Abstract
Tumor mutation burden offers a promising predictive biomarker for patients with small cell lung cancer. An exploratory analysis presented at the World Conference on Lung Cancer showed that the patients with large numbers of mutations in their cancer cells were more likely to respond—and for a longer time—to a single checkpoint inhibitor or a combination of them than those with a low mutation load.
The quest to find a predictive biomarker for small cell lung cancer (SCLC) now has a leading candidate.
Researchers presented an exploratory analysis last month at the International Association for the Study of Lung Cancer's 18th World Conference on Lung Cancer in Yokohama, Japan. They reported that patients with previously treated SCLC who had a high tumor mutation burden (TMB) had better response rates and longer survival following treatment with the PD-1–targeted agent nivolumab (Opdivo; Bristol-Myers Squibb), either alone or in combination with the anti-CTLA4 drug ipilimumab (Yervoy; Bristol-Myers Squibb), compared with patients whose tumors had a medium or low TMB.
“This is an important step forward for identifying patients who can profoundly benefit from immunotherapy,” says trial investigator Matt Hellmann, MD, of Memorial Sloan Kettering Cancer Center in New York, NY, who previously presented overall efficacy data (J Clin Oncol 2017;35 Suppl 15:8503). “It justifies and encourages molecular testing in small cell lung cancer.”
In the phase I/II CheckMate 032 trial, which included an expansion cohort of patients with advanced SCLC, individuals with a high TMB in their lung tumors had an objective response rate that was about twice as high as the SCLC population average—21% versus 11% for nivolumab monotherapy, and 46% versus 22% for the combination. In addition, 62% of patients with high TMB were still alive a year after receiving the combination therapy, compared with 20% to 23% among those with low or medium TMB given the same two-drug regimen.
The biomarker was measured by whole-exome analysis in cancer cells and defined as the total number of missense mutations in the genome. Tumors with higher mutation loads are believed to express more neoantigens, which could explain why they're more susceptible to immunotherapy.
According to Hellman, the study is the first to demonstrate the value of TMB in SCLC, and the first to evaluate the ability of this biomarker to predict the efficacy of combination immunotherapy in any tumor type.
“The data are very exciting and may one day help us best decide who needs immunotherapy alone, immunotherapy and chemotherapy, or chemotherapy alone,” says David Spigel, MD, of the Sarah Cannon Research Institute in Nashville, TN. However, TMB is unlikely to inform current clinical practice for second-line SCLC treatment, he says, because, even in those with low mutation burden, response rates are generally higher with the checkpoint inhibitor combination than with standard topotecan chemotherapy.
“It's a tough one when you're dealing with a cancer for which you don't have many other good options,” says Spigel, who worked on CheckMate 032 but not the exploratory biomarker analysis.
Because there are better therapeutic options for non–small cell lung cancer (NSCLC), TMB could point to the optimal treatment for particular patients. As reported in June, the CheckMate 026 trial showed that a high TMB was associated with longer progression-free survival among patients with NSCLC receiving first-line nivolumab instead of platinum-based chemotherapy, whereas the reverse was true for those with low/medium TMB (N Engl J Med 2017;376:2415–26). That study also showed that PD-L1 levels provided an independent biomarker of response. In contrast, PD-L1 expression is generally uncommon in SCLC and thus not predictive of tumor response.
The CheckMate 026 analysis was retrospective, however, and whether those two biomarkers can help inform routine decision-making in NSCLC remains a matter of active investigation. “We're still waiting on well-designed prospective studies to sort this out,” Spigel says. –Elie Dolgin
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