This study was supported by a Grant-in-Aid for Scientific Research (C) from the Japan Society for the Promotion of Science (JSPS) (No. 15K08397) to Tomoaki Kahyo, and by grants from the Japan Agency for Medical Research and Development (AMED) (No. 927960719), Grant-in-Aid for Exploratory Research (No. 16K15256), Expenditure for Associated Projects of an Incentive Special Budget for the Promotion of a National University Reform in Management Expenses Grants (No. 1019253), and the Smoking Research Foundation to Haruhiko Sugimura. The authors thank Dr. Iwaizumi and Dr. Kurachi for their clinical support. The funders had no role in the preparation of the manuscript. Figure 3, Figure 4, and Table 4 are adapted and reprinted from an article by Kahyo et al.10, with permission from Elsevier.

The study design was approved by the Institutional Review Boards of the Hamamatsu University School of Medicine (G-260-4). Written informed consent was obtained from the patient and his parents.
1. Quality Control of Genomic DNA
NOTE: Genomic DNA (gDNA) was extracted from peripheral blood using the well-established silica-membrane-based DNA purification method. In advance of the below procedures, the concentration of gDNA was determined using a spectrophotometer.
<ol>
	<li>Prepare the gDNA sample at a concentration of 10&#8211;100 ng/&#181;L.</li>
	<li>Add 10 &#181;L of DNA sample buffer to an 8-tube strip.</li>
	<li>Add 1 &#181;L of DNA ladder or&#160;gDNA to the tubes. Vortex the mixture for 1 min using the microplate attachment.</li>
	<li>Load the tube,&#160;the gel device and pipette tips into the electrophoresis instrument (Table of Materials) and start the run by pressing the &#39;Start&#39; button. 
	NOTE: The electrophoresis system will automatically operate with one click on the Start button.</li>
	<li>Confirm that the lower marker contained in the DNA sample buffer is correctly assigned on the electropherograms. If it is incorrectly assigned, manually assign the marker in the &#39;Electroherogram&#160;mode&#39; of the software. 
	NOTE: The DNA integrity number (DIN) will be automatically calculated. The DIN value comes from the DNA integrity. High and low DIN values indicate highly intact and strongly degraded gDNA, respectively.</li>
	<li>Specify the size region of the gDNA (&#62; 200 bp) in the &#39;Region mode&#39; of the software to automatically calculate the concentration of gDNA (&#62; 200 bp).</li>
</ol>
2. Primer and Probe Design
<ol>
	<li>Calculate the melting temperature (Tm) values using any open access tool under the following conditions: 10&#8211;25 bases, 50 mM Na+/K+, 0.80 mM dNTPs, and 3 mM Mg2+ (Table of Materials). Design the forward and reverse primers to amplify the genomic region containing target alleles with the Tm value around 60 &#176;C and the amplicon length at 100&#8211;300 bp. 
	NOTE: Refer to Table 1 for the concentration of oligonucleotides.</li>
	<li>Design the locked nucleic acid (LNA) probes for the reference and variant alleles based on the following conditions: (i) 1&#8211;6 LNAs are present in each probe; (ii) a fluorescent dye and a quencher are present at the 5&#39;- and 3&#39;-terminuses of each probe, respectively; (iii) the difference between the Tm values of the matched and mismatched probes is &#62; 10 &#176;C; (iv) Tm values of the matched and mismatched probes are higher and lower than those of the primers, respectively [e.g., forward primer: 60.8 &#176;C, reverse primer: 59.8 &#176;C, reference allele probe (matched/mismatched): 62.6/45.3 &#176;C, variant allele probe (matched/mismatched): 61.7/50.5 &#176;C]. The Tm values were calculated using the open access tool also used for step 2.1.</li>
	<li>Ensure that the designed primers and probes do not encompass the single nucleotide polymorphisms with a frequency of &#62; 0.1% as determined from databases [e.g., the Single Nucleotide Polymorphism database (dbSNP)].</li>
</ol>
3. Digital PCR
<ol>
	<li>Prepare the primers, probes, and gDNA stock solutions in the concentrations described in Table 1 with a TE buffer and store them at -20&#8211;4 &#176;C.</li>
	<li>Mix the reagents at room temperature in a total volume of 15 &#181;L to a final concentration as described in Table 1.
	<ol>
		<li>Add 3 &#181;L of distilled water instead of gDNA in a no-template control (NTC).</li>
		<li>Prepare 3.5x the amount of the PCR mixture in triplicate to account for the pipetting error.</li>
	</ol>
	</li>
	<li>Pipette the PCR mixture up and down to mix it.</li>
	<li>Set the loading platform onto the chips built in the 8-tube strip and set them on the autoloader. Ensure that there is a contact between the chip and the loading platform.</li>
	<li>Fit a loading slider on the platform and hold the slider with the stopper off of the loader.</li>
	<li>Pipette 15 &#181;L of the PCR mixture on the platform near the tip of the slider (Figure 1A).</li>
	<li>Run the loader by pressing the button of the loader (for approximately 1 min). 
	NOTE: It is not a problem if a small amount of PCR mixture remains on the platform. It is possible to sequentially rerun the loader.</li>
	<li>Set the chip-in-a-tube filled with PCR mixture in the side slot of the sealing enhancer. Push the slide lid and the edge of the top lid to not break the chip (Figure 1B).</li>
	<li>Run the sealing enhancer (approximately 2 min). Sequentially rerun the sealing enhancer for 1 min if a puddle of liquid is still visible because an incomplete sealing causes a cross-contamination of the positive signals (Figures 1C and 1D).</li>
	<li>Add 230 &#181;L of sealing fluid, an oil-based reagent, to the tubes. 
	NOTE: The chips should now be immersed in the fluid.</li>
	<li>Set the tubes in the thermal cycler. Run the thermal cycler as described in Table 2 (for approximately 2 h). Tune the temperature or the duration of the PCR if there is an uneven distribution of positive partitions (Figure 1E). 
	NOTE: It is recommended to set the ramp rate to around 1 &#176;C/s.</li>
	<li>Leave the tubes in the thermal cycler for at least 15 min to reduce the baseline noise. 
	NOTE: The tubes can be left overnight as well. Fluorescence signals were detected even the following day.</li>
	<li>Set the tubes on the detection jig and pour 6 mL of distilled water into the jig. If air bubbles are visible inside and outside of the tubes, clear them (Figures 1F and 1G).</li>
	<li>Load the jig into the detector and run it with a click on the &#39;Run&#39; button of the software after the selection of Fluorescene, Experiment and Sample/NTC tabs (Table of Materials). 
	NOTE: The dual color detection of eight samples with a default intensity takes approximately 4 - 5 min.</li>
	<li>Confirm the position plot, histogram and 2D scatter plot. 
	NOTE:&#160;iIf the fluorescence intensity of the negative partitions is high, adjust the intensity with a click on the Settings button of the software so that it falls within the range of 30&#8211;70.</li>
	<li>Calculate the variant allele fraction (VAF) using the following formula: 
	<img alt="Equation 1" src="/files/ftp_upload/58199/58199eq1.jpg" /> 
	Here, Cv and Cr are the copy numbers of the variant and the reference allele, respectively. 
	NOTE: They are automatically calculated in the software program based on Poisson statistics.</li>
</ol>
4. Collection of PCR Product
<ol>
	<li>Remove the sealing fluid from the tube.</li>
	<li>Add 100 &#181;L of TE buffer to the tube. Vortex vigorously for 30 s and briefly centrifuge the tube.</li>
	<li>Transfer the TE solution to another tube and add 30 &#181;L of 3 M sodium acetate and 200 &#181;L of ethanol.</li>
	<li>Cool the solution at -20 &#176;C overnight.</li>
	<li>Centrifuge the solution for 30 min at 16,000 x g and remove the supernatant.</li>
	<li>Add 300 &#181;L of 80% ethanol to the tube and vortex.</li>
	<li>Centrifuge the solution for 15 min at 16,000 x g and remove the supernatant. Allow the precipitate to air-dry for 5 min.</li>
	<li>Dissolve the precipitate in 1&#8211;5 &#181;L of TE buffer after air-drying.</li>
	<li>If necessary, assess the product size using an electrophoresis instrument with reference to step 1. Load 1 &#181;L of the solution to the gel device for a high sensitivity (Table of Materials).</li>
</ol>

