Caption: A decoy protein that mimics the CD4 receptor (red), the CCR5 receptor (green), and a natural antibody (grey), binds to the HIV envelope protein (three white blobs) and blocks it from infecting immune cells.
Credit: Michael Farzan
Over more than a century, researchers have succeeded in developing vaccines to prevent polio, smallpox, cervical cancer, and many other viral diseases. For three decades now, they have tried to design an effective vaccine for the human immunodeficiency virus (HIV) that causes AIDS. Despite plenty of hard work, lots of great science, and some promising advances along the way, an effective traditional vaccine still remains elusive. That has encouraged consideration of alternative approaches to block HIV infection.
Now in the journal Nature , an NIH-funded team reports promising early results with one of these interesting alternatives. The team hypothesized that producing a protein that binds to HIV and prevents it from entering cells might provide protection. So they designed such a protein, and, using an animal model, introduced multiple copies of a gene that makes this protein. In a small study of non-human primates, this gene-therapy approach blocked HIV infection, even when the animals were exposed repeatedly to large doses of the virus.
Today, we hear a great deal about which foods to eat and which to avoid to maintain a healthy body. Though we know that one of the strongest contributors to body weight is heredity, there has been less specific information available about the genetics underlying obesity. But research in this area is progressing at a phenomenal pace, and new genomic discoveries are helping to bring into better focus how our bodies store fat and how the complex interplay of genetics, diet, behavior, and other factors determine whether we can readily maintain a healthy body weight, or whether it takes a lot of work to do so.
Two papers in Nature provide lots of fresh clues into the genetic factors involved in predisposing to obesity. Researchers in the international Genetic Investigation of ANthropometric Traits (GIANT) Consortium, more than 500 strong and including some of the members of my own NIH research lab (including me), examined the genomes of more than half a million people to look for genes and regions of chromosomes that play a role in body fat distribution and obesity. They turned up over 140 genetic locations that, like low-intensity voices in a choir of many, contribute to these traits. Further analyses of the specific genes located in these regions suggest the possibility that the programming behind how fat cells form may influence their distribution, a discovery that could lead to exploitable findings down the road.
Caption: The location and abundance of six proteins—e-cadherin (green), vimentin (blue), actin (red), estrogen receptor, progesterone receptor, and Ki67—found in breast cancer cells are seen in this multiplexed ion beam image. Cells positive for estrogen receptor a, progesterone receptor, and Ki-67 appear yellow; cells expressing estrogen receptor a and the progesterone receptor appear aqua.
Credit: Michael Angelo
The artistic masterpiece above, reminiscent of a stained glass window, is the work of Michael Angelo—no, not the famous 16th Century Italian artist, but a 21st Century physician-scientist who’s out to develop a better way of looking at what’s going on inside solid tumors. Called multiplexed ion beam imaging (MIBI), Angelo’s experimental method may someday give clinicians the power to analyze up to 100 different proteins in a single tumor sample.
In this image, Angelo used MIBI to analyze a human breast tumor sample for nine proteins simultaneously—each protein stained with an antibody tagged with a metal reporter. Six of the nine proteins are illustrated here. The subpopulation of cells that are positive for three proteins often used to guide breast cancer treatment (estrogen receptor a, progesterone receptor, Ki-67) have yellow nuclei, while aqua marks the nuclei of another group of cells that’s positive for only two of the proteins (estrogen receptor a, progesterone receptor). In the membrane and cytoplasmic regions of the cell, red indicates actin, blue indicates vimentin, which is a protein associated with highly aggressive tumors, and the green is E-cadherin, which is expressed at lower levels in rapidly growing tumors than in less aggressive ones. Taken together, such “multi-dimensional” information on the types and amounts of proteins in a patient’s tumor sample may give oncologists a clearer idea of how quickly that tumor is growing and which types of treatments may work best for that particular patient. It also shows dramatically how much heterogeneity is present in a group of breast cancer cells that would have appeared identical by less sophisticated methods.
Caption: Triple immunohistochemical stained oral squamous cell carcinoma: nuclei in brown, cytoplasm in red, and cytoplasmic membranes in blue green.
Credit: Alfredo A. Molinolo, Oral and Pharyngeal Cancer Branch, National Institute of Dental and Craniofacial Research, NIH
An exciting new era in cancer research is emerging, called precision oncology. It builds on decades of research establishing that cancers start with glitches in the genome, the cell’s instruction book. Researchers have now identified numerous ways that mutations in susceptible genes can drive the cancer process. Knowing where and how to look for them brings greater precision to diagnosing cancers and gives doctors key clues about which treatments might work and which ones won’t.
To build a firmer evidence base for precision oncology, more and more cancer genomes, from many different body sites, must be analyzed for clues about the drivers of the malignant process. That’s why it’s always exciting to see a new genomic analysis that adds substantially to our understanding of a common tumor. The latest to appear, published online at the journal Nature, comes from an NIH-supported study on the most common type of head and neck cancer, called squamous cell carcinoma. The technologically advanced analysis confirms that many previously suspected genes do indeed play a role in head and neck cancer. But that’s not all. The new data also identify several previously unknown subtypes of this cancer. The first descriptions of the abnormal molecular wiring in these subtypes are outlined, suggesting possible strategies to neutralize or destroy the cancer cells. That’s potentially good news to help guide and inform the treatment of the estimated 55,000 Americans who are diagnosed with a head and neck cancer each year.
Caption: When the biopsy is completed, a 3D data map is generated. In this actual example, what is shown is the contour of the prostate (red), location of the tumor (green), the location of the standard random prostate biopsies (white cores), and the location of the targeted fusion biopsies (yellow cores).
Credit: Peter A. Pinto, National Cancer Institute, NIH
Many of you probably know that prostate cancer is the most frequently diagnosed cancer in American men. But here’s something that might surprise you: the way in which doctors biopsy for prostate cancer hasn’t changed significantly in nearly 30 years—even though about a million such biopsies are conducted every year in the United States.
Unlike breast cancer biopsies, which sample tissue from a suspicious area seen on a mammogram, prostate cancer biopsies still are generally performed as random, 12-point searches to see if any cancerous cells might be lurking somewhere in the prostate gland. While random biopsies have helped to save many lives, NIH-supported research has developed a targeted approach that brings much-needed efficiency to the diagnostic process—and appears to be better at detecting aggressive, high-risk prostate cancer than current methods.