Deciphering Breast Cancer
Breast cancer is one of the most common cancers, and one of the leading causes of death in women globally. Breast cancer is a disease where cells located in the breast grow out of control. Although a majority of breast cancers are discovered in women at the age of 50 years or older, the disease can affect anyone, including men and younger women, according to the Centers for Disease Control and Prevention (CDC). Last year there were 9.6 million deaths and 18.1 million new cases of breast cancer diagnosed globally according to the latest report from the International Agency for Research on Cancer (IARC) released in September 2018.
In 2019 alone, the U.S. National Cancer Institute estimates that there will be 268,600 new female breast cancer cases and 41,760 fatalities. Earlier this month, researchers based in Switzerland published in Cell their study in using applied artificial intelligence (AI) machine learning to create a comprehensive tumor and immune atlas of breast cancer ecosystems that lays the foundation for innovative precision medicine and immunotherapy.
The study was led by professor Bernd Bodenmiller, Ph.D. at the Institute of Molecular Life Sciences at the University of Zurich in Switzerland. Bodenmiller is a recipient of the 2019 Friedrich Miescher Award, Switzerland’s highest distinction for outstanding achievements in biochemistry. His team worked in collaboration with the Systems Biology Group at IBM Research in Zurich led by María Rodríguez Martínez, Ph.D. with the shared goal to produce a foundation for more targeted breast cancer treatment through precision medicine.