AUTHOR=Pei Guotian , Li Mingwei , Min Xianjun , Liu Qiang , Li Dasheng , Yang Yingshun , Wang Shuai , Wang Xiaoyu , Wang Huina , Cheng Huanqing , Cao Shanbo , Huang Yuqing TITLE=Molecular Identification and Genetic Characterization of Early-Stage Multiple Primary Lung Cancer by Large-Panel Next-Generation Sequencing Analysis JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.653988 DOI=10.3389/fonc.2021.653988 ISSN=2234-943X ABSTRACT=Objective

The incidence of early stage multiple primary lung cancer (MPLC) has been increasing in recent years, while the ideal strategy for its diagnosis and treatment remains controversial. The present study conducted genomic analysis to identify a new molecular classification method for accurately predicting the diagnosis and therapy for patients with early stage MPLC.

Methods

A total of 240 tissue samples from 203 patients with multiple-non-small-cell lung cancers (NSCLCs) (n = 30), early stage single-NSCLC (Group A, n = 94), and advanced-stage NSCLC (Group B, n = 79) were subjected to targeted multigene panel sequencing.

Results

Thirty patients for whom next-generation sequencing was performed on >1 tumor were identified, yielding 45 tumor pairs. The frequencies of EGFR, TP53, RBM10, ERBB2, and CDKN2A mutations exhibited significant differences between early and advanced-stage NSCLCs. The prevalence of the EGFR L858R mutation in early stage NSCLC was remarkably higher than that in advanced-stage NSCLC (P = 0.047). The molecular method classified tumor pairs into 26 definite MPLC tumors and four intrapulmonary metastasis (IM) tumors. A high rate of discordance in driver genetic alterations was found in the different tumor lesions of MPLC patients. The prospective Martini histologic prediction of MPLC was discordant with the molecular method for three patients (16.7%), particularly in the prediction of IM (91.7% discordant).

Conclusions

Comprehensive molecular evaluation allows the unambiguous delineation of clonal relationships among tumors. In comparison, the Martini and Melamed criteria have notable limitations in the recognition of IM. Our results support the adoption of a large panel to supplement histology for strongly discriminating NSCLC clonal relationships in clinical practice.