Sunday, 22 April 2012

How Predictive are Genomes?

Researchers put the predictive power of whole genome sequencing to the test.

By Cristina Luiggi.

Although the price of genome sequencing is rapidly becoming more affordable to the general population, to what extent these tests will impact a person’s lifestyle and medical treatment choices remains unclear. By analyzing life-long data collected from thousands of twins, researchers led by renowned Johns Hopkins oncologist Bert Vogelstein tested how well whole genome sequencing could predict an individual’s risk of developing 24 common diseases. Their analysis, published today (April 2) in Science Translational Medicine, showed that most people are likely to get negative results for the majority of the diseases studied, thus failing to provide any actionable information. For example, while sequencing tests are effective at predicting cancer risks in people with hereditary cancers, they are not as informative for people who lack a family history of the disease. “In families with strong histories of cancer, whole genome sequencing can still be very informative for identifying inherited genes that increase cancer risk,” Victor Velculescu, a professor of oncology at Johns Hopkins, said in a press release. “But hereditary cancers are rare. Most cancers arise from mutations acquired through environmental exposures, lifestyle choices, and random mistakes in genes that occur when cells divide.” The results suggest that genome sequencing is not likely to displace other preventive measures any time soon. “We need other strategies,” Vogelstein said today at the American Association for Cancer Research (AACR) annual meeting in Chicago. “My favorite is early detection.”

Wednesday, 28 March 2012

Finding a Good Research Question, in Theory

Nicolai Bodemer & Azzurra Ruggeri

Newton needed an apple, Franklin a flash, Galileo a telescope, and Archimedes a crown. What do these people have in common? They observed a phenomenon that they could not explain, devoted their lives to investigating it, and in doing so achieved groundbreaking discoveries. From observations to hypotheses, from experiments to potential explanations, they conducted every part of the research required to answer the question they had chosen.

Nowadays, rarely—if ever—can a single scientist start at the beginning of the research process and follow it through all the way to its conclusion. Rather than a marathon, research today resembles a relay race: We focus on a small part of a larger question and then pass the baton to the next scientist. In a system where most advances are incremental, many scientists struggle to pursue original research questions. We identifi ed and evaluated several methods that scientists use to select the subject of their research.

Some scientists approach the task by picking a theory and reading all the papers within its theoretical framework in search of a question not yet asked. However, the mere fact that some aspect has not been explored yet does not necessarily make it interesting. Others create a problem they think they can solve by applying one of the solutions their theories or methodologies have already provided to them. This may be an engaging intellectual exercise, but it usually leads to sterile research questions, unlinked to the real world. These question generation strategies lead to smart and creative solutions to problems that do not exist—a phenomenon called Type III error: fi nding the right answer to the wrong question. It seems to us that too much research is based on these approaches, especially in behavioral economics and behavioral sciences.

There is another way to generate a research question: Go back to the basics. Observe the world, and when you encounter a phenomenon that intrigues you, investigate it. Theories should not be the only source of research questions or the benchmark against which we defi ne what is right and wrong. Shall we abandon a research question when there is no theory from which we could derive our hypotheses? Should we feel compelled to conform our own results only to the mainstream theoretical framework to be accepted in the fi eld? Should we be more concerned about the theory than about the actual problem under investigation? Research runs the risk of growing too dependent on theories, neglecting real-world problems as a result and constraining perspectives and methodologies. If Newton had been preoccupied with established theories, he might have been too busy in his offi ce to realize how surprisingly interesting an apple falling from a tree could be.

Monday, 16 January 2012

Unraveling the Obesity-Cancer Connection

Gary Taubes from Science

Growing breast cancer cells in the lab has been a revelation to Vuk Stambolic. The protocol he follows is decades old and widely used, but there’s a puzzle at its core. The recipe calls for a large dose of glucose, a growth factor called EGF, and insulin. Add these to tissue culture, and tumor cells will be fruitful and multiply. A curious thing happens if you try to wean the tumor cells off insulin, however: They “drop off and they die,” says Stambolic, a cancer researcher at the University of Toronto in Canada. “They’re addicted to [insulin].”

