Dynamic monitoring serum tumor markers to predict molecular features of EGFR‐mutated lung cancer during targeted therapy. (11th May 2022) - Chen, Zhuxing; Liu, Liping; Zhu, Feng; Cai, Xiuyu; Zhao, Yi; Liang, Peng; Ou, Limin; Zhong, Ran; Yu, Ziwen; Li, Caichen; Li, Jianfu; Xiong, Shan; et al.
Abstract: To reveal the correlation of dynamic serum tumor markers (STMs) and molecular features of epidermal growth factor receptor‐mutated (EGFR‐mutated) lung cancer during targeted therapy, we retrospectively reviewed 303 lung cancer patients who underwent dynamic STM tests [neuron‐specific enolase (NSE), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), the soluble fragment of cytokeratin 19 (CYFRA21‐1), and squamous cell carcinoma antigen (SCC)] and circulating tumor DNA (ctDNA) testing with a panel covering 168 genes. At baseline, patients with EGFR mutation trended to have abnormal CEA, abnormal CA153, and normal SCC levels. Additionally, patients with Thr790Met (T790M) mutation were more likely to have abnormal CEA levels than patients without T790M mutation. Among patients with secondary resistance to EGFR tyrosine kinase inhibitors (TKI), the dynamic STMs showed a descending trend in the responsive stage and a rising trend in the resistant stage. However, the changing slopes differed between T790M subgroup and the non‐T790M subgroup in individual STMs. Our study demonstrated that the combination of baseline levels and variations of STMs (including the responsive stage and resistant stage) can be suggestive of secondary EGFR‐T790M mutation [area under the curve (AUC) = 0.897] and that changing trends of STMs (within 8 weeks after initiating the TKI therapy) can be potential predictors for the clearance of EGFR ctDNA [AUC = 0.871]. In conclusion, dynamic monitoring STMs can help to predict the molecular features of EGFR‐mutated lung cancer during targeted therapy. Abstract : Predicting the molecular features of cancer at an earlier time would be conducive to precise clinical diagnoses and treatments. To our knowledge, there is still no research on whether dynamic monitoring tumor markers could predict the molecular features of lung cancer during targeted therapy. In this study, we demonstrated that dynamic lung‐cancer‐relate STMs can be effective predictors for secondary EGFR T790M mutation and the clearance of EGFR ctDNA during targeted treatment.