We gratefully acknowledge the UND Genomics Core facility for outstanding technical assistance.
This work was funded by the National Institutes of Health [P20GM104360 to M.T., P20 GM104360 to A.D.] and start-up funds provided by the University of North Dakota School of Medicine and Health Sciences, Department of Biomedical Sciences [to M.T.].

1. Preparations before beginning the experiment
<ol>
	<li>Prepare lysis buffer stock. 
	NOTE: The optimal nuclear isolation buffer can be different for each cell type. We recommend testing both the hypotonic buffer used in the original paper8 and a CSK buffer12,13 for each cell type using trypan blue staining.
	<ol>
		<li>To prepare hypotonic buffer (Greenleaf buffer), mix 10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, and 0.1% NP-40.</li>
		<li>To prepare CSK buffer, mix 10 mM PIPES pH 6.8, 100 mM NaCl, 300 mM sucrose, 3 mM MgCl2, and 0.1% Triton X-100.</li>
	</ol>
	</li>
	<li>Ensure that the cell culture conditions are optimal; examine the cells under a light microscope to make sure that there are no elevated levels of apoptosis.</li>
	<li>Turn on the centrifuge to let it reach 4 &#176;C.</li>
</ol>
2. Cell harvest
<ol>
	<li>Aspirate media from a culture of cells at &#60;80% confluency. Cells are typically grown in a 35 mm or 60 mm dish, based on the number of cells needed, treatments, etc.</li>
	<li>Wash the cells with 1 mL or 3 mL of PBS.</li>
	<li>Add 0.5 mL or 1 mL of Trypsin and incubate for 2-3 min (depending on the cell types). Carefully use a 1 mL pipette to mix well.</li>
	<li>Add 1 mL or 2 mL of media to the plate and mix well. Transfer to a 15 mL conical tube. Centrifuge the cells in a 15 mL tube for 3 min at 300 x g. 
	NOTE: A swinging bucket rotor is recommended to minimize cell loss.</li>
	<li>Aspirate the media and resuspend the cells&#160;in 1 mL or 2 mL of medium. 
	NOTE: It is critical to prepare a homogenous single-cell solution. For tissues, a Dounce homogenizer can be used to homogenize tissues and minimize large cell clumps or aggregates. Some tissues require filtration (e.g., cell strainers) and/or FACS cell sorting to isolate viable cells and obtain a single cell solution.</li>
	<li>Count the cells using a cell counter. 
	NOTE: In this study, an automated cell counter (Table of Materials) was used.</li>
	<li>Centrifuge the required cell volume (e.g., a volume containing 1 x 106 cells based on cell count) at 300 x g for 3 min at room temperature (RT).</li>
	<li>Resuspend the cell pellet containing 1 x 106 cells in 1 mL of cold PBS. 
	NOTE: If cell numbers are less than 1 x 106&#160;cells, decrease the cold PBS volume to prepare the cell solution at the same concentration (1 x 106&#160;cells/mL).</li>
</ol>
3. Cell lysis
<ol>
	<li>Transfer 25 &#181;L (= 2.5 x 104 cells) to a new 1.7 mL microcentrifuge tube. Centrifuge&#160;for 5 min at 500 x g at 4 &#176;C and carefully discard the supernatant 
	NOTE: A swinging bucket rotor is recommended to minimize cell loss. Leave about 3 &#181;L of supernatant to ensure that the cells are not being discarded.</li>
	<li>Add 25 &#181;L of lysis buffer and resuspend the cells by gentle pipetting up and down. Incubate on ice for 5 min</li>
	<li>Centrifuge for 5 min at 500 x g at 4 &#176;C and carefully&#160;discard the supernatant. 
	NOTE: A swinging bucket rotor is recommended to minimize cell loss. Leave about 3 &#181;L of supernatant to ensure that the cells are not being discarded.</li>
</ol>
4. Tn5 tagmentation
<ol>
	<li>Immediately resuspend the pellet in 25 &#181;L of Tn5 reaction mixture. The Tn5 reaction mixture is as follows: 12.5 &#181;L of 2x Tagmentation DNA buffer (TD buffer), 1.25-5 &#181;L of Tn5 transposase, and 11.25-7.5 &#181;L of nuclease-free water. 
	NOTE: The standard concentration of Tn5 is 2.5 &#181;L for 2.5 x 104 cells.</li>
	<li>Incubate for 30 min at 37 &#176;C. 
	&#8203;NOTE: Mix the solution every 10 min.</li>
</ol>
5. DNA purification
NOTE: Purification is required before amplification. DNA purification is done using the MinElute PCR purification kit (Table of Materials).
<ol>
	<li>Add 5 &#181;L of 3 M sodium acetate (pH 5.2).</li>
	<li>Immediately add 125 &#181;L of Buffer PB and mix well.</li>
	<li>Follow the PCR purification kit protocol starting at step 2.
	<ol>
		<li>Place the spin column in a 2 mL collection tube.</li>
		<li>Apply the sample to the spin column and centrifuge for 1 min at 17,900 x g at RT.</li>
		<li>Discard the flow-through and place the spin column back in the same collection tube.</li>
		<li>Add 750 &#181;L of Buffer PE to the spin column and centrifuge for 1 min at 17,900 x g at RT.</li>
		<li>Discard the flow-through and place the spin column back in the same collection tube.</li>
		<li>Centrifuge the spin column for 5 min to dry the membrane completely.</li>
		<li>Discard the flow-through and place the spin column in a new 1.7 mL microcentrifuge tube.</li>
		<li>Elute the DNA fragments with 10 &#181;L of Buffer EB.</li>
		<li>Let the column stand for 1 min at RT.</li>
