Increasing applications of Next-Generation Sequencing (NGS) in oncology have helped scientists and clinicians in depicting the genomic landscape of breast cancer (BC) [
ctDNA, derived from necrotic and apoptotic tumor cells of multiple lesions, has become a promising biomarker. It may provide the whole scale of tumor genomic profiles with the advantages of being noninvasive. Considering the short half-life of ctDNA, it is also expected to be a sensitive marker to reflect tumor status and treatment efficacy in real time. But, the concentration of ctDNA in the cell-free DNA (cfDNA) varied, ranging from less than 0.01% to more than 90% [
Accumulating studies have investigated the concordance between two biopsies in various cancers, with varied concordance rate. Previous studies in BC found that 15.6% to 48% tissue single nucleotide variants (SNVs) and insertions and deletions (InDels) could be detected in ctDNA, and 33% to 48% ctDNA SNVs and InDels could be detected in tissues in studies with the sample size of 62 and 45, respectively [
Eighty-one patients diagnosed as BC were included in this study. Clinical TNM classification was defined according to American Joint Committee on Cancer (Breast Cancer Staging, 7th Edition). Tumor tissues and blood samples were collected from 81 patients. The tumor tissue samples were collected by either percutaneous needle biopsy or surgery. The blood samples were collected in Streck tubes (La Vista, Nebraska). For concordance study, the blood samples were collected at least one day before surgery.
This study was approved by the Ethics Committee of Cancer Hospital, Chinese Academy of Medical Sciences, and conformed to the provisions of the Declaration of Helsinki. Every patient signed an informed consent form. Patients were selected according to the following criteria: (1) age of 18 or above; (2) those who fulfilled the diagnostic criteria of NCCN Clinical Practice Guidelines in Oncology for BC. Patients were excluded according to following criteria: (1) who had second primary tumor before enrollment; (2) who had poor control of medical treatment with severe cardiovascular, cerebrovascular diseases, or diabetes; (3) noncompliant, or there was a situation that researchers thought it was not suitable to be included in the study; (4) pregnant or lactating women; (5) who had previous transplant surgery; (6) who had previous stem cell treatment; (7) who had received allogeneic blood transfusion within one year and immunotherapy within four weeks.
Whole-blood samples were processed within three days after blood collection, and they were separated into plasma and buffy coat by two-step centrifugations. Tissues, plasma, and white blood cell (WBC) samples were stored at −80°C until further processing. Circulating cell-free DNA (cfDNA) was extracted from 3-4 mL plasma by the MagMAX™ Cell-Free DNA Isolation kit (Life technologies, A29319, USA). Genomic DNAs (gDNAs) were extracted from tumor tissue and buffy coat using a Qiamp FFPE tissue kit (Qiagen, 56404, Germany) and TiANamp Blood DNA Maxi kit (TianGen Biotech, DP332, China), respectively. Qubit dsDNA high-sensitivity (HS) assay kit (Invitrogen, Q32854, USA) was used to quantify the DNA concentration.
gDNAs from tumor tissue and buffy coat were sheared into 150–250 bp fragments by Covaris S220 (Covaris, S220, USA). The cfDNA and gDNA libraries were prepared by KAPA Hyper Prep Kit (KAPA, KK8504, USA) according to the manufacturers’ instructions. One to five libraries from the same sample type were pooled at an equal molar concentration and hybridized to a customized Agilent SureSelect panel (∼0.45 M). After PCR amplification, the quality and quantity of captured library were assessed by an Agilent 2100 bioanalyzer and ABI 7500 real-time PCR system (Life Technologies, 4351107, USA). Sequencing libraries were loaded on a Nextseq 500 (Illumina, San Diego, CA) sequencing platform to generate 75 bp pair-end reads. The minimal read depths of plasma, tissue, and buffy coat were 800x, 800x, and 250x, respectively.
FASTQ files were generated by bcl2fastq2 (v.2.17.1.14). The raw reads containing P5/P7 adapters were trimmed off, and the reads containing over 30% low-quality (base quality <30) sequencing bases and over 60% N bases were also discarded. Then, the clean reads were mapped to the GRCh37/hg19 human genome using Burrows-Wheeler Aligner (BWA, v.0.7.12,
Concordance of SNVs and InDels was defined as that the same mutation could be found in both tissue and plasma. Discordance was defined as mutation could be only detected in one biopsy. The concordance for gene amplification was defined as the gene amplification found or absent in both biopsies.
