We would like to thank all our co-authors in the article where this method was first described14, especially Tatiana Cajuso, Kimmo Palin, Outi Kilpivaara and Esa Pitk&#228;nen for valuable discussions while developing the method. L.K. is funded by the Academy of Finland (grant numbers 25996, 292789, 306026 and 314394), the Sigrid Juselius Foundation, and the Finnish Cancer Society. B.P. is recipient of University of Helsinki Research Foundation PhD studentship, a Finnish Cancer Society dissertation grant, and a doctoral research grant from Ida Montinin S&#228;&#228;ti&#246;. We also thank Teemu Masalin (University of Helsinki) and Kul Shrestha from L.K.&#39;s research group for assisting us with the video production.

This research was approved by the Institutional Review Board and Ethics committee of Helsinki University Hospital. Signed informed consent was obtained from the subject for the blood sample used to demonstrate this protocol.
1. Designing inverse primers and selecting restriction enzymes (bioinformatics)
<ol>
	<li>Determining a LINE-1 associated unique tag
	<ol>
		<li>Download the TTC28-LINE-1 sequence in FASTA format from a LINE-1 database such as L1Base17. The L1base ID for TTC28-LINE-1 is 135.</li>
		<li>Include 5 kb sequence flanking both 5&#180; and 3&#180; ends of the LINE-1 sequence and annotate it in a word processor. 
		NOTE: Here the LINE-1 flanking sequence is annotated in brown font, and LINE-1 sequence is in grey font (Supplemental File).</li>
		<li>Enter 1 kb sequence downstream of selected LINE-1&#39;s cognate PAS into a PAS prediction tool such as polyadq18 or Dragon PolyA spotter19 and annotate all the polyadenylation signal in this 1 kb window. 
		NOTE: If there is no PAS in the 1 kb window, search for PAS in next 1 kb window downstream. TTC28-LINE-1&#39;s own weak PAS is highlighted in pink and all the other PAS in 1 kb window downstream is highlighted in red (Supplemental File).</li>
		<li>Annotate the sequence between the end of LINE-1&#39;s cognate PAS and the strongest PAS downstream as &#34;unique tag&#34;. 
		NOTE: The &#34;unique tag&#34; of TTC28-LINE-1 is highlighted in yellow (Supplemental File).</li>
	</ol>
	</li>
	<li>Designing inverse primers
	<ol>
		<li>Design inverse PCR primers by entering the &#34;unique tag&#34; sequence into a web-based primer-designing tool like Primer 3 (http://bioinfo.ut.ee/primer3-0.4.0/) or NCBI&#8217;s primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). Since primer pairs designed by these tools face each other facilitating conventional PCR, use the reverse-complement function for the primer pair to perform inverse PCR. 
		NOTE: As LINE-1 transductions are heavily truncated at their 5&#180; end and the size of the transduced region is highly variable, aim to keep the distance between the two inverse primers minimal, by setting the &#34;PCR product length&#34; parameter in NCBI primer-BLAST to the minimum. In the case of multiple PAS within the unique tag, design several primer pairs that correspond to different PASs. Design primers close to the PAS, as LINE-1 insertions initiate from the 3&#180;end of the RNA intermediate and the 5&#180; end is variably truncated. Here three primer pairs were designed, highlighted in teal and green, corresponding to three strong polyadenylation signals in the unique tag of TTC28 LINE-1 (Supplemental File).</li>
	</ol>
	</li>
	<li>Selecting restriction enzymes
	<ol>
		<li>Digest the LINE-1 sequence along with its 5 kb upstream and downstream flanks in silico using web-based tool such as RestrictionMapper. This will give a comprehensive list of restriction enzymes that digests this region, generating different restriction fragments.</li>
		<li>Select restriction enzymes that cut the native locus of LINE-1 as follows: at the 5&#180; end, either upstream of the LINE-1&#180;s 5&#180;end or far 5&#180;end of the LINE-1 itself, and at the 3&#180; end, downstream of the LINE-1&#39;s unique tag. 
		NOTE: The selected restriction enzyme should be insensitive to DNA methylation, should be heat-inactivatable, and should generate staggered &#34;sticky&#34; ends that are complementary to each other. In order to demonstrate LDI-PCR, SacI restriction enzyme that cuts DNA at GAGCTC sites, highlighted here in light green, is used (Supplemental File).</li>
		<li>Take note of the restriction fragment size made by selected restriction enzymes. This should not be longer than 12 kb as it might not be efficiently amplified by PCR.</li>
	</ol>
	</li>
</ol>
2. Making circular DNA templates for long-distance inverse PCR
<ol>
	<li>DNA extraction and quality assessment
	<ol>
		<li>Extract genomic DNA from samples (tumor or blood) using commercially available DNA extraction kits that can extract good quality, high molecular weight DNA necessary for LDI-PCR according to the manufacturer&#39;s instructions. Alternatively, high molecular weight DNA can also be extracted by phenol:chloroform20.</li>