		<li>Centrifuge for 1 min at 17,900 x g at RT to elute the DNA.</li>
	</ol>
	</li>
</ol>
6. PCR amplification
NOTE: PCR amplification of transposed (tagmented) DNAs is necessary for sequencing. Nextera kit adapters (Table of Materials) were used in this example. The primers used in this study are listed in Table 1.
<ol>
	<li>Set up the following PCR reaction in 200 &#181;L PCR tubes (50 &#181;L for each sample). The PCR reaction mixture is as follows: 10 &#181;L of eluted DNA (step 5.), 2.5 &#181;L of 25 mM Adapter 1, 2.5 &#181;L of 25 mM Adapter 2, 25 &#181;L of 2x PCR master mix, and 10 &#181;L of nuclease-free water</li>
	<li>Perform PCR amplification program part 1 (Table 2). 
	NOTE: For initial amplification, the same conditions are used for all samples using a standard thermal cycler.</li>
	<li>Real-time qPCR (total of 14.5 &#181;L per sample)
	<ol>
		<li>Using 5 &#181;L of the product from the PCR amplification part 1 (step 6.2.), set up the following reaction, this time including SYBR gold and detection in a real-time PCR machine.</li>
		<li>Prepare the PCR reaction mixture as follows: 5 &#181;L of PCR product from step 6.2., 0.75 &#181;L of SYBR gold (1000x diluted), 5 &#181;L of 2x PCR master mix, and 3.75 &#181;L of nuclease-free water. 
		&#8203;NOTE: The precise cycle numbers for library amplification before reaching saturation for each sample are determined by qPCR (Table 3) to reduce the GC and size bias in PCR10. SYBR Gold was diluted with nuclease-free water. To make the diluted solution, 1 &#181;L of SYBR Gold (stock concentration 10,000x) was added to&#160;999 &#181;L of nuclease-free water. The run time of RT-qPCR mentioned in Table 3 is about 60 min.</li>
	</ol>
	</li>
	<li>Determine the required number of additional PCR cycles using the run parameters from step 6.3.
	<ol>
		<li>Number of cycles = 1/4 maximum (saturated) fluorescence intensity (typically 3 or 4 PCR cycles)</li>
	</ol>
	</li>
	<li>PCR amplification program part 2 (volume = 45 &#181;L; Table 4): Once you determine the cycle number, set up PCRs with additional cycles calculated at step 6.4.1. For instance, if the cycle number calculated is 3, set up 3 cycles in the program below. The total cycles would be 8 (5 in step 6.2., plus 3 additional cycles in step 6.5.)</li>
</ol>
7. Beads purification
NOTE: Here, AMPure XP (Table of Materials) beads were used.
<ol>
	<li>To the PCR products amplified in the previous step, add 150 &#181;L of beads at RT. 
	NOTE: Homemade AMPure beads14 can be used in this process.</li>
	<li>Incubate for 15 min at RT.</li>
	<li>Place the tubes on a magnetic stand for 5 min.</li>
	<li>Carefully remove the supernatant.</li>
	<li>Wash the beads with 200 &#181;L of 80% ethanol. 
	NOTE: 80% ethanol should be prepared fresh.</li>
	<li>Repeat step 7.4.</li>
	<li>Remove the ethanol completely.</li>
	<li>Air dry the samples for 10 min at RT.</li>
	<li>Resuspend with 50 &#181;L of elution buffer (10 mM Tris-HCL pH 8.0).</li>
	<li>Repeat the beads purification (steps 7.1.-7.9.) to further minimize primer contamination.</li>
</ol>
8. DNA concentration and quality check
<ol>
	<li>Measure the DNA concentration by using a nucleic acid quantification kit (Table of Materials).</li>
	<li>Check the amplified DNA fragments by gel electrophoresis using SYBR Gold (0.5x TBE, 1.5% agarose gel) or an automated electrophoresis system (e.g., TapeStation, bioanalyzer).</li>
</ol>
9. Sequencing
<ol>
	<li>Perform high-throughput sequencing using the amplified DNA samples12,13. 
	&#8203;NOTE: Amplified DNA samples are ready for high-throughput sequencing. To retain nucleosomal DNA fragment information, paired-end sequencing is recommended over single-end sequencing. Both ends of the DNA fragments indicate where the transposase bind. For mapping open chromatin regions, 30 million reads/sample is typically sufficient.</li>
</ol>
10. Data analysis
<ol>
	<li>Data filtration based on base call quality: Set the minimum average base quality score to 20 (99% accuracy).</li>
	<li>Adapter trimming: Remove the adapter sequences using an appropriate tool. 
	NOTE: The Trim Galore wrapper tool (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) was used to remove adapter sequences. For ATAC-seq libraries prepared by Illumina Tn5, the following sequence is used as an adapter sequence: CTGTCTCTTATACACATCT. The minimum sequence length to recognize adapter contamination is set to 5.</li>
	<li>Genome mapping: Map the reads to the appropriate genome with Bowtie using the following parameters &#34;-I 0 -X 2000 -m 1&#34;15. An example of mapping quality from MDA-MB-231 basal breast cancer cells is below: 
	Reads with at least one reported alignment: 52.79% 
	Reads that failed to align: 13.10% 
	Reads with alignments suppressed due to -m: 34.11%</li>
	<li>Deduplication: Mark the PCR duplicates by Picard tools16.</li>
	<li>Generating a genome coverage file for data visualization: Convert the deduplicated paired-end reads to single-end read fragments. Genome coverage tracks are obtained using genomeCoverageBed from bedtools17.</li>
</ol>

