Does histological assessment accurately distinguish separate primary lung adenocarcinomas from intrapulmonary metastases? A study of paired resected lung nodules in 32 patients using a routine next-generation sequencing panel for driver mutations

Using molecular characteristics to distinguish multiple primary lung cancers and intrapulmonary metastases

Objectives

Multiple lung cancers may present as multiple primary lung cancers (MPLC) or intrapulmonary metastasis (IPM) with variations in clinical stage, treatment, and prognosis. However, the existing differentiation criteria based on histology do not fully meet the clinical needs. Next-generation sequencing (NGS) may play an important role in assisting the identification of different pathologies. Here, we extended the relevant data by combining histology and NGS to develop detailed identification criteria for MPLC and IPM.

Materials and Methods

Patients with lung cancer (each patient had ≥2 tumors) were enrolled in the training (n = 22) and validation (n = 13) cohorts. Genomic profiles obtained from 450-gene-targeted NGS were analyzed, and the new criteria were developed based on our findings and pre-existing Martini & Melamed criteria and molecular benchmarks.

Results

The analysis of the training cohort indicated that patients identified with MPLC had no (or <2) trunk or shared mutations. However, 98.02% of mutations were branch mutations, and 69.23% of MPLC had no common mutations. In contrast, a higher percentage of trunk (33.08%) or shared (9.02%) mutations were identified in IPM, suggesting significant differences among mutated components. Subsequently, eight MPLC and five IPM cases were identified in the validation cohort, aligning with the independent imaging and pathologic distinction. Overall, the percentage of trunk and shared mutations was higher in patients with IPM than in patients with MPLC. Based on these results and the establishment of new determination criteria for MPLC and IPM, we emphasize that the type and number of shared variants based on histologic consistency assist in identification.

Conclusion

Determining genetic alterations may be an effective method for differentiating MPLC and IPM, and NGS can be used as a valuable assisting tool.

Towards the molecular era of discriminating multiple lung cancers

In the era of histopathology-based diagnosis, the discrimination between multiple lung cancers (MLCs) poses significant uncertainties and has thus become a clinical dilemma. However, recent significant advances and increased application of molecular technologies in clonal relatedness assessment have led to more precision in distinguishing between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). This review summarizes recent advances in the molecular identification of MLCs and compares various methods based on somatic mutations, chromosome alterations, microRNAs, and tumor microenvironment markers. The paper also discusses current challenges at the forefront of genomics-based discrimination, including the selection of detection technology, application of next-generation sequencing, and intratumoral heterogeneity (ITH). In summary, this paper highlights an entrance into the primary stage of molecule-based diagnostics.

Integrating NGS-derived mutational profiling in the diagnosis of multiple lung adenocarcinomas

MICROABSTRACT

Integration of Next Generation Sequencing (NGS) information for use in distinguishing between Multiple Primary Lung Cancer and intrapulmonary metastasis was evaluated. We used a probabilistic model, comprehensive histologic assessment and NGS to classify patients. Integrating NGS data confirmed initial diagnosis (n = 41), revised the diagnosis (n = 12), while resulted in non-informative data (n = 8). Accuracy of diagnosis can be significantly improved with integration of NGS data.

BACKGROUND

Distinguishing between multiple primary lung cancers (MPLC) and intrapulmonary metastases (IPM) is challenging. The goal of this study was to evaluate how Next Generation Sequencing (NGS) information may be integrated in the diagnostic strategy.

PATIENTS AND METHODS

Patients with multiple lung adenocarcinomas were classified using both the comprehensive histologic assessment and NGS. We computed the joint probability of each pair having independent mutations by chance (thus being classified as MPLC). These probabilities were computed using the marginal mutation rates of each mutation, and the known negative dependencies between driver genes and different gene loci. With these NGS-driven data, cases were re-classified as MPLC or IPM.

RESULTS

We analyzed 61 patients with a total of 131 tumors. The most frequent mutation was KRAS (57.3%) which occured at a rate higher than expected (p < 0.001) in lung cancer. No mutation was detected in 25/131 tumors (19.1%). Discordant molecular findings between tumor sites were found in 46 patients (75.4%); 11 patients (18.0%) had concordant molecular findings, and 4 patients (6.6%) had concordant molecular findings at 2 of the 3 sites. After integration of the NGS data, the initial diagnosis was confirmed for 41 patients (67.2%), the diagnosis was revised for 12 patients (19.7%) or was considered as non-informative for 8 patients (13.1%).

CONCLUSION

Integrating the information of NGS data may significantly improve accuracy of diagnosis and staging.