Feasibility of shape-sensing robotic-assisted bronchoscopy for biomarker identification in patients with thoracic malignancies

Objective: Molecular diagnostic assays require samples with high nucleic acid con-tent to generate reliable data. Similarly, programmed death-ligand 1 (PD-L1) immu-nohistochemistry (IHC) requires samples with adequate tumor content. We investigated whether shape-sensing robotic-assisted bronchoscopy (ssRAB) pro-vides adequate samples for molecular and predictive testing. Methods: We retrospectively identified diagnostic samples from a prospectively collected database. Pathologic reports were reviewed to assess adequacy of sam-ples for molecular testing and feasibility of PD-L1 IHC. Tumor cellularity was quan-tified by an independent pathologist using paraffin-embedded sections. Univariable and multivariable linear regression models were constructed to assess associations between lesion-and procedure-related variables and tumor cellularity. Results: In total, 128 samples were analyzed: 104 primary lung cancers and 24 met-astatic lesions. On initial pathologic assessment, ssRAB samples were deemed to be adequate for molecular testing in 84% of cases; on independent review of cellular blocks, median tumor cellularity was 60% (interquartile range, 25%-80%). Hybrid capture-based next-generation sequencing was successful for 25 of 26 samples (96%), polymerase chain reaction-based molecular testing (Idylla; Biocartis) was successful for 49 of 52 samples (94%), and PD-L1 IHC was successful for 61 of 67 samples (91%). Carcinoid and small cell carcinoma histologic subtype and ade-quacy on rapid on-site evaluation were associated with higher tumor cellularity. Conclusions: The ssRAB platform provided adequate tissue for next-generation sequencing, polymerase chain reaction-based molecular testing, and PD-L1 IHC in >80% of cases. Tumor histology and adequacy on intraoperative cytologic assess-ment might be associated with sample quality and suitability for downstream assays. (J Thorac Cardiovasc Surg 2023;166:231-40)