Abstract 1227P
Background
The incidence of early stage multiple primary lung cancer (MPLC) has been increasing recently, but the ideal methods for diagnosis and treatment strategies remains controversial. The present study conducted the genomic analysis to propose a molecular classification method and investigate the appropriate strategy for patients with early stage MPLC.
Methods
A total of 247 tissue samples from 203 patients with early stage MPLC (group A, n = 30), early stage single primary lesion (group B, n = 94), and advanced stage (group C, n = 79) non-small cell lung cancer were subjected to targeted multigene sequencing and immunohistochemistry staining for programmed death-ligand 1 (PD-L1).
Results
A total of 86 driver mutations were identified from 59 out of 67 (88.06%) lesions in group A. Mutations in EGFR were the most prevalent variation (62.69%), followed by those in TP53, KRAS, RBM10, BRAF and KMT2D. The frequency of EGFR, TP53, RBM10, ERBB2 and CDKN2A mutations was significantly difference in group A and group C. Additionally, exon 19 deletion (19 del) and L858R mutations comprised most in the EGFRvariants, and the prevalence of EGFR L858R mutation was remarkably higher than that of EGFR 19 del alteration only in group A (P = 0.048). Moreover, the molecular features of immunotherapy in group A and B were characterized by low PD-L1 expression level, low tumor mutation burden (TMB), microsatellite stability (MSS) and DNA mismatch repair proficiency (pMMR), indicating that the efficacy of immunotherapy may be poor in non-invasive and early invasive lung cancer. A high rate of discordance of genetic alterations was found in different lesions within individual tumors of MPLC patients. Furthermore, there is a high degree of consistency in identifying MPLC between our molecular method and the Martini method (93.33%).
Conclusions
Targeted multigene sequencing greatly contributes to the improvement of the diagnostic accuracy in patients with MPLC. The molecular signatures in early stage MPLC will be critical to guide personalized therapy in this population.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Beijing Haidian Hospital.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.