High Sensitivity Detection and Quantitation of DNA Copy Number and Single Nucleotide Variants with Single Color Droplet Digital PCR

In this study, we present a highly customizable method for quantifying copy number and point mutations utilizing a single-color, droplet digital PCR platform. Droplet digital polymerase chain reaction (ddPCR) is rapidly replacing real-time quantitative PCR (qRT-PCR) as an efficient method of independent DNA quantification. Compared to quantative PCR, ddPCR eliminates the needs for traditional standards; instead, it measures target and reference DNA within the same well. The applications for ddPCR are widespread including targeted quantitation of genetic aberrations, which is commonly achieved with a two-color fluorescent oligonucleotide probe (TaqMan) design. However, the overall cost and need for optimization can be greatly reduced with an alternative method of distinguishing between target and reference products using the nonspecific DNA binding properties of EvaGreen (EG) dye. By manipulating the length of the target and reference amplicons, we can distinguish between their fluorescent signals and quantify each independently. We demonstrate the effectiveness of this method by examining copy number in the proto-oncogene <i>FLT3</i> and the common V600E point mutation in <i>BRAF</i>. Using a series of well-characterized control samples and cancer cell lines, we confirmed the accuracy of our method in quantifying mutation percentage and integer value copy number changes. As another novel feature, our assay was able to detect a mutation comprising less than 1% of an otherwise wild-type sample, as well as copy number changes from cancers even in the context of significant dilution with normal DNA. This flexible and cost-effective method of independent DNA quantification proves to be a robust alternative to the commercialized TaqMan assay

DataSheet_1_Tumor-associated microbiome features of metastatic colorectal cancer and clinical implications.docx

BackgroundColon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) and prognosis. We analyzed 16S rRNA sequencing data from tumor samples of patients with metastatic CRC and determined the clinical implications.Materials and methodsWe enrolled 133 patients with metastatic CRC at St. Vincent Hospital in Korea. The V3-V4 regions of the 16S rRNA gene from the tumor DNA were amplified, sequenced on an Illumina MiSeq, and analyzed using the DADA2 package.ResultsAfter excluding samples that retained ConclusionTumor microbiome features may be useful prognostic biomarkers for metastatic CRC.</p