<ol>
	<li>Majumdar, N., Wessel, T., Marks, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+PCR+modeling+for+maximal+sensitivity,+dynamic+range+and+measurement+precision.">Digital PCR modeling for maximal sensitivity, dynamic range and measurement precision.</a> PLoS One. 10 (3), 0118833 (2015).</li><li>Huggett, J. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+digital+MIQE+guidelines:+Minimum+Information+for+Publication+of+Quantitative+Digital+PCR+Experiments.">The digital MIQE guidelines: Minimum Information for Publication of Quantitative Digital PCR Experiments.</a> Clinical Chemistry. 59 (6), 892-902 (2013).</li><li>Chen, L., Liu, P., Evans, T. C., Ettwiller, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+damage+is+a+pervasive+cause+of+sequencing+errors,+directly+confounding+variant+identification.">DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification.</a> Science. 355 (6326), 752-756 (2017).</li><li>Alix-Panabi&#232;res, C., Pantel, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+Applications+of+Circulating+Tumor+Cells+and+Circulating+Tumor+DNA+as+Liquid+Biopsy.">Clinical Applications of Circulating Tumor Cells and Circulating Tumor DNA as Liquid Biopsy.</a> Cancer Discovery. 6 (5), 479-491 (2016).</li><li>Kiss, M. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+quantitative+polymerase+chain+reaction+in+picoliter+droplets.">High-throughput quantitative polymerase chain reaction in picoliter droplets.</a> Analytical Chemistry. 80 (23), 8975-8981 (2008).</li><li>Hindson, B. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+droplet+digital+PCR+system+for+absolute+quantitation+of+DNA+copy+number.">High-throughput droplet digital PCR system for absolute quantitation of DNA copy number.</a> Analytical Chemistry. 83 (22), 8604-8610 (2011).</li><li>Ottesen, E. A., Hong, J. W., Quake, S. R., Leadbetter, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microfluidic+digital+PCR+enables+multigene+analysis+of+individual+environmental+bacteria.">Microfluidic digital PCR enables multigene analysis of individual environmental bacteria.</a> Science. 314 (5804), 1464-1467 (2006).</li><li>Low, H., Chan, S. J., Soo, G. H., Ling, B., Tan, E. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clarity&#8482;+digital+PCR+system:+a+novel+platform+for+absolute+quantification+of+nucleic+acids.">Clarity&#8482; digital PCR system: a novel platform for absolute quantification of nucleic acids.</a> Analytical and Bioanalytical Chemistry. 409 (7), 1869-1875 (2017).</li><li>Iwaizumi, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+APC+mosaicism+in+a+patient+with+familial+adenomatous+polyposis.">A novel APC mosaicism in a patient with familial adenomatous polyposis.</a> Human Genome Variation. 2, 15057 (2015).</li><li>Kahyo, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+digital+PCR+with+chip-in-a-tube+format+to+analyze+Adenomatous+polyposis+coli+(APC)+somatic+mosaicism.">Application of digital PCR with chip-in-a-tube format to analyze Adenomatous polyposis coli (APC) somatic mosaicism.</a> Clinica Chimica Acta. 475, 91-96 (2017).</li><li>Kanai, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Japanese+Society+of+Pathology+Guidelines+on+the+handling+of+pathological+tissue+samples+for+genomic+research:+Standard+operating+procedures+based+on+empirical+analyses.">The Japanese Society of Pathology Guidelines on the handling of pathological tissue samples for genomic research: Standard operating procedures based on empirical analyses.</a> Pathology International. 68 (2), 63-90 (2018).</li><li>Lorenz, T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polymerase+chain+reaction:+basic+protocol+plus+troubleshooting+and+optimization+strategies.">Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.</a> Journal of Visualized Experiments. (63), e3998 (2012).</li><li>Cao, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+digital+polymerase+chain+reaction+(dPCR)+and+its+emerging+biomedical+applications.">Advances in digital polymerase chain reaction (dPCR) and its emerging biomedical applications.</a> Biosensors and Bioelectronics. 90, 459-474 (2017).</li><li>. Bio-Rad Laboratories Available from: <a target="_blank" href="https://www.bio-rad.com/webroot/web/pdf/Isr/literature/Bulletin_6311.pdf">https://www.bio-rad.com/webroot/web/pdf/Isr/literature/Bulletin_6311.pdf</a> (2018)</li><li>. Thermo Fisher Scientific Available from: <a target="_blank" href="https://www.garvan.org.au/research/capabilities/molecular-genetics/documents/qs-3d-user-guide.pdf">https://www.garvan.org.au/research/capabilities/molecular-genetics/documents/qs-3d-user-guide.pdf</a> (2013)</li></ol>

The authors have nothing to disclose.

