In medicine, one size doesn’t fit all. Two people who take the same cancer medication, for instance, may have very different responses. One may have severe, even life-threatening side effects, while the other experiences few if any side effects and seems to sail through treatment. Or, the drug may shrink a tumor in one person but not in another.

One major reason this difference happens is because people inherit variations in their genes. And even slight variations can affect how your body responds to certain medications. Pharmacogenomics is the science that studies, among other things, how individuals react to medications. Pharmacogenomics is sometimes described as “personalized” or “individualized” medicine because it offers the potential to recommend drug treatment based on your individual genetic background.

The field of pharmacogenomics is promising. In fact, a handful of tests are available that can detect some of these genetic variations and predict how you’re likely to respond to certain medications. But pharmacogenomics still isn’t widely used, so it’s wise to educate yourself about just what pharmacogenomics can — and can’t — offer.

How do genes influence response to medications?

Genes are segments of DNA, which are found in all of your cells. DNA is essentially a chemical operating system for your body, instructing it how to behave and interact on a cellular level. A basic gene can have many different forms. For instance, consider the gene that determines hair color. Normal variations of that gene determine specific hair color, such as brown or blond.

Similarly, your genes can determine how you react to a medication. You may have a genetic variation that makes the drug stay in your body longer than normal, causing serious side effects. Or you may have a variation that makes the medication less potent.

Scientists are trying to identify and record as many genetic variations as possible. Once a variation is identified, scientists might be able to match it up with a response to a particular medication and then develop a personalized approach to medicine.

Personalized medicine: Using pharmacogenomics

Say you’re diagnosed with a certain disease, such as breast cancer, for which you must take medication. You and your doctor choose a medication based on standard drug therapy and dosing guidelines for that disease. Your doctor may also take into account such factors as your weight, age, medical history and even how any blood relatives have reacted to the same medication.

Despite all of that, neither you nor your doctor knows how you’ll actually react to the medication. You may experience terrible side effects — or none at all. The medication may put your cancer into remission — or it may have no effect. Consequently, you may have to return to your doctor many times to adjust the dosage or to switch medications. This is how medication choices generally work today — it’s often a matter of trial and error.

Pharmacogenomics could potentially speed up that process. Before you take a single dose of medication, you may be able to have a blood test to see which genetic variations you have. The test may show that you have a variation that’s likely to adversely affect how you respond to the medication. So your doctor skips that drug and prescribes a different one, or your doctor alters the dose to match your body’s genetics.

What are the benefits of pharmacogenomics?

Though current uses are limited, pharmacogenomics has the potential to offer many benefits.

Some of the potential benefits include:

* Making better medication choices. Each year, some 100,000 Americans die from adverse reactions to medications and more than 2 million are hospitalized. Medications generally undergo a rigorous review and testing process before being approved for sale. But there’s still often no way to predict how a certain individual will react to a drug. So even if a medication appears safe for most people, some people may have a toxic reaction to it because of variations in their genes. Pharmacogenomics may be able to predict the people likely to have a bad reaction to a drug before they ever take it. It may also be able to predict if you’ll respond well to a medication — whether your breast tumor will shrink, for example.
* Safer dosing options. As it stands now, the dosage of a medication either is a standard one-size-fits-all dose or is based on factors such as your weight and age. That might not be good enough, though. A standard dose may prove toxic to one person and not another, because of their genetic variations. Using pharmacogenomics, doctors may get around this problem by predicting which dose of medication is right for you, not just which particular medication is right. So you and your doctor may spend less time trying out various dosages to find one that works well, with the fewest side effects and most benefits for your condition.
* Improvements in drug development. Pharmaceutical companies often must spend years conducting research and clinical trials for a new drug before it goes to market. They have to test a drug in many people to ensure that it’s safe and effective. Pharmacogenomics may help these companies better focus their drug testing. If companies know ahead of time that someone has a genetic variation that will cause a bad reaction to the drug or that will make the drug ineffective, those people can be excluded from the clinical trial. This may speed up the clinical trial process and better target people who can be helped by a certain medication.

What are some of the barriers to using pharmacogenomics?

The field of pharmacogenomics is still in its early stages. It’s possible that millions of genetic variations may exist, and identifying them all could take many years — if it’s even possible. In addition, how you respond to a medication may not be determined by just one gene but rather by many genes interacting with each other. Combing through this complicated genetic map is expensive and time-consuming.
What types of personalized medicine are in use today?

Some types of personalized medicine based on the science of pharmacogenomics are in use today but on a limited basis. A few tests are now available that can help predict likely responses or bad reactions to certain medications.

Some of the tests available include:

* Cytochrome P450 genotyping test. A group of enzymes known as cytochrome P450 (CYP450) enzymes are responsible for metabolizing more than 30 types of medications and thus determine how quickly and effectively these medications are eliminated from your body. Because of your genetic makeup, your body may not break down the medications fast enough, instead allowing them to accumulate to levels that can result in severe side effects. Or, you may have a genetic variation that makes your body break down the medications too quickly, before they have a chance to work. The CYP450 test can be used to determine dosing and effect of certain antidepressant medications, anticoagulants such as warfarin, proton pump inhibitors and a number of other medications.
* Thiopurine methyltransferase test. An enzyme called thiopurine methyltransferase (TPMT) breaks down a type of chemotherapy drug called thiopurine that’s used to treat some leukemias and autoimmune disorders. Some people have genetic variations that prevent them from producing this enzyme. As a result, thiopurine levels can build up in the body, leading to severe toxic reactions. A blood test can check for this genetic variation before treatment begins, giving doctors better dosing guidelines.
* UGT1A1 TA repeat genotype test. This test, commonly known as the UGT1A1 test, detects a variation in a gene that affects the UGT1A1 enzyme. This enzyme determines how the body breaks down irinotecan (Camptosar), a chemotherapy drug used to treat colorectal cancer. Some people have a deficiency in this enzyme, allowing the medication to build up to toxic levels and possibly causing suppression of the bone marrow, infection and even death. Doctors can test for this genetic variation before treatment starts and then customize the dosage to prevent a toxic buildup of the drug. On the flip side, if someone has normal levels of the UGT1A1 enzyme, the test may help doctors ensure that the dosage of irinotecan isn’t lower than necessary.
* Dihydropyrimidine dehydrogenase test. The medication 5-fluorouracil (5-FU) including its related compounds is one of the most commonly used chemotherapy medications. Some people have a genetic variation that results in a decrease in the dihydropyrimidine dehydrogenase enzyme, which is responsible for breaking down 5-FU. As a result of this deficiency, some people may develop severe or even fatal reactions to 5-FU. Knowing ahead of time who has this deficiency can help doctors tailor the medication dosage to prevent these kinds of dangerous adverse reactions.

Where does the science of pharmacogenomics stand now?

In the future, pharmacogenomics could have an expanding role in the practice of medicine. But despite the promise of personalized medicine, pharmacogenomic testing is not widely available today. You should be skeptical of news reports and other sources of information proclaiming that pharmacogenomics or other types of personalized medicine will offer revolutionary results today. It is hoped that this will be true sometime in the future.

By Mayo Clinic Staff
June 27, 2008

BERKELEY LAB — The dream of personalized medicine — in which diagnostics, risk predictions and treatment decisions are based on a patient’s genetic profile — may be on the verge of being expanded beyond the wealthiest of nations with state-of-the-art clinics. A team of researchers with the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) has invented a technique in which DNA or RNA assays — the key to genetic profiling and disease detection — can be read and evaluated without the need of elaborate chemical labeling or sophisticated instrumentation. Based on electrostatic repulsion — in which objects with the same electrical charge repel one another — the technique is relatively simple and inexpensive to implement, and can be carried out in a matter of minutes.

“One of the most amazing things about our electrostatic detection method is that it requires nothing more than the naked eye to read out results that currently require chemical labeling and confocal laser scanners,” said Jay Groves, a chemist with joint appointments at Berkeley Lab’s Physical Biosciences Division and the Chemistry Department of the University of California (UC) at Berkeley, who led this research. “We believe this technique could revolutionize the use of DNA microarrays for both research and diagnostics.”

Groves, who is also a Howard Hughes Medical Institute (HHMI) investigator, and members of his research group Nathan Clack and Khalid Salaita, have published a paper on their technique in the journal /Nature Biotechnology/, which is now available online. The paper is entitled “Electrostatic readout of DNA microarrays with charged microspheres.”

In their paper, Groves, Clack, and Salaita describe how dispersing a fluid containing thousands of electrically-charged microscopic beads or spheres made of silica (glass) across the surface of a DNA microarray and then observing the Brownian motion of the spheres provides measurements of the electrical charges of the DNA molecules. These measurements can in turn be used to interrogate millions of DNA sequences at a time. What’s more, these measurements can be observed and recorded with a simple hand-held imaging device — even a cell phone camera will do.

“The assumption has been that no detection technique could be more sensitive than fluorescent labeling, but this is completely untrue, as our results have plainly demonstrated,” said Groves. “We’ve shown that changes in surface charge density as a result of specific DNA hybridization can be detected and quantified with 50-picometer sensitivity, single base-pair mismatch selectivity, and in the presence of complex backgrounds. Furthermore, our electrostatic detection technique should render DNA and RNA microarrays sufficiently cost effective for broad world-health applications, as well as research.”

Your susceptibility to a given disease and how your body will respond to drugs or other interventions is unique to your genetic makeup. Under a personalized medicine plan, treatment effectiveness is maximized and risks are minimized by tailoring disease treatments specifically to you. This requires the precise diagnostic tests and targeted therapies that can stem from assays using a DNA microarray — a thumbnail-sized substrate containing thousands of microscopic spots of oligonucleotides (stretches of DNA about 20 base pairs in length) laid out in a grid.

Often referred to as “gene chips,” DNA microarray assays and their RNA counterparts have become one of the most powerful tools for gene-expression profiling, the identification of mutations, and the detection of multiple pathogens in patients afflicted either by multiple diseases or drug-resistant strains of diseases. Aside from their potential future role in personalized medicine, the widespread use of DNA microarray assay devices could have an immediate and profound impact on the treatment of diseases today. For example, according to a report two years ago from the Global Health Diagnostics Forum, 400,000 lives could be saved each year from death by tuberculosis through the use of DNA microarray assays rather than the standard TB diagnostic test, which is known to miss nearly half of all cases.

Until now, however, the use of DNA microarray assays has been limited because current techniques typically depend upon fluorescence detection, a demanding methodology that requires time-consuming chemical labeling, high-power excitation sources, and sophisticated instrumentation for scanning. Such demands are generally well beyond the capabilities of individual laboratories or clinics, especially in developing countries. While label-free DNA detection strategies do exist, they require either complex device fabrication or sophisticated instrumentation for readouts, and in addition none are compatible with conventional DNA microarrays, where up to one million sequences are available for interrogation in a single experiment.

“We have demonstrated parallel sampling of a microarray surface with micron-scale resolutions over centimeter-scale lengths,” said Groves. “This is four orders of magnitude larger than what has been achieved to date with conventional scanning-electrostatic-force microscopy.”

In a typical experiment, a microarray is prepared and mounted in a well chamber and the DNA is hybridized (a standard technique in which complementary single strands of DNA bind to form double-stranded DNA “hybrids”). A suspension of negatively-charged silica microspheres is then dispersed through gravitational sedimentation over the microarray surface, a process which takes about 20 minutes. Because the substrate or background surface of the microassay is positively charged, the silica microspheres will spread across the entire surface and adhere to it. However, on surface areas containing double-stranded DNA, which is highly negatively charged, and on areas containing single-stranded DNA, also negatively charged but to a lesser degree than double-stranded DNA, the microspheres will levitate above the substrate surface, stacking up in “equilibrium heights” that are dictated by a balance between gravitational and electrostatic forces.

These electrostatic interactions on the microarray surface result in charge-density contrasts that are readily observed. Surface areas containing DNA segments take on a frosted or translucent appearance, and can be correlated to specific hybridizations that reveal the presence of genes, mutations and pathogens.

“Our technique is essentially a millionfold parallel version of the classic experiment used by Robert Millikan almost 100 years ago, when he determined the charge of a single/ /electron by observing the positions of oil droplets levitated above a charged plate,” said Groves.

There are a number of short-term “next steps” for this research, Groves said, including testing its application in high-density arrays and pushing its ultimate resolution limits.

“Since the resolution of electrostatic-based imaging is determined by the number of particle-observations rather than by the diffraction limit of light, our readouts could serve as a form of ultramicroscopy,” he said. “The real grand challenge for this technology, however, will be for us to find suitable industrial partners with whom we can work to see that useful new products actually make it to market.”

The electrostatic detection technology is now available for licensing through Berkeley Lab’s Technology Transfer Department; visit their website at http://www.lbl.gov/Tech-Transfer/index.html.

This research was funded by the U.S. Department of Energy’s Office of Science through its Office of Basic Energy Sciences.

Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California. Visit our website at www.lbl.gov .