In addition, the patterns of mutations found in lung squamous cell carcinoma more closely resemble those seen in squamous cell carcinomas of the head and neck than those in other lung cancers. That finding adds further weight to the idea that classifying tumours by their molecular profiles, rather than their sites of origin, will be more effective in picking the right drugs to treat them. Perhaps, for instance, a drug approved for treating breast cancer could be tried in a lung cancer if both carry similar mutations.
And mutations implicated in other cancers did show up in the lung cancers. Overall, these studies reveal lung cancer as an extremely varied disease, says Roy Herbst, chief of medical oncology at the Yale Cancer Center in New Haven, Connecticut. “What amazes me is the heterogeneity,” he says. He foresees the rise of an era of “focused sequencing” over the next year or so, in which clinicians could profile 400 or 500 genes to help guide the course of therapy. Profiling all the genes or all of a patient's genome would provide more data than oncologists could use. But to do this well, he says, mutations need to be linked with more information, such as when and where metastases occurred and how effective the drugs were. Meyerson agrees. “The data that are really going to be informative is when you combine genomic data with outcomes of targeted therapies,” he says.
But lung cancer will still be tough to beat, he warns. For example, tumours usually become resistant to targeted therapies, and picking the best drug to try next would probably require a second genomic analysis.