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

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Article Abstract

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 ( = 22) and validation ( = 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10838092PMC
http://dx.doi.org/10.7717/peerj.16808DOI Listing

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