		<li>Measure the DNA concentration using a fluorometer according to the manufacturer&#39;s instructions, and run 100 ng of DNA on 1% (w/v) agarose gel containing ethidium bromide (0.5 &#181;g/mL) in 1x Tris-acetate-EDTA (TAE) buffer at 4.5 V/cm21 alongside &#955;-HindIII DNA molecular weight markers to check DNA quality and quantity.</li>
	</ol>
	</li>
	<li>Digesting genomic DNA
	<ol>
		<li>Make a digestion reaction mix (final volume of 50 &#181;L) by adding 20 units SacI restriction enzyme, 5 &#181;L of 10x reaction buffer (Table of Materials), 100 ng of DNA (up to 44 &#181;L) in a 0.2 mL PCR tube on ice (1 &#181;L of restriction enzyme from most manufacturers is sufficient to completely digest 100 ng of genomic DNA). Mix the solution by flicking the tube, and centrifuge briefly.</li>
		<li>Use a thermal cycler to incubate the reaction mix at 37 &#176;C for 1 h, followed by heat inactivation at 65 &#176;C for 5 min.</li>
	</ol>
	</li>
	<li>Self-ligating the digested genomic DNA
	<ol>
		<li>To the 50 &#181;L digestion mix (after step 2.2.2), add 8 &#181;L of 10x T4 DNA ligase buffer, 1 &#181;L (5 units) of T4 DNA ligase and 21 &#181;L of ultrapure water to make a final reaction volume of 80 &#181;L. Mix the solution by flicking the tubes, and centrifuge briefly.</li>
		<li>Incubate in a thermal cycler at 22 &#176;C for 10 min, terminating with a heat inactivation step at 65 &#176;C for 10 min.</li>
	</ol>
	</li>
</ol>
3. Long-distance inverse PCR
<ol>
	<li>Determining primer annealing temperature by gradient PCR
	<ol>
		<li>Set an annealing temperature gradient of (A-4) &#176;C, (A-2)&#176;C, A, (A+2)&#176;C, (A+4) &#176;C where A is the theoretical&#160;annealing temperature of the primer pair calculated using the commercial vendor&#39;s web-based tool. 
		NOTE: Thermal cyclers from some manufacturers may not allow setting the temperature gradient manually. In that case, the automatic gradient setting can be used with a temperature range of (A-4) &#176;C to (A+4) &#176;C.</li>
		<li>Prepare a master mix for the PCR by combining and mixing the following components in a 1.5 mL microcentrifuge tube: 4 &#181;L of 5x reaction buffer, 0.4 &#181;L of 10 mM dNTP, 5 &#181;L of 2 &#181;M PCR primer (forward and reverse, designed in step 1.3.1), 0.2 &#181;L (0.1 U) of DNA polymerase per reaction. Set up one reaction for each annealing temperature in the gradient.</li>
		<li>For each reaction, aliquot 19 &#181;L of the master mix into 0.2 mL PCR tubes and add 1 &#181;L (1.25 ng) of circular DNA template made in section 2. 
		NOTE: Use circular self-ligated DNA generated from normal blood DNA as template so as to avoid consuming potentially precious tumor DNA for this optimization step.</li>
		<li>Run gradient PCR program on a thermal cycler as described below: (i) one cycle of 3 min&#160;at 98 &#176;C (denaturation); (ii) 35 cycles of (10 s at 98 &#176;C [denaturation], 20 s at the temperature gradient of [A-4] to [A+4] &#176;C [Annealing] and 1&#8722;6 min [30 s per kilobase of expected PCR product] at 72 &#176;C [extension]); (iii) one cycle of 10 min at 72 &#176;C (final extension).</li>
		<li>Run 6 &#181;L of the PCR product in 1% agarose gel21 prepared in 1x TAE buffer at 4.5 V/cm and analyze the PCR products yielded at different annealing temperatures.</li>
		<li>Select the annealing temperature that yields a PCR product that corresponds to the expected size.</li>
	</ol>
	</li>
	<li>Detecting de novo LINE-1 retrotransposition activity in the tumor genome
	<ol>
		<li>Perform LDI-PCR using the inverse PCR primer pair on circular DNA templates generated from tumor samples (section 2). Follow same instructions as for gradient PCR (section 3.1), but this time replacing the temperature gradient with the optimal annealing temperature.</li>
		<li>Analyze the PCR products by agarose gel electrophoresis as done in step 3.1.5. PCR product of known size or the &#34;native&#34; PCR product corresponding to the LINE-1 at its native locus should be visible for each reaction. De novo LINE-1 3&#180; transduction in the tumor sample assayed is detectable as PCR products of different sizes, along with the native PCR product in the agarose gel.</li>
	</ol>
	</li>
</ol>
4. Sequencing LDI-PCR products to reveal the identity of target sites for LINE-1 3&#180; transduction
<ol>
	<li>Perform single-molecule long read sequencing of all the PCR amplicons generated in each LDI-PCR reaction to identify the target integration sites of these LINE-1 3&#180; transduction events. 
	NOTE: Cloning and Sanger sequencing of the LDI-PCR products is also a possible, albeit cumbersome, approach.</li>
	<li>Align the reads produced by single-molecule long read sequencing platforms to the reference genome using standard sequence alignment pipelines. Analyze the aligned reads using LDI-PCR software14 to identify de novo LINE-1 insertions and its target sites.</li>
</ol>