The DIN value is often used to assess damaged DNA (e.g., gDNA from formalin-fixed paraffin-embedded tissue) before quantification or sequencing, because an advanced degradation of gDNA can result in low-quality data. DIN assessment is, thus, becoming an important step in the quality control of human gDNA11. Since the gDNA used in the representative experiment had been stored at 4 &#176;C for 4&#8211;11 years after its extraction from blood, its DIN values were determined for a quality control before the dPCR assay. This step is especially recommended if the materials are suspected to be damaged. The concentration of gDNA was also determined by electrophoresis. Because the dynamic range of dPCR is not as wide as for qPCR due to the limitations of the partitions, a measurement of the gDNA concentration is an important step for a successful dPCR assay. As the amount of input DNA was correlated with the total copy number of the variant and reference alleles in the dPCR assay (R-squared = 0.935; Table 4), electrophoresis is useful for measuring the gDNA concentration before the dPCR assay.
The loading and sealing processes are important steps for successful results. It is crucial to confirm the appropriate mounting of the PCR mixture on the platform and ensure contact between the chip and the platform (Figure 1A). Protrusion of PCR mixture from the slider can cause invalid distribution on the chip. Confirming the distribution of the positive and negative partitions on a position plot is also necessary for a precise analysis, because it is assumed in Poisson statistics that DNA templates are randomly partitioned into chambers1. In the representative results, positive partitions were distributed throughout the chip (Figure 3). This outcome meets the requirement for Poisson statistics and reflects that the loading and sealing procedures were effective. When setting the tubes in the sealing enhancer, the chips could be broken if the central portion of the top lid is pushed too strongly (Figure 1B). To avoid this, gently push the edge of the top lid. If there is an artificial cluster of positive partitions (Figure 1D), the copy number may be overestimated due to a cross-contamination between partitions. The sealing procedure should be improved if a puddle of liquid is visible on the surface (Figure 1C) (e.g., by sequentially rerunning the sealing enhancer for 1 min). If there is an uneven distribution of positive partitions (Figure 1E), the copy number may be underestimated due to insufficient amplification or contamination of the sealing fluid and water. The PCR conditions should be adjusted in this case [e.g., by tuning the temperature or the duration of the PCR (step 3.11 of the protocol), or by ensuring that the sealing fluid and water poured into the jig are clean]. Fluorescence signals are detected from the 8-tube strip immersed in distilled water. If air bubbles adhere to the tube surface, there is the possibility that they may interfere with the signal detection (Figure 1F). Therefore, bubbles should be cleared using a tool, such as a fine pipette tip. Additionally, air bubbles may form inside the tubes when they are set in the jig (Figure 1G). If the bubbles inside the tubes are large enough to cover the chip, they should also be cleared. The bubbles may clear if they are left for several minutes at room temperature.
Some positive partitions might be detected in the NTC. To avoid a contamination of the DNA templates, keep the bench clean and, if possible, make a clean space with a fan filter unit. If a contamination of the DNA templates is suspected, thoroughly clean the space and/or discard the used reagents. By contrast, if the positive partitions of the reference allele are not detected in the presence of gDNA, reconfirm the concentrations of the gDNA, primers, and probes. Notably, the primers were used at a lower concentration in the representative experiment, compared to conventional PCR (Table 1)12. It is also crucial to confirm the ramp rate, which is rarely altered in conventional PCR.
What makes dPCR with the chip-in-a-tube format unique is the partitioning of the PCR mixture inside the universal 8-tube strip8,13. A transfer of the partitioning chambers into a PCR tube is not required in this system, thus reducing the contamination risk. There is also an advantage in the dPCR system with chip-in-a-tube format; it takes &#60; 4 h to finish 96 assays in that dPCR system, while it takes at least 5 h to finish the same number of assays in droplet-based dPCR14. Furthermore, the universal 8-tube strip enables the use of a conventional thermal cycler, unlike another chip-based dPCR15, which requires a thermal cycler with a flat block. Also, the accumulated knowledge and reagents for conventional PCR can be applied to the dPCR system. This will be helpful for expanding the applications of dPCR.
It should be noted that dPCR has several limitations. In dPCR with the chip-in-a-tube format, the partition number of the chip is relatively low compared with those in other dPCR platforms. Further improvement to the chip device will be required to increase the dynamic range, which depends on the number of partitions. Because the internal space of the universal tube is limited, a breakthrough design for the chip device is required to increase the number of partitions. The automation of the entire dPCR procedure in the future would greatly reduce human error, resulting in even more reliable results. Because of its high-throughput and high-sensitivity nature, the dPCR with chip-in-a-tube format is expected to be applied to treat a number of samples for liquid biopsies and environmental DNA.