<ol>
	<li>Klemm, S. L., Shipony, Z., Greenleaf, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatin+accessibility+and+the+regulatory+epigenome.">Chromatin accessibility and the regulatory epigenome.</a> Nature Reviews Genetics. 20 (4), 207-220 (2019).</li><li>Liu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+implications+of+chromatin+accessibility+in+human+cancers.">Clinical implications of chromatin accessibility in human cancers.</a> Oncotarget. 11 (18), 1666-1678 (2020).</li><li>Sanghi, A., 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=Chromatin+accessibility+associates+with+protein-RNA+correlation+in+human+cancer.">Chromatin accessibility associates with protein-RNA correlation in human cancer.</a> Nature Communications. 12 (1), 5732 (2021).</li><li>Corces, M. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+chromatin+accessibility+landscape+of+primary+human+cancers.">The chromatin accessibility landscape of primary human cancers.</a> Science. 362 (6413), (2018).</li><li>Boyle, A. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+mapping+and+characterization+of+open+chromatin+across+the+genome.">High-resolution mapping and characterization of open chromatin across the genome.</a> Cell. 132 (2), 311-322 (2008).</li><li>Giresi, P. G., Kim, J., McDaniell, R. M., Iyer, V. R., Lieb, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FAIRE+(Formaldehyde-Assisted+Isolation+of+Regulatory+Elements)+isolates+active+regulatory+elements+from+human+chromatin.">FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin.</a> Genome Research. 17 (6), 877-885 (2007).</li><li>Pardo, C. E., Nabilsi, N. H., Darst, R. P., Kladde, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrated+DNA+methylation+and+chromatin+structural+analysis+at+single-molecule+resolution.">Integrated DNA methylation and chromatin structural analysis at single-molecule resolution.</a> Methods in Molecular Biology. 1288, 123-141 (2015).</li><li>Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., Greenleaf, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transposition+of+native+chromatin+for+fast+and+sensitive+epigenomic+profiling+of+open+chromatin,+DNA-binding+proteins+and+nucleosome+position.">Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position.</a> Nature Methods. 10 (12), 1213-1218 (2013).</li><li>Song, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Open+chromatin+defined+by+DNaseI+and+FAIRE+identifies+regulatory+elements+that+shape+cell-type+identity.">Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity.</a> Genome Research. 21 (10), 1757-1767 (2011).</li><li>Buenrostro, J. D., Wu, B., Chang, H. Y., Greenleaf, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATAC-seq:+A+method+for+assaying+chromatin+accessibility+genome-wide.">ATAC-seq: A method for assaying chromatin accessibility genome-wide.</a> Current Protocols in Molecular Biology. , 1 (2015).</li><li>Mehrmohamadi, M., Sepehri, M. H., Nazer, N., Norouzi, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparative+overview+of+epigenomic+profiling+methods.">A comparative overview of epigenomic profiling methods.</a> Frontiers in Cell and Developmental Biology. 9, 714687 (2021).</li><li>Fujiwara, S., Baek, S., Varticovski, L., Kim, S., Hager, G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+quality+ATAC-Seq+data+recovered+from+cryopreserved+breast+cell+lines+and+tissue.">High quality ATAC-Seq data recovered from cryopreserved breast cell lines and tissue.</a> Scientific Reports. 9 (1), 516 (2019).</li><li>Takaku, 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=GATA3-dependent+cellular+reprogramming+requires+activation-domain+dependent+recruitment+of+a+chromatin+remodeler.">GATA3-dependent cellular reprogramming requires activation-domain dependent recruitment of a chromatin remodeler.</a> Genome Biology. 17, 36 (2016).</li><li>Rohland, N., Reich, D. C. o. s. t. -. e. f. f. e. c. t. i. v. e. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=high-throughput+DNA+sequencing+libraries+for+multiplexed+target+capture.">high-throughput DNA sequencing libraries for multiplexed target capture.</a> Genome Research. 22 (5), 939-946 (2012).</li><li>Langmead, B., Trapnell, C., Pop, M., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+and+memory-efficient+alignment+of+short+DNA+sequences+to+the+human+genome.">Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.</a> Genome Biology. 10 (3), 25 (2009).</li><li>. Picard Toolkit Broad Institute, GitHub Repository Available from: <a target="_blank" href="https://broadinstitute.github.io/picard/">https://broadinstitute.github.io/picard/</a> (2022)</li><li>Quinlan, A. R., Hall, I. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BEDTools:+A+flexible+suite+of+utilities+for+comparing+genomic+features.">BEDTools: A flexible suite of utilities for comparing genomic features.</a> Bioinformatics. 26 (6), 841-842 (2010).</li><li>Strober, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trypan+blue+exclusion+test+of+cell+viability.">Trypan blue exclusion test of cell viability.</a> Current Protocols in Immunology. 111, 1-3 (2015).</li><li>Zhou, 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=INO80+governs+superenhancer-mediated+oncogenic+transcription+and+tumor+growth+in+melanoma.">INO80 governs superenhancer-mediated oncogenic transcription and tumor growth in melanoma.</a> Genes &amp; Development. 30 (12), 1440-1453 (2016).</li><li>Takaku, 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=GATA3+zinc+finger+2+mutations+reprogram+the+breast+cancer+transcriptional+network.">GATA3 zinc finger 2 mutations reprogram the breast cancer transcriptional network.</a> Nature Communications. 9 (1), 1059 (2018).</li><li>Oldfield, A. 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=NF-Y+controls+fidelity+of+transcription+initiation+at+gene+promoters+through+maintenance+of+the+nucleosome-depleted+region.">NF-Y controls fidelity of transcription initiation at gene promoters through maintenance of the nucleosome-depleted region.</a> Nature Communications. 10 (1), 3072 (2019).</li><li>Langer, L. F., Ward, J. M., Archer, T. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+suppressor+SMARCB1+suppresses+super-enhancers+to+govern+hESC+lineage+determination.">Tumor suppressor SMARCB1 suppresses super-enhancers to govern hESC lineage determination.</a> Elife. 8, 45672 (2019).</li><li>Elrod, N. 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=The+integrator+complex+attenuates+promoter-proximal+transcription+at+protein-coding+genes.">The integrator complex attenuates promoter-proximal transcription at protein-coding genes.</a> Molecular Cell. 76 (5), 738-752 (2019).</li><li>Corces, M. R., 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=An+improved+ATAC-seq+protocol+reduces+background+and+enables+interrogation+of+frozen+tissues.">An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues.</a> Nature Methods. 14 (10), 959-962 (2017).</li><li>Porter, J. R., 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=Global+inhibition+with+specific+activation:+How+p53+and+MYC+redistribute+the+transcriptome+in+the+DNA+double-strand+break+response.">Global inhibition with specific activation: How p53 and MYC redistribute the transcriptome in the DNA double-strand break response.</a> Molecular Cell. 67 (6), 1013-1025 (2017).</li><li>Dhasarathy, A., Kajita, M., Wade, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+transcription+factor+snail+mediates+epithelial+to+mesenchymal+transitions+by+repression+of+estrogen+receptor-alpha.">The transcription factor snail mediates epithelial to mesenchymal transitions by repression of estrogen receptor-alpha.</a> Molecular Endocrinology. 21 (12), 2907-2918 (2007).</li><li>McCarthy, M. T., O'Callaghan, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PeaKDEck:+A+kernel+density+estimator-based+peak+calling+program+for+DNaseI-seq+data.">PeaKDEck: A kernel density estimator-based peak calling program for DNaseI-seq data.</a> Bioinformatics. 30 (9), 1302-1304 (2014).</li><li>Grandi, F. C., Modi, H., Kampman, L., Corces, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatin+accessibility+profiling+by+ATAC-seq.">Chromatin accessibility profiling by ATAC-seq.</a> Nature Protocols. 7 (6), 1518-1552 (2022).</li><li>Heinz, S., 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=Simple+combinations+of+lineage-determining+transcription+factors+prime+cis-regulatory+elements+required+for+macrophage+and+B+cell+identities.">Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.</a> Molecular Cell. 38 (4), 576-589 (2010).</li><li>Hanahan, D., Weinberg, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hallmarks+of+cancer:+The+next+generation.">Hallmarks of cancer: The next generation.</a> Cell. 144 (5), 646-674 (2011).</li><li>Garcia-Martinez, L., Zhang, Y., Nakata, Y., Chan, H. L., Morey, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epigenetic+mechanisms+in+breast+cancer+therapy+and+resistance.">Epigenetic mechanisms in breast cancer therapy and resistance.</a> Nature Communications. 12 (1), 1786 (2021).</li><li>Bhattacharya, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+calcium+channel+proteins+ORAI3+and+STIM1+mediate+TGF-&#946;+induced+Snai1+expression.">The calcium channel proteins ORAI3 and STIM1 mediate TGF-&#946; induced Snai1 expression.</a> Oncotarget. 9 (50), 29468-29483 (2018).</li><li>Schep, A. 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=Structured+nucleosome+fingerprints+enable+high-resolution+mapping+of+chromatin+architecture+within+regulatory+regions.">Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions.</a> Genome Research. 25 (11), 1757-1770 (2015).</li></ol>

