The authors have no acknowledgments.

Patients were recruited at the Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) of Meldola (FC, Italy) between 2013 and 2015. Enrolled patients were into protocol IRSTB002, approved by the Ethics Committee of IRST - IRCCS AVR (25/10/2012, ver. 1). All methods were performed in accordance with relevant guidelines and regulations. Written informed consent was obtained from all patients.
1. DNA extraction from stool
<ol>
	<li>Use a kit to prepare stool samples (see Table of Materials). Select and treat the fecal material by performing the extraction according to the manufacturer&#8217;s instructions. Amplify the purified DNA directly or store at -20 &#176;C for subsequent analysis.</li>
</ol>
2. Preparation of positive control, standards, spike-in DNA, and clinical samples
<ol>
	<li>Preparation of standards and samples
	<ol>
		<li>To prepare the positive control, standards, spike-in DNA, and all clinical samples, centrifuge an aliquot of positive control, standards, and spike-in DNA, then resuspend each reagent by adding the correct amount of provided water (see below). Then, carefully vortex the positive control, standard, and spike-in DNA, then centrifuge for 10 s. To achieve a complete resuspension of the dry reagents, store the liquid reagents at room temperature (RT) for 30 min before use.
		<ol>
			<li>The positive control is human DNA in a dry format. Resuspend each aliquot with 750 &#181;L of water.</li>
			<li>The spike-in DNA is salmon (Oncorhynchus keta) DNA, which is used as an exogenous internal control to verify the possible presence of inhibitors in DNA samples extracted from stool. Resuspend each aliquot with 100 &#181;L of water.</li>
		</ol>
		</li>
		<li>To prepare the standard curve, produce four 1:5 dilutions starting from the stock solution. The standard points must be 10 ng/reaction, 2 ng/reaction, 0.4 ng/reaction, and 0.08 ng/reaction.</li>
	</ol>
	</li>
	<li>Preparation of the 1x spike-in DNA
	<ol>
		<li>Prepare the spike-in DNA control directly before use.</li>
		<li>Prepare the 1x spike-in DNA control by mixing 5 &#181;L of FL-DNa spike with 20 &#181;L of sterile water. The number of 1x spike-in DNA control samples will be prepared according to the number of the samples to be analyzed, plus the positive control.</li>
	</ol>
	</li>
	<li>Preparation of samples
	<ol>
		<li>Mix 75 &#181;L of the samples (clinical samples or positive control) with 25 &#181;L of 1x spike-in DNA, yielding a total volume of 100 &#181;L.</li>
	</ol>
	</li>
</ol>
3. Amplification and determination of the FL-DNA value using qPCR Easy PGX
NOTE: Complete amplification mixtures containing specific primers and probes targeting the human DNA and the internal control are provided in a lyophilised format in 8 well strips for FL-DNA Mix A and FL-DNA Mix B. Standards, positive and negative controls, and samples must be amplified with both lyophilized mixes. Clinical samples only must only be amplified in duplicate with both lyophilized mixes.
<ol>
	<li>See the Table of Materials for qPCR instrument and operating software.
	<ol>
		<li>Open the operating software and set up the plate and thermal profile:
		<ol>
			<li>Set up the plate as shown in Table 1.
			<ol>
				<li>Set the well type for all eight positions in column 1 as Standard.</li>
				<li>Set the well type for the A2 and B2 wells as NTC.</li>
				<li>Set the well type for C2 and D2 (the positive controls) as Unknown.</li>
				<li>Set the well type for all other positions as Unknown.</li>
				<li>Select all 96 positions, and add the Dyes FAM and HEX. Click Sync Plate.</li>
			</ol>
			</li>
			<li>Set the thermal profile according to Table 2.</li>
		</ol>
		</li>
		<li>Centrifuge the needed number of strips for 10 s to bring the contents to the bottom of the tube.</li>
		<li>Gently remove the seals from the strips, while paying attention to retain the contents, and add to the respective strips: negative control: 20 &#181;L of water; sample: 20 &#181;L of DNA; standard curve: 20 &#181;L of standard 1, 2, 3, or 4; positive control: 20 &#181;L of positive control.</li>
		<li>Close carefully all the strips using the 8 strip flat optical caps and vortex for few seconds.</li>
		<li>Centrifuge the strips for 10 s and load them into the instrument. Then, start the run.</li>
	</ol>
	</li>
</ol>
4. Data analysis
NOTE: Data analysis can be performed automatically or manually depending on the software (see Table of Materials).
<ol>
	<li>At the end of the run, select columns A, C, E, G for &#34;FAM: FL-DNA-A&#34;&#160;and &#34;HEX: IC&#34;, and columns B, D, F, H for &#34;FAM: FL-DNA-B&#34;&#160;and &#34;HEX: IC&#34;.</li>
	<li>Set the following for the Standard Quantities Starting Amount: 10 ng/reaction for A1 and B1 wells, 2 ng/reaction for C1 and D1, 0.4 ng/reaction for E1 and F1, and 0.08 ng/reaction for G1 and H1.</li>
	<li>Set Threshold Fluorescence values to 150 for both FAM (FL-DNA A and FL-DNA B) and HEX (IC) channels.</li>
	<li>In the box Result Table, click Column Options | Select All | Ok to obtain the results in both channels with their respective Cq (&#8710;R) and &#8710;R last values. 
	NOTE: These values are supplied by the Real Time PCR instrument software. &#916;R last corresponds to the fluorescence value normalized to the last amplification cycle.</li>
	<li>In the box Result Table, right-click on the table to open the context menu and click Send to Excel to export the raw data.</li>
	<li>Check the values of the standards to verify the suitability of the standard curve.</li>
	<li>For each FL-DNA mix, check the R2 [&#34;R&#178; (&#8710;R)&#34;&#160;column] and efficiency [&#34;Efficiency (%)&#34;&#160;column] values. If they are in an acceptable range, it is possible to proceed with analysis accordingly to manufacturer&#8217;s instructions (Table 3).</li>
	<li>If the results of the FAM channel are not in the expected range, omit one point of the standard curve and reanalyze the run.</li>
	<li>Determine the values of the negative and positive controls with the following formula, considering the &#34;No Cq&#34;&#160;values as zero: 
	<img alt="Equation 1" src="/files/ftp_upload/59426/59426eq1.jpg" /> 
	<img alt="Equation 2" src="/files/ftp_upload/59426/59426eq2.jpg" /></li>
	<li>Compare the obtained values with those reported in Table 4.</li>
	<li>If the reaction controls are in the range of expected values, proceed with analysis of the samples. 
	NOTE: Verify that the Cq values obtained are generated from a real amplification reaction (sigmoidal fluorescence curve) and not from an artifact (linear fluorescence curve).</li>
	<li>To analyze suitability of the sample for each FL-DNA mix, compare the Cq values of the HEX channel. If the value is &#8805;16, proceed with analysis of the samples. If the value is &#60;16 or there is no Cq, it is likely due to a dispensing error of the FL-DNA Spike. Therefore, it is not possible to analyze the samples.</li>
	<li>Calculate the average of the Cq values in the &#34;HEX&#34;&#160;channel of the positive control using the following formula: 
	<img alt="Equation 3" src="/files/ftp_upload/59426/59426eq3.jpg" /></li>
	<li>Calculate the average of the Cq values in the &#34;HEX&#34;&#160;channel of the sample replicates using the following formula: 
	<img alt="Equation 4" src="/files/ftp_upload/59426/59426eq4.jpg" /></li>
	<li>Calculate the &#8710;CqHEX values according to the following formula: 
	<img alt="Equation 5" src="/files/ftp_upload/59426/59426eq5.jpg" /></li>
	<li>Compare the &#8710;CqHEX values of the samples with those reported in Table 5.&#160;</li>
	<li>For each mix (Mix A and Mix B), compare the Cq values of the FAM channel with those reported in Table 6.</li>
	<li>To determine the FL-DNA value of each suitable sample, use the following formula, considering the &#34;No Cq&#34;&#160;values as zero: 
	<img alt="Equation 6" src="/files/ftp_upload/59426/59426eq6.jpg" /> 
	<img alt="Equation 2" src="/files/ftp_upload/59426/59426eq2.jpg" /> 
	NOTE: Colorectal cancer risk and prevalence is a function of iFOBT and FL-DNA evaluations according to the Fagan nomogram results obtained by Rengucci et al.12 (Table 7).</li>
</ol>