Quantitative PCR (qPCR) is frequently used to quantify human genetic variation, including single nucleotide variants (SNVs) and DNA copy number variations (CNVs). In qPCR, a polymerase reaction is performed in each tube in the same way as in the conventional end-point PCR, and an amplification signal is acquired from the tube after every thermal cycle. By contrast, in dPCR, meaning end-point dPCR in this report, the PCR mixture is loaded into many microscopic chambers, termed partitions, where DNA templates are present or absent at a limiting dilution, and every partition containing PCR mixture is assessed as negative or positive after the complete PCR. While it is easy to estimate that there are no DNA templates in the negative partitions, it is unclear how many copies of DNA templates are present in the positive partitions. Therefore, the number of DNA templates in the positive partitions is estimated based on the Poisson distribution, using the count from the negative partitions1. dPCR is more expensive and has a smaller dynamic range compared to qPCR, but this method enables an absolute quantification and offers a higher sensitivity and greater precision2.
One of the main applications of dPCR is the validation of the variants identified by next-generation sequencing (NGS). Especially in the case of rare variants, meaning low variant fractions, validation is crucial due to sequencing errors that may occur in NGS3. While Sanger sequencing and qPCR are useful tools for the validation of SNVs and CNVs, their sensitivity is low compared to dPCR. Therefore, dPCR technology is in demand for genetic studies dealing with rare variants. Recently, the detection by liquid biopsy of rare variants related to cancer characteristics, such as drug-resistance, has become a hot topic in molecular diagnosis and therapy4. The dPCR technology appears suitable for liquid biopsy studies and is expected to have important clinical applications in the near future, although improvements related to the dynamic range and cost are still required to be implemented.
Commercially-available dPCR technology can be roughly categorized into droplet-based and chip-based platforms; the difference is how the DNA templates are partitioned5,6,7. In the dPCR with chip-in-a-tube format, the PCR mixture is distributed by the capillary action into the partitions on a chip. The chips are built in eight-tube strips, which many lab staff will already be familiar with, and, thus, eight samples can be treated at one time8. In the reading step, it takes &#60; 1 h to treat 96 samples by detecting the whole image of the chip and not each partition. Since dPCR with the chip-in-a-tube format has a high throughput compared with other dPCR systems, usability and productivity are the key advantages for its users.
In this report, somatic mosaicism of the APC gene in a patient with sporadic familial adenomatous polyposis is used as a representative case and the results of dPCR and NGS are compared. The main purpose of this report is to clearly quantify a single nucleotide variant using dPCR with the chip-in-a-tube format. We hope that this report is helpful for researchers interested in adopting the dPCR platform for their own work.

<table border="0" cellpadding="0" cellspacing="0" style="width:772px;" width="771">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">QIAamp DNA Blood Maxi Kit</td>
			<td style="width:147px;">Qiagen</td>
			<td style="width:188px;">51194</td>
			<td style="width:291px;">Before Protocol 1: Extraction of genomic DNA</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">NanoDrop 1000</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">ND-8000</td>
			<td>Before Protocol 1: Spectrophotometer</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:147px;">8-strip tube</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">401428</td>
			<td>Protocol 1</td>
		</tr>
		<tr height="98">
			<td height="98" style="height:98px;width:147px;">Genomic DNA sample buffer</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5366</td>
			<td style="width:291px;">Protocol 1: 
			A component of Genomic DNA Screen Tape Assay</td>
		</tr>
		<tr height="83">
			<td height="83" style="height:83px;width:147px;">DNA ladder</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5366</td>
			<td style="width:291px;">Protocol 1: 
			A component of Genomic DNA Screen Tape Assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">MS3 Basic Small Shaker</td>
			<td style="width:147px;">IKA</td>
			<td style="width:188px;">3617000</td>
			<td>Protocol 1: Vortex mixer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Genomic DNA ScreenTape</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5365</td>
			<td>Protocol 1: Gel device</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">2200 TapeStation system</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">G2965AA</td>
			<td>Protocol 1: Electrophoresis instrument</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">TapeStation Analysis Software</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">Bundled with G2965AA</td>
			<td>Protocol 1: Analysis software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">DNA oligo primers</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Custom order</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">LNA probes</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Custom order</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="51">
			<td height="51" style="height:51px;width:147px;">Software tool</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Web site: http://biophysics.idtdna.com/</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="70">
			<td height="70" style="height:70px;width:147px;">dbSNP database</td>
			<td style="width:147px;">NCBI</td>
			<td style="width:188px;">Web site: https://www.ncbi.nlm.nih.gov/projects/SNP/</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">TE buffer</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">12090015</td>
			<td>Protocol 3</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">DNase/RNase-Free Distilled Water</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">10977015</td>
			<td>Protocol 3 (Table 1)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Digital PCR Probe Mastermix</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12013</td>
			<td style="width:291px;">Protocol 3 (Table 1): 2xPCR Master Mix 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sealing Fluid</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12005</td>
			<td style="width:291px;">Protocol 3: Sealing fluid 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity JN Solution</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12006</td>
			<td style="width:291px;">Protocol 3 (Table 1): 20xdPCR solution 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Tube-strip</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12007</td>
			<td style="width:291px;">Protocol 3: Chip-in-a-tube 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sample Loading Kit</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12008</td>
			<td style="width:291px;">Protocol 3: Loading platform and slider 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Auto Loader</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11002</td>
			<td style="width:291px;">Protocol 3: Auto loader 
			A component of #10001</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sealing Enhancer</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11003</td>
			<td style="width:291px;">Protocol 3: Sealing enhancer 
			A component of #10001</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Reader</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11004</td>
			<td style="width:291px;">Protocol 3: Reader 
			A component of #10001</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:46px;width:147px;">Life Eco Thermal Cycler</td>
			<td style="width:147px;">Bioer Technology</td>
			<td style="width:188px;">TC-96GHbC</td>
			<td>Protocol 3: Thermal cycler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">Clarity Software</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">Bundled with #10001</td>
			<td style="width:291px;">Protocol 3: Analysis software</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">High Sensitivity D1000 screen tape</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5584</td>
			<td>Protocol 4: Gel device for high sensitivity</td>
		</tr>
	</tbody>
</table>

digital polymerase chain reaction assay for the genetic variation in a sporadic familial adenomatous polyposis patient using the chip-in-a-tube format

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as tumors. Because digital polymerase chain reactions (PCR) enable the precise quantification of DNA copy number variants, they are becoming an essential tool for detecting rare genetic variations, such as drug-resistant mutations. It is expected that molecular diagnoses using digital PCR (dPCR) will be available in clinical practice in the near future; thus, how to efficiently conduct dPCR with human genetic material is a hot topic. Here, we introduce a method to detect Adenomatous polyposis coli (APC) somatic mosaicism using dPCR with the chip-in-a-tube format, which allows eight dPCR reactions to be simultaneously conducted. Care should be taken when filling and sealing the reaction mixture on the chips. This article demonstrates how to avoid the over- and underestimation of positive partitions. Furthermore, we present a simple procedure for collecting the dPCR product from the partitions on the chips, which can then be used to confirm the specific amplification. We hope that this methods report will help promote the dPCR with the chip-in-a-tube method in genetic research.