The continuous normally distributed variables were represented using mean and standard deviation (SD), and the continuous abnormally distributed variables were represented using median and interquartile range (IQR) and counting number and percentage for categorical variables. Mutation density was calculated as mutation counts within the gene divided by the length of the coding region of the gene. For the comparison of VAF levels, we applied the Wilcoxon rank sum test with a statistically significant level of
The clinical characteristics of BC patients included in this study are summarized in Supplementary Table
The custom-designed 136-gene-panel (Agilent) used in this study (Supplementary Table
In total, 387 mutations were detected in 76 (93.8%, 76/81) BC tissue samples, including 350 SNVs and 37 InDels. The median genomic mutations per sample in tissues were 3.0 (IQR 4.0) with mean of 4.8 (SD 5.5) (Figure
Comparison of the mutation number in different biopsies. (a) Mutation counts in 41 ctDNA samples and 81 tissue samples. One dot in the figure represented as the mutation counts of one sample. (b) Mutation counts and density of the top 10 genes in two biopsies. Green and blue bars represented the mutation counts or density in ctDNAs and tissues, respectively.
Then, we investigated the mutation level among targeted genes.
As for gene amplification, 43 amplifications of 12 genes were identified in two biopsies of 81 tissue samples and 41 plasma samples. The affected genes included
For 41 patients with paired tissue and liquid biopsy samples, a total of 410 alterations were detected in two biopsies, including 161 alterations in tissues and 249 alterations in ctDNAs. 31 alterations were shared by both biopsies, including 24 SNVs, four InDels, and five amplifications (Figure
Concordant and discordant alterations detected in ctDNAs and tissues. (a) Venn diagrams representing the counting number of alterations, SNVs, InDels, and detected amplifications (AMPs) detected only in tissues (blue), detected only in ctDNAs (green), and detected in both biopsies (overlap). (b) Oncoprint chart for 17 genes which had at least one concordant protein-coding mutation site or concordant gene amplification across all 41 patients. One vertical bar represents one patient. Green bar: mutations in plasma; blue bar: mutations in tissue; red bar: concordant mutation in two biopsies; orange bar: mutations in the same gene, but discordant in ctDNA and tissue.
At the gene level, the concordance rate for each patient, including genes with detected mutation and mutation absent from both biopsies, ranged from 83.8% (114/136) to 99.3% (135/136). The concordance of 41 paired samples with detected mutations at gene level ranged from 0.0% (0/41) to 24.4% (10/41). The top genes with the highest concordance rate (Figure
For gene amplifications, five patients were detected with gene CNVs in both biopsies, and gene amplification were absent from 23 patients. The overall concordance rate was 68.3%. Given BC patients with
Concordance of
Tissues | Sensitivity | Specificity | Concordance | |||
---|---|---|---|---|---|---|
(+) | (−) | (%) | (%) | (%) | ||
ctDNA | (+) | 2 | 1 | |||
(−) | 5 | 33 | 28.6 | 97.1 | 85.4 |
We compared the VAF of concordant and discordant somatic mutations in ctDNA (Figure
Comparison of VAF between concordant and discordant ctDNA mutations. Boxplot displayed the minimum, maximum, median, and interquartile range of VAF of ctDNA. Concordant ctDNA mutations had higher frequency than discordant ctDNA mutations (
We analyzed the sensitivity, specificity, PPV, NPV, and diagnostic accuracy across five genes which carried the most concordant mutations, including
Sensitivity, specificity, and diagnostic accuracy across 6 genes.
