Abstract
The distinction between different separate primary lung cancers (SPLCs) and intrapulmonary metastases (IPMs) is a challenging but clinically significant issue. Histopathology-based classification is the current practice; however, it is subjective and affected by interobserver variability. Recently, next-generation sequencing (NGS) panels have been used in lung cancer diagnostics. This study aimed to investigate the value of large-scale NGS panels for distinguishing between SPLCs and IPMs. A total of 32 patients with 69 lung adenocarcinomas were included. Comprehensive histopathologic assessments of multiple pulmonary adenocarcinomas were performed independently by 3 pathologists. The consensus of histopathologic classification was determined by a majority vote. Genomic analysis was performed using an amplicon-based large-scale NGS panel, targeting single-nucleotide variants and short insertions and deletions in 409 genes. Tumor pairs were classified as SPLCs or IPMs according to a predefined molecular classification algorithm. Using NGS and our molecular classification algorithm, 97.6% of the tumor pairs can be unambiguously classified as SPLCs or IPMs. The molecular classification was predictive of postoperative clinical outcomes in terms of overall survival (P = .015) and recurrence-free interval (P = .0012). There was a moderate interobserver agreement regarding histopathologic classification (κ = 0.524 at the tumor pair level). The concordance between histopathologic and molecular classification was 100% in cases where pathologists reached a complete agreement but only 53.3% where they did not. This study showed that large-scale NGS panels are a powerful modality that can help distinguish SPLCs from IPMs in patients with multiple lung adenocarcinomas and objectively provide accurate risk stratification.
Original language | English |
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Pages (from-to) | 100047 |
Journal | Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc |
Volume | 36 |
Issue number | 3 |
DOIs | |
Publication status | E-pub ahead of print - Jan 2023 |