<ol>
	<li>Fearon, E. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+Genetics+of+Colorectal+Cancer.">Molecular Genetics of Colorectal Cancer.</a> Annual Review of Pathology. 6, 479-507 (2011).</li><li>Sears, C. L., Garrett, W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbes,+Microbiota,+and+Colon+Cancer.">Microbes, Microbiota, and Colon Cancer.</a> Cell Host and Microbe. 15, 317-328 (2014).</li><li>Levin, B., 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=Screening+and+Surveillance+for+the+Early+Detection+of+Colorectal+Cancer+and+Adenomatous+Polyps,+2008:+A+Joint+Guideline+From+the+American+Cancer+Society,+the+US+Multi-Society+Task+Force+on+Colorectal+Cancer,+and+the+American+College+of+Radiology.">Screening and Surveillance for the Early Detection of Colorectal Cancer and Adenomatous Polyps, 2008: A Joint Guideline From the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology.</a> Gastroenterology. 134, 1570-1595 (2008).</li><li>Bosch, L. 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=Molecular+tests+for+colorectal+cancer+screening.">Molecular tests for colorectal cancer screening.</a> Clinical Colorectal Cancer. 10, 8-23 (2011).</li><li>Ahlquist, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+detection+of+colorectal+neoplasia.">Molecular detection of colorectal neoplasia.</a> Gastroenterology. 138, 2127-2139 (2010).</li><li>Calistri, D., 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=Fecal+multiple+molecular+tests+to+detect+colorectal+cancer+in+stool.">Fecal multiple molecular tests to detect colorectal cancer in stool.</a> Clinical Gastroenterology and Hepatology. 1, 377-383 (2003).</li><li>Calistri, D., 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=Detection+of+colorectal+cancer+by+a+quantitative+fluorescence+determination+of+DNA+amplification+in+stool.">Detection of colorectal cancer by a quantitative fluorescence determination of DNA amplification in stool.</a> Neoplasia. 6, 536-540 (2004).</li><li>Calistri, D., 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=Quantitative+fluorescence+determination+of+long-fragment+DNA+in+stool+as+a+marker+for+the+early+detection+of+colorectal+cancer.">Quantitative fluorescence determination of long-fragment DNA in stool as a marker for the early detection of colorectal cancer.</a> Cellular Oncology. 31, 11-17 (2009).</li><li>Calistri, D., 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=Fecal+DNA+for+noninvasive+diagnosis+of+colorectal+cancer+in+immunochemical+fecal+occult+blood+test-positive+individuals.">Fecal DNA for noninvasive diagnosis of colorectal cancer in immunochemical fecal occult blood test-positive individuals.</a> Cancer Epidemiology Biomarkers and Prevention. 19, 2647-2654 (2010).</li><li>De Maio, G., 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=Circulating+and+stool+nucleic+acid+analysis+for+colorectal+cancer+diagnosis.">Circulating and stool nucleic acid analysis for colorectal cancer diagnosis.</a> World Journal of Gastroenterology. 20, 957-967 (2014).</li><li>Rengucci, C., 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=Improved+stool+DNA+integrity+method+for+early+colorectal+cancer+diagnosis.">Improved stool DNA integrity method for early colorectal cancer diagnosis.</a> Cancer Epidemiology Biomarkers and Prevention. 23, 2553-2560 (2014).</li></ol>

