Uncommon de novo EGFRT790M-Mutant NSCLC characterized with unique genetic Features: Clinical response and acquired resistance to the third-generation EGFR-TKIs treatment

INTRODUCTION

The literature on de novo EGFRT790M-mutant patients diagnosed with lung cancer is limited, and there is currently no consensus concerning the most effective treatment protocols. This study aimed to investigate the genomic characteristics of de novoEGFRT790M-mutant non-small cell lung cancer (NSCLC) and provide insights into its clinical response and resistance mechanism to third-generation EGFR-TKIs.

METHODS

Next-generation sequencing was utilized to screen a substantial cohort of 4,228 treatment-naïve patients from the Mygene genomic database to identifythe de novo EGFR-T790M mutation. Meanwhile, we recruited 83 individuals diagnosed with lung cancer who harbored de novo EGFRT790M mutation in the real world. In addition, 166 patients who acquired EGFR-T790M mutation after becoming resistant to first- or second-generation EGFR-TKIs were included as a comparison cohort.

RESULTS

De novo EGFRT790M mutation identified by next-generation sequencing is rare (∼1.3 %) in Chinese lung cancer patients. The relative variant allele frequency (VAF) of de novo EGFRT790M mutation was either comparable to or significantly lower than those of EGFR-activating mutations. Patients with de novo-T790M mutations exhibited less favorable clinical outcomes when administered third-generation EGFR-TKIs as first-line therapy thanthose with 19del mutationsdue to a high overlap rate in EGFR p.L858R mutation. In patients with a de novo EGFRT790M mutation, no correlation was observed between T790M clonality and treatment outcomes with third-generation EGFR-TKIs. In contrast, the sub-clonality of the T790M mutation detrimentally affected the third-generation EGFR-TKI treatment efficacy in patients with acquired T790M mutation. Potential resistance mechanisms of third-generation EGFR TKIs in NSCLC patients with de novo or acquired EGFRT790M mutations included EGFR p.C797S in cis or EGFR p.E709X mutation, as well as activation of bypass pathways.

CONCLUSIONS

The present study characterized the uncommon but unique de novo EGFRT790M-mutant NSCLC and laid a foundation for designing future clinical trials in the setting of uncommon EGFR mutation.

Variability within a clonal population of Erwinia amylovora disclosed by phenotypic analysis

Background

Fire blight is a destructive disease of pome trees, caused by Erwinia amylovora, leading to high losses of chain-of-values fruits. Major outbreaks were registered between 2010 and 2017 in Portugal, and the first molecular epidemiological characterization of those isolates disclosed a clonal population with different levels of virulence and susceptibility to antimicrobial peptides.

Methods

This work aimed to further disclose the genetic characterization and unveil the phenotypic diversity of this E. amylovora population, resorting to MLSA, growth kinetics, biochemical characterization, and antibiotic susceptibility.

Results

While MLSA further confirmed the genetic clonality of those isolates, several phenotypic differences were recorded regarding their growth, carbon sources preferences, and chemical susceptibility to several antibiotics, disclosing a heterogeneous population. Principal component analysis regarding the phenotypic traits allows to separate the strains Ea 630 and Ea 680 from the remaining.

Discussion

Regardless the genetic clonality of these E. amylovora strains isolated from fire blight outbreaks, the phenotypic characterization evidenced a population diversity beyond the genotype clonality inferred by MLSA and CRISPR, suggesting that distinct sources or environmental adaptations of this pathogen may have occurred.

Conclusion

Attending the characteristic clonality of E. amylovora species, the data gathered here emphasizes the importance of phenotypic assessment of E. amylovora isolates to better understand their epidemiological behavior, namely by improving source tracking, make risk assessment analysis, and determine strain-specific environmental adaptations, that might ultimately lead to prevent new outbreaks.