<ol>
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L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Restricting+retrotransposons:+a+review.">Restricting retrotransposons: a review.</a> Mobile DNA. 7, 16 (2016).</li><li>Lee, E., 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=Landscape+of+somatic+retrotransposition+in+human+cancers.">Landscape of somatic retrotransposition in human cancers.</a> Science. 337 (6097), 967-971 (2012).</li><li>Miki, 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=Disruption+of+the+APC+gene+by+a+retrotransposal+insertion+of+L1+sequence+in+a+colon+cancer.">Disruption of the APC gene by a retrotransposal insertion of L1 sequence in a colon cancer.</a> Cancer Research. 52 (3), 643-645 (1992).</li><li>Scott, E. 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=A+hot+L1+retrotransposon+evades+somatic+repression+and+initiates+human+colorectal+cancer.">A hot L1 retrotransposon evades somatic repression and initiates human colorectal cancer.</a> Genome Research. 26 (6), 745-755 (2016).</li><li>Pitkanen, E., 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=Frequent+L1+retrotranspositions+originating+from+TTC28+in+colorectal+cancer.">Frequent L1 retrotranspositions originating from TTC28 in colorectal cancer.</a> Oncotarget. 5 (3), 853-859 (2014).</li><li>Tubio, J. 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=Mobile+DNA+in+cancer.+Extensive+transduction+of+nonrepetitive+DNA+mediated+by+L1+retrotransposition+in+cancer+genomes.">Mobile DNA in cancer. Extensive transduction of nonrepetitive DNA mediated by L1 retrotransposition in cancer genomes.</a> Science. 345 (6196), 1251343 (2014).</li><li>Badge, R. M., Alisch, R. S., Moran, J. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATLAS:+a+system+to+selectively+identify+human-specific+L1+insertions.">ATLAS: a system to selectively identify human-specific L1 insertions.</a> American Journal of Human Genetics. 72 (4), 823-838 (2003).</li><li>Rodic, N., 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=Retrotransposon+insertions+in+the+clonal+evolution+of+pancreatic+ductal+adenocarcinoma.">Retrotransposon insertions in the clonal evolution of pancreatic ductal adenocarcinoma.</a> Nature Medicine. 21 (9), 1060-1064 (2015).</li><li>Ewing, A. D., Kazazian, H. 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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retrotransposon+Capture+Sequencing+(RC-Seq):+A+Targeted,+High-Throughput+Approach+to+Resolve+Somatic+L1+Retrotransposition+in+Humans.">Retrotransposon Capture Sequencing (RC-Seq): A Targeted, High-Throughput Approach to Resolve Somatic L1 Retrotransposition in Humans.</a> Methods in Molecular Biology. 1400, 47-77 (2016).</li><li>Zhao, 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=Somatic+LINE-1+retrotransposition+in+cortical+neurons+and+non-brain+tissues+of+Rett+patients+and+healthy+individuals.">Somatic LINE-1 retrotransposition in cortical neurons and non-brain tissues of Rett patients and healthy individuals.</a> PLOS Genetics. 15 (4), e1008043 (2019).</li><li>Pradhan, 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=Detection+of+subclonal+L1+transductions+in+colorectal+cancer+by+long-distance+inverse-PCR+and+Nanopore+sequencing.">Detection of subclonal L1 transductions in colorectal cancer by long-distance inverse-PCR and Nanopore sequencing.</a> Scientific Reports. 7 (1), 14521 (2017).</li><li>Moran, J. V., DeBerardinis, R. J., Kazazian, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exon+shuffling+by+L1+retrotransposition.">Exon shuffling by L1 retrotransposition.</a> Science. 283 (5407), 1530-1534 (1999).</li><li>Philippe, 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=Activation+of+individual+L1+retrotransposon+instances+is+restricted+to+cell-type+dependent+permissive+loci.">Activation of individual L1 retrotransposon instances is restricted to cell-type dependent permissive loci.</a> Elife. 5, (2016).</li><li>Penzkofer, 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=L1Base+2:+more+retrotransposition-active+LINE-1s,+more+mammalian+genomes.">L1Base 2: more retrotransposition-active LINE-1s, more mammalian genomes.</a> Nucleic Acids Research. 45 (D1), D68-D73 (2017).</li><li>Tabaska, J. E., Zhang, M. Q. <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+polyadenylation+signals+in+human+DNA+sequences.">Detection of polyadenylation signals in human DNA sequences.</a> Gene. 231 (1-2), 77-86 (1999).</li><li>Kalkatawi, 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=Dragon+PolyA+Spotter:+predictor+of+poly(A)+motifs+within+human+genomic+DNA+sequences.">Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.</a> Bioinformatics. 29 (11), 1484 (2013).</li><li>Sambrook, J., Russell, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Purification+of+nucleic+acids+by+extraction+with+phenol:chloroform.">Purification of nucleic acids by extraction with phenol:chloroform.</a> Cold Spring Harbor Protocols. 2006 (1), (2006).</li><li>Green, M. R., Sambrook, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Agarose+Gel+Electrophoresis.">Agarose Gel Electrophoresis.</a> Cold Spring Harbor Protocols. 2019 (1), (2019).</li><li>Macfarlane, C. 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The authors have nothing to disclose.

