| BackgroundBreast cancer is one of the most common malignant tumors among women in the world,which seriously threatens human health.With the continuous progress of diagnosis and treatment technology,more accurate cancer diagnosis and more effective cancer treatment have been achieved.However,there are still some patients eventually recur and metastases several years after treatment because of resistant to treatment,which greatly affects the prognosis and survival of patients.As a class of malignant tumors with obvious heterogeneity,breast cancer can be divided into different molecular subtypes based on different gene expression profiles.Currently,breast cancer is based on comprehensive treatment of surgery,systemic chemotherapy,endocrine therapy,radiotherapy and targeted therapy.The above mentioned treatment methods have made an important contribution to the continuous decline in the mortality caused by breast cancer in the past decades.Since 2015,neoadjuvant chemotherapy(NAC)has become the standard treatment for locally advanced breast cancer,which can achieve the purpose of degradation and downstaging by eliminating disseminated tumor cells(micrometastasis)in blood.However,some patients may still have minimal residual disease even after completing NAC or receiving local treatment,which is the key reason for distant recurrence and metastasis.Current clinical biomarker detection such as CEA,CA-153,and imaging methods,can not accurately evaluate the disease in the early stage.Although histopathology biopsy of tumor specimens is the current gold standard for clinical and pathological diagnosis,this method also has some limitations.As a kind of non-invasive liquid biopsy technology,circulating tumor DNA(ct DNA)sequencing has been widely used for early screening,diagnosis,treatment,and prognosis of breast cancer.The shorter half-life gives ct DNA more advantages over traditional protein-based cancer biomarkers.Moreover,ct DNA can overcome the limitations of traditional pathological biopsy,fully reflect the spatial and temporal heterogeneity and the characteristics of the tumor gene spectrum.Another potential advantage of ct DNA detection and analysis is the near-realtime monitoring of a patient's response to treatment,which facilitates rapid feedback on whether a given therapy works well,thereby allowing treatment options to be adjusted in a timely manner,truly achieve personalized and precise treatment.In recent years,with the development of high-throughput sequencing technologies,liquid biopsy has been applied in the standard treatment process of solid tumors.It can reveal comprehensive cancer information independent of tissue specimens in the traditional method.However,to date,the value of ct DNA in the evaluation of locally advanced breast cancer NAC response and prognosis remains unclear.PurposeThis study intends to use next-generation sequencing(NGS)technology,which contains727 genes to perform multi-time points ct DNA detection and tissue sample gene detection in locally advanced breast cancer patients,aiming to evaluate mutational characteristics in ct DNA before and after NAC,as well as in tissues during surgery.Based on the mutations detected,we further evaluated the feasibility of using ct DNA as a new biomarker for NAC response prediction.At the same time,we explored whether ct DNA analysis six months after surgery can predict breast cancer relapse.Methods1.Patient enrollmentBetween January 2018 and January 2019,female patients with locally advanced breast cancer from Department of Breast,Thyroid Surgery,Daping Hospital,Army Medical University were prospectively recruited.The inclusion criteria:(1)Female,no chemotherapy contraindication;(2)Carcinoma were diagnosed by needle biopsy;(3)No history of malignant tumors in other parts;(4)The clinical stage before neoadjuvant chemotherapy was ?B-III;(5)The patient underwent 4-6 cycles of NAC,and the treatment is discontinued when severe side effect or disease progression occur and the doctor thinks it is not appropriate to continue chemotherapy;(6)Operable patients undergo surgery within one month after last cycle of