The authors declare that there are no relevant or material financial interests that relate to the research described in this paper.

ATAC-seq has been widely used for mapping open and active chromatin regions. Cancer cell progression is frequently driven by genetic alterations and epigenetic reprogramming, resulting in altered chromatin accessibility and gene expression. An example of this reprogramming is seen during the epithelial-to-mesenchymal transition (EMT) and its reverse process, mesenchymal-to-epithelial transition (MET), which are known to be key cellular reprogramming processes during tumor metastasis30. Another exa...

Chromatin accessibility is a key requirement for the regulation of gene expression on a genome-wide scale1. Changes in chromatin accessibility are frequently associated with several disease states, including cancer2,3,4. Over the years, numerous techniques have been developed to enable researchers to probe the chromatin landscape by mapping regions of chromatin accessibility. Some of them include DNase-seq (DNase I hypersensitive sites sequencing)5, FAIRE-seq (formaldehyde-assisted isolation of regulatory elements)6, MAPit (methyltransferase accessibility protocol for individual templates)7, and the focus of this paper, ATAC-seq (assay for transposase-accessible chromatin)8. DNase-seq maps accessible regions by employing a key feature of DNase, namely the preferential digestion of naked DNA free from histones and other proteins such as transcription factors5. FAIRE-seq, similar to ChIP-seq, utilizes formaldehyde crosslinking and sonication, except no immunoprecipitation is involved, and the nucleosome-free regions are isolated by phenol-chloroform extraction6. The MAPit method uses a GC methyltransferase to probe chromatin structure at single-molecule resolution7. ATAC-seq relies on the hyperactive transposase, Tn58. The Tn5 transposase preferentially binds to open chromatin regions and inserts sequencing adapters into accessible regions. Tn5 operates through a DNA-mediated &#34;cut and paste&#34; mechanism, whereby the transposase preloaded with adapters binds to open chromatin sites, cuts DNA, and ligates the adapters8. Tn5 bound regions are recovered by PCR amplification using primers that anneal to these adapters. FAIRE-seq and DNase-seq require a large amount of starting material (~100,000 cells to 225,000 cells) and a separate library preparation step before sequencing9. On the other hand, the ATAC-seq protocol is relatively simple and requires a small number of cells (&#60;50,000 cells)10. Unlike the FAIRE-seq and DNase-seq techniques, the sequencing library preparation of ATAC-seq is relatively easy, as the isolated DNA sample is already being tagged with the sequencing adapters by Tn5. Therefore, only the PCR amplification step with appropriate primers is needed to complete the library preparation, and the prior processing steps such as end-repair and adapter ligation need not be performed, thus saving time11. Secondly, ATAC-seq avoids the need for bisulfite conversion, cloning, and amplification with region-specific primers required for MAPit7. Due to these advantages, ATAC-seq has become a hugely popular method for defining open chromatin regions. Although the ATAC-seq method is simple, multiple steps require optimization to obtain high-quality and reproducible data. This manuscript discusses optimization procedures for standard ATAC-seq library preparation, especially highlighting three parameters: (1) lysis buffer composition, (2) Tn5 transposase concentration, and (3) cell number. In addition, this paper provides example data from the optimization conditions using both cancerous and non-cancerous adherent epithelial cells.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1.5 mL microcentrifuge tubes</td>
			<td>USA Scientific</td>
			<td>1615-5500</td>
			<td>Natural</td>
		</tr>
		<tr>
			<td>10 &#181;L XL TipOne tips</td>
			<td>USA Scientific</td>
			<td>1120-3810</td>
			<td>Filtered and low-retention</td>
		</tr>
		<tr>
			<td>100 &#181;L XL TipOne RPT tips</td>
			<td>USA Scientific</td>
			<td>1182-1830</td>
			<td>Filtered and low-retention</td>
		</tr>
		<tr>
			<td>100 &#181;L XL TipOne tips</td>
			<td>USA Scientific</td>
			<td>1120-1840</td>
			<td>Filtered and low-retention. Beveled Grade</td>
		</tr>
		<tr>
			<td>15 mL Conical Centrifuge Tubes</td>
			<td>Corning</td>
			<td>352096</td>
			<td></td>
		</tr>
		<tr>
			<td>20 &#181;L TipOne RPT tips</td>
			<td>USA Scientific</td>
			<td>1183-1810</td>
			<td>Filtered and low-retention</td>
		</tr>
		<tr>
			<td>200 &#181;L TipOne RPT tips</td>
			<td>USA Scientific</td>
			<td>1180-8810</td>
			<td>Filtered and low-retention</td>
		</tr>
		<tr>
			<td>50 mL Centrifuge Tubes</td>
			<td>Fisherbrand</td>
			<td>06-443-19</td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose</td>
			<td>ThermoFisher Scientific</td>
			<td>YBP136010</td>
			<td>Genetic Analysis Grade</td>
		</tr>
		<tr>
			<td>All the cell lines used in this study are obtained from ATCC</td>