ctDNA mutations | Tissue mutations | Sensitivity | Specificity | PPV | NPV | Diagnostic | Youden’s | |
---|---|---|---|---|---|---|---|---|
(+) | (−) | (%) | (%) | (%) | (%) | Accuracy (%) | J Index | |
(+) | 10 | 7 | ||||||
(−) | 9 | 20 | 52.6 | 74.1 | 58.8 | 70.0 | 65.2 | 0.27 |
(+) | 4 | 2 | ||||||
(−) | 10 | 27 | 28.6 | 93.1 | 66.7 | 73.0 | 72.1 | 0.22 |
(+) | 2 | 4 | ||||||
(−) | 1 | 35 | 66.7 | 89.7 | 33.3 | 97.2 | 88.1 | 0.56 |
(+) | 4 | 9 | ||||||
(−) | 2 | 29 | 66.7 | 76.3 | 30.8 | 93.5 | 75.0 | 0.43 |
(+) | 4 | 2 | ||||||
(−) | 3 | 35 | 57.1 | 94.6 | 66.7 | 92.1 | 60.9 | 0.52 |
Total positive | 24 | 24 | ||||||
Total negative | 25 | 146 | ||||||
Total(positive + negative) | 49 | 170 | 49.0 | 85.9 | 50.0 | 85.4 | 77.6 | 0.35 |
We selected six liver cancer and 20 colorectal cancer patients and evaluated the concordance between ctDNA and tissue biopsy. There were 13 females and 13 males. And, the mean age was 60.0 (SD 12.0) with the median of 60.0 (IQR 15.0). Patients with stages I, II, III, and IV accounted for 0.0% (0/26), 11.5% (3/26), 46.2% (12/26), and 34.6% (9/26), respectively (Supplementary Table
A total of 119 alterations were detected in tissues, including 90 SNVs, 20 InDels, and 9 CNVs, and 189 alterations in ctDNAs, including 140 SNVs, 46 InDels and 3 CNVs. The median genomic mutations per sample were 4.0 (IQR 3.0) with mean of 4.0 (SD 2.4) in tissues, and 4.0 (IQR 3.8) with mean of 7.2 (SD 10.1) in ctDNAs. There was no difference of the average mutations per sample between tissue and ctDNA (
For the protein-coding mutation level, 15 SNVs and five InDels were detected in two biopsies. 46.2% (12/26) samples had at least one concordant mutation in two biopsies; in the meantime, the concordance rate ranged from 0.0% to 50.0% across 26 samples. 18.2% (20/110) tissue-derived mutations were detected in ctDNAs, and 10.8% (20/186) ctDNA-derived mutations were detected in tissues. For gene amplifications, two patients had concordant CNVs and 20 patients had no gene amplifications in two biopsies. The overall concordance rate was 84.6% (22/26).
Tumor heterogeneity has been widely observed, which may lead to sampling bias and loss of valuable clinical information. Liquid biopsy like ctDNA analysis was expected to overcome the genomic heterogeneity within tumor. But, related studies in BC are still limited compared with those in lung and gastrointestinal cancer. To investigate the concordance of genomic alterations, we used paired samples with normal controls in this study. Previous studies in American and Japanese patients with BC showed that the concordance rates ranged from 10.8% to 74.3%. According to Chea’s study, 10.8% concordant mutations were detected in both biopsies among 45 American patients [
Moreover, VAFs of concordant ctDNA mutations were much higher than those of discordant ones in our study, which was consistent with the previous study [
It is important to note that we found a relatively high concordant rate of
Overall, our findings contributed to the understanding of tumor heterogeneity and provide more information on the clinical value of ctDNA. Precision medicine on solid tumors based on the genomic alteration profiles is promising and effective [
Our study evaluated the concordance of genomic alterations between solid and liquid biopsies in 41 breast tumor patients. 39.0% patients had at least one concordant mutation in two biopsies. 20.0% tissue-derived mutations could be detected via ctDNA-based sequencing, whereas 11.7% ctDNA-derived mutations could be found in paired tissues. VAF was higher in concordant ctDNA mutations than that in the discordant ones. For gene amplifications,
The analyzed data sets used to support the findings of this study are available from the corresponding author upon request.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
We thank all the patients who participated in this study, the support of Cancer Foundation of China, and colleagues who contributed to this work. This study was funded by the USCI special grant of Cancer Foundation of China (ZH0046).
Figure S1: the number of genomic alterations in detected genes of two biopsies. Table S1: clinical characteristics of all BC patients; Table S2: genes included in the panel; and Table S3: clinical characteristics of liver cancer and colorectal cancer patients.