We reviewed somatic mosaicism of the APC gene in a patient with sporadic familial adenomatous polyposis according to the procedures described above. In a previous study, the APC c.834 + 2T &#62; C mutation was found in the patient, but not in their parents, using Sanger sequencing and NGS9. The designs of the primers and probes used in the representative results are shown in Table 3. Genomic DNA was extracted from the blood of the proband, the parents, and six healthy donors. The DIN values of the nine gDNA samples ranged to 6.7&#8211;7.9 (Figure 2 and Table 4). FAM and HEX were used as the fluorescence dyes for the C and T alleles, respectively. The green and yellow spots on the position plots represent FAM-positive and HEX-positive partitions, respectively (Figure 3A). The blue spots represent negative partitions for both FAM and HEX. The black background corresponds to partitions where the reaction mixture was not added. Many positive partitions of the C and T alleles were detected in the proband, while few positive partitions of the C allele were detected in the proband&#39;s father or the NTC and, in the latter, positive partitions of the T allele were not detected. The signal separation between the C and T alleles was clear on the two-dimensional (2-D) scatterplot, and the most positive signals of HEX and FAM were exclusive of each other (Figure 3B). The VAF of the proband was 13.2%, which is similar to that determined using NGS (12.7%) (Table 4). The VAFs of the proband&#39;s parents and healthy donors were &#60; 0.1%. The detection limit for the APC c.834 + 2T &#62; C mutation was estimated to be 0.3% using 3x the standard deviation for the repeated measurements with 10&#8211;11 ng of the total gDNA10.
The amplicon size in the dPCR assay for APC c.834 + 2T &#62; C was predicted to be 123 bp. To confirm that the dPCR product was amplified as a single band, the dPCR product was collected from the assayed chip. Using electrophoresis, a single band was clearly detected, and the product size was consistent with the prediction (Figure 4).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58199/58199fig1.jpg" /> 
Figure 1: Points to note for the dPCR assay with chip-in-a-tube format. (A) This panel shows how to set up the 8-tube strip in the autoloader. (B) This panel shows broken chips. (C) This panel shows how the chip surfaces just after (i) loading and (ii) sealing. (iii) A puddle of liquid is visible in the case of an incomplete sealing. (D) This panel shows the position plot in the case of a cross-contamination. (E) This panel shows the position plot in the case of an uneven distribution. (F) This panel shows how air bubbles on the tube surface immersed in water. (G) This panel shows air bubbles inside of the tube. Throughout the entire figure, black and white arrowheads indicate broken chip pieces and air bubbles, respectively. <a href="https://www.jove.com/files/ftp_upload/58199/58199fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58199/58199fig2.jpg" /> 
Figure 2: Representative electropherograms of blood gDNA. Electropherograms of blood gDNA with DIN values of 6.7 and 7.9 are shown in the upper and bottom panel, respectively. The asterisk indicates a lower marker. DIN: DNA integrity number. <a href="https://www.jove.com/files/ftp_upload/58199/58199fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58199/58199fig3.jpg" /> 
Figure 3: Representative results of APC somatic mosaicism using dPCR with the chip-in-a-tube format. (A) The position plots and (B) scatterplots of the no-template control (NTC), the proband, and the father are shown here. HEX and FAM correspond to the reference and variant alleles, respectively. Vertical and horizontal lines indicate the thresholds of HEX and FAM intensities, respectively. This figure has been modified from Kahyo et al.10. <a href="https://www.jove.com/files/ftp_upload/58199/58199fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58199/58199fig4.jpg" /> 
Figure 4: Collection of dPCR products from the assayed chip. The collected and concentrated dPCR products were subjected to electrophoresis. The predicted target size was 123 bp. This figure has been modified from Kahyo et al.10. NTC: no-template control. <a href="https://www.jove.com/files/ftp_upload/58199/58199fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Concentration 
			of stock solution</td>
			<td>Volume (&#956;L)</td>
			<td>Final concentration</td>
			<td>Recommended 
			final concentration</td>
		</tr>
		<tr>
			<td>DNase/RNase-Free Distilled Water</td>
			<td>-</td>
			<td>1.75</td>
			<td>-</td>
			<td>-</td>
		</tr>
		<tr>
			<td>2x PCR Master mix</td>
			<td>-</td>
			<td>7.5</td>
			<td>-</td>
			<td>-</td>
		</tr>
		<tr>
			<td>LNA probe for major allele</td>
			<td>2 &#956;M</td>
			<td>0.5</td>
			<td>66.7 nM</td>
