells per plate). Broadly, proteins in solution are adsorbed to ELISA plates. Antibodies specific for the protein of interest are used to probe the plate.

Enzyme Linked ImmunoSorbent Assay (ELISA)

Background is minimized by optimizing blocking and washing methods (as for IHC), and specificity is ensured via the presence of positive and negative controls. Detection methods are usually colorimetric or chemilumi-nescence based.

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In FISH, DNA or RNA molecules with sequence complemen-tarity to the HER-2 gene sequence are added to the fixed tissue on the slide.

These DNA or RNA probes are labeled with a fluorescent tag molecule. After hybridizing the probes to the tissue and washing off excess probe, the location and intensity of the probe are determined by observing the tissue under a fluorescence microscope.

The number of HER-2 genes is assessed by comparing the fluorescence signal of the HER-2 probe with a control signal from another gene that is not amplified in the cells.

Herceptin has had a major effect on the treatment of HER-2 positive breast cancers. When Herceptin is used in combination with chemotherapy, there is a 25 to 50 percent increase in survival, compared with the use of chemotherapy alone. Herceptin is now one of the biggest selling biotechno-logy products in the world, generating more than $5 billion in annual sales.

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HER-2 gene and protein assays. (a) Normal and breast cancer cells within a biopsy sample, stained by HER-2 immunohistoche-mistry. Cell nuclei are stained blue. Cancer cells that overexpress HER-2 protein stain brown. (b) Cancer cells from the same tumor assayed for HER-2 gene copy number by FISH. Cancer cell nuclei appear green under the fluorescence microscope and the HER-2 gene DNA appears bright yellow. Large clumps of yellow stain indicate HER-2 gene amplification (>20 copies per nucleus).

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Reducing adverse drug reactions Every year, about 2 million people in the United

States suffer serious side-effects from pharmaceutical drugs, and appro-ximately 100,000 people die from that adverse side-effects.

The costs associated with these adverse drug reactions (ADRs) are estimated to be $136 billion annually.

Although some ADRs result from drug misuse, others result from a patient’s inherent physiological reactions to a drug.

Sequence variations in a large number of genes can affect drug responsiveness (see Table in the next slide).

Of particular significance are the genes that encode the cytochrome P450 families of enzymes. These family members are encoded by 57 different genes.

The products of the CYP2A6, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 genes are responsible for metabolizing most clinically important pharmaceutical drugs.

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Examples of variant gene products that affect drug responses

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Personalized medicine and disease diagnosis

Growth of gene tests and testing laboratories from 1993 to 2009. (from the GeneTests Web site at www.ncbi.nlm.nih.gov/).

As of 2009, there were genetic tests for approximately 2000 different diseases.

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Table: Some single-gene defects for which genetic

tests are available.

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Although these genetic tests are extremely useful for detecting some future diseases and guiding treatment, it is clear that most disorders are multifactorial and complex.

It is likely that diseases such as diabetes, Alzheimer’s, and heart disease are caused by interactions between many genes, as well as by factors contributed by epigenetic effects, lifestyle, and environment.

These diseases tend to be chronic and have a significant burden on health-care systems.

Genome sequencing, SNP identification, and genome-wide association studies (GWAS) are beginning to reveal some of the DNA variants that may contribute to the risk of developing multifactorial diseases such as cancer, heart disease, and diabetes.

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The Pharmacogenomics Knowledge Base (PharmGKB): Genes, Drugs, and Diseases on

the Web PharmGKB is a publicly available Internet database and information source developed by Stanford University. It is funded by the National Institutes of Health (NIH)

On the PharmGKB Web site (http://www.pharmgkb.org), you may search for genes and more than 650 variants that affect drug reactions, information on a large number of drugs, diseases and their genetic links, pharmaco-genomic pathways, gene tests, and relevant publications.

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Pharmacogenomics and Rational Drug Design

Fig. Different individuals with the same disease, in this case childhood leukemia, often respond differently to a drug treatment because of subtle differences in gene expression. The dose of an anticancer drug (6-MP) that works for one person may be toxic for another person.

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Several methods are being developed for expanding the uses of pharmacogenomics. One promising method involves the detection of SNPs.

Perhaps researchers will be able to identify a shared SNP sequence in the DNA of people who also share a heritable reaction to a drug.

If the SNP segregates with a part of the genome containing the gene responsible for the drug reaction, it may be possible to devise gene tests based on the SNP, without even knowing the identity of the gene responsible for the drug reaction.

In the future, DNA microarrays may be used to screen a patient’s genome for multiple drug reactions.

Knowledge from genetics and molecular biology is also contributing to the development of new drugs targeted at specific disease-associated molecules.

Most drug development is currently based on trial-and-error testing of chemicals in lab animals, in the hope of finding a chemical that has a useful effect.

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Fig. Microarray analysis for analyzing gene-expression patterns in a tissue.

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RDD involves the synthesis of specific chemical substances that affect specific gene products.

An example of a rational drug design product is the new drug imatinib, trade name Gleevec, used to treat chronic myelogenous leukemia (CML).

Geneticists had discovered that CML cells contain the Philadelphia chromosome, which results from a reciprocal translocation between chromosomes 9 and 22.

