Method for Early Detection of Pancreatic Cancer

Nearly 50,000 Americans will be diagnosed with pancreatic cancer in 2015, according to NIH’s National Cancer Institute (NCI). Only 7% are expected to survive 5 years or longer because the disease is difficult to detect early enough for effective treatment.

The GPC1biomarker (black dots) on exosomes from 2 patients. Image by the researchers, courtesy of Nature.

One method of spotting cancer early is to find biomarkers—substances in the body that signal the presence of a disease. A team of scientists lead by Dr. Raghu Kalluri of the University of Texas MD Anderson Cancer Center searched for biomarkers on tiny, fluid-filled sacs called exosomes. Exosomes are released by cells and circulate in blood. The research, which was partially funded by NCI, was published in Nature on July 9, 2015.

The scientists compared exosomes from a human cancer cell line and several noncancerous cell lines. They tested a variety of biomarkers and found 48 that were unique to the cancer exosomes. One, called Glypican-1 or GPC1, was found at high levels in pancreatic and breast cancer cells.

The team next isolated exosomes in blood samples taken from healthy people and patients with breast cancer or pancreatic cancer. The researchers found that 75% of the patients with breast cancer (24 out of 32) and all of the 251 pancreatic cancer patients had higher levels of GPC1-containing exosomes in their blood compared to healthy controls. Patients with late-stage pancreatic cancer had more of these exosomes in their blood than patients with early-stage disease.

Patients with precancerous pancreatic lesions had more GPC1-positive exosomes in their blood than both healthy controls and patients with noncancer pancreatic illnesses like pancreatitis. In contrast, a commonly used pancreatic cancer biomarker called carbohydrate antigen 19-9 couldn’t distinguish people with precancerous lesions from healthy controls. This suggests that GPC1-positive exosomes may be a better biomarker than the current standard.

Finally, the group examined a mouse model of pancreatic cancer. GPC1-positive exosomes predicted cancer emergence before tumors could be detected with MRI or other techniques.

If confirmed, this research could lead to fast and accurate tests for detecting early-stage pancreatic cancer, which would allow for earlier treatment and raise the disease’s survival rate.

“This presents an unprecedented opportunity for informative early detection of pancreatic cancer and in designing potential curative surgical options,” Kalluri says.

—by Brandon Levy

Cardiovascular Research: Hip strengthening might ease pain of clogged leg arteries ♦ New cause discovered for arterial stiffness ♦ Computer for acute stroke detection

Hip strengthening might ease pain of clogged leg arteries Exercise to strengthen hip flexor muscles may increase how far some patients can walk without calf pain. Gait analysis reveals that people with clogged leg arteries use calf muscles to compensate for weakness of certain hip muscles

Dexamethasone May Help Prevent Severe Kidney Injury Following Heart Surgery Acute kidney injury can be a serious complication following heart surgery. Patients who received dexamethasone during heart surgery had about a 2.5-times lower risk of developing kidney failure requiring dialysis compared with those receiving a placebo. The greatest benefits of dexamethasone were seen in patients with pre-existing advanced chronic kidney disease.

New cause discovered for arterial stiffness, a contributor to cardiovascular disease Previous studies of aortic stiffness have focused on changes in structural proteins that alter the properties of vascular walls causing them to become rigid. Now, researchers have determined that smooth muscle cells, which line the interior of vascular walls, are a major contributing factor to vascular stiffness, one of the major causes of hypertension.

Novel computer intelligence system for acute stroke detection Medical researchers have developed a novel computer-aided detection system for acute stroke using computer intelligence technology. The detection accuracy is 90%, which is as high as that conducted by specialists, but at a much reduced time from 10-15 minutes to 3 minutes.