			<td>3.33&#8211;100 nM</td>
		</tr>
		<tr>
			<td>LNA probe for minor allele</td>
			<td>2 &#956;M</td>
			<td>0.5</td>
			<td>66.7 nM</td>
			<td>3.33&#8211;100 nM</td>
		</tr>
		<tr>
			<td>Forward primer</td>
			<td>1 &#956;M</td>
			<td>0.5</td>
			<td>33.3 nM</td>
			<td>3.33&#8211;50.0 nM</td>
		</tr>
		<tr>
			<td>Reverse primer</td>
			<td>1 &#956;M</td>
			<td>0.5</td>
			<td>33.3 nM</td>
			<td>3.33&#8211;50.0 nM</td>
		</tr>
		<tr>
			<td>20x dPCR solution</td>
			<td>-</td>
			<td>0.75</td>
			<td>-</td>
			<td>-</td>
		</tr>
		<tr>
			<td>gDNA</td>
			<td>3.33 ng/&#956;L</td>
			<td>3</td>
			<td>666 pg/&#956;L</td>
			<td>20 pg/&#956;L&#8211;2,000 pg/&#956;L1</td>
		</tr>
	</tbody>
</table>
Table 1: Reagents used for the dPCR assay.&#160;1Depending on expected precision and sensitivity.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Step</td>
			<td>Temperature</td>
			<td>Time</td>
			<td>Cycles</td>
		</tr>
		<tr>
			<td>Initial denature</td>
			<td>95 &#176;C</td>
			<td>5 m</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Denature 
			Annealing and extension</td>
			<td>95 &#176;C 
			58 &#176;C</td>
			<td>50 s 
			90 s</td>
			<td>42</td>
		</tr>
		<tr>
			<td>Final extension</td>
			<td>70 &#176;C</td>
			<td>5 m</td>
			<td>1</td>
		</tr>
	</tbody>
</table>
Table 2: Thermal cycler conditions.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Sequence1</td>
			<td>Tm value2</td>
		</tr>
		<tr>
			<td>Forward primer</td>
			<td>5&#39;-GGTCAAGGAGTGGGAGAAATC-3&#8242;</td>
			<td>60.8 &#176;C</td>
		</tr>
		<tr>
			<td>Reverse primer</td>
			<td>5&#39;-TCTTAGAACCATCTTGCTTCATACT-3&#8242;</td>
			<td>59.8 &#176;C</td>
		</tr>
		<tr>
			<td>LNA probe for T allele</td>
			<td>5&#39;-HEX-ATTT[A]CCTGACCA-IBFQ-3&#39;</td>
			<td>Matched: 62.6 &#176;C 
			Mismatched: 45.3 &#176;C</td>
		</tr>
		<tr>
			<td>LNA probe for C allele</td>
			<td>5&#39;-FAM-TTT[G]CCTGACC-IBFQ-3&#39;</td>
			<td>Matched: 61.7 &#176;C 
			Mismatched: 50.5 &#176;C</td>
		</tr>
	</tbody>
</table>
Table 3: Design of the primers and probes. 1Underlined and bracketed letters are the LNA and targeted variant, respectively. 2Calculated according to step 2 of the protocol.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td>NGS3</td>
			<td colspan="4">dPCR4</td>
		</tr>
		<tr>
			<td rowspan="2">Sample1</td>
			<td rowspan="2">Tissue</td>
			<td rowspan="2">Input DNA (ng)</td>
			<td rowspan="2">DIN2</td>
			<td rowspan="2">VAF (%)</td>
			<td rowspan="2">Variant (copies)</td>
			<td rowspan="2">Reference (copies)</td>
			<td colspan="2">VAF (%)</td>
		</tr>
		<tr>
			<td>Mean</td>
			<td>RSD</td>
		</tr>
		<tr>
			<td>NTC</td>
			<td>-</td>
			<td>-</td>
			<td>-</td>
			<td>-</td>
			<td>1.23</td>
			<td>0</td>
			<td>N/A</td>
			<td>N/A</td>
		</tr>
		<tr>
			<td>Proband</td>
			<td>Blood</td>
			<td>11.3</td>
			<td>7.6</td>
			<td>12.7</td>
			<td>379</td>
			<td>2.48 x 103</td>
			<td>13.2</td>
			<td>0.0353</td>
		</tr>
		<tr>
			<td>Father</td>
			<td>Blood</td>
			<td>10.3</td>
			<td>7.7</td>
			<td>0.0167</td>
			<td>1.08</td>
			<td>3.42 x 103</td>
			<td>0.0341</td>
			<td>0.439</td>
		</tr>
		<tr>
			<td>Mother</td>
			<td>Blood</td>
			<td>10.8</td>
			<td>7.6</td>
			<td>0.0136</td>
			<td>0.956</td>
			<td>3.04 x 103</td>
			<td>0.0313</td>
			<td>0.637</td>
		</tr>
		<tr>
			<td>Donor-1</td>
			<td>Blood</td>
			<td>11.7</td>
			<td>7.3</td>
			<td>-</td>
			<td>1.64</td>
			<td>3.01x 103</td>
			<td>0.0543</td>
			<td>0.414</td>
		</tr>
		<tr>
			<td>Donor-2</td>
			<td>Blood</td>
			<td>10.5</td>
			<td>7.6</td>
			<td>-</td>
			<td>1.06</td>
			<td>2.90 x 103</td>
			<td>0.0406</td>
			<td>0.539</td>
		</tr>
		<tr>
			<td>Donor-3</td>
			<td>Blood</td>
			<td>17.6</td>
			<td>7.9</td>
			<td>-</td>
			<td>4.24</td>
			<td>5.65 x 103</td>
			<td>0.0713</td>
			<td>0.783</td>
		</tr>
		<tr>
			<td>Donor-4</td>
			<td>Blood</td>
			<td>12.3</td>
			<td>7.6</td>
			<td>-</td>
			<td>2.38</td>
			<td>4.16 x 103</td>
			<td>0.0666</td>
			<td>0.557</td>
		</tr>
		<tr>
			<td>Donor-5</td>
			<td>Blood</td>
			<td>19.2</td>
			<td>7</td>
			<td>-</td>
			<td>1.48</td>
			<td>6.79 x 103</td>
			<td>0.0213</td>
			<td>0.571</td>
		</tr>
		<tr>
			<td>Donor-6</td>
			<td>Blood</td>
			<td>14.4</td>
			<td>6.7</td>
			<td>-</td>
			<td>3.44</td>
			<td>4.67 x 103</td>
			<td>0.0728</td>
			<td>0.729</td>
		</tr>
	</tbody>
</table>
Table 4: Results of the dPCR assay for APC somatic mosaicism.&#160;1NTC: no-template control; Donor: healthy donor. 2DIN: DNA integrity number. 3Iwaizumi et al.9, Hum Genome Var. 2 15057 (2015). 4The experiments were run in triplicate and independently repeated 3x; the data are expressed as the mean value; RSD: relative standard deviation; N/A: not applicable. The table has been modified from Kahyo et al.10.