Here we describe a method that can be used to identify de novo LINE-1 insertions stemming from any active LINE-1 of interest. We have optimized this method for a highly active LINE-1, located at 22q12.1, and previously demonstrated it to be highly sensitive in detecting sub-clonal insertions in colorectal cancer14.
Success of LDI-PCR depends on the quality of genomic DNA. Therefore, we have included an additional quality control step to ensure that at the start of the protocol, high-molecular weight DNA is present (step 2.1.2). We recommend storing genomic DNA at -20 &#176;C for long term storage, and to prepare aliquots in order to avoid cycles of freezing and thawing. Using genomic DNA from blood or patient-matched normal tissue is highly recommended to distinguish whether the LINE-1 retrotransposition detected is a germline or a somatic event. Since cut sites for restriction enzymes are stochastic in the genome, it is possible that a particular de novo LINE-1 insertion site might not harbor any cut sites for the restriction enzyme being used in its vicinity. Hence to increase the likelihood of detecting the majority of de novo LINE-1 insertions in tumor DNA, more than one restriction enzyme should be used in separate reactions to generate different libraries of circular DNA template. Furthermore, if the unique tag of the LINE-1 of interest has more than one PAS, then using primer pairs adjacent to each PAS improves the chances of detecting heavily truncated transductions.
Although elegant methods for genome-wide detection of de novo LINE-1 insertions exist, they can be overwhelming if the aim is to probe the retrotransposition competence of a particular LINE-1 in a specific cellular context. For this purpose, LDI-PCR can be an inexpensive and simple yet robust approach to visualize LINE-1 retrotransposition events. The targeting approach used in this method is similar to TS-ATLAS22; however, LDI-PCR avoids using linker oligonucleotides and can amplify both 5&#180; and 3&#180; junctions of de novo LINE-1 insertion simultaneously. Information regarding both 5&#180; and 3&#180; junctions of the LINE-1 insertion, the target site of integration, polyA tail and target-site modifications, all of which are hallmarks of LINE-1 retrotransposition, can be obtained by coupling LDI-PCR with single-molecule long-read sequencing technologies. Long reads thus generated contain the inserted LINE-1 sequence, its unique tag and the target sequences in one single read, circumventing difficulties of mapping short reads in the repetitive region.
There are two major limitations to using LDI-PCR for detection of LINE-1 activity. The first is inherent to PCR: it can only reliably amplify fragments up to 10 kb in size. This should be considered while selecting restriction enzyme(s), as the native fragment should not exceed this limit. Secondly, this method can only detect retrotransposition events that mobilize the LINE-1&#39;s 3&#180; flanking region by 3&#180; transductions. Hence, activity of those LINE-1s that do not exhibit 3&#180; transduction will not be detected using this method. Additionally, despite of being amplified by LDI-PCR, some LINE-1 retrotransposition events that (a) generate a PCR target of similar size as the &#34;native&#34; location or other retrotranspositions or (b) are rare or subclonal, may not be detected by agarose gel electrophoresis. Such LINE-1 retrotransposition events can be captured by sequencing the LDI-PCR product using single molecule long-read sequencing technologies14.
The workflow described here can be easily modified to detect the activity of other &#34;hot&#34; LINE-1s by using a suitable restriction enzyme and by designing inverse primers targeting these LINE-1s. In addition to detection of LINE-1 mediated 3&#180; transduction, this method can be adapted to detect less frequent LINE-1 mediated 5&#180; transductions23. Similar method have been used to identify the integration site of LINE-1 reporters in cell-based assays24 and proviral integration sites in cancer25. Besides LINE-1 insertions, this method can also be utilized to detect other genomic aberrations, such as DNA rearrangements, where information regarding the rearrangement-prone region pre-exists26.

Long interspersed nuclear elements (LINE-1s) are a family of mobile genetic elements called retrotransposons that can independently move from one place to another via a copy-and-paste mechanism called retrotransposition. Over evolutionary time, the human genome has accumulated more than 500,000 copies of LINE-1 repeats1. However, most of the LINE-1 copies present in the genome are mutated and hence cannot move via retrotransposition; only ~150 copies have intact copy of DNA sequence necessary for them to move2. In normal somatic cells, the mobility of these LINE-1s is restricted by different host factors3. These restrictions are relieved in different epithelial tumors, causing LINE-1s to be derepressed and resulting in many de novo insertions in the tumor genome4. Some of these tumor-associated de novo insertions have been shown to cause insertional mutagenesis in genes, hence driving tumor progression5,6. Therefore, it is important to be able to map novel insertions in the tumor genome.
Existing methods to detect de novo LINE-1 insertions use (1) whole-genome sequencing approach4,7,8, where different computational algorithms are used to find de novo LINE-1 insertions from WGS data, or (2) next-generation sequencing that targets the 3&#180; end of young, potentially active LINE-1s9,10,11,12,13. However, finding novel insertions among several thousand near-identical copies with these methods is far from trivial, and the challenge is further aggravated by tumor heterogeneity and genomic alterations associated with LINE-1 insertion4.
Studies using these existing methods showed that just a few LINE-1s account for&#160;the majority of de novo LINE-1 insertions observed in tumors7,8. Therefore, to answer whether or not a particular tumor sample displays LINE-1 activity, it suffices to map retrotransposition events caused by this handful of highly active LINE-1 loci. In this article, we describe a simple polymerase chain reaction (PCR)-based method14 that can be used to monitor the activity of a particular LINE-1 locus in the first intron of the TTC28 gene at 22q12.1 that is highly active in colorectal cancer7,8. This LINE-1 locus will be referred to as TTC28-LINE-1 throughout the article. This assay specifically identifies de novo LINE-1 retrotransposition events that mobilize non-repetitive sequence on the 3&#180; flanking region of the source LINE-1 by a mechanism called 3&#180; transduction15. 3&#180; transduction occurs due to the weak LINE-1 polyadenylation signal (PAS) that causes the transcriptional machinery to skip it and to instead terminate transcription at the stronger PAS downstream, thus capturing the flanking non-repetitive sequence (henceforth referred to as the &#34;unique tag&#34;) which is then inserted into the target location alongside the LINE-1 sequence. Philippe et al.16 recently showed that different cell types can express different LINE-1 loci. In light of this finding, this method can be applied to monitor the activity of the most highly expressed LINE-1 that mobilize&#160;their&#160;unique tag in the cancer type of interest.
The first step in LDI-PCR is digestion of genomic DNA with a restriction enzyme that generates a restriction fragment containing the LINE-1 being assayed (here, TTC28-LINE-1) and its unique tag (Figure 1). Digested DNA is then circularized by self-ligation and PCR amplified using inverse primers located within the unique tag. By doing so, the full-length source LINE-1 at its &#34;native&#34; location is always amplified and alongside it, offspring LINE-1 insertions at different target loci containing the unique tag will also be amplified (Figure 1), thus reporting retrotransposition activity of the LINE-1 in question.

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		<tr height="21">
			<td height="21" style="height:21px;width:288px;">1 Kb DNA Ladder</td>
			<td style="width:174px;">New England Biolabs</td>
			<td style="width:166px;">N3232L</td>
			<td style="width:172px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">10 mM dNTP</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">18427013</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Acetic acid</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td>64-19-7</td>
			<td>Used to make TAE buffer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Agarose</td>
			<td style="width:174px;">BioNordika</td>
			<td style="width:166px;">BN-50004</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Blood sample (frozen)</td>
			<td style="width:174px;"></td>
			<td style="width:166px;"></td>
			<td>Blood sample from a healthy individual for control PCR</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">ChemiDoc XRS+ System</td>
			<td style="width:174px;">Bio-rad</td>
			<td style="width:166px;">1708265</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">DNA Gel Loading Dye (6X)</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">R0611</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">DNeasy Blood &#38; Tissue Kits</td>
			<td style="width:174px;">Qiagen</td>
			<td style="width:166px;">69504</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Ethidium Bromide</td>
			<td style="width:174px;">Bio-rad</td>
			<td style="width:166px;">161-0433</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Ethylenediaminetetraacetic acid (EDTA)</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">25102-12-9</td>
			<td>Used to make TAE buffer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">FastDigest buffer</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">B64</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">FastDigest SacI</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td>FD1133</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Generuler 1 Kb plus DNA Ladder</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">SM1331</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Generuler Lambda DNA/HindIII Marker, 2</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">SM0103</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Mini-Sub&#160;Cell GT Cell</td>
			<td style="width:174px;">Bio-rad</td>
			<td style="width:166px;">1704406</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:288px;">Phusion Green Hot Start II High-Fidelity DNA Polymerase</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">F537L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">PowerPac Basic Power Supply</td>
			<td style="width:174px;">Bio-rad</td>
			<td style="width:166px;">1645050</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Quantus Fluorometer</td>
			<td style="width:174px;">Promega</td>
			<td style="width:166px;">E6150</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">T4 DNA Ligase</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">EL0011</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Tear-A-Way 96/8, 96 Well PCR Plate</td>
			<td style="width:174px;">4titude</td>
			<td style="width:166px;">4ti-0750/TA</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Tris(hydroxymethyl)aminomethane</td>
			<td style="width:174px;">ThermoFisher Scientific</td>
			<td style="width:166px;">77-86-1</td>
			<td>Used to make TAE buffer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:288px;">Veriti Thermal Cycler</td>
			<td style="width:174px;">Applied Bioscience</td>
			<td style="width:166px;">4375786</td>
			<td></td>
		</tr>
	</tbody>
</table>

detection of retrotransposition activity of hot line-1s by long-distance inverse pcr