neoadjuvant chemotherapy.The operation methods include radical mastectomy and breast-conserving surgery,combined with sentinel lymph node biopsy or axillary lymph node dissection.The excluded criteria:(1)Inflammatory breast cancer;(2)Pregnancy associated breast cancer;(3)The patient had a mastectomy prior to admission;(4)Failure to complete chemotherapy and surgery as scheduled;(5)Stage IV with distant metastasis;(6)Male breast cancer.All clinical and pathological data were fully recorded.This study set up 3 time points,namely before neoadjuvant chemotherapy(C1),surgical removal of tumor tissue(T time node),and 6 months after surgery(C2).We collected the peripheral blood samples of patients both at the C1 and C2 time points,the tumor tissue of patients at the T time point.The tissue DNA of all tissue samples and ct DNA of all blood samples are analyzed based on next-generation sequencing(NGS)technology,which contains 727 genes.At the same time,cancer biomarkers that are widely used in clinical practice include carbohydrate antigen 15-3(CA15-3),carbohydrate antigen 12-5(CA12-5)and carcinoembryonic antigen(CEA)were tested at the same 3 time points.This study was approved by the Ethics Committee of Daping Hospital,Army Medical University(No.2018(57)),and the study protocol adhered to the principles of the Declaration of Helsinki.Written informed consent was obtained from the patient.2.Sample preparationRegarding the 10 ml of peripheral blood from C1 and C2,plasma was separated from the blood sample within 72 hours by centrifugation(1,600 ×g at 4°C for 15 minutes).The supernatants were further centrifuged at 16,000 ×g at 4°C for 15 minutes.Plasma samples and peripheral blood cells were used to extract cell-free DNA(cf DNA)and genomic DNA(g DNA)according to the respective operating instructions.Tumor DNA(t DNA)was also extracted from tissue samples based on the standard protocol.3.Library construction,sequencing,and processingIn this study,a 727-gene panel which was designed by Top Gene Tech Co.,Ltd.(Guangzhou,China)covering a 2.8 megabase(Mb)region was used to capture the target DNA fragments.The lower limit of the target panel detection was ? 0.50% for somatic single nucleotide variants(SNVs)and small insertions/deletions(In Dels)and ? 3 copies for copy number variants(CNVs).All of the collected cf DNA from C1 and C2 and t DNA from tissue samples were subjected to DNA library preparation using a Kapa DNA library preparation kit(Kapa Biosystems,Wilmington,USA)while the g DNA library was prepared using an Illumina Tru Seq DNA library preparation kit(Illumina,San Diego,USA).The DNA libraries were hybridized to our customdesigned 727-gene probes(Nanodigmbio,Nanjing,China).Then,DNA sequencing was conducted using a DNBSEQ-2000 sequencer(BGI,Shenzhen,China).The raw sequencing data was filtered according to the default parameters to retain high quality reads for subsequent analysis.The clean reads were aligned to human genome assembly(hg19)using the BurrowsWheeler Aligner(BWA-0.7.17-r1188).Removal of duplicate reads,local realignments,and base-quality recalibrations were performed using the Genome Analysis Toolkit(GATK4.0.12.0).The resulting binary alignment map(BAM)files were used for subsequent variant calling analysis.4.Somatic mutation callingSNVs/small In Dels were detected using GATK(4.0.12.0)according to the reference standard pipeline.Germline variants were detected using the Haplotype Caller in GATK with the default parameters.For all mutational analyses,matched g DNA for each sample was used as the matched control.In short,the peripheral blood sample before neoadjuvant therapy,tissue sample during surgery,and peripheral blood sample six months after surgery were compared to the matched normal samples to exclude germline variants.A Panel of Normal(Po N)was generated from the normal samples to improve the variant calling results.Unreliable somatic mutations found in the Po N,Single Nucleotide Polymorphism Database,or 1000 Genomes Project database were filtered out,resulting in high quality among the remaining detected SNVs and small In Dels.In order to verify the detected