Development of a new methylation-based fetal fraction estimation assay using multiplex ddPCR

Simultaneous detection of eight cancer types using a multiplex droplet digital PCR assay

DNA methylation biomarkers have emerged as promising tools for cancer detection. Common methylation patterns across tumor types allow multi-cancer detection. Droplet digital PCR (ddPCR) has gained considerable attention for methylation detection. However, multi-cancer detection using multiple targets in ddPCR has never been performed before. Therefore, we developed a multiplex ddPCR assay for multi-cancer detection. Based on previous data analyses using The Cancer Genome Atlas (TCGA), we selected differentially methylated targets for eight frequent tumor types (lung, breast, colorectal, prostate, pancreatic, head and neck, liver, and esophageal cancer). Three targets were validated using ddPCR in 103 tumor and 109 normal adjacent fresh frozen samples. Two distinct ddPCR assays were successfully developed. Output data from both assays is combined to obtain a read-out from the three targets together. Our overall ddPCR assay has a cross-validated area under the curve (cvAUC) of 0.948. Performance between distinct cancer types varies, with sensitivities ranging from 53.8% to 100% and specificities ranging from 80% to 100%. Compared to previously published single-target parameters, we show that combining targets can drastically increase sensitivity and specificity, while lowering DNA input. In conclusion, we are the first to report a multi-cancer methylation ddPCR assay, which allows for highly accurate tumor predictions.

Critical appraisal of droplet digital polymerase chain reaction application for noninvasive prenatal testing

Maternal-fetal medicine (FM) is currently a highly demanding branch and is gaining importance as increasing number of genetic disorders rise in incidence. Prenatal testing helps to detect such abnormalities that could affect the health status of the developing fetus like birth defects or genetic disorders. Considering the rising trend of genetic disorders, there is a need for a highly sensitive way of noninvasive prenatal testing (NIPT) that may reduce the incidence of unnecessary invasive procedures and iatrogenic fetal loss. The concept of NIPT for screening of genetic disorders is continuously evolving over the last two decades and multiple techniques have come up to utilize this in the field of FM. The crucial factor which decides the accuracy of NIPS is cell free fetal DNA (cffDNA) that is present in extremely low fraction (10%-15%) in the maternal plasma. Among the available methods, the next generation sequencing (NGS) is considered as the gold standard. However, the higher cost diminishes its utility in low-resource settings. Droplet digital Polymerase chain reaction (ddPCR), a type of digital PCR is a novel technique that is frugal, equally sensitive, less labor intensive, less time-consuming and plain algorithm dependent method for detecting cffDNA fraction. Considering these impressive attributes of ddPCR, we decided to critically review the existing literature on ddPCR for NIPT whilst highlighting the clinical utility, challenges and its advantages over NGS.

Application of droplet digital PCR method for DNA methylation-based age prediction from saliva

The recent studies reported that DNA methylation markers show changes with age, and expected that the DNA methylation markers can be effectively used for estimation of age in forensic genetics. In this study, we applied droplet digital PCR (ddPCR) method to investigate the DNA methylation pattern in the CpG sites, and we constructed an age prediction model based on the ddPCR method. The ddPCR is capable of highly sensitive quantitation of nucleic acid and detection of sequence variations in gene by separating the sample into large number of partitions and clonally amplifying nucleic acids in each partition. We extracted DNA from saliva samples collected from several age groups. The DNA was bisulfite converted and subjected to ddPCR using specifically designed primers and probes. The methylation ratio of each sample was calculated and correlation between the methylation ratio and the chronological age was analyzed. In the results, methylated DNA ratio at the 4 CpG sites (cg14361627, cg14361627, cg08928145 and cg07547549) showed strong correlation with chronological age. Percent-methylation values at 4 CpG markers and chronological ages of the 76 individuals were analyzed by multiple regression analysis, and we constructed an age prediction model. We observed a strong correlation (Spearman's rho = 0.922) between predicted and chronological ages of 76 individuals with a MAD from chronological age of 3.3 years. Collectively, the result in this study showed the potential applicability of ddPCR to predict age from saliva.