Long interspersed nuclear elements 1 (LINE-1s) are the only family of mobile genetic elements in the human genome that can move autonomously. They do so by a process called retrotransposition wherein they transcribe to form an mRNA intermediate which is then consequently inserted into the genome by reverse transcription. Despite being silent in normal cells, LINE-1s are highly active in different epithelial tumors. De novo LINE-1 insertions can potentially drive tumorigenesis, and hence it is important to systematically study LINE-1 retrotransposition in cancer. Out of ~150 retrotransposition-competent LINE-1s present in the human genome, only a handful of LINE-1 loci, also referred to as &#34;hot&#34; LINE-1s, account for the majority of de novo LINE-1 insertion in different cancer types. We have developed a simple polymerase chain reaction (PCR)-based method to monitor retrotransposition activity of these hot LINE-1s. This method, based on long-distance inverse (LDI)-PCR, takes advantage of 3&#180; transduction, a mechanism by which a LINE-1 mobilizes its flanking non-repetitive region, which can subsequently be used to identify de novo LINE-1 3&#180; transduction events stemming from a particular hot LINE-1.

In case of TTC28-LINE-1, there is more than one PAS within a 1 kb window downstream of its cognate PAS, hence the region between the TTC28-LINE-1 PAS and strongest PAS at 811 bp downstream was considered as the unique tag for TTC28-LINE-1. Three inverse PCR primer pairs were designed at this unique tag that correspond to different PASs present14. We selected three restriction enzymes: (i) NsiI that cuts 5&#180; upstream of TTC28-LINE-1 and 3&#180; outside the unique tag, and (ii) SacI and (iii) PstI that cut 5&#180; within the LINE-1 in its far 5&#180; end, and 3&#180; outside the unique tag. These generate restriction fragments of 10,288 bp, 5,699 bp, and 6,305 bp respectively.
In order to demonstrate this method, we performed LDI-PCR on DNA extracted from MCF7 cell line. This breast cancer cell line has been previously reported to display TTC28-LINE-1 activity16. For simplicity, we made a circular DNA template using one restriction enzyme, SacI, out of three and performed an LDI-PCR using one primer pair out of three (Table 1) to detect de novo LINE-1 insertions stemming from TTC28-LINE-1.
Good quality of DNA extracted from MCF7 cell line was ensured by agarose gel electrophoresis (Figure 2). Intact high molecular weight DNA shows that the genomic DNA is of optimum quality for this assay. If a smear is visible instead, this indicates poor quality of the extracted DNA, which in turn will hamper downstream procedures.
Figure 3&#160;shows a representative result of a gradient PCR experiment, aimed at determining the optimal annealing temperature of the TTC28-LINE-1 inverse primer pair. Blood genomic DNA digested with SacI, followed by self-ligation to form a circular DNA template, was used for this reaction. A highly specific PCR product of expected size (5,649 bp) at 62, 64 and 66 &#176;C shows that the optimum annealing temperature for this primer pair lies within the range of 62&#8722;66 &#176;C.
We generated a circular DNA template by digesting MCF7 genomic DNA with the SacI restriction enzyme followed by self-ligation. Figure 4 shows that TTC28-LINE-1 3&#180; transduction occurs in MCF7 cell lines: de novo insertions can be detected as LDI-PCR products of varying sizes along with a native PCR product of known size (5,649 bp). To identify genomic coordinates of the de novo target sites, PCR amplicons can be sequenced (see protocol section 4).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59880/59880fig1.jpg" /> 
Figure 1: Overview of LDI-PCR to detect LINE-1 3&#180; transduction. A circular DNA template is generated by first digesting (I) it with a restriction enzyme and self-ligating (II) it. This step is followed by inverse PCR (III) with inverse PCR primers targeted to the unique tag of the LINE-1 of interest (sequence between LINE-1&#39;s own weaker PAS, in pink, and stronger PAS downstream, in red). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59880/59880fig1large.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/59880/59880fig2.jpg" /> 
Figure 2: Quality assessment of extracted DNA. 100 ng of DNA extracted from the MCF7 cell line and blood from a normal individual, which will be used as a control sample, were run alongside 1 &#181;L and 2 &#181;L of &#955; DNA/HindIII marker labelled as M. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59880/59880fig2large.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/59880/59880fig3.jpg" /> 
Figure 3: Gradient PCR to determine optimal annealing temperature for inverse PCR primers (Table 1). LDI-PCR using inverse primer pairs at annealing temperature ranging from 56 to 66 &#176;C shows a distinct PCR product at 62&#8722;66 &#176;C. Green arrow indicates the selected annealing temperature for future experiments. Circular DNA template generated by digesting blood genomic DNA from a normal individual with SacI followed by self-ligation was used for this optimization step. M, marker (1 kb plus DNA ladder). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59880/59880fig3large.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/59880/59880fig4.jpg" /> 
Figure 4: LDI-PCR to identify LINE-1 3&#180; transduction stemming from TTC28-LINE-1. Circular DNA templates generated by digesting MCF7 and blood (from normal individual) genomic DNA with SacI followed by self-ligation were amplified by inverse primers in optimum annealing temperature. &#34;Native&#34; PCR product, marked with asterisk, of expected size (5,649 bp) was detected in both MCF7 DNA and normal blood DNA, while MCF7 also produced additional PCR products of varying sizes, indicating de novo LINE-1 retrotransposition. M, marker (1 kb DNA ladder). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59880/59880fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Primer name</td>
			<td>Sequence (5&#180;&#8594; 3&#180;)</td>
		</tr>
		<tr>
			<td>L1_001 (rev)</td>
			<td>TTCACTAAGCATGTATGTGGAAAAC</td>
		</tr>
		<tr>
			<td>L1_002 (fwd)</td>
			<td>CCCAAAATATACCCAATTACTGGCA</td>
		</tr>
	</tbody>
</table>
Table 1: Inverse PCR primer pair designed for the unique tag of TTC28-LINE-114.
Supplemental File.&#160; <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/59880/Supplemental_File_revised.docx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR at JoVE.com

Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR

This article outlines a simple PCR-based assay to monitor the activity of an active LINE-1 retrotransposon and to map de novo retrotranspositions in a given genome. Using the MCF7 cell line, we demonstrate herein how this method can be applied to detect activity of a LINE-1 located at 22q12.1.

Long interspersed nuclear elements 1 (LINE-1s) are the only family of mobile genetic elements in the human genome that can move autonomously. They do so ...

detection-retrotransposition-activity-hot-line-1s-long-distance

Universidad de Cartagena UDEC

Research

JoVE Journal

Cancer Research

8.5K Views.  University of Helsinki. This article outlines a simple PCR-based assay to monitor the activity of an active LINE-1 retrotransposon and to map de novo retrotranspositions in a given genome. Using the MCF7 cell line, we demonstrate herein how this method can be applied to detect activity of a LINE-1 located at 22q12.1.

Video: Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR

Serum and Plasma Copy Number Detection Using Real-time PCR

Serum and plasma cell free DNA (cfDNA) has been shown as an informative, non-invasive source of biomarkers for cancer diagnosis, prognosis, monitoring, and prediction of treatment resistance. Starting from the hypothesis that androgen receptor (AR) gene copy number (CN) gain is a frequent event in metastatic castration resistance prostate cancer (mCRPC), we propose to analyze this event in cfDNA as a potential predictive biomarker.
We evaluated AR CN in cfDNA using 2 different real-time PCR assays and 2 reference genes (RNaseP and AGO1). DNA amount of 60 ng was used for each assay combination. AR CN gain was confirmed using Digital PCR as a more accurate method. CN variation analysis has already been demonstrated to be informative for the prediction of treatment resistance in the setting of mCRPC, but it could be useful also for other purposes in different patient settings. CN analysis on cfDNA has several advantages: it is non-invasive, rapid and easy to perform, and it starts from a small volume of serum or plasma material.

This manuscript describes the copy number variation analysis performed in serum or plasma DNA using real-time PCR approach. This method is suitable for the prediction of drug resistance in castration resistant prostate cancer patients, but it could be informative also for other diseases.

Serum and plasma cell free DNA (cfDNA) has been shown as an informative, non-invasive source of biomarkers for cancer diagnosis, prognosis, monitoring, ...

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal gastric mucosa. Recently, we detected CDH1a transcript variant in fresh-frozen tumor tissues obtained from patients with GC. The expression of this variant in tissue samples was investigated by the chip-based digital PCR (dPCR) approach presented here. dPCR offers the potential for an accurate, robust, and highly sensitive measurement of nucleic acids and is increasingly utilized for many applications in different fields. dPCR is capable of detecting rare targets; in addition, dPCR offers the possibility for absolute and precise quantification of nucleic acids without the need for calibrators and standard curves. In fact, the reaction partitioning enriches the target from the background, which improves amplification efficiency and tolerance to inhibitors. Such characteristics make dPCR an optimal tool for the detection of the CDH1a rare transcript.

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

The manuscript describes a chip-based digital PCR assay to detect a rare CDH1 transcript variant (CDH1a) in fresh-frozen normal and tumor tissues obtained from patients with gastric cancer.

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal ...

High-sensitivity Detection of Micrometastases Generated by GFP Lentivirus-transduced Organoids Cultured from a Patient-derived Colon Tumor

Despite current advances in human colorectal cancer (CRC) treatment, few radical therapies are effective for the late stages of CRC. To overcome this clinical challenge, tumor xenograft mouse models using long-established human carcinoma cell lines and many transgenic mouse models with tumors have been developed as preclinical models. They partially mimic the features of human carcinomas, but often fail to recapitulate the key aspects of human malignancies including invasion and metastasis. Thus, alternative models that better represent the malignant progression in human CRC have long been awaited.
We herein show generation of patient-derived tumor xenografts (PDXs) by subcutaneous implantation of small CRC fragments surgically dissected from a patient. The colon PDXs develop and histopathologically resemble the CRC in the patient. However, few spontaneous micrometastases are detectable in conventional cross-sections of affected distant organs in the PDX model. To facilitate the detection of metastatic dissemination into distant organs, we extracted the tumor organoid cells from the colon PDXs in culture and infected them with GFP lentivirus prior to injection into highly immunodeficient NOD/Shi-scid IL2R&#947;null (NOG) mice. Orthotopically injected PDX-derived CRC organoid cells consistently form primary tumors positive for GFP in recipient mice. Moreover, spontaneously developing micrometastatic colonies expressing GFP are notably detected in the lungs of these mice by fluorescence microscopy. Moreover, intrasplenic injection of CRC organoids frequently produces hepatic colonization. Taken together, these findings indicate GFP-labelled PDX-derived CRC organoid cells to be visually detectable during a multistep process termed the invasion-metastasis cascade. The described protocols include the establishment of PDXs of human CRC and 3D culture of the corresponding CRC organoid cells transduced by GFP lentiviral particles.

To allow highly sensitive detection of the disseminating human colorectal cancer (CRC) cells colonizing tissues, we herein show a protocol for efficient transduction of green fluorescent protein (GFP) lentiviral particles into PDX-derived CRC organoid cells prior to their injection into recipient mice, with stereo-fluorescence microscopic observation.

Despite current advances in human colorectal cancer (CRC) treatment, few radical therapies are effective for the late stages of CRC. To overcome this ...

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Potentiation of hostile monoclonal antibodies (mAb) by chemotherapeutic agents constitutes a valuable strategy for designing effective and safer therapy against cancer. Here we provide a protocol to identify a rational combination at the preclinical step. First, we describe a cell-based assay to assess the synergism between anticancer mAb and cytotoxic drugs, that uses the combination index equation of Chou and Talalay1. This includes the measurement of tumor cell drug- and antibody-sensitivity using an MTT assay, followed by an automated computer analysis to calculate the combination index (CI) values. CI values of &lt;1 indicate synergism between tested mAbs and cytotoxic agents1. To corroborate the in vitro findings in vivo, we further describe a method to assess the combination regimen efficacy in a xenograft tumor model. In this model, the combined regimen significantly delays tumor growth, which results in a significant extended survival in comparison to single-agent controls. Importantly, the in vivo experimentation reveals that the combination regimen is well tolerated. This protocol allows the effective evaluation of anticancer drug combinations in preclinical models and the identification of rational combination to evaluate in clinical trials.

This protocol describes how to assess synergism between an anticancer antibody and antineoplastic drugs in preclinical models by using the combination index equation of Chou and Talalay.

Potentiation of hostile monoclonal antibodies (mAb) by chemotherapeutic agents constitutes a valuable strategy for designing effective and safer therapy ...

Real Time Detection of In Vitro Tumor Cell Apoptosis Induced by CD8+ T Cells to Study Immune Suppressive Functions of Tumor-infiltrating Myeloid Cells

Potentiation of the tumor-killing ability of CD8+ T cells in tumors, along with their efficient tumor infiltration, is a key element of successful immunotherapies. Several studies have indicated that tumor infiltrating myeloid cells (e.g., myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs)) suppress cytotoxicity of CD8+ T cells in the tumor microenvironment, and that targeting these regulatory myeloid cells can improve immunotherapies. Here, we present an in vitro assay system to evaluate immune suppressive effects of monocytic-MDSCs and TAMs on the tumor-killing ability of CD8+ T cells. To this end, we first cultured na&#239;ve splenic CD8+ T cells with anti-CD3/CD28 activating antibodies in the presence or absence of suppressor cells, and then co-cultured the pre-activated T cells with target cancer cells in the presence of a fluorogenic caspase-3 substrate. Fluorescence from the substrate in cancer cells was detected by real-time fluorescence microscopy as an indicator of T-cell induced tumor cell apoptosis. In this assay, we can successfully detect the increase of tumor cell apoptosis by CD8+ T cells and its suppression by pre-culture with TAMs or MDSCs. This functional assay is useful for investigating CD8+ T cell suppression mechanisms by regulatory myeloid cells and identifying druggable targets to overcome it via high throughput screening.

Real Time Detection of In Vitro Tumor Cell Apoptosis Induced by CD8+ T Cells to Study Immune Suppressive Functions of Tumor-infiltrating Myeloid Cells

We describe here a protocol to investigate cytotoxicity of pre-activated CD8+ T cells against cancer cells by detecting apoptotic cancer cells via real-time microscopy. This protocol can investigate mechanisms behind myeloid cell-induced T cell suppression and evaluate compounds aimed at replenishing T cells via blockade of immune suppressive myeloid cells.

Potentiation of the tumor-killing ability of CD8+ T cells in tumors, along with their efficient tumor infiltration, is a key element of successful ...

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 ...

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 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 ...

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 ...

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 ...

Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR

Summary

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Chapters in this video

Serum and Plasma Copy Number Detection Using Real-time PCR

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

High-sensitivity Detection of Micrometastases Generated by GFP Lentivirus-transduced Organoids Cultured from a Patient-derived Colon Tumor

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation

Real Time Detection of In Vitro Tumor Cell Apoptosis Induced by CD8⁺ T Cells to Study Immune Suppressive Functions of Tumor-infiltrating Myeloid Cells

Detection of Protease Activity by Fluorescent Peptide Zymography

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

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

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

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging