Abstract

Background

Successful practice of precision medicine in advanced lung cancers relies on therapeutic regimens tailored to individual molecular characteristics. The aim of this study was to investigate the accuracy of small specimens for molecular profiling using next-generation sequencing (NGS).

Methods

Genetic alternations, tumor mutational burden (TMB), status of microsatellite instability (MSI), and expression of programmed death ligand 1 (PD-L1) were compared side-by-side between the concurrently obtained core needle biopsy (CNB) and resection specimens in 17 patients with resectable non-small cell lung cancers.

Results

DNA yield and library complexity were significantly lower in CNB specimens (both p < 0.01), whereas the insert size, sequencing depth, and Q30 ratio were similar between the matched specimens (all p > 0.05). The total numbers of genetic alternations detected in resection and CNB specimens were 186 and 211, respectively, with 156 alternations in common, yielding a specific concordance rate of 83.9%. The prevalence of mutations in 8 major driver genes was 100% identical between surgical and CNB specimens, though the allele frequency was lower in CNB specimens, with a median underestimation of 57%. Results of TMB were similar (p = 0.547) and MSI status was 100% matched in all paired specimens.

Conclusions

Pulmonary CNB specimens were suitable for NGS given the satisfactory accuracy when compared to corresponding surgical specimens. NGS results yielding from CNB specimens should be deemed reliable to provide instructive information for the treatment of advanced lung cancers.

Details

Title
Accuracy of next-generation sequencing for molecular profiling of small specimen of lung cancer: a prospective pilot study of side-by-side comparison
Author
Xiaosong Ben; Tian, Dan; Zhuang, Weitao; Chen, Rixin; Wang, Sichao; Zhou, Zihao; Deng, Cheng; Shi, Ruiqing; Liu, Songlin; Zhang, Dongkun; Tang, Jiming; Xie, Liang; Zhou, Haiyu; Zhang, Zhou; Li, Min; Zhang, Xuanye
Pages
1-12
Section
Research
Publication year
2022
Publication date
2022
Publisher
BioMed Central
e-ISSN
1746-1596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2725934077
Copyright
© 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.