variants,manual inspection of the BAM files was conducted using the Integrative Genomics Viewer.Tumor mutational burden(TMB)was defined as the number of somatic mutations per Mb.5.CNV callingCNVs were estimated by paired samples with Varscan2 according to the default parameters as follows: first,mpileup was performed on the BAM files of normal and tumor samples using samtools mpileup,and guanine-cytosine correction was performed on the mpileup results with Copy Caller software.Second,the regions with different copy numbers were cut with the circular binary segmentation algorithm.Finally,CNVs were obtained after combining the segments of candidate CNVs.As in somatic mutation calling,a CNV Po N from the normal samples was created to improve the results.6.Statistical analysisUnivariate and multivariate Cox proportional hazard analyses were conducted to assess the correlation between clinical features and the treatment outcome of neoadjuvant therapy.A Kaplan-Meier plot was also used to identify the correlation between ct DNA samples from the C2 time point and tumor recurrence.A ?2 test was utilized to determine whether the level of ct DNA in the blood before neoadjuvant treatment was related to its therapeutic efficacy.Statistical significance was defined as a 2-sided p-value of < 0.05.Statistical analyses were performed using Graph Pad Prism 6 software and SPSS 21.0 software.Results1.Sample cohort descriptionA total of 43 patients with locally advanced breast cancer who underwent NAC were prospectively enrolled in the study since January 2018.Five patients were excluded from further study because they refused to undergo surgery in our hospital due to personal reasons.Besides,seven other patients were excluded form further study because of insufficient cf DNA in plasma before NAC.Finally,31 breast cancer patients(mean age: 48.2 ± 7.0 years)were recruited in this study,9 cases with the luminal A subtype(29.0%),8 cases with the luminal B subtype(25.8%),7 cases with HER2 overexpression(22.58%),and 7 cases with TNBC(22.58%).According to the pathological MP classification,4 cases(12.9%)achieved p CR after neoadjuvant chemotherapy,and 27 cases(87.1%)were non-p CR patients.Regarding the widely used clinical cancer biomarkers,3 out of 31 patients(P5C1,P16C1,and P17C1)displayed abnormal results at time point C1,1(P5T1)at T,and another 1(P5C2)at C2.2.The results of the target-panel squencing quality controlFor the raw sequencing data,the average sequencing capture efficiency for the C1,T,and C2 samples was 72.89%(64.20–78.72%),74.98%(59.72%–80.62%),and 72.80%(67.53%–81.05%),respectively,and the effective target sequencing depth for the C1,T,and C2 samples was 1,010.19X(633.1X–1,650.01X),1071.61X(474.41X–1,624.33X),and 925.15X(625.15X–1,383.41X),respectively.3.Target-capture sequencing and genetic profilesOverall,159,271,and 70 somatic mutations were identified in the C1,T,and C2 samples,respectively.Somatic mutations were detected in 30 out of 31 C1 samples(96.8%)and 12 out of 25 C2 samples(48%).Higher baseline(C1 time point)ct DNA levels were significantly associated with younger patients(age<50)(p<0.05).However,the correlation between the baseline ct DNA levels and other clinical characteristic was insignificant(p>0.05),such as tumor stage,molecular subtype,lumph nodes status,BMI and cancer embolus.In addition,10,26,and 10 somatic hotspot mutations were identified in the C1,T,and C2 samples,respectively.Among the tissue samples,the most common somatically mutated genes were PIK3CA(48.50%),TP53(41.90%),and KMT2C(9.70%).However,when considering all 87 samples,the most common mutated genes were KMT2C(20.69%),PIK3CA(18.39%),and TP53(18.39%).In addition to somatic mutations,we also identified 6 germline mutations(19.35%)in the 31 breast cancer patients involving BRCA2,CHEK2,and MUTYH.They were BRCA2 c.5645C>A(P1),BRCA2 c.987?988ins A(P7),MUTYH c.892-2A>G(P15),BRCA2 c.31del(P17),CHEK2 c.1651dup(P29),and BRCA2 c.3940?3941del(P31).Overall,23 out of 87(26.44%)samples were detected to have gene copy number variation;among them,19 out of 23(82.61%)were from tissue samples while the remaining 4(17.29%)were