Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2023-05-05 Cooperative journals: 《中国全科医学》
Abstract： Background Targeted therapy，represented by epidermal growth factor receptor-targeting tyrosine kinase inhibitors （EGFR-TKIs），has significantly prolonged the survival time of patients with EGFR mutations with relatively mild adverse reactions，and become a prior choice for advanced non-small cell lung cancer （NSCLC） patients with driver genes. Dynamic monitoring of treatment progress and gene mutations in NSCLC patients by means of gene detection will help to provide a more effective，long-term and stable individualized targeted therapy for such patients. Objective To compare the gene mutations before and after the progression of NSCLC，and to analyze the regularities of gene mutations dynamically monitored and related prognostic value in NSCLC patients. Methods NSCLC outpatients and inpatients undergoing genetic tests were selected from Department of Integrated Medicine and Lung Cancer Center of China-Japan Friendship Hospital from January 2007 to December 2021. Their data were collected and used to establish a lung cancer genes testing database. Tissue samples or peripheral blood circulating tumor DNA（ctDNA） before and after progression were obtained for full-coding area detection of lung cancer genes，and the number of gene mutations and testing results were recorded. We divided enrolled patients into gene clearance group and non-gene clearance group，and compared baseline characteristics and survival status between the groups. Results A total of 217 cases were enrolled and followed until their clinical endpoint. The total changes in gene mutations in tissue samples before and after the disease progression were as follows：the number of patients with wild type increased from 70（32.3%） to 95（43.8%），the number of patients with mutant type decreased from 147（67.7%） to 122（56.2%），the number of patients with 19DeL mutation increased from 64 （29.5%） to 67 （19.8%），the number of patients with 21 L858R mutations decreased from 74 （34.1%） to 64 （24.0%），the number of patients with T790M mutations increased from 2（0.9%） to 45（20.7%），and the number of those with rare mutations or concomitant rare mutations such as TP53 increased from 20（9.2%） to 84（38.7%）. Gene clearance group（n=67） and non-gene clearance group（n=150） had significant differences in clinical features except the history of lung disease（P=0.032） and the history of targeted therapy（P=0.001）. The median progression-free survival （PFS） of patients in the two groups was 9.8 months and 11.8 months，respectively，with no significant difference［HR=0.89，95%CI（0.66，1.20），P=0.310］. The median PFS of 134 patients with advanced NSCLC in two groups was 8.1 months and 9.8 months，respectively，with no significant difference〔HR=0.83，95%CI（0.58，1.19），P=0.359〕. The median overall survival （OS） of patients in two groups was 50.5 months and 28.5 months，respectively，with statistically significant difference〔HR=0.56，95%CI （0.41，0.78），P<0.000 1〕. The median OS of 134 patients with advanced NSCLC in two groups were 45.5 months and 24.9 months，respectively，showing statistically significant difference〔HR=0.55，95%CI（0.37，0.81），P=0.000 2〕.Conclusion The gene mutation status before and after disease progression for patients with NSCLC changed dynamically. After the progression，the proportion of wild type increased significantly compared with mutant type. The proportion of classical mutation decreased，but the proportion of concomitant mutations increased. Patients with 19DeL mutations developed a higher rate of T790M after disease progression. Monitoring gene clearance could not help to predict a PFS，but the gene clearance type predicted better OS benefits. Dynamic monitoring of changes in gene status could help guide treatment promptly for optimal clinical benefits.
Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2022-12-01 Cooperative journals: 《中国全科医学》
Abstract：
Objective To compare the characteristic differences of gene mutations before and after lung cancer recurrence, and analyze the prognostic effect of lung cancer gene dynamic monitoring for NSCLC patients. Methods Tissue samples or peripheral blood ctDNA before and after progression were obtained for full-coding area detection of lung cancer genes. Clinical characteristics of different gene mutation types were compared. Survival data were followed up to conduct survival regression analysis for enrolled patients. Results A total of 217 lung cancer patients were screened and enrolled for clinical tumor gene sequencing analysis. All participators were followed until clinical endpoints. Patients with wild type changed from 70 (32.3%) to 95 (43.78%), gene mutated type from 147 (67.7%) to 122 (56.22%), the 19DEL mutation from 64 (29.49%) to 67 ( 19.82%), 21 L858R mutations from 74 (34.10%) to 64 (23.96%), T790M mutations from 2 (0.92%) to 45 (20.74%), and rare mutations or combined rare mutations such as TP53 from 20 (9.2%) to 20 84 (38.71%). All genetic changes were calculated with a statistical difference (P < 0.05). The proportion of NSCLC patients with gene clearance type was 30.9%(67/217), and that of non-gene clearance type was 69.1%(150/217). The predictive value of monitoring gene clearance for PFS was poor, and there was no significant difference. While for OS data, whether in NSCLC patients or 134 patients with advanced NSCLC, the OS of NSCLC patients with gene clearance type was significantly longer. NGS results showed that there might be potential drug resistance mutations, such as L792H, G61S and so on. Conclusion The mutation status of the gene before and after disease progression for patients with NSCLC was changed dynamically. The proportion of wild type increased significantly compared with mutant type. The proportion of the classical mutation decreased, but the proportion of concomitant mutations increased. Patients with 19DEL mutations developed a higher rate of T790M after disease progression. Monitoring gene clearance could not help to predict a longer PFS, but the gene clearance type predicted better OS benefits. Dynamic monitoring of changes in gene status could help guide treatment promptly for optimal clinical benefits.
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