Comprehensive characterization reveals sputum supernatant as a valuable alternative liquid biopsy for genome profiling in advanced non-small cell lung cancer

Respiratory Research(2022)

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摘要
Background Sputum biopsies offer unique advantages such as non-invasiveness and convenient collection. The one investigation so far on sputum for genome profiling in advanced non-small cell lung cancer (aNSCLC) suggested promising performance. However, it remains undefined whether clinicohistologic characteristics were associated with performance and how this knowledge could help guide choice of liquid biopsy. Methods Targeted sequencing with a 520-gene panel was performed on prospectively collected matched tumor tissue (TIS), plasma (PLA), and sputum supernatant (SPU) from 71 aNSCLC patients (NCT05034445). Genomic alteration detection was characterized in a series of aspects and interrogated for association with 14 clinicohistologic features. Nomograms were constructed with logistic regression for predicting the liquid biopsy type with greater sensitivity. Results Compared with PLA, SPU showed comparable quality control metrics, mutation detection rate (SPU: 67.6%, PLA: 70.4%), concordance with tumor tissue (67.6% vs. 73.2%), and correlation with tissue-based tumor mutation burden levels ( r = 0.92 vs. 0.94). For driver alterations, detection was less sensitive with SPU (50.0%) than PLA (63.5%) in the entire cohort but similarly or more sensitive in patients with centrally located lung tumors or smoking history or for altered ALK or KRAS . Two nomograms were constructed and enabled predicting the probability of superior sensitivity with SPU with moderate to borderline high accuracy. Conclusion In addition to demonstrating comparable performance in multiple aspects, this study is the first to propose nomograms for choosing liquid biopsy based on clinicohistologic characteristics. Future research is warranted to delineate the clinical utility of sputum for genome profiling.
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关键词
NSCLC, Liquid biopsy, Sputum supernatant, Driver alterations, Genomic profiling, Next-generation sequencing
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