from peripheral blood samples.4.The correlation between gene mutations and the efficacy of neoadjuvant chemotherapy for breast cancer4.1.The correlation between gene mutation and neoadjuvant chemotherapy p CR rateAfter neoadjuvant chemotherapy,there are 4 patients(P3,P4,P8,P12)achieved p CR(12.9%)and 27 patients were non-p CR(77.1%).No matter on the C1 time point or T time point,there is no statistical difference in the number of gene mutations between patients with p CR and non-p CR.Therefore,the number of tumor mutations in ct DNA before NAC or tissue samples is unrelated to the p CR rate.The correlation between the three most common mutations in tissues and blood(PIK3CA,TP53,KMT2C)and p CR was insignificant(p>0.05).The effectiveness of TMB and germline mutation were also insignificant.4.2 The correlation between gene mutation and the efficacy of neoadjuvant chemotherapy(RECIST)We evaluate the efficacy of neoadjuvant chemotherapy based on the Response Evaluation Criteria in Solid Tumors(RECIST).Those who achieved CR and PR after NAC were effective,while those who achieved SD and PD were ineffective.The effective rate of neoadjuvant chemotherapy was 64.5%(20/31),and the ineffective rate was 35.5%(11/31).No matter on the C1 time point or T time point,there is no statistical difference in the number of gene mutations between patients with effective NAC and ineffective NAC.Therefore,the number of tumor mutations in ct DNA before NAC or tissue samples is unrelated to the effective rate of NAC.The correlation between the three most common mutations in tissues and blood(PIK3CA,TP53,KMT2C)and effective rate of NAC was insignificant(p>0.05).The effectiveness of TMB and germline mutation were also insignificant.5.Risk Factors for breast cancer recurrence and progression5.1 Multivariate analysis of breast cancer recurrence and metastasisUp to now,a total of 7 patients have experienced postoperative recurrence and metastasis.Univariate analysis and multivariate analysis found that patients with high lymph node count(? 4)and SD after NAC relapsed or progressed within a short period(p = 0.012 and p = 0.036,respectively),while cancer embolus,age,molecular type,BMI were not correlate with the period of relapse(p>0.05).We thus concluded that lymph node status and SD could be used as predictors of breast cancer recurrence.5.2 The correlation between gene mutation and recurrence of breast cancerThe survival analysis(Kaplan-Meier curve)showed that ct DNA KMT2 C c.5053G>T at C2 time point was significantly associated with recurrence and progression of breast cancer after surgery(P=0.0014).ct DNA mutation could be used as a potential predictor of recurrence and progression of breast cancer after neoadjuvant therapy.5.3 The correlation between the traditional tumor biomarkers and the recurrence of breast cancerAs for the CA 15-3,CA 12-5,and CEA results in the 7 relapsed patients,only one relapsed patient(P5)displayed abnormal levels while the remaining six were normal,suggesting that traditional tumor biomarkers could not meet the requirements for early tumor recurrence detection.ConclusionOur study demonstrates the feasibility and validity of ct DNA detection based on NGS in patients with locally advanced breast cancer.Overall,159,271,and 70 somatic mutations were identified in the C1,T,and C2 samples,respectively.Somatic mutations were detected in 30 out of 31 C1 samples(96.8%)and 12 out of 25 C2 samples(48%).We found that the most common mutated genes were KMT2C(20.69%),PIK3CA(18.39%),and TP53(18.39%).The incidence of KMT2 C mutations is higher in breast cancer patients,especially among TNBC patients.Kaplan-Meier survival and multivariate analyses indicated that ct DNA KMT2 C c.5053G>T could be a predictor of the relapse of breast cancer,while the association between ct DNA and efficiency of neoadjuvant therapy was insignificant(p>0.05).The continuous detection of ct DNA has significant potential to complement imaging-based tumor assessment,which helps to identify the disease progress of patients and achieve individualized therapy. |
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