			<td>ATCC</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Allegra X-30R Centrifuge</td>
			<td>Beckman Coulter</td>
			<td>364658</td>
			<td>SX2415</td>
		</tr>
		<tr>
			<td>AMPure XP beads</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td>Bead purification kit</td>
		</tr>
		<tr>
			<td>CellDrop Cell Counter</td>
			<td>DeNovix</td>
			<td>CellDrop FL</td>
			<td>Cell counter</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>MilliporeSigma</td>
			<td>EDS</td>
			<td>BioUltra, anhydrous, &#8805;99% (titration)</td>
		</tr>
		<tr>
			<td>EGTA</td>
			<td>MilliporeSigma</td>
			<td>E3889</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethanol 100%</td>
			<td>ThermoFisher Scientific</td>
			<td>AC615100020</td>
			<td>Anhydrous; Fisher Scientific - Decon Labs Sterilization Products</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum - TET Tested</td>
			<td>R&#38;D Systems</td>
			<td>S10350</td>
			<td>Triple 0.1 &#181;m filtered</td>
		</tr>
		<tr>
			<td>Gibco DMEM 1x</td>
			<td>ThermoFisher Scientific</td>
			<td>11965092</td>
			<td>[+] 4.5 g/L D-glucose; [+] L-Glutamine; [-] Sodium pyruvate</td>
		</tr>
		<tr>
			<td>Gibco PBS 1x</td>
			<td>ThermoFisher Scientific</td>
			<td>10010023</td>
			<td>pH 7.4</td>
		</tr>
		<tr>
			<td>Gibco Trypsin-EDTA 1x</td>
			<td>ThermoFisher Scientific</td>
			<td>25200056</td>
			<td>(0.25%), phenol red</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>IBI Scientific</td>
			<td>56-81-5</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>MilliporeSigma</td>
			<td>G8898</td>
			<td></td>
		</tr>
		<tr>
			<td>HCl</td>
			<td>MilliporeSigma</td>
			<td>H1758</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>MilliporeSigma</td>
			<td>H3375</td>
			<td></td>
		</tr>
		<tr>
			<td>Invitrogen Qubit Fluorometer</td>
			<td>ThermoFisher Scientific</td>
			<td>Q32857</td>
			<td></td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>MilliporeSigma</td>
			<td>M3634</td>
			<td></td>
		</tr>
		<tr>
			<td>MinElute PCR Purification kit</td>
			<td>Qiagen</td>
			<td>28004</td>
			<td>DNA purification kit</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>IBI Scientific</td>
			<td>7647-14-5</td>
			<td></td>
		</tr>
		<tr>
			<td>NaOH</td>
			<td>MilliporeSigma</td>
			<td>S8045</td>
			<td>BioXtra, &#8805;98% (acidimetric), pellets (anhydrous)</td>
		</tr>
		<tr>
			<td>NEBNext High-Fidelity 2x PCR Master Mix</td>
			<td>New England Biolabs</td>
			<td>M0541</td>
			<td></td>
		</tr>
		<tr>
			<td>Nextera DNA Sample Preparation Kit</td>
			<td>Illumina</td>
			<td>FC-121-1030</td>
			<td>2x TD and Tn5 Transposase</td>
		</tr>
		<tr>
			<td>NP - 40 (IGEPAL CA-630)</td>
			<td>MilliporeSigma</td>
			<td>I8896</td>
			<td>for molecular biology</td>
		</tr>
		<tr>
			<td>PCR Detection System</td>
			<td>BioRad</td>
			<td>1855484</td>
			<td>CFX384 Real-Time System. C1000 Touch Thermal Cycler</td>
		</tr>
		<tr>
			<td>PIPES</td>
			<td>MilliporeSigma</td>
			<td>P1851</td>
			<td>BioPerformance Certified, suitable for cell culture</td>
		</tr>
		<tr>
			<td>Qubit dsDNA HS Assay kit</td>
			<td>ThermoFisher Scientific</td>
			<td>Q32854</td>
			<td>Invitrogen; Nucleic acid quantitation kit</td>
		</tr>
		<tr>
			<td>Quibit Assay Tubes</td>
			<td>ThermoFisher Scientific</td>
			<td>Q32856</td>
			<td>Invitrogen</td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>MilliporeSigma</td>
			<td>L3771</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Acetate</td>
			<td>Homemade</td>
			<td>-</td>
			<td>pH 5.2</td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>IBI Scientific</td>
			<td>57-50-1</td>
			<td></td>
		</tr>
		<tr>
			<td>SYBR Gold</td>
			<td>ThermoFisher Scientific</td>
			<td>S11494</td>
			<td></td>
		</tr>
		<tr>
			<td>SYBR Green Supermix, 1.25 mL</td>
			<td>BioRad</td>
			<td>1708882</td>
			<td></td>
		</tr>
		<tr>
			<td>T100 Thermal Cycler</td>
			<td>BioRad</td>
			<td>1861096</td>
			<td></td>
		</tr>
		<tr>
			<td>TempAssure 0.2 mL PCR 8-Tube Strips</td>
			<td>USA Scientific</td>
			<td>1402-4700</td>
			<td>Flex-free, natural, polypropylene</td>
		</tr>
		<tr>
			<td>TempPlate 384-WELL PCR PLATE</td>
			<td>USA Scientific</td>
			<td>1438-4700</td>
			<td>Single notch. Natural polypropylene</td>
		</tr>
		<tr>
			<td>Tris Base</td>
			<td>MilliporeSigma</td>
			<td>648311</td>
			<td>ULTROL Grade</td>
		</tr>
		<tr>
			<td>Triton x-100</td>
			<td>IBI Scientific</td>
			<td>9002-93-1</td>
			<td></td>
		</tr>
		<tr>
			<td>TrueSeq Dual Index Sequencing Primer Kit</td>
			<td>Illumina</td>
			<td>PE-121-1003</td>
			<td>paired-end</td>
		</tr>
		<tr>
			<td>Trypan Blue Stain</td>
			<td>ThermoFisher Scientific</td>
			<td>Q32851</td>
			<td></td>
		</tr>
		<tr>
			<td>Tween-20</td>
			<td>MilliporeSigma</td>
			<td>P7949</td>
			<td>BioXtra, viscous liquid</td>
		</tr>
		<tr>
			<td>Water</td>
			<td>MilliporeSigma</td>
			<td>W3500</td>
			<td>sterile-filtered, BioReagent, suitable for cell culture</td>
		</tr>
	</tbody>
</table>

atac-seq optimization for cancer epigenetics research

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

To obtain successful and high-quality ATAC-seq data, it is important to optimize the experimental conditions. ATAC-seq library preparation can be separated into the five major steps (Figure 1), namely cell lysis, tagmentation (fragmentation and adapter insertion by Tn5), genomic DNA purification, PCR amplification, and data analysis. As an initial process, the cell lysis (nuclear isolation) buffer must be first optimized for each cell type. Either the hypotonic buffer described in the origin...

Watch this Scientific Journal Video about ATAC-Seq Optimization for Cancer Epigenetics Research at JoVE.com

ATAC-Seq Optimization for Cancer Epigenetics Research

ATAC-seq is a DNA sequencing method that uses the hyperactive mutant transposase, Tn5, to map changes in chromatin accessibility mediated by transcription factors. ATAC-seq enables the discovery of the molecular mechanisms underlying phenotypic alterations in cancer cells. This protocol outlines optimization procedures for ATAC-seq in epithelial cell types, including cancer cells.

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the ...

atac-seq-optimization-for-cancer-epigenetics-research

Research

JoVE Journal

Cancer Research

3.9K Views.  University of North Dakota School of Medicine and Health Sciences. ATAC-seq is a DNA sequencing method that uses the hyperactive mutant transposase, Tn5, to map changes in chromatin accessibility mediated by transcription factors. ATAC-seq enables the discovery of the molecular mechanisms underlying phenotypic alterations in cancer cells. This protocol outlines optimization procedures for ATAC-seq in epithelial cell types, including cancer cells. 

Video: ATAC-Seq Optimization for Cancer Epigenetics Research

A Unified Methodological Framework for Vestibular Schwannoma Research

Vestibular schwannomas are the most common neoplasms of the cerebellopontine angle, making up 6-8% percent of all intracranial growths. Though these tumors cause sensorineural hearing loss in up to 95% of affected individuals, the molecular mechanisms underlying this hearing loss remain elusive. This article outlines the steps established in our laboratory to facilitate the collection and processing of various primary human tissue samples for downstream research applications integral to the study of vestibular schwannomas. Specifically, this work describes a unified methodological framework for the collection, processing, and culture of Schwann and schwannoma cells from surgical samples. This is integrated with parallel processing steps now considered essential for current research: the collection of tumor and nerve secretions, the preservation of RNA and the extraction of protein from collected tissues, the fixation of tissue for the preparation of sections, and the exposure of primary human cells to adeno-associated viruses for application to gene therapy. Additionally, this work highlights the translabyrinthine surgical approach to collect this tumor as a unique opportunity to obtain human sensory epithelium from the inner ear and perilymph. Tips to improve experimental quality are provided and common pitfalls highlighted.

The goal of this protocol is to outline the collection and processing of human surgical samples for multiple downstream applications in vestibular schwannoma and Schwann cell research.

Vestibular schwannomas are the most common neoplasms of the cerebellopontine angle, making up 6-8% percent of all intracranial growths. Though these ...

A Three-dimensional Thymic Culture System to Generate Murine Induced Pluripotent Stem Cell-derived Tumor Antigen-specific Thymic Emigrants

The inheritance of pre-rearranged T cell receptors (TCRs) and their epigenetic rejuvenation make induced pluripotent stem cell (iPSC)-derived T cells a promising source for adoptive T cell therapy (ACT). However, classical in vitro methods for producing regenerated T cells from iPSC result in either innate-like or terminally differentiated T cells, which are phenotypically and functionally distinct from na&#239;ve T cells. Recently, a novel three-dimensional (3D) thymic culture system was developed to generate a homogenous subset of CD8&#945;&#946;+ antigen-specific T cells with a na&#239;ve T cell-like functional phenotype, including the capacity for proliferation, memory formation, and tumor suppression in vivo. This protocol avoids aberrant developmental fates, allowing for the generation of clinically relevant iPSC-derived T cells, designated as iPSC-derived thymic emigrants (iTE), while also providing a potent tool to elucidate the subsequent functions necessary for T cell maturation after thymic selection.

This article describes a novel method to generate tumor antigen-specific induced pluripotent stem cell-derived thymic emigrants (iTE) by a three-dimensional (3D) thymic culture system. iTE are a homogenous subset of T cells closely related to na&#239;ve T cells with the capacity for proliferation, memory formation, and tumor suppression.

The inheritance of pre-rearranged T cell receptors (TCRs) and their epigenetic rejuvenation make induced pluripotent stem cell (iPSC)-derived T cells a ...

Optimization, Design and Avoiding Pitfalls in Manual Multiplex Fluorescent Immunohistochemistry

Microenvironment evaluation of intact tissue for analysis of cell infiltration and spatial organization are essential in understanding the complexity of disease processes. The principle techniques used in the past include immunohistochemistry (IHC) and immunofluorescence (IF) which enable visualization of cells as a snapshot in time using between 1 and 4 markers. Both techniques have shortcomings including difficulty staining poorly antigenic targets and limitations related to cross-species reactivity. IHC is reliable and reproducible, but the nature of the chemistry and reliance on the visible light spectrum allows for only a few markers to be used and makes co-localization challenging. Use of IF broadens potential markers but typically relies on frozen tissue due to the extensive tissue autofluorescence following formalin fixation. Flow cytometry, a technique that enables simultaneous labeling of multiple epitopes, abrogates many of the deficiencies of IF and IHC, however, the need to examine cells as a single cell suspension loses the spatial context of cells discarding important biologic relationships. Multiplex fluorescent immunohistochemistry (mfIHC) bridges these technologies allowing for multi-epitope cellular phenotyping in formalin fixed paraffin embedded (FFPE) tissue while preserving the overall microenvironment architecture and spatial relationship of cells within intact undisrupted tissue. High fluorescent intensity fluorophores that covalently bond to the tissue epitope enables multiple applications of primary antibodies without worry of species specific cross-reactivity by secondary antibodies. Although this technology has been proven to produce reliable and accurate images for the study of disease, the process of creating a useful mfIHC staining strategy can be time consuming and exacting due to extensive optimization and design. In order to make robust images that represent accurate cellular interactions in-situ and to mitigate the optimization period for manual analysis, presented here are methods for slide preparation, optimizing antibodies, multiplex design as well as errors commonly encountered during the staining process.

Multiplex fluorescent immunohistochemistry is an emerging technology that enables the visualization of multiple cell types within intact formalin-fixed, paraffin embedded (FFPE) tissue. Presented are guidelines for ensuring a successful 7-color multiplex with instructions for optimizing antibodies and reagents, preparing slides, design and tips for avoiding common problems.

Microenvironment evaluation of intact tissue for analysis of cell infiltration and spatial organization are essential in understanding the complexity of ...

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less aggressive breast tumors, the 5-year survival rate of TNBC patients is 77% due to their characteristic drug-resistant phenotype and metastatic burden. Toward this end, murine models have been established aimed at identifying novel therapeutic strategies limiting TNBC tumor growth and metastatic spread. This work describes a practical guide for the TNBC orthotopic model where MDA-MB-231 breast cancer cells suspended in a basement membrane matrix are implanted in the fourth mammary fat pad, which closely mimics the cancer cell behavior in humans. Measurement of tumors by caliper, lung metastasis assessment via in vivo and ex vivo imaging, and molecular detection are discussed. This model provides an excellent platform to study therapeutic efficacy and is especially suitable for the study of the interaction between the primary tumor and distal metastatic sites.

This work presets an advanced protocol to accurately assess tumor loading by detection of green fluorescent protein and bioluminescence signals as well as the integration of quantitative molecular detection technique.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less ...

Generation of Orthotopic Pancreatic Tumors and Ex vivo Characterization of Tumor-Infiltrating T Cell Cytotoxicity

In vivo models of pancreatic cancer provide invaluable tools for studying disease dynamics, immune infiltration and new therapeutic strategies. The orthotopic murine model can be performed on large cohorts of immunocompetent mice simultaneously, is relatively inexpensive and preserves the cognate tissue microenvironment. The quantification of T cell infiltration and cytotoxic activity within orthotopic tumors provides a useful indicator of an antitumoral response.
This protocol describes the methodology for surgical generation of orthotopic pancreatic tumors by injection of a low number of syngeneic tumor cells resuspended in 5 &#181;L basement membrane directly into the pancreas. Mice bearing orthotopic tumors take approximately 30 days to reach endpoint, at which point tumors can be harvested and processed for characterization of tumor-infiltrating T cell activity. Rapid enzymatic digestion using collagenase and DNase allows a single-cell suspension to be extracted from tumors. The viability and cell surface markers of immune cells extracted from the tumor are preserved; therefore, it is appropriate for multiple downstream applications, including flow-assisted cell sorting of immune cells for culture or RNA extraction, flow cytometry analysis of immune cell populations. Here, we describe the ex vivo stimulation of T cell populations for intracellular cytokine quantification (IFN&#947; and TNF&#945;) and degranulation activity (CD107a) as a measure of overall cytotoxicity. Whole-tumor digests were stimulated with phorbol myristate acetate and ionomycin for 5 h, in the presence of anti-CD107a antibody in order to upregulate cytokine production and degranulation. The addition of brefeldin A and monensin for the final 4 h was performed to block extracellular transport and maximize cytokine detection. Extra- and intra-cellular staining of cells was then performed for flow cytometry analysis, where the proportion of IFN&#947;+, TNF&#945;+ and CD107a+ CD4+ and CD8+ T cells was quantified.
This method provides a starting base to perform comprehensive analysis of the tumor microenvironment.

Generation of Orthotopic Pancreatic Tumors and Ex vivo Characterization of Tumor-Infiltrating T Cell Cytotoxicity

This protocol describes the surgical generation of orthotopic pancreatic tumors and the rapid digestion of freshly isolated murine pancreatic tumors. Following digestion, viable immune cell populations can be used for further downstream analysis, including ex vivo stimulation of T cells for intracellular cytokine detection by flow cytometry.

In vivo models of pancreatic cancer provide invaluable tools for studying disease dynamics, immune infiltration and new therapeutic strategies. The ...

Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq

Adult diffuse gliomas exhibit inter- and intra-tumor heterogeneity. Until recently, the majority of large-scale molecular profiling efforts have focused on bulk approaches that led to the molecular classification of brain tumors. Over the last five years, single cell sequencing approaches have highlighted several important features of gliomas. The majority of these studies have utilized fresh brain tumor specimens to isolate single cells using flow cytometry or antibody-based separation methods. Moving forward, the use of fresh-frozen tissue samples from biobanks will provide greater flexibility to single cell applications. Furthermore, as the single-cell field advances, the next challenge will be to generate multi-omics data from either a single cell or the same sample preparation to better unravel tumor complexity. Therefore, simple and flexible protocols that allow data generation for various methods such as single-nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin with high-throughput sequencing (snATAC-seq) will be important for the field.
Recent advances in the single cell field coupled with accessible microfluidic instruments such as the 10x genomics platform have facilitated single cell applications in research laboratories. To study brain tumor heterogeneity, we developed an enhanced protocol for the isolation of single nuclei from fresh frozen gliomas. This protocol merges existing single cell protocols and combines a homogenization step followed by filtration and buffer mediated gradient centrifugation. The resulting samples are pure single nuclei suspensions that can be used to generate single nucleus gene expression and chromatin accessibility data from the same nuclei preparation.

