Abstract

The liquid biopsy is being integrated into cancer diagnostics and surveillance. However, critical questions still remain, such as how to precisely evaluate cancer mutation burden and interpret the corresponding clinical implications. Herein, we evaluated the role of peripheral blood cell-free DNA (cfDNA) in characterizing the dynamic mutation alterations of 48 cancer driver genes from cervical cancer patients. We performed targeted deep sequencing on 93 plasma cfDNA from 57 cervical cancer patients and from this developed an algorithm, allele fraction deviation (AFD), to monitor in an unbiased manner the dynamic changes of genomic aberrations. Differing treatments, including chemotherapy (n = 22), radiotherapy (n = 14) and surgery (n = 15), led to a significant decrease in AFD values (Wilcoxon, p = 0.029). The decrease of cfDNA AFD values was accompanied by shrinkage in the size of the tumor in most patients. However, in a subgroup of patients where cfDNA AFD values did not reflect a reduction in tumor size, there was a detection of progressive disease (metastasis). Furthermore, a low AFD value at diagnosis followed a later increase of AFD value also successfully predicted relapse. These results show that plasma cfDNA, together with targeted deep sequencing, may help predict treatment response and disease development in cervical cancer.