Make precision medicine work for cancer care

Mark A. Rubin in Nature:

Ten months ago, the physicians of a feisty 76-year-old sales clerk from New Jersey who had an advanced carcinoma in her urinary tract decided to try an unconventional therapy. A few weeks earlier, they had sent a sample of her tumour to my team at the Institute of Precision Medicine at Weill Cornell Medical College and NewYork-Presbyterian Hospital in New York City. Genetic sequencing had revealed that she had more copies than usual of the HER2 gene (also known as ERBB2). After years of failure with the usual arsenal of surgery, chemotherapy and radiation, the physicians included the drug Herceptin (trastuzumab) in the woman's treatment. Herceptin is more commonly used for breast cancer, but it targets the HER2 mutation. Since taking the drug, she has been free of disease.

Advances in sequencing have dramatically increased the likelihood of discovering mutations that drive tumour growth in certain people and in certain tumours — even in specific cells within tumours. Yet mountains of genomic data are accumulating that are of little use because they are not tied to clinical information, such as family medical history. What is more, genomic data are generally confined to documents that cannot easily be searched, shared or even understood by most physicians. To achieve the level of success in precision medicine for cancer care that US President Barack Obama and others are anticipating, sequence data needs to be linked, in real time, to the patient sitting in front of his or her doctor. Integrated genomic and clinical data will also need to be available, in a searchable way, to a broad community of practitioners and researchers. Prototypes for centralized data banks are showing promise, but serious and sustained investment is needed to scale them up. Clinicians are used to appraising 20–50 measurements from routine laboratory tests, such as for blood-sugar levels. Such data can be easily entered into patients' electronic health records. Genomic data introduces a whole new level of complexity. To give an idea of the scale, it would take more than 25 days to transfer from one computer server to another the 2.5 petabytes (a petabyte is 1,000 terabytes) of data generated by The Cancer Genome Atlas — a US project started in 2005 to catalogue the mutations that drive cancer. This is according to my colleague Toby Bloom, deputy director for informatics at the New York Genome Center, a consortium that specializes in large-scale human genome sequencing.

More here.