In the study, two-thirds of the patients were “reclassified” using genomic information, and the new staging system was associated with “improved overall model fit, enhanced identification of high-risk patients, and better differentiation of patients without vs patients with recurrence,” according to the study.
Although other experts acknowledged the growing importance of genomics to the field, they said more research is needed to justify changing current practices. “Here we have something that’s interesting but not definitive. And it’s nothing that would change my clinical practice,” said Roy Herbst, MD, PhD, chief of medical oncology at Yale Cancer Center in New Haven, Connecticut, and vice chair for developmental therapeutics for the Southwestern Oncology Group Lung Committee. “The current system is adequate now, but clearly just looking at x-rays won’t be enough to tell you if something is aggressive. It’s all about the genes and the engines in the tumor that are causing it to tick.”
Dr Herbst, who is also steering committee chair for the Lung Master Protocol trial that uses genetic screening to match patients to investigational new treatments for NSCLC, said the field needs a bigger study that’s randomized. “We don’t have enough data yet. We don’t know how we would use these molecular classifiers. This will require big data and a prospective approach,” he said. “Someday we will sequence all tumors and use that information more precisely.”
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Using molecular classifiers will eventually become a routine part of the staging process for all patients, but more studies are needed in the meantime, added Fred Hirsch, MD, PhD, executive director at the Center for Thoracic Oncology at the Tisch Cancer Institute at Mount Sinai Health System in New York, New York. He and his colleagues at the International Association for the Study of Lung Cancer (IASLC) are working on a large-scale study that he hopes will validate the JAMA Network Open’s findings. “We’re collecting tissue from thousands of patients from all over the world,” said Dr Hirsch, co-investigator for the IASLC’s international staging committee. “We’re hoping that by adding molecular characteristics to the conventional TNM system, it will improve staging and the ability to distinguish early-stage patients who have a good prognosis.”
Although it will take about 3 to 5 years to collect and analyze the data, he said that any resulting recommendation could be quickly implemented into clinical practice. That’s because many large cancer institutions are already developing a learning curve integrating genomics into the care of advanced cancer patients and are developing in-house labs. “This is clearly where the field is going,” added Dr Hirsch.
Such changes have been a long time coming, said Dr Kratz, whose UCSF team is now recruiting for a multi-institutional, randomized trial to look at whether giving high-risk patients chemotherapy following surgery reduces their risk of recurrence and improves their chances of survival. “Our work is just the latest evidence calling for a paradigm shift in personalized medicine,” he said, “It’s important because it gives people an actual mechanism and provides a framework for how this paradigm shift can happen and how we can gain a deeper understanding of what drives these tumors.”
Disclosure: Dr Kratz reported having a consulting relationship with, and receiving personal fees and nonfinancial support from, Razor Genomics Inc, the company that established a Clinical Laboratory Improvement Amendments–certified laboratory and developed the molecular assay based on University of California, San Francisco technology. He also disclosed being an inventor of related technology owned by the University of California, for which the University submitted patent applications that have been licensed to Razor Genomics Inc. Dr Kratz also reported the receipt of funds related to a patent for the Prognostic Assay For Early-Stage Lung Cancer.
Editor’s note: The title of this article was changed on 1/16/20 to more accurately reflect the genomic technology discussed.
Reference
Haro GJ, Sheu B, Cook NR, et al. Comparison of conventional TNM and novel TNMB staging systems for non–small cell lung cancer. JAMA Netw Open. 2019;2(12):e1917062.
