Application Of Cervical Cancer Related Genes Based On CfDNA Targeted Sequencing

Objective:Cervical cancer is one of the commonest gynecological cancer affecting women.With rising population and aging,number of cervical cancer cases is expected to increase 1.5-fold by 2030.And the incidence of cervical cancer in China is becoming younger,so it cannot be ignored.It is also one of the commonest cancers of females that can be detected and treated completely at precancerous stages.But even so,many cases of cervical cancer die every year.How to effectively monitor the treatment of cervical cancer patients by one method is a difficult problem to be solved.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(PB)cell-free DNA(cfDNA)in characterizing the dynamic mutation alterations of 48 cancer driver genes from cervical cancer patients.Method: In this study,48 cancer-related genes were screened based on previous cancer research,and a total of 2158 pairs of primers were designed to cover the exons of all target genes.We recruited a total of 57 cervical cancer patients from The Second Hospital of Dalian Medical University and collected their peripheral blood.Six of these patients did not receive any treatment,and the rest were treated with certain treatments(surgery,radiotherapy or chemotherapy).Each patient was given at least one blood draw,and a total of 93 plasma-free DNA samples were obtained,and WBC in the blood of 57 patients was used as a control group.By building the library of cfDNA and WBC separately,targeted deep sequencing was performed using multiplex primer PCR technology.At the same time,we also developed an algorithm,Allele Frequency Deviation(AFD),to monitor in an unbiased manner the dynamic changes of genomic aberrations.Results: By targeted deep sequencing of plasma cell free DNA from 57 cervical cancer patients,we identified 1,245 mutations in the target region: 425 non-synonymous mutations and 815 synonymous mutations,2 stopgain,1 stoploss and 2 non-frameshift mutations.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 were 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.Conclusion: These results show that plasma cell free DNA,together with targeted deep sequencing,may help predict treatment response and disease development in cervical cancer.We developed a new algorithm named AFD for cancer liquid biopsy which evaluates the mutation deviation of every single site in the target regions,including the sites that usually fail to pass the SNV-calling criteria of most algorithms.By analyzing 93 cervical cancer samples,we demonstrate that AFD is able to efficiently monitor patient responses to tumor treatment and prognosticate tumor progression.The expansion of these algorithms into larger patient cohorts will hopefully validate if patient treatment response can be measured and the probability of disease progression predicted.Once validated,these tools will allow the medical oncologist to more effectively treat advanced stage patients.