Maura Menghi is full-time employee of Diatech Pharmacogenetics srl.

Previous studies have demonstrated that DNA integrity analysis of stools extracted by manual and semi-automatic approaches can represent an alternative tool for the early detection of colorectal lesions7,8,9,10,11,12. Molecular, noninvasive screening tests have been developed over the years for the detection of colorectal cancer, but the widespread diffusion of these methods is limited due to time-consuming approaches and poor cost-effectiveness compared to other screening tests.
This approach is relatively cheap and not too time-consuming. It also has increased accuracy in detecting colorectal lesions due to a new procedure requiring few manual steps. The approach described here is fast with fewer manual steps, and it is able to be easily performed on many samples per week. The DNA extraction does not present particular issues and can be performed through easy manual steps or use of an automatic instrument. In the latter case, it is necessary to determine the automatic DNA extraction instrument, allowing for the most reproducible results. The most critical step of DNA extraction is the collection of stool and method of its storage before DNA extraction. It is advisable to keep the stool frozen and proceed with &#160;extraction as soon as possible.
Another critical issue is represented by possible inhibitors of the amplification reactions. The fecal extraction is not able to purify the genomic DNA, as impurities compromise the correct amplification reaction. In this regard, the protocol requires the use of spike-in DNA for verifying the presence/absence of reaction inhibitors.
Until recently, the fecal occult blood test is the main approach used to detect colorectal lesions in screening programs; although, it presents some limits in terms of accuracy. An alternative strategy for the diagnosis of colorectal cancer is based on the analysis of DNA from exfoliated cells excreted in stool. Several approaches have been evaluated in the past year, but none are available for use in screening programs.
The FL-DNA integrity value can be a useful alternative, which in combination with the standard screening iFOBT test value, can predict the presence of tumors and/or high-risk adenomas11,12 by a Fagan Nomogram approach10 (Table 7). This approach estimates the combined test probability of neoplastic lesion presence, improving diagnostic accuracy compared to the standard approach used alone.
This information may help clinicians in planning diagnostic tests in addition to an appropriate colonoscopy and personalizing its surveillance. Indeed, the FL-DNA kit simplifies the manual steps and ensures stable and consistent results. However, some issues remain to be clarified to improve diagnostic accuracy of the method. For instance, the frequency at which the tests should be performed and number of stool samples that need to be analyzed at specific timepoints for each individual should be carefully selected. Given that this test must be performed concurrently with iFOBT, a method that requires collection every 2 years, as is standard in numerous screening protocols, is necessary to verify the effectiveness of this test as a replacement or alternative to the current screening tests.

An erratum was issued for:&#160;<a href="https://www.jove.com/t/59426/evaluation-colorectal-cancer-risk-prevalence-stool-dna-integrity">Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection</a>. An&#160;affiliation&#160;was&#160;updated.
The first&#160;affiliation was updated from:
Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST)
to:
Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy

An erratum was issued for:&#160;<a href="https://www.jove.com/t/59426/evaluation-colorectal-cancer-risk-prevalence-stool-dna-integrity">Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection</a>. An&#160;affiliation&#160;was&#160;updated.

Erratum: Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Colorectal cancer (CRC) derives from a multi-step process in which healthy epithelium slowly develops into adenomas or polyps, which progress into malignant carcinomas over time1,2. Despite CRC&#39;s high incidence rate, a downward trend in the percentage of deaths has been observed over the past decade3. Indeed, early diagnostic tools adopted in screening programs have led to early detection and removal of pre-neoplastic adenomas or polyps4. However, due to the different technical limits, none of these methods is optimal. Indeed, in order to improve sensitivity and specificity, many stool DNA tests have been proposed alone or in combination with current routine diagnostic tests5,6.
Typically, healthy mucosa sheds into the fecal stream apoptotic colonocytes, whereas diseased mucosa exfoliates non-apoptotic colonocytes. Fragments of 200 bp or more in length characterize non-apoptotic DNA. This DNA is called long DNA (L-DNA) and has become a utilizable biomarker for CRC early diagnosis. The L-DNA can be isolated from stool specimen and quantified by qPCR using an in vitro diagnostic FL-DNA kit7,8,9,10,11,12.
The test consists of two assays for the detection of FL-DNA fragments ranging from 138 bp to 339 bp. Each assay allows the amplification of FL-DNA (FAM) as well as spike-in DNA (HEX). To ensure optimal amplification of all fragments, the test has been divided into two assays (named &#34;A&#34;&#160;and &#34;B&#34;). The A assay detects two regions of exon 14 of the APC gene (NM_001127511) and a fragment of exon 7 of the TP53 gene (NM_001276760). The B assay detects a fragment of&#160; exon 14 of the APC gene (NM_001127511) and two regions of exons 5 and 8 of the TP53 gene (NM_001276760). The assays do not distinguish between the regions detected. The spike-in DNA corresponds to the Oncorhynchus keta salmon DNA and enables verification that the procedure has been done properly and checks for the possible presence of inhibitors, which may yield false negative results. The FL-DNA concentration is evaluated by absolute quantification using the standard curve method and is expressed as ng/reaction.
The FL-DNA method is a non-invasive and inexpensive stool DNA test that, combined with the immunochemical-based fecal occult blood test (iFOBT), is currently used in CRC screening programs and allows for better predictions of CRC and/or high-risk adenoma lesions12.

<table border="0" cellpadding="0" cellspacing="0" style="width:1051px;" width="1051">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="63">
			<td height="63" style="height:63px;width:267px;">1.5 mL and 2 mL polypropylene twist-lock tubes (DNase-, RNase-, DNA-, PCR inhibitor-free)</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td style="width:525px;">Consumables required for DNA extraction and Real Time PCR</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">Absolute Ethanol (quality of analytical degree)</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td>Reagent required for DNA extraction</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:267px;">Benchtop centrifuge&#160;</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td>Maximum speed of 20000 x g. Instrument required for DNA extraction</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;">EasyPGX analysis software version 2.0.0</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td>RT800-SW</td>
			<td>Analysis software&#160;</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">EasyPGX centrifuge/vortex 8-well strips</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td style="width:119px;">RT803</td>
			<td>Instrument recommended for the Real Time PCR assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">EasyPGX qPCR instrument 96&#160;</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td style="width:119px;">RT800-96</td>
			<td>Instrument recommended for the Real Time PCR assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">EasyPGX ready FL-DNA</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td style="width:119px;">RT029</td>
			<td>Kit required for the Real Time PCR assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">Micropipettes (volumes from 1 to 1.000 &#181;L)</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td>Consumables required for DNA extraction and Real Time PCR</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:267px;">Powder-free disposable gloves</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td>Consumables required for DNA extraction and Real Time PCR</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:267px;">QIAamp Fast DNA Stool</td>
			<td style="width:140px;">Qiagen</td>
			<td style="width:119px;">51604</td>
			<td>Kit recommended for the DNA extraction and purification from stool</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">Sterile filter tips DNase-, RNase-free (volumes from 1 to 1.000 &#181;L)</td>
			<td style="width:140px;"></td>
			<td style="width:119px;"></td>
			<td>Consumables required for DNA extraction and Real Time PCR</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">Thermal block e.g. EasyPGX dry block</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td style="width:119px;">RT801</td>
			<td>Instrument required for DNA extraction</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:267px;">Vortex e.g. EasyPGX centrifuge/vortex 1.5 ml&#160;</td>
			<td style="width:140px;">Diatech Pharmacogenetics</td>
			<td style="width:119px;">RT802</td>
			<td>Instrument required for DNA extraction</td>
		</tr>
	</tbody>
</table>

evaluation of colorectal cancer risk and prevalence by stool dna integrity detection

Nowadays, stool DNA can be isolated and analyzed by several methods. The long fragments of DNA in stool can be detected by a qPCR assay, which provides a reliable probability of the presence of pre-neoplastic or neoplastic colorectal lesions. This method, called fluorescence long DNA (FL-DNA), is a fast, non-invasive procedure that is an improvement upon the primary prevention system. This method is based on evaluation of fecal DNA integrity by quantitative amplification of specific targets of genomic DNA. In particular, the evaluation of DNA fragments longer than 200 bp allows for detection of patients with colorectal lesions with very high specificity. However, this system and all currently available stool DNA tests present some general issues that need to be addressed (e.g., the frequency at which tests should be carried out and optimal number of stool samples collected at each timepoint for each individual). However, the main advantage of FL-DNA is the possibility to use it in association with a test currently used in the CRC screening program, known as the immunochemical-based fecal occult blood test (iFOBT). Indeed, both tests can be performed on the same sample, reducing costs and achieving a better prediction of the eventual presence of colorectal lesions.

The workflow of this protocol is shown in Figure 1. The workflow provides two control steps and different actions according to these step results. First, if a sample presents unsuitable controls, the amplification must be repeated. Second, if the amplification is inhibited, the sample must be reprocessed from the beginning or classified as not valuable.
Figure 2 shows the fluorescence curves produced by positive and negative samples. (A) Shown is an example of a suitable positive sample. The sample signal on the HEX channel is within the acceptable range. The positive signal is above the threshold on the FAM channel. (B) Shown is an example of a suitable negative/not positive sample. The sample signal is within the acceptable range on the HEX channel. The negative control signal is below the threshold on the FAM channel. (C) Shown is an example of a not-suitable sample. The sample signal is not within the acceptable range on the HEX channel; thus, a potential inhibition can be assumed. This sample must be repeated, starting from the extraction.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59426/59426fig1.jpg" /> 
Figure 1: Workflow for FL-DNA quantification. <a href="https://www.jove.com/files/ftp_upload/59426/59426fig1large.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/59426/59426fig2.jpg" /> 
Figure 2: Fluorescence curves showing the amplification of Mix A (or Mix B) target genes (channel FAM) and internal control (channel HEX). (A) FL-DNA positive sample. (B) FL-DNA negative sample. (C) Inhibition of sample amplification. Red curve: positive control; green curve: negative control; black curve: clinical sample. <a href="https://www.jove.com/files/ftp_upload/59426/59426fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:font-size="7px" fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td>1</td>
			<td>2</td>
			<td>3</td>
			<td>4</td>
			<td>5</td>
			<td>6</td>
			<td>7</td>
			<td>8</td>
			<td>9</td>
			<td>10</td>
			<td>11</td>
			<td>12</td>
			<td></td>
			<td></td>
			<td>X&#160;</td>
		</tr>
		<tr>
			<td>A</td>
			<td>Standard 1</td>
			<td>WATER</td>
			<td>DNA2</td>
			<td>DNA4</td>
			<td>DNA6</td>
			<td>DNA8</td>
			<td>DNA10</td>
			<td>DNA12</td>
			<td>DNA14</td>
			<td>DNA16</td>
			<td>DNA18</td>
			<td>DNA20</td>
			<td></td>
			<td>1</td>
			<td>FL-DNA Mix A</td>
		</tr>
		<tr>
			<td>B</td>
			<td>Standard 1</td>
			<td>WATER</td>
			<td>DNA2</td>
			<td>DNA4</td>
			<td>DNA6</td>
			<td>DNA8</td>
			<td>DNA10</td>
			<td>DNA12</td>
			<td>DNA14</td>
			<td>DNA16</td>
			<td>DNA18</td>
			<td>DNA20</td>
			<td></td>
			<td>2</td>
			<td>FL-DNA Mix B</td>
		</tr>
		<tr>
			<td>C</td>
			<td>Standard 2</td>
			<td>POS</td>
			<td>DNA2</td>
			<td>DNA4</td>
			<td>DNA6</td>
			<td>DNA8</td>
			<td>DNA10</td>
			<td>DNA12</td>
			<td>DNA14</td>
			<td>DNA16</td>
			<td>DNA18</td>
			<td>DNA20</td>
			<td></td>
			<td>3</td>
			<td>FL-DNA Mix A</td>
		</tr>
		<tr>
			<td>D</td>
			<td>Standard 2</td>
			<td>POS</td>
			<td>DNA2</td>
			<td>DNA4</td>
			<td>DNA6</td>
			<td>DNA8</td>
			<td>DNA10</td>
			<td>DNA12</td>
			<td>DNA14</td>
			<td>DNA16</td>
			<td>DNA18</td>
			<td>DNA20</td>
			<td></td>
			<td>4</td>
			<td>FL-DNA Mix B</td>
		</tr>
		<tr>
			<td>E</td>
			<td>Standard 3</td>
			<td>DNA1</td>
			<td>DNA3</td>
			<td>DNA5</td>
			<td>DNA7</td>
			<td>DNA9</td>
			<td>DNA11</td>
			<td>DNA13</td>
			<td>DNA15</td>
			<td>DNA17</td>
			<td>DNA19</td>
			<td>DNA21</td>
			<td></td>
			<td>5</td>
			<td>FL-DNA Mix A</td>
		</tr>
		<tr>
			<td>F</td>
			<td>Standard 3</td>
			<td>DNA1</td>
			<td>DNA3</td>
			<td>DNA5</td>
			<td>DNA7</td>
			<td>DNA9</td>
			<td>DNA11</td>
			<td>DNA13</td>
			<td>DNA15</td>
			<td>DNA17</td>
			<td>DNA19</td>
			<td>DNA21</td>
			<td></td>
			<td>6</td>
			<td>FL-DNA Mix B</td>
		</tr>
		<tr>
			<td>G</td>
			<td>Standard 4</td>
			<td>DNA1</td>
			<td>DNA3</td>
			<td>DNA5</td>
			<td>DNA7</td>
			<td>DNA9</td>
			<td>DNA11</td>
			<td>DNA13</td>
			<td>DNA15</td>
			<td>DNA17</td>
			<td>DNA19</td>
			<td>DNA21</td>
			<td></td>
			<td>7</td>
			<td>FL-DNA Mix A</td>
		</tr>
		<tr>
			<td>H</td>
			<td>Standard 4</td>
			<td>DNA1</td>
			<td>DNA3</td>
			<td>DNA5</td>
			<td>DNA7</td>
			<td>DNA9</td>
			<td>DNA11</td>
			<td>DNA13</td>
			<td>DNA15</td>
			<td>DNA17</td>
			<td>DNA19</td>
			<td>DNA21</td>
			<td></td>
			<td>8</td>
			<td>FL-DNA Mix B</td>
		</tr>
	</tbody>
</table>
Table 1: Set-up plate with distribution of control, curve, and samples. Column X indicates the number imprinted on the top of the strip.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Step</td>
			<td>Temperature and time</td>
		</tr>
		<tr>
			<td>Hot Start (1 Cycle)</td>
			<td>95 &#176;C for 5 min</td>
		</tr>
		<tr>
			<td>Amplification (40 cycles)</td>
			<td>95 &#176;C for 15 s 
			54 &#176;C for 15 s 
			60 &#176;C for 45 s (Data Collection)</td>
		</tr>
	</tbody>
</table>
Table 2: Thermal profile for DNA amplification.
<img alt="Table 3" src="/files/ftp_upload/59426/59426tbl3v2.jpg" /> 
Table 3: Range of HEX and FAM channel values of the standards to verify suitability of the standard curve.
<img alt="Table 4" src="/files/ftp_upload/59426/59426tbl4v2.jpg" /> 
Table 4: Range of HEX and FAM channel values of negative and positive controls to verify suitability of the run.
<img alt="Table 5" src="/files/ftp_upload/59426/59426tbl5v3.jpg" /> 
Table 5: Range of HEX and FAM channel values of samples to verify suitability of the sample analysis.
<img alt="Table 6" src="/files/ftp_upload/59426/59426tbl6v2.jpg" /> 
Table 6: Mix A and Mix B Cq values of the FAM channel to verify suitability of FL-DNA analysis.
<img alt="Table 7" src="/files/ftp_upload/59426/59426tbl7v2.jpg" /> 
Table 7: Cancer risk evaluation as a function of iFOBT and FL-DNA values. According to the relationship between iFOBT and FL-DNA values, the table estimates the probability of colorectal neoplastic lesions.

Watch this Scientific Journal Video about Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection at JoVE.com

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

The presented diagnostic FL-DNA kit is a time-saving and user-friendly method to determine the reliable probability of the presence of colorectal cancer lesions.

Nowadays, stool DNA can be isolated and analyzed by several methods. The long fragments of DNA in stool can be detected by a qPCR assay, which provides a ...

evaluation-colorectal-cancer-risk-prevalence-stool-dna-integrity

Nanyang Technological University

Research

JoVE Journal

Cancer Research

6.8K Views.  Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy. The presented diagnostic FL-DNA kit is a time-saving and user-friendly method to determine the reliable probability of the presence of colorectal cancer lesions.

Video: Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Cell-Free DNA Integrity Analysis in Urine Samples

Although the presence of circulating cell-free DNA in plasma or serum has been widely shown to be a suitable source of biomarkers for many types of cancer, few studies have focused on the potential use of urine cell-free (UCF) DNA. Starting from the hypotheses that normal apoptotic cells produce highly fragmented DNA and that cancer cells release longer DNA, the potential role of UCF DNA integrity was evaluated as an early diagnostic marker capable of distinguishing between patients with prostate or bladder cancer and healthy individuals.
A UCF DNA integrity analysis is proposed on the basis of four quantitative real-time PCRs of four sequences longer than 250 bp: c-MYC, BCAS1, HER2, and AR. Sequences that frequently have an increased DNA copy number in bladder and prostate cancers were chosen for the analysis, but the method is flexible, and these genes could be substituted with other genes of interest. The potential utility of UCF DNA as a source of biomarkers has already been demonstrated for urologic malignancies, thus paving the way for further studies on UCF DNA characterization. The UCF DNA integrity test has the advantage of being non-invasive, rapid, and easy to perform, with only a few milliliters of urine needed to carry out the analysis.

A method for analyzing DNA integrity in the cell-free supernatant fraction of urine samples is proposed. The method is suitable for early detection of urological malignancies and has proven accurate for the early diagnosis of bladder cancer.

Although the presence of circulating cell-free DNA in plasma or serum has been widely shown to be a suitable source of biomarkers for many types of ...

Isolation of Circulating Tumor Cells in an Orthotopic Mouse Model of Colorectal Cancer

Despite the advantages of easy applicability and cost-effectiveness, subcutaneous mouse models have severe limitations and do not accurately simulate tumor biology and tumor cell dissemination. Orthotopic mouse models have been introduced to overcome these limitations; however, such models are technically demanding, especially in hollow organs such as the large bowel. In order to produce uniform tumors which reliably grow and metastasize, standardized techniques of tumor cell preparation and injection are critical. 
We have developed an orthotopic mouse model of colorectal cancer (CRC) which develops highly uniform tumors and can be used for tumor biology studies as well as therapeutic trials. Tumor cells from either primary tumors, 2-dimensional (2D) cell lines or 3-dimensional (3D) organoids are injected into the cecum and, depending on the metastatic potential of the injected tumor cells, form highly metastatic tumors. In addition, CTCs can be found regularly. We here describe the technique of tumor cell preparation from both 2D cell lines and 3D organoids as well as primary tumor tissue, the surgical and injection techniques as well as the isolation of CTCs from the tumor-bearing mice, and present tips for troubleshooting.

We describe the establishment of orthotopic colorectal tumors via injection of tumor cells or organoids into the cecum of mice and the subsequent isolation of circulating tumor cells (CTCs) from this model.

Despite the advantages of easy applicability and cost-effectiveness, subcutaneous mouse models have severe limitations and do not accurately simulate ...

A Genetically Engineered Mouse Model of Sporadic Colorectal Cancer

Despite the advantages of easy applicability and cost-effectiveness, colorectal cancer mouse models based on tumor cell injection have severe limitations and do not accurately simulate tumor biology and tumor cell dissemination. Genetically engineered mouse models have been introduced to overcome these limitations; however, such models are technically demanding, especially in large organs such as the colon in which only a single tumor is desired.
As a result, an immunocompetent, genetically engineered mouse model of colorectal cancer was developed which develops highly uniform tumors and can be used for tumor biology studies as well as therapeutic trials. Tumor development is initiated by surgical, segmental infection of the distal colon with adeno-cre virus in compound conditionally mutant mice. The tumors can be easily detected and monitored via colonoscopy. We here describe the surgical technique of segmental adeno-cre infection of the colon, the surveillance of the tumor via high-resolution colonoscopy and present the resulting colorectal tumors.

A protocol for the establishment of a genetically engineered mouse model of colorectal cancer by segmental adeno-cre infection and its surveillance via high-resolution colonoscopy is presented.

Despite the advantages of easy applicability and cost-effectiveness, colorectal cancer mouse models based on tumor cell injection have severe limitations ...

Characterizing DNA Repair Processes at Transient and Long-lasting Double-strand DNA Breaks by Immunofluorescence Microscopy

The repair of double-stranded breaks (DSBs) in DNA is a highly coordinated process, necessitating the formation and resolution of multi-protein repair complexes. This process is regulated by a myriad of proteins that promote the association and disassociation of proteins to these lesions. Thanks in large part to the ability to perform functional screens of a vast library of proteins, there is a greater appreciation of the genes necessary for the double-strand DNA break repair. Often knockout or chemical inhibitor screens identify proteins involved in repair processes by using increased toxicity as a marker for a protein that is required for DSB repair. Although useful for identifying novel cellular proteins involved in maintaining genome fidelity, functional analysis requires the determination of whether the protein of interest promotes localization, formation, or resolution of repair complexes. 
The accumulation of repair proteins can be readily detected as distinct nuclear foci by immunofluorescence microscopy. Thus, association and disassociation of these proteins at sites of DNA damage can be accessed by observing these nuclear foci at representative intervals after the induction of double-strand DNA breaks. This approach can also identify mis-localized repair factor proteins, if repair defects do not simultaneously occur with incomplete delays in repair. In this scenario, long-lasting double-strand DNA breaks can be engineered by expressing a rare cutting endonuclease (e.g., I-SceI) in cells where the recognition site for the said enzyme has been integrated into the cellular genome. The resulting lesion is particularly hard to resolve as faithful repair will reintroduce the enzyme's recognition site, prompting another round of cleavage. As a result, differences in the kinetics of repair are eliminated. If repair complexes are not formed, localization has been impeded. This protocol describes the methodology necessary to identify changes in repair kinetics as well as repair protein localization.

Repair of double-strand DNA breaks is a dynamic process, requiring not only formation of repair complexes at the breaks, but also their resolution after the lesion is addressed. Here, we use immunofluorescence microscopy for transient and long-lasting double-stranded breaks as a tool to dissect this genome maintenance mechanism.

The repair of double-stranded breaks (DSBs) in DNA is a highly coordinated process, necessitating the formation and resolution of multi-protein repair ...

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

There is increasing interest in liquid biopsy for cancer diagnosis, prognosis and therapeutic monitoring, creating the need for reliable and useful biomarkers for clinical practice. Here, we present a protocol to extract, reverse transcribe and evaluate the expression levels of circulating miRNAs from plasma samples of patients with colorectal cancer (CRC). microRNAs (miRNAs) are a class of non-coding RNAs of 18-25 nucleotides in length that regulate the expression of target genes at the translational level and play an important role, including that of pro- and anti-angiogenic function, in the physiopathology of various organs. miRNAs are stable in biological fluids such as serum and plasma, which renders them ideal circulating biomarkers for cancer diagnosis, prognosis and treatment decision-making and monitoring. Circulating miRNA extraction was performed using a rapid and effective method that involves both organic and column-based methodologies. For miRNA retrotranscription, we used a multi-step procedure that considers polyadenylation at 3&#39; and the ligation of an adapter at 5&#39; of the mature miRNAs, followed by random miRNA pre-amplification. We selected a 24-miRNA custom panel to be tested by quantitative real-time polymerase chain reaction (qRT-PCR) and spotted the miRNA probes on array custom plates. We performed qRT-PCR plate runs on a real-time PCR System. Housekeeping miRNAs for normalization were selected using GeNorm software (v. 3.2). Data were analyzed using Expression suite software (v 1.1) and statistical analyses were performed. The method proved to be reliable and technically robust and could be useful to evaluate biomarker levels in liquid samples such as plasma and/or serum.

We present a protocol to evaluate the expression levels of circulating microRNA (miRNAs) in plasma samples from cancer patients. In particular, we used a commercially available kit for circulating miRNA extraction and reverse transcription. Finally, we analyzed a panel of 24 selected miRNAs using real-time pre-spotted probe custom plates.

There is increasing interest in liquid biopsy for cancer diagnosis, prognosis and therapeutic monitoring, creating the need for reliable and useful ...

