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personalized medicine

DNA Barcodes Interrogate Cancer Cells

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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.

Different Cancers Can Share Genetic Signatures

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Cancer types floating over a cell with unraveling DNA

NIH-funded researchers analyzed the DNA of these cancers.

Cancer is a disease of the genome. It arises when genes involved in promoting or suppressing cell growth sustain mutations that disturb the normal stop and go signals.  There are more than 100 different types of cancer, most of which derive their names and current treatment based on their tissue of origin—breast, colon, or brain, for example. But because of advances in DNA sequencing and analysis, that soon may be about to change.

Using data generated through The Cancer Genome Atlas, NIH-funded researchers recently compared the genomic fingerprints of tumor samples from nearly 3,300 patients with 12 types of cancer: acute myeloid leukemia, bladder, brain (glioblastoma multiforme), breast, colon, endometrial, head and neck, kidney, lung (adenocarcinoma and squamous cell carcinoma), ovarian, and rectal. Confirming but greatly extending what smaller studies have shown, the researchers discovered that even when cancers originate from vastly different tissues, they can show similar features at the DNA level

Personalizing Depression Treatment with Brain Scans

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Brain scan showing three red dots, the largest of which is in the cross hairs of two green lines

Caption: Depressed patients with higher activity in the anterior insula (where the green lines intersect) did better with medication than cognitive behavior therapy.
Source: Helen Mayberg, Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences

Today, figuring out who will benefit from which antidepressant medication is hit or miss—physicians prescribe a medication to treat major depression for two to three months, and then gauge the results. This trial and error is frustrating and expensive; typically only about 40% get well after this first treatment or see an improvement in symptoms. The other 60% must try a different drug or some other approach. In a new NIH funded study, researchers showed how brain scans could predict which individuals would benefit from a medication and which might respond better to psychotherapy [1].

Genome Exhibit Opens at Smithsonian

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Photo of one of the interacive touch screen exhibits

Credit: Sasan Azami-Soheily, National Human Genome Research Institute, NIH

To celebrate the 10th anniversary of the completion of the Human Genome Project—a 13-year endeavor that I had the privilege of leading—the Smithsonian’s National Museum of Natural History in Washington, DC is launching an absolutely fantastic exhibit called “Genome: Unlocking Life’s Code.”

DNA’s Double Anniversary

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Images of the first publication of DNA's structure adjacent to the image on the cover of the published human genome

April 25 is a very special day. In 2003, Congress declared April 25th DNA Day to mark the date that James Watson and Francis Crick published their seminal one-page paper in Nature [1] describing the helical structure of DNA. That was 60 years ago. In that single page, they revealed how organisms elegantly store biological information and pass it from generation to generation; they discovered the molecular basis of evolution; and they effectively launched the era of modern biology.

But that’s not all that’s special about this date. It was ten years ago this month that we celebrated the completion of all of the original goals of the Human Genome Project (HGP), which produced a reference sequence of the 3 billion DNA letters that make up the instruction book for building and maintaining a human being. The $3 billion, 13-year project involved more than 2,000 scientists from six countries. As the scientist tasked with leading that effort, I remain immensely proud of the team. They worked tirelessly and creatively to do something once thought impossible, never worrying about who got the credit, and giving all of the data away immediately so that anyone who had a good idea about how to use it for human benefit could proceed immediately. Biology will never be the same. Medical research will never be the same.

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