Gene cloning revealed that the t(9;22) translocation creates a fusion of the C-ABL proto-oncogene with the BCR gene. This BCR-ABL fusion gene encodes a powerful fusion protein that causes cells to escape cell-cycle control.

The fusion protein, which acts as a tyrosine kinase, is not present in non-cancer cells from CML patients.

Rational Drug Design (RDD)

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To develop Gleevec, chemists used high-throughput screens of chemical libraries to find a molecule that bound to the BCR-ABL enzyme.

After chemical modifications to make the inhibitory molecule bind more tightly, tests showed that it specifically inhibited BCR-ABL activity.

Clinical trials revealed that Gleevec was effective against CML, with minimal side effects and a higher remission rate than that seen with conventional therapies.

Gleevec is now used to treat CML and several other cancers.

With scientists discovering more genes and gene products associated with diseases, rational drug design promises to become a powerful technology within the next decade.

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Gene Therapy Although drug treatments are often effective in controlling

symptoms of genetic disorders, the ideal outcome of medical treatment is to cure these diseases.

In an effort to cure genetic diseases, scientists are actively investigating gene therapy - a therapeutic technique that aims to transfer normal genes into a patient’s cells.

In theory, the normal genes will be transcribed and translated into functional gene products, which, in turn, will bring about a normal phenotype.

Human gene therapy began in 1990 with the treatment of a young girl named Ashanti DeSilva who has a heritable disorder called severe combined immunodeficiency (SCID). Individuals with SCID have no functional immune system and usually die from what would normally be minor infections.

Ashanti has an autosomal form of SCID caused by a mutation in the gene encoding the enzyme adenosine deaminase (ADA). Her gene therapy began when clinicians isolated some of her white blood cells, called T cells. These cells, which are key components of the immune system, were mixed with a retroviral vector carrying an inserted copy of the normal ADA gene.

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(a) Ashanti DeSilva, the first person to be treated by gene therapy. (b) To treat SCID using gene therapy, a cloned human ADA gene is transferred into a viral vector, which is then used to infect white blood cells removed from the patient.

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To date, gene therapy has successfully restored the health of about 20 children affected by SCID. Although gene therapy was originally developed as a treatment for single-gene (monogenic) inherited diseases, the technique was quickly adapted for the treatment of acquired diseases such as cancer, neurodegenerative diseases, cardiovascular disease, and infectious diseases, such as HIV.

In the case of HIV, scientists are exploring ways to deliver immune system-stimulating genes that could make individuals resistant to HIV infection or cripple the virus in HIV positive persons.

There are nearly 1000 gene therapy trials actively underway in the United States alone.

Over a 10-year period, from 1990 to 1999, more than 4000 people underwent gene therapy for a variety of genetic disorders. These trials often failed and thus led to a loss of confidence in gene therapy.

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Scientists are also working on gene replacement approaches that involve removing a defective gene from the genome.

Recent work with enzymes called zinc-finger nucleases have shown promise in animal models and cultured cells.

These enzymes can create site-specific cleavage in the genome and when coupled with certain integrases may lead to gene editing by cutting out defective sequences and introducing normal homologous sequences into the genome.

Encouraging breakthroughs have taken place in this area using model organisms such as mice; however, this technology has not advanced sufficiently for use in humans.

Attempts have been made to use antisense oligonucleo-tides in order to inhibit translation of mRNAs from defective genes, but this approach to gene therapy has generally not yet proven to be reliable.

Gene replacement approaches

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The recent emergence of RNA interference as a powerful gene-silencing tool has reinvigorated gene therapy approaches by gene silencing. RNA interference (RNAi) is a form of gene-expression regulation.

In animals, short and double stranded RNA molecules are delivered into cells where the enzyme Dicer chops them into 21-nt long pieces called small interfering RNAs (siRNAs).

siRNAs then join with an enyzme complex called the RNA inducing silencing complex (RISC), which shuttles the siRNAs to their target mRNA, where they bind by complementary base pairing.

The RISC complex can block siRNA-bound mRNAs from being translated into protein or can lead to degradation of siRNA-bound mRNAs so they cannot be translated into protein.

A main challenge to RNAi-based therapeutics so far has been in vivo delivery of double-stranded RNA or siRNA. However, several RNAi clinical trials to treat blindness are underway in USA.

Gene silencing approaches

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Fig. Mechanisms of gene regulation by RNA-induced gene silencing.

RNA-induced silencing complex (RISC). RNA-induced initiation of transcription silencing complex (RITS).

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What is Bioinformatics? In today’s world, computers are as likely to be used by

biologists as by any other professionals - bankers or flight controllers, for example.

Many of the tasks performed by such professionals are common to most of us: we all tend to write lots of memos and send lots of e-mails; many of us use spreadsheets, and we all store immense amounts of never-to-be-seen-again data in complicated file systems.

However, besides these general tasks, biologists also use computers to address problems that are very specific to biologists, which are of no interest to bankers or flight controllers.

These specialized tasks, taken together, make up the field of bioinformatics. More specifically, we can define bioinformatics as the computational branch of molecular biology.

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What bioinformatics can do for us?Analyzing DNAsAnalyzing RNAsAnalyzing proteinsAnalyzing others such as complex

pathways, in silico simulation, bioimaging, etc.

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How most people use bioinformatics?

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