Dynamic analysis of circulating tumor DNA to predict prognosis and monitor therapeutic response in metastatic relapsed cervical cancer

Xiaoyuan Tian, Dongcen Ge, Feng Zhang, Bocheng Zhang, Wanting Bai, Xiaoying Xu, Zongjuan Li, Ying Cao, Peiying Li, Kun Zou, Lijuan Zou, Xiaoyuan Tian, Dongcen Ge, Feng Zhang, Bocheng Zhang, Wanting Bai, Xiaoying Xu, Zongjuan Li, Ying Cao, Peiying Li, Kun Zou, Lijuan Zou

Abstract

Limited and inefficient treatment options exist for metastatic relapsed cervical cancer (MRCC), and there are currently no reliable indicators to guide therapeutic selection. We performed deep sequencing analyses targeting 322 cancer-related genes in plasma cell-free DNA and matched white blood cells in 173 serial blood samples from 82 locally advanced CC (LACC) or MRCC patients and when possible during treatment. We identified five notable nonsynonymous mutant genes (PIK3CA, BRAF, GNA11, FBXW7 and CDH1) in the MRCC samples as the metastatic relapse significantly mutated (MSG) genes and found that MRCC patients with any detectable MSG mutations had significantly shorter progression-free survival (PFS) (P = .005) and overall survival (OS) (P = .007) times than those without detectable MSG mutations. Additionally, analyses of matched prechemotherapy and postchemotherapy plasma revealed that a reduction in the number of MSG mutations after chemotherapy was significantly associated with partial remission (PR) and stable disease (SD) (P = .007). Among the patients included in the longitudinal tracking ctDNA analysis, an increase in MSG mutations was observed earlier in response to disease progression than radiological imaging. Our results outline the mutation profiles of MRCC. We show how longitudinal monitoring with ctDNA in liquid biopsy samples provides both predictive and prognostic information during treatment.

Keywords: biomarkers; circulating tumor DNA; metastatic relapsed cervical cancer; prognostic prediction; tumor monitoring.

© 2020 Union for International Cancer Control.

References

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Source: PubMed

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