Haiyan He, Hang Ma, Zhuo Chen, Jingliang Chen, Dandan Wu, Xuedong Lv, Jie Zhu
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引用次数: 0
Abstract
Purpose: Chromosomal abnormalities represent genomic signatures linked to cancer prognosis and responses to chemotherapy, immunotherapy, and drug resistance. This study aimed to investigate the impact of chromosome copy number variants (CNVs) on the efficacy of tyrosine kinase inhibitors (TKIs) in EGFR-mutated non-small cell lung cancer (NSCLC) patients, as well as its prognostic implications for progression-free survival (PFS) and overall survival (OS) in EGFR wild-type patients.
Methods: A total of 110 patients with advanced NSCLC were enrolled in this study and categorized into EGFR-mutated and wild-type groups. Utilizing next-generation sequencing (NGS) technology, we assessed 24 genes and chromosome CNVs associated with lung cancer pathways in patients' tissue samples.
Results: Within the EGFR-mutated group, patients with a gain in Chr 1p13.3-p13.1 exhibited poor TKI responses, a high relapse rate, and shortened PFS (P = 0.002). Conversely, EGFR-mutated patients with a gain in 14q31.1-q31.3 demonstrated favorable TKI responses and relatively extended PFS (P = 0.005). Among EGFR wild-type patients, the presence of 7q31.1-q31.31 CNV emerged as an independent factor influencing both PFS and OS (P = 0.013, P = 0.004). Notably, patients with a gain in 7q31.1-q31.31 exhibited prolonged PFS and OS. Additionally, independent prognostic significance for OS in EGFR wild-type patients was observed for CNVs in 9q21.31-q22.2 and 11p11.11-q12.1 regions (P = 0.001). Patients with gains in these regions experienced extended OS, while losses were predictive of poorer outcomes.
Conclusion: Our results suggested that chromosomal copy number variation is a practical indicator for predicting the response of EGFR-targeted therapy and prognosis for NSCLC patients.
期刊介绍:
Pharmacogenomics and Personalized Medicine is an international, peer-reviewed, open-access journal characterizing the influence of genotype on pharmacology leading to the development of personalized treatment programs and individualized drug selection for improved safety, efficacy and sustainability.
In particular, emphasis will be given to:
Genomic and proteomic profiling
Genetics and drug metabolism
Targeted drug identification and discovery
Optimizing drug selection & dosage based on patient''s genetic profile
Drug related morbidity & mortality intervention
Advanced disease screening and targeted therapeutic intervention
Genetic based vaccine development
Patient satisfaction and preference
Health economic evaluations
Practical and organizational issues in the development and implementation of personalized medicine programs.