Self-Internal-Reference Probe System for Control-Free Quantification of Mutation Abundance

Gene mutations are important biomarkers for the diagnosis, classification, monitoring, and prognosis evaluation of cancers and genetic diseases. Both personalized cancer treatment and noninvasive prenatal testing require methods to accurately determine the abundance of mutation. At present, the widely adopted and convenient methods for measuring mutation abundance are mainly based on relative quantification, which requires negative samples and strict control of the analyte amounts. The development of DNA-probe-based methods that can determine the mutation abundance without negative samples nor control of analyte amount is highly preferred. The key to solving this bottleneck lies in whether the probe's response to mutation abundance can be completely independent of the number of targeted DNA strands. Herein, we propose the design of a self-internal-reference probe system. We established a theoretical model of this system and used the model to guide the design of probes. In this model, we provided quantitative corrections to the test results from the internal reference, thereby eliminating the influence of substrate amount. Therefore, the purification and quantification processes toward polymerase chain reaction (PCR) amplicons can be omitted. We applied this system to analyze unquantified PCR products aimed at cancer mutation detection and noninvasive prenatal testing.

Calculation of Fetal Fraction for Non-Invasive Prenatal Testing

Estimating the fetal fraction of DNA in a pregnant mother’s blood is a risk-free, non-invasive way of predicting fetal aneuploidy. It is a rapidly developing field of study, offering researchers a plethora of different complementary methods. Such methods include examining the differences in methylation profiles between the fetus and the mother. Others include calculating the average allele frequency based on the difference in genotype of a number of single-nucleotide polymorphisms. Differences in the length distribution of DNA fragments between the mother and the fetus as well as measuring the proportion of DNA reads mapping to the Y chromosome also constitute fetal fraction estimation methods. The advantages and disadvantages of each of these main method types are discussed. Moreover, several well-known fetal fraction estimation methods, such as SeqFF, are described and compared with other methods. These methods are amenable to not only the estimation of fetal fraction but also paternity, cancer, and transplantation monitoring studies. NIPT is safe, and should aneuploidy be detected, this information can help parents prepare mentally and emotionally for the birth of a special needs child.

Development of a new methylation-based fetal fraction estimation assay using multiplex ddPCR

Background

Non‐invasive prenatal testing (NIPT) for fetal aneuploidies has rapidly been incorporated into clinical practice. Current NGS‐based methods can reliably detect fetal aneuploidies non‐invasively with fetal fraction of at least 4%. Inaccurate fetal fraction assessment can compromise the accuracy of the test as affected samples with low fetal fraction have an increased risk for misdiagnosis. Using a novel set of fetal‐specific differentially methylated regions (DMRs) and methylation sensitive restriction digestion (MSRD), we developed a multiplex ddPCR assay for accurate detection of fetal fraction in maternal plasma.

Methods

We initially performed MSRD followed by methylation DNA immunoprecipitation (MeDIP) and NGS on fetal and non‐pregnant female tissues to identify fetal‐specific DMRs. DMRs with the highest methylation difference between the two tissues were selected for fetal fraction estimation employing MSRD and multiplex ddPCR. Chromosome Y multiplex ddPCR assay (YMM) was used as a reference standard, to develop our fetal fraction estimation model in male pregnancy samples. Additional 123 samples were tested to examine whether the model is sex dependent and/or ploidy dependent.

Results

In all, 93 DMRs were identified of which seven were selected for fetal fraction estimation. Statistical analysis resulted in the final model which included four DMRs (FFMM). High correlation with YMM‐based fetal fractions was observed using 85 male pregnancies (r = 0.86 95% CI: 0.80–0.91). The model was confirmed using an independent set of 53 male pregnancies.

Conclusion

By employing a set of well‐characterized DMRs, we developed a SNP‐, sex‐ and ploidy‐independent methylation‐based multiplex ddPCR assay for accurate fetal fraction estimation.