Watch this Scientific Journal Video about Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format at JoVE

Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

Digital polymerase chain reaction (PCR) is a useful tool for the high-sensitivity detection of single nucleotide variants and DNA copy number variants. Here, we demonstrate key considerations for measuring rare variants in the human genome using digital PCR with the chip-in-a-tube format.

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as ...

digital-polymerase-chain-reaction-assay-for-genetic-variation

Research

JoVE Journal

Cancer Research

10.8K Views.  Hamamatsu University School of Medicine. Digital polymerase chain reaction (PCR) is a useful tool for the high-sensitivity detection of single nucleotide variants and DNA copy number variants. Here, we demonstrate key considerations for measuring rare variants in the human genome using digital PCR with the chip-in-a-tube format.

Video: Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the context of a whole organism. Sophisticated techniques to generate genetic mosaics facilitate induction of visually marked, genetically defined clones surrounded by normal tissue. The clones can be analyzed through diverse molecular, cellular and omics approaches. This study describes how to generate fluorescently labeled clonal tumors of varying malignancy in the eye/antennal imaginal discs (EAD) of Drosophila larvae using the Mosaic Analysis with a Repressible Cell Marker (MARCM) technique. It describes procedures how to recover the mosaic EAD and brain from the larvae and how to process them for simultaneous imaging of fluorescent transgenic reporters and antibody staining. To facilitate molecular characterization of the mosaic tissue, we describe a protocol for isolation of total RNA from the EAD. The dissection procedure is suitable to recover EAD and brains from any larval stage. The fixation and staining protocol for imaginal discs works with a number of transgenic reporters and antibodies that recognize Drosophila proteins. The protocol for RNA isolation can be applied to various larval organs, whole larvae, and adult flies. Total RNA can be used for profiling of gene expression changes using candidate or genome-wide approaches. Finally, we detail a method for quantifying invasiveness of the clonal tumors. Although this method has limited use, its underlying concept is broadly applicable to other quantitative studies where cognitive bias must be avoided.

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

This protocol demonstrates how to generate fluorescently marked, genetically defined clonal tumors in the Drosophila eye/antennal imaginal discs (EAD). It describes how to dissect the EAD and brain from the third instar larvae and how to process them to visualize and quantify gene expression changes and tumor invasiveness.

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the ...

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

The inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene plays a crucial role in the development of hemangioblastomas (HBs) within the human central nervous system (CNS). However, both the cytological origin and the evolutionary process of HBs (including neovascularization) remain controversial, and anti-angiogenesis for VHL-HBs, based on classic HB angiogenesis, have produced disappointing results in clinical trials. One major obstacle to the successful clinical translation of anti-vascular treatment is the lack of a thorough understanding of neovascularization in this vascular tumor. In this article, we present a comprehensive procedure to evaluate in vitro whether classic tumor angiogenesis exists in HBs, as well as its role in HBs. With this procedure, researchers can accurately understand the complexity of HB neovascularization and identify the function of this common form of angiogenesis in HBs. These protocols can be used to evaluate the most promising anti-vascular therapy for tumors, which has high translational potential either for tumors treatment or for aiding in the optimization of the anti-angiogenic treatment for HBs in future translations. The results highlight the complexity of HB neovascularization and suggest that this common form angiogenesis is only a complementary mechanism in HB neovascularization.

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

This paper presents a comprehensive procedure to evaluate in vitro whether classic tumor angiogenesis exists in hemangioblastomas (HBs) and its role in HBs. The results highlight the complexity of HB-neovascularization and suggest that this common form of angiogenesis is only a complementary mechanism in the HB-neovascularization.

The inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene plays a crucial role in the development of hemangioblastomas (HBs) within the human ...

Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including osteosarcoma--one of the most frequent primary non-hematologic malignancies in the childhood and adolescence. Therefore, LFS provides an ideal model to study this malignancy. Taking advantage of iPSC methodologies, LFS-associated osteosarcoma can be successfully modeled by differentiating LFS patient iPSCs to mesenchymal stem cells (MSCs), and then to osteoblasts--the cells of origin for osteosarcomas. These LFS osteoblasts recapitulate oncogenic properties of osteosarcoma, providing an attractive model system for delineating the pathogenesis of osteosarcoma. This manuscript demonstrates a protocol for the generation of iPSCs from LFS patient fibroblasts, differentiation of iPSCs to MSCs, differentiation of MSCs to osteoblasts, and in vivo tumorigenesis using LFS osteoblasts. This iPSC disease model can be extended to identify potential biomarkers or therapeutic targets for LFS-associated osteosarcoma.

Here, we present a protocol for the generation of induced pluripotent Stem Cells (iPSCs) from Li-Fraumeni Syndrome (LFS) patient derived fibroblasts, differentiation of iPSCs via mesenchymal stem cells (MSCs) to osteoblasts, and modeling in vivo tumorigenesis using LFS patient-derived osteoblasts.

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including ...

Patient-derived Heterogeneous Xenograft Model of Pancreatic Cancer Using Zebrafish Larvae as Hosts for Comparative Drug Assessment

Patient-derived tumor xenograft (PDX) and cell-derived tumor xenograft (CDX) are important techniques for preclinical assessment, medication guidance and basic cancer researches. Generations of PDX models in traditional host mice are time-consuming and only working for a small proportion of samples. Recently, zebrafish PDX (zPDX) has emerged as a unique host system, with the characteristics of small-scale and high efficiency. Here, we describe an optimized methodology for generating a dual fluorescence-labeled tumor xenograft model for comparative chemotherapy assessment in zPDX models. Tumor cells and fibroblasts were enriched from freshly-harvested or frozen pancreatic cancer tissue at different culture conditions. Both cell groups were labeled by lentivirus expressing green or red fluorescent proteins, as well as an anti-apoptosis gene BCL2L1. The transfected cells were pre-mixed and co-injected into the 2 dpf larval zebrafish that were then bred in modified E3 medium at 32 &#176;C. The xenograft models were treated by chemotherapy drugs and/or BCL2L1 inhibitor, and the viabilities of both tumor cells and fibroblasts were investigated simultaneously. In summary, this protocol allows researchers to quickly generate a large amount of zPDX models with a heterogeneous tumor microenvironment and provides a longer observation window and a more precise quantitation in assessing the efficiency of drug candidates.

This protocol describes optimization procedures in a virus-based dual fluorescence-labeled tumor xenograft model using larval zebrafish as hosts. This heterogeneous xenograft model mimics the tissue composition of pancreatic cancer microenvironment in vivo and serves as a more precise tool for assessing drug responses in personalized zPDX (zebrafish patient-derived xenograft) models.

Patient-derived tumor xenograft (PDX) and cell-derived tumor xenograft (CDX) are important techniques for preclinical assessment, medication guidance and ...

