Co‐mutational assessment of circulating tumour DNA (ctDNA) during osimertinib treatment for T790M mutant lung cancer. Issue 10 (8th August 2019)

• Record Type: Journal Article
• Authors: Xing, Puyuan; Han, Xiaohong; Wang, Sha; Liu, Yutao; Yang, Sheng; Hao, Xuezhi; Wang, Yan; Liu, Peng; Li, Junling; Wang, Lin; Chang, Lianpeng; Guan, Yanfang; Zhang, Zhishang; Wu, Di; Yao, Jiarui; Yi, Xin; Shi, Yuankai
• Is Part Of: Journal of cellular and molecular medicine. Volume 23:Issue 10(2019)
• Page Start: 6812
• Page End: 6821
• Publication Date: 2019-08-08
• Subjects: circulating tumour DNA -- non‐small‐cell lung cancer -- osimertinib -- resistance; Cytology; Medicine; Molecular Biology; Cytologie -- Périodiques; Médecine -- Périodiques; Biologie moléculaire -- Périodiques; Cytology -- Periodicals; Medicine -- Periodicals; Molecular biology -- Periodicals; 611.01805
• DOI: 10.1111/jcmm.14565
• Languages: English
• ISSNs: 1582-1838

Abstract

Abstract: Osimertinib is designed to target the secondary resistant EGFR T790M mutant and has shown outstanding clinical efficacy. However, the prognostic prediction of osimertinib patients is a big problem in clinical practice. The resistance mechanism of osimertinib is also not fully understood. NGS and a 1021 gene capture panel were used to analyse the somatic mutation profile of thirty‐six lung adenocarcinoma patients' serial ctDNA samples. Progression‐free survival of subgroup patients is analysed. Patients harbour TP53 mutations and patients with higher TMB value in pre‐treatment samples showed a shorter PFS. Moreover, compared to CT evaluation, ctDNA changes generally correlated with treatment responses in most patients. Novel resistance mechanisms are discovered including EGFR mutations and alternative activation pathway. Our results implied a broad potential of ctDNA as an adjuvant tool in practical clinical management of NSCLC patients. ctDNA could help with clinical practice during osimertinib treatment, regarding monitoring tumour response, detecting development of heterogeneity, identifying potential resistance mechanisms, predicting treatment efficacy and patient outcome.