Detection of Protease Activity by Fluorescent Peptide Zymography

The purpose of this method is to measure the proteolytic activity of complex biological samples. The samples are separated by molecular weight using electrophoresis through a resolving gel embedded with a degradable substrate. This method differs from traditional gel zymography in that a quenched fluorogenic peptide is covalently incorporated into the resolving gel instead of full length proteins, such as gelatin or casein. Use of the fluorogenic peptides enables direct detection of proteolytic activity without additional staining steps. Enzymes within the biological samples cleave the quenched fluorogenic peptide, resulting in an increase in fluorescence. The fluorescent signal in the gels is then imaged with a standard fluorescent gel scanner and quantified using densitometry. The use of peptides as the degradable substrate greatly expands the possible proteases detectable with zymographic techniques.

Here, we present a detailed protocol for a modified zymographic technique in which fluorescent peptides are used as the degradable substrate in place of native proteins. Electrophoresis of biological samples in fluorescent peptide zymograms enables detection of a wider range of proteases than previous zymographic techniques.

The purpose of this method is to measure the proteolytic activity of complex biological samples. The samples are separated by molecular weight using ...

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 ...

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

With ~1.6 million victims per year, lung cancer contributes tremendously to the worldwide burden of cancer. Lung cancer is partly driven by genetic alterations in oncogenes such as the KRAS oncogene, which constitutes ~25% of lung cancer cases. The difficulty in therapeutically targeting KRAS-driven lung cancer partly stems from having poor models that can mimic the progression of the disease in the lab. We describe a method that permits the relative quantification of primary KRAS lung tumors in a Cre-inducible LSL-KRAS G12D mouse model via ultrasound imaging. This method relies on brightness (B)-mode acquisition of the lung parenchyma. Tumors that are initially formed in this model are visualized as B-lines and can be quantified by counting the number of B-lines present in the acquired images. These would represent the relative tumor number formed on the surface of the mouse lung. As the formed tumors develop with time, they are perceived as deep clefts within the lung parenchyma. Since the circumference of the formed tumor is well-defined, calculating the relative tumor volume is achieved by measuring the length and width of the tumor and applying them in the formula used for tumor caliper measurements. Ultrasound imaging is a non-invasive, fast and user-friendly technique that is often used for tumor quantifications in mice. Although artifacts may appear when obtaining ultrasound images, it has been shown that this imaging technique is more advantageous for tumor quantifications in mice compared to other imaging techniques such as computed tomography (CT) imaging and bioluminescence imaging (BLI). Researchers can investigate novel therapeutic targets using this technique by comparing lung tumor initiation and progression between different groups of mice.

This protocol describes the steps taken to induce KRAS lung tumors in mice as well as the quantification of formed tumors by ultrasound imaging. Small tumors are visualized in early timepoints as B-lines. At later timepoints, relative tumor volume measurements are achieved by the measurement tool in the ultrasound software.

With ~1.6 million victims per year, lung cancer contributes tremendously to the worldwide burden of cancer. Lung cancer is partly driven by genetic ...

Establishing a Competing Risk Regression Nomogram Model for Survival Data

The Kaplan&#8211;Meier method and Cox proportional hazards regression model are the most common analyses in the survival framework. These are relatively easy to apply and interpret and can be depicted visually. However, when competing events (e.g., cardiovascular and cerebrovascular accidents, treatment-related deaths, traffic accidents) are present, the standard survival methods should be applied with caution, and real-world data cannot be correctly interpreted. It may be desirable to distinguish different kinds of events that may lead to the failure and treat them differently in the analysis. Here, the methods focus on using the competing regression model to identify significant prognostic factors or risk factors when competing events are present. Additionally, nomograms based on a proportional hazard regression model and a competing regression model are established to help clinicians make individual assessments and risk stratifications in order to explain the impact of controversial factors on prognosis.

Presented here is a protocol to build nomograms based on the Cox proportional hazards regression model and competing risk regression model. The competing method is a more rational method to apply when competing events are present in the survival analysis.

The Kaplan&#8211;Meier method and Cox proportional hazards regression model are the most common analyses in the survival framework. These are relatively ...

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Cancer stem cells play a vital role against clinical therapies, contributing to tumor relapse. There are many oncogenes involved in tumorigenesis and the initiation of cancer stemness properties. Since gene expression in the formation of colorectal cancer-derived tumorspheres is unclear, it takes time to discover the mechanisms working on one gene at a time. This study demonstrates a method to quickly discover the driver genes involved in the survival of the colorectal cancer stem-like cells in vitro. Colorectal HT29 cancer cells that express the LGR5 when cultured as spheroids and accompany an increase CD133 stemness markers were selected and used in this study. The protocol presented is used to perform RNAseq with available bioinformatics to quickly uncover the overexpressed driver genes in the formation of colorectal HT29-derived stem-like tumorspheres. The methodology can quickly screen and discover potential driver genes in other disease models.

Presented here is a protocol to discover the overexpressed driver genes maintaining the established cancer stem-like cells derived from colorectal HT29 cells. RNAseq with available bioinformatics was performed to investigate and screen gene expression networks for elucidating a potential mechanism involved in the survival of targeted tumor cells.

Cancer stem cells play a vital role against clinical therapies, contributing to tumor relapse. There are many oncogenes involved in tumorigenesis and the ...