Circulating tumor <scp>DNA</scp> predicts the outcome of chemotherapy in patients with lung cancer
Min Zhang, Chao Huang, Huan Zhou, Dan Liu, Runze Chen, Xiuhua Li, Ye Cheng, Bing Gao, Jun Chen
Abstract
BACKGROUND: Circulating tumor DNA (ctDNA) has potential as a specific, noninvasive, and cost-effective new biomarker for patients with lung cancer. This study aimed to determine whether plasma ctDNA can be used to predict treatment outcomes in patients with lung cancer. METHODS: Pre- and in-treatment blood samples were collected from 14 patients with lung cancer receiving chemotherapy. Based on next-generation sequencing technology, we constructed a unique molecular identifier (UMI) library and performed targeted deep sequencing of 72 genes (15 000×). We used dVAF to evaluate the change level and trend of variant allele frequency (VAF). RESULTS: We identified MUC16, KMT2D, AMER1, and NTRK1 as the most-frequently mutated genes in ctDNA associated with lung cancer. Furthermore, we showed that the change trend of dVAF in patients with lung cancer undergoing chemotherapy was closely related to the changes in both tumor volume and tumor biomarkers, including CEA, CA125, NSE, and CK (Cytokeratin). Moreover, the ctDNA analysis revealed disease progression of SCLC patients earlier than did computed tomography. CONCLUSIONS: The dynamic detection of plasma ctDNA VAF has the potential value as a biomarker for evaluating the efficacy of chemotherapy in patients with SCLC and advanced NSCLC, and may predict the progression of lung cancer patients earlier than radiography.