What makes this so “bizarre,” Stambolic says, is that this behavior is totally unlike that of the healthy breast cells from which these tumor cells are derived. Normal cells are not sensitive to insulin - or at least not nearly to the same degree. They don’t have insulin receptors, and they lack key elements of the insulin signaling pathway necessary to make insulin outside the cell immediately relevant to what goes on inside. Indeed, normal cells thrive without insulin. By contrast, the tumor cells in culture can’t live without it.

Insulin, a hormone produced in the pancreas, is more commonly known for its role in diabetes. But its reputation may be changing. Insulin and a related hormone known as insulin-like growth factor (IGF) are now at the center of a growing wave of research around the world aimed at elucidating what many scientists consider to be their critical role in fueling a wide range of cancers. Elevated levels of insulin and IGF are also the leading candidates to explain a signifi cant correlation in epidemiology that has gained attention over the past 30 years: Obese and diabetic individuals have a far higher risk than lean healthy people of getting cancer, and when they do get it, their risk of dying from it is greater. And now that obesity and diabetes rates are skyrocketing, the need to understand this link has become far more urgent.

The correlation between obesity and cancer can be found in the medical literature going back for several decades. But it wasn’t until 2004 that two cancer epidemiologists put it all together, says Robert Weinberg, a cancer researcher at the Massachusetts Institute of Technology (MIT) in Cambridge. An article that year in Nature Reviews Cancer by Rudolf Kaaks, then of the International Agency for Research on Cancer, and the late Eugenia Calle of the American Cancer Society “laid down a challenge to the rest of us … to determine why obesity is such an important determinant of cancer risk,” Weinberg says.

The message of this research is straightforward, Kaaks says: Excess body fat seems to account for between one-quarter and one-half of the occurrence of many frequent cancer types—breast, colorectal, endometrial, renal cell, and adenocarcinoma in the esophagus, in particular. Kaaks adds, “The list is growing.”

“The magnitude of the effect is huge,” in large part because obesity and diabetes are now so common, says Michael Pollak, an oncologist at McGill University in Montreal, Canada. It seems that cancer “loves the metabolic environment of the obese person,” Pollak says. Epidemiologic studies have also found that not only is type 2 diabetes associated with increased cancer incidence and mortality but so are circulating levels of insulin and IGF.

Recent drug studies have sharpened the picture: Type 2 diabetics who get insulin therapy or drugs to stimulate insulin secretion have a significantly higher incidence of cancer than those who get metformin, a drug that works to lower insulin levels. There’s a large and growing body of evidence implicating insulin and IGF in cancer, Pollak says, “and it’s causing a lot of people to stay up at night thinking about it.”

Ravenous for Glucose
The focus on obesity, cancer, and hormones has kindled a wide interest in the metabolism of cancer cells and particularly in work done in the 1920s by the German biochemist and later Nobel laureate Otto Warburg. Warburg observed that tumor cells can survive without oxygen and generate energy by a relatively ineffi cient process known as aerobic glycolysis. This conversion of cancer cell metabolism to aerobic glycolysis has been known as the Warburg effect ever since. It is akin to how bacteria generate energy in the absence of oxygen, although cancer cells do it even when oxygen is present (hence “aerobic”). Rather than converting glucose to pyruvate and burning that with oxygen in the cells’ mitochondria, the pyruvate is converted to lactate in the cells’ cytoplasm outside the mitochondria, and no oxygen is used. The process yields only one-ninth the energy, four ATP molecules instead of 36, from each molecule of glucose. One result is that cancer cells have to burn enormous amounts of glucose to thrive and multiply.


That insulin and IGF may be the relevant “something else” that fuels cancer is a relatively new idea. But the evidence has been accumulating for decades. In the mid-1960s, researchers demonstrated that insulin acts as a promoter of growth and proliferation in both healthy and malignant tissues. By the late 1970s, C. Kent Osborne, then at the National Cancer Institute, and his colleagues reported that a line of particularly aggressive breast cancer cells were “exquisitely sensitive to insulin” and that breast cancer cells express insulin receptors, even though the cells from which the tumors derive do not.