Droplet Digital TRAP (ddTRAP): Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction

The telomere repeat amplification protocol (TRAP) is the most widely used assay to detect telomerase activity within a given a sample. The polymerase chain reaction (PCR)-based method allows for robust measurements of enzyme activity from most cell lysates. The gel-based TRAP with fluorescently labeled primers limits sample throughput, and the ability to detect differences in samples is restricted to two fold or greater changes in enzyme activity. The droplet digital TRAP, ddTRAP, is a highly sensitive approach that has been modified from the traditional TRAP assay, enabling the user to perform a robust analysis on 96 samples per run and obtain absolute quantification of the DNA (telomerase extension products) input within each PCR. Therefore, the newly developed ddTRAP assay overcomes the limitations of the traditional gel-based TRAP assay and provides a more efficient, accurate, and quantitative approach to measuring telomerase activity within laboratory and clinical settings.

Droplet Digital TRAP ddTRAP: Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction

We successfully converted the standard telomere repeat amplification protocol (TRAP) assay to be employed in droplet digital polymerase chain reactions. This new assay, called ddTRAP, is more sensitive and quantitative, allowing for better detection and statistical analysis of telomerase activity within various human cells.

The telomere repeat amplification protocol (TRAP) is the most widely used assay to detect telomerase activity within a given a sample. The polymerase ...

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in&#160;patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.

Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular ...

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples from cancer patients often directly influences diagnosis, prognosis, and/or therapy selection. As a result, the accurate detection of gene fusions has become a critical component of clinical management for many disease types. Until recently, clinical gene fusion detection was predominantly accomplished through the use of single-gene assays. However, the ever-growing list of gene fusions with clinical significance has created a need for assessing fusion status of multiple genes simultaneously. Next generation sequencing (NGS)-based testing has met this demand through the ability to sequence nucleic acid in massively parallel fashion. Multiple NGS-based approaches that employ different strategies for gene target enrichment are now available for use in clinical molecular diagnostics, each with its own strengths and weaknesses. This article describes the use of anchored multiplex PCR (AMP)-based target enrichment and library preparation followed by NGS to assess for gene fusions in clinical solid tumor specimens. AMP is unique among amplicon-based enrichment approaches in that it identifies gene fusions regardless of the identity of the fusion partner. Detailed here are both the wet-bench and data analysis steps that ensure accurate gene fusion detection from clinical samples.

This article details the use of an anchored multiplex polymerase chain reaction-based library preparation kit followed by next-generation sequencing to assess for oncogenic gene fusions in clinical solid tumor samples. Both wet-bench and data analysis steps are described.

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples ...

Enhanced Viability for Ex vivo 3D Hydrogel Cultures of Patient-Derived Xenografts in a Perfused Microfluidic Platform

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically stable, thereby preserving molecular, genetic, and histological features, as well as heterogeneity of the original tumor. However, using these models to perform a multitude of experiments, including drug screening, is prohibitive both in terms of cost and time. Three-dimensional (3D) culture systems are widely viewed as platforms in which cancer cells retain their biological integrity through biochemical interactions, morphology, and architecture. Our team has extensive experience culturing PDX cells in vitro using 3D matrices composed of hyaluronic acid (HA). In order to separate mouse fibroblast stromal cells associated with PDXs, we use rotation culture, where stromal cells adhere to the surface of tissue culture-treated plates while dissociated PDX tumor cells float and self-associate into multicellular clusters. Also floating in the supernatant are single, often dead cells, which present a challenge in collecting viable PDX clusters for downstream encapsulation into hydrogels for 3D cell culture. In order to separate these single cells from live cell clusters, we have employed density step gradient centrifugation. The protocol described here allows for the depletion of non-viable single cells from the healthy population of cell clusters that will be used for further in vitro experimentation. In our studies, we incorporate the 3D cultures in microfluidic plates which allow for media perfusion during culture. After assessing the resultant cultures using a fluorescent image-based viability assay of purified versus non-purified cells, our results show that this additional separation step substantially reduced the number of non-viable cells from our cultures.

This protocol demonstrates methods to enable extended in vitro culture of patient-derived xenografts (PDX). One step enhances overall viability of multicellular cluster cultures in 3D hydrogels, through straightforward removal of non-viable single cells. A secondary step demonstrates best practices for PDX culture in a perfused microfluidic platform.

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically ...

Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous metastasis models are available. Thus, the experimental metastasis model involving tail-vein injection of suitable cell lines is a mainstay of metastasis research. When cancer cells are injected into the lateral tail-vein, the lung is their preferred site of colonization. A potential limitation of this technique is the accurate quantification of the metastatic lung tumor burden. While some investigators count macrometastases of a pre-defined size and/or include micrometastases following sectioning of tissue, others determine the area of metastatic lesions relative to normal tissue area. Both of these quantification methods can be exceedingly difficult when the metastatic burden is high. Herein, we demonstrate an intravenous injection model of lung metastasis followed by an advanced method for quantifying metastatic tumor burden using image analysis software. This process allows for investigation of multiple end-point parameters, including average metastasis size, total number of metastases, and total metastasis area, to provide a comprehensive analysis. Furthermore, this method has been reviewed by a veterinary pathologist board-certified by the American College of Veterinary Pathologists (SEK) to ensure accuracy.

Intravenous injection of cancer cells is often used in metastasis research, but the metastatic tumor burden can be difficult to analyze. Herein, we demonstrate a tail-vein injection model of metastasis and include a novel approach to analyze the resulting metastatic lung tumor burden.

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous ...

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture models. PDOs have been successfully generated from a variety of human tumors to recapitulate the architecture and function of tumor tissue accurately and efficiently. However, PDOs are unsuitable for an in vitro high-throughput assay system (HTS) or cell analysis using 96-well or 384-well plates when evaluating anticancer drugs because they are heterogeneous in size and form large clusters in culture. These cultures and assays use extracellular matrices, such as Matrigel, to create tumor tissue scaffolds. Therefore, PDOs have a low throughput and high cost, and it has been difficult to develop a suitable assay system. To address this issue, a simpler and more accurate HTS was established using PDOs to evaluate the potency of anticancer drugs and immunotherapy. An in vitro HTS was created that uses PDOs established from solid tumors cultured in 384-well plates. An HTS was also developed for assessment of antibody-dependent cellular cytotoxicity activity to represent the immune response using PDOs cultured in 96-well plates.

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

A highly accurate in vitro high-throughput assay system was developed to evaluate anticancer drugs using patient-derived tumor organoids (PDOs), similar to cancer tissues but are unsuitable for in vitro high-throughput assay systems with 96-well and 384-well plates.

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture ...