Missing Genes Point to Possible Drug Targets

Human knockout projectEvery person’s genetic blueprint, or genome, is unique because of variations that occasionally occur in our DNA sequences. Most of those are passed on to us from our parents. But not all variations are inherited—each of us carries 60 to 100 “new mutations” that happened for the first time in us. Some of those variations can knock out the function of a gene in ways that lead to disease or other serious health problems, particularly in people unlucky enough to have two malfunctioning copies of the same gene. Recently, scientists have begun to identify rare individuals who have loss-of-function variations that actually seem to improve their health—extraordinary discoveries that may help us understand how genes work as well as yield promising new drug targets that may benefit everyone.

In a study published in the journal Nature, a team partially funded by NIH sequenced all 18,000 protein-coding genes in more than 10,500 adults living in Pakistan [1]. After finding that more than 17 percent of the participants had at least one gene completely “knocked out,” researchers could set about analyzing what consequences—good, bad, or neutral—those loss-of-function variations had on their health and well-being.

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Fighting Parasitic Infections: Promise in Cyclic Peptides

Cyclic peptide bound to iPGM

Caption: Cyclic peptide (middle) binds to iPGM (blue).
Credit: National Center for Advancing Translational Sciences, NIH

When you think of the causes of infectious diseases, what first comes to mind are probably viruses and bacteria. But parasites are another important source of devastating infection, especially in the developing world. Now, NIH researchers and their collaborators have discovered a new kind of treatment that holds promise for fighting parasitic roundworms. A bonus of this result is that this same treatment might work also for certain deadly kinds of bacteria.

The researchers identified the potential new  therapeutic after testing more than a trillion small protein fragments, called cyclic peptides, to find one that could disable a vital enzyme in the disease-causing organisms, but leave similar enzymes in humans unscathed. Not only does this discovery raise hope for better treatments for many parasitic and bacterial diseases, it highlights the value of screening peptides in the search for ways to treat conditions that do not respond well—or have stopped responding—to more traditional chemical drug compounds.

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Precision Medicine: Using Genomic Data to Predict Drug Side Effects and Benefits

Gene Variant and Corornary Heart DiseasePeople with type 2 diabetes are at increased risk for heart attacks, stroke, and other forms of cardiovascular disease, and at an earlier age than other people. Several years ago, the Food and Drug Administration (FDA) recommended that drug developers take special care to show that potential drugs to treat diabetes don’t adversely affect the cardiovascular system [1]. The challenge in implementing that laudable exhortation is that a drug’s long-term health risks may not become clear until thousands or even tens of thousands of people have received it over the course of many years, sometimes even decades.

Now, a large international study, partly funded by NIH, offers some good news: proof-of-principle that “Big Data” tools can help to identify a drug’s potential side effects much earlier in the drug development process [2]. The study, which analyzed vast troves of genomic and clinical data collected over many years from more than 50,000 people with and without diabetes, indicates that anti-diabetes therapies that lower glucose by targeting the product of a specific gene, called GLP1R, are unlikely to boost the risk of cardiovascular disease. In fact, the evidence suggests that such drugs might even offer some protection against heart disease.

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DNA Barcodes Interrogate Cancer Cells

Blue and green blobs with one purple and red blob with a yellow and red striped box

Caption: A mix of cells collected from an abdominal cancer. The cancer cells (green) are positive for a cell surface cancer marker called EpCAM. The red cell is a normal mesothelial cell. The nuclei of all the cells are stained blue. Each of the five rows in the red, orange, and yellow “heat map” in the corner represents one cell, and the intensity of the color in each of the ~30 narrow columns reflects the abundance of a particular protein. It is apparent that there is a lot of heterogeneity in this collection of cancer cells.
Credit: Ralph Weissleder, Center for Systems Biology, Massachusetts General Hospital, Boston

The proteins speckling the surface of a cancer cell reveal critical clues—the type of cancer cell and a menu of possible mutations that may have triggered the malignancy.  Since these proteins are exposed on the outside of the cell, they are also ideal targets for so-called precision cancer therapies (especially monoclonal antibodies), optimized for the particular individual. But in the past, to analyze and identify these different proteins, large samples of tissue have been needed. Typically, these are derived from surgical biopsies. But biopsies are expensive and invasive. Furthermore, they aren’t a practical option if you want to monitor the effects of a drug in a patient closely over time.

Using a minimally invasive method of cell sampling called fine needle aspiration, physicians can collect miniscule cell samples frequently, cheaply, and safely. But, until now, these tiny samples only provided enough material to analyze a handful of cell surface proteins. So, it comes as particularly good news that NIH-funded researchers at Massachusetts General Hospital in Boston have developed a new technology that quickly identifies hundreds of these proteins simultaneously, using just a few of the patient’s cells [1]. The key to this new method is a clever adaptation of the familiar barcode.

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Introducing AMP: The Accelerating Medicines Partnership

Pie charts showing AMP targets reducing failures due to efficacy

Caption: Lack of efficacy currently accounts for more than half of all drug failures in Phase II clinical studies (left). If AMP’s target validation efforts improve efficacy by 90% (right), the success rate will rise significantly.

It would seem like there’s never been a better time for drug development. Recent advances in genomics, proteomics, imaging, and other technologies have led to the discovery of more than a thousand risk factors for common diseases—biological changes that ought to hold promise as targets for drugs.

But this deluge of new opportunities has to be put in context: drug development is a terribly difficult business. To the dismay of researchers, drug companies, and patients alike, the vast majority of drugs entering the development pipeline fall by the wayside. The most distressing failures occur when a drug is found to be ineffective in the later stages of development—in Phase II or Phase III clinical studies—after years of work and millions of dollars have already been spent [1]. Why is this happening? One major reason is that we’re not selecting the right biological changes to target from the start.

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