A multicenter real-world study of tumor-derived DNA from pleural effusion supernatant in genomic profiling of advanced lung cancer.

Abstract

BackgroundPleural effusion (PE) is commonly observed in advanced lung cancer. Research has suggested that molecular profiling of PE could be used to detect tumor driver mutations, thus informing clinical decision-making. However, the performance of PE samples in a real-world setting has yet to be examined.MethodsA total of 678 metastatic lung cancer patients with pleural effusion were enrolled in this study. Cohort 1 included 22 patients whose PE and matched plasma samples were simultaneously collected as a pilot study. Cohort 2 comprised 656 patients, from whom 734 samples were collected in a real world setting. These samples were subjected to targeted next-generation sequencing (NGS) of 1,021 cancer-related genes.ResultsPE supernatant was the preferred choice for genetic profiling. While the maximal somatic allele frequency (MSAF) of plasma in patients with M1a stage was significantly lower than that in patients with M1b/c stages (4.4%±9.6% vs. 9.0%±14.1%, P<0.01), the MSAF of PE supernatant was similar between M1a and M1b/c stages. PE supernatant demonstrated higher sensitivity than plasma in detecting actionable mutations in cohort 1 (81.8% vs. 45.5%, P=0.01) as well as in M1a disease (84.7% vs. 42.1%, P<0.01), but not in M1b/c disease, in cohort 2. Known resistant mutations were identified in 72 of the 117 patients who were resistant to first- or second-generation EGFR-TKIs, 22 of the 42 patients who were resistant to osimertinib, and 9 of the 13 patients who were resistant to crizotinib. Remarkably, PE supernatant outperformed plasma in identifying mutations that confer resistance to first- and second-generation EGFR-TKIs (75.4% vs. 29.8%, P<0.001).ConclusionsThis real-world large cohort study verified that PE supernatant had higher sensitivity than plasma for identifying actionable mutations, including resistance mutations. PE supernatant would be preferred by physicians for assessing tumor genomics in advanced lung cancer when tumor tissue is not available.