Efficacy of Robotic Bronchoscopy for Molecular Marker Analysis in Primary Lung Cancer.

Clin Lung Cancer

Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN; Department of Surgery, Division of Thoracic Surgery, Mayo Clinic, Rochester, MN. Electronic address:

Published: January 2024

Background: Molecular testing has become a more frequent necessity in NSCLC management. Using next-generation sequencing, multiple targets for therapy can be identified with small amounts of nuclear material. The authors evaluated the performance of robotic-assisted bronchoscopy in acquiring tissue that meets pre-analytic criteria for PD-L1 immunohistochemistry and/or next-generation sequencing.

Materials And Methods: Patients with a diagnosis of primary lung cancer identified through robotic bronchoscopy were retrospectively reviewed. Pathology reports were assessed for results of molecular testing and detection of programmed death-ligand 1 (PD-L1). An independent pathologist evaluated each specimen type (smears, cell block, tissue biopsy, and/or touch prep) to determine whether each tissue type would meet pre-analytic criteria for attempting next-generation sequencing and/or PD-L1 immunohistochemistry.

Results: Seventy-eight patients with primary lung were reviewed. By independent pathologic assessment of cytological smears, cell block, biopsy, and/or touch preparations, 72% of samples were found to be adequate for molecular and PD-L1 testing. Preanalytic adequacy (%) for next-generation sequencing (NGS) and PD-L1 staining was determined based on specimen type: cytological smear 48.6% for NGS; cell block 14.3% for NGS and 32.9% for PD-L1; biopsy 29.2% for NGS and 62.5% for PD-L1; and touch prep 61.4% for NGS.

Conclusion: Robotic-assisted bronchoscopy yielded samples that met preanalytic criteria for molecular testing in 72% of cases. These results support the use of robotic-assisted bronchoscopy for both the diagnosis and molecular testing of early-stage lung cancer.

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http://dx.doi.org/10.1016/j.cllc.2023.10.003DOI Listing

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