Using big data to boost cancer research
In a study published in Nature Communications, researchers at the University of California at San Francisco describe how they used big data to pinpoint the methods by which eight different cancers invade normal tissues and spread in the body. The team took data from the Cancer Genome Atlas, analyzed which genes were turned on and off in tissues adjacent to the tumors, then used another large cancer database and several smaller ones to identify patterns of inflammation leading to metastasis. They identified 82 relevant genes, some of which could be therapeutic targets, they believe. (Release)
Defining a superbug
Pseudomonas aeruginosa, identified by the World Health Organization as posing a high-level threat to human health, is especially virulent because of its ability to secrete multiple toxins and enzymes that infect its host. Scientists at Monash University have identified a system the bug uses to secrete its most toxic substance, Exotoxin A—a “nanomachine” on its surface that pumps out the virulent culprit. They reconstructed a 3D image of the nanomachine, providing a blueprint that they believe could be used to design a drug to halt the bacterium’s ability to produce Exotoxin A. (Release)
New genetic discoveries shed light on breast cancer risk
The OncoArray Consortium, a collaboration of 550 researchers at 300 institutions, has identified 72 new genetic variants that predispose women to breast cancer. They include seven variants that raise the risk of the toughest form of the disease to treat, estrogen receptor-negative breast cancer. The researchers were able to identify genetic patterns underlying breast carcinogenesis that had not been suspected before and that may lead to better methods for predicting risk, both in women who carry known mutations (such as BRCA1) and those who don’t. The research was published in the journals Nature and Nature Genetics. (Release)