Intra-tumoral heterogeneity is an inherent feature of tumors, including gliomas. We developed a simple and efficient protocol that utilizes a combination of buffers and gradient centrifugation to isolate single nuclei from fresh frozen glioma tissues for single nucleus RNA and ATAC sequencing studies.

Adult diffuse gliomas exhibit inter- and intra-tumor heterogeneity. Until recently, the majority of large-scale molecular profiling efforts have focused ...

An Orthotopic Resectional Mouse Model of Pancreatic Cancer

There is a lack of satisfactory animal models to study adjuvant and/or neoadjuvant therapy in patients being considered for surgery of pancreatic cancer (PC). To address this deficiency, we describe a mouse model involving orthotopic implantation of PC followed by distal pancreatectomy and splenectomy. The model has been demonstrated to be safe and suitably flexible for the study of various therapeutic approaches in adjuvant and neo adjuvant settings.
In this model, a pancreatic tumor is first generated by implanting a mixture of human pancreatic cancer cells (luciferase-tagged AsPC-1) and human cancer associated pancreatic stellate cells into the distal pancreas of Balb/c athymic nude mice. After three weeks, the cancer is resected by re-laparotomy, distal pancreatectomy and splenectomy. In this model, bioluminescence imaging can be used to follow the progress of cancer development and effects of resection/treatments. Following resection, adjuvant therapy can be given. Alternatively, neoadjuvant treatment can be given prior to resection.
Representative data from 45 mice are presented. All mice underwent successful distal pancreatectomy/splenectomy with no issues of hemostasis. A macroscopic proximal pancreatic margin greater than 5 mm was achieved in 43 (96%) mice. The technical success rate of pancreatic resection was 100%, with 0% early mortality and morbidity. None of the animals died during the week after resection.
In summary, we describe a robust and reproducible technique for a surgical resection model of pancreatic cancer in mice which mimics the clinical scenario. The model may be useful for the testing of both adjuvant and neoadjuvant treatments.

In the clinical context, patients with localized pancreatic cancer will undergo pancreatectomy followed by adjuvant treatment. This protocol reported here aims to establish a safe and effective method of modelling this clinical scenario in nude mice, through orthotopic implantation of pancreatic cancer followed by distal pancreatectomy and splenectomy.

There is a lack of satisfactory animal models to study adjuvant and/or neoadjuvant therapy in patients being considered for surgery of pancreatic cancer ...

Circulating Tumor Cell Lines: an Innovative Tool for Fundamental and Translational Research

Metastasis is a leading cause of cancer death. Despite improvements in treatment strategies, metastatic cancer has a poor prognosis. We thus face an urgent need to understand the mechanisms behind metastasis development, and thus to propose efficient treatments for advanced cancer. Metastatic cancers are hard to treat, as biopsies are invasive and inaccessible. Recently, there has been considerable interest in liquid biopsies including both cell-free circulating deoxyribonucleic acid (DNA) and circulating tumor cells from peripheral blood and we have established several circulating tumor cell lines from metastatic colorectal cancer patients to participate in their characterization. Indeed, to functionally characterize these rare and poorly described cells, the crucial step is to expand them. Once established, circulating tumor cell (CTC) lines can then be cultured in suspension or adherent conditions. At the molecular level, CTC lines can be further used to assess the expression of specific markers of interest (such as differentiation, epithelial or cancer stem cells) by immunofluorescence or cytometry analysis. In addition, CTC lines can be used to assess drug sensitivity to gold-standard chemotherapies as well as to targeted therapies. The ability of CTC lines to initiate tumors can also be tested by subcutaneous injection of CTCs in immunodeficient mice.
Finally, it is possible to test the role of specific genes of interest that might be involved in cancer dissemination by editing CTC genes, by short hairpin ribonucleic acid (shRNA) or Crispr/Cas9. Modified CTCs can thus be injected into immunodeficient mouse spleens, to experimentally mimic part of the metastatic development process in vivo.
In conclusion, CTC lines are a precious tool for future research and for personalized medicine, where they will allow prediction of treatment efficiency using the very cells that are originally responsible for metastasis.

Culturing CTCs allows a deeper functional characterization of cancer, through assaying specific marker expression, and assessing drug resistance and the ability to colonize the liver among other possibilities. Overall, CTC culture could be a promising clinical tool for personalized medicine to improve patient outcome.

Metastasis is a leading cause of cancer death. Despite improvements in treatment strategies, metastatic cancer has a poor prognosis. We thus face an ...

Translational Orthotopic Models of Glioblastoma Multiforme

Genetically engineered mouse (GEM) models for human glioblastoma multiforme (GBM) are critical to understanding the development and progression of brain tumors. Unlike xenograft tumors, in GEMs, tumors arise in the native microenvironment in an immunocompetent mouse. However, the use of GBM GEMs in preclinical treatment studies is challenging due to long tumor latencies, heterogeneity in neoplasm frequency, and the timing of advanced grade tumor development. Mice induced via intracranial orthotopic injection are more tractable for preclinical studies, and retain features of the GEM tumors. We generated an orthotopic brain tumor model derived from a GEM model with Rb, Kras, and p53 aberrations (TRP), which develops GBM tumors&#160;displaying linear foci of necrosis by neoplastic cells, and dense vascularization analogous to human GBM. Cells derived from GEM GBM tumors are injected intracranially into wild-type, strain-matched recipient mice and reproduce grade IV tumors, therefore bypassing the long tumor latency period in GEM mice and allowing for the creation of large and reproducible cohorts for preclinical studies. The highly proliferative, invasive, and vascular features of the TRP GEM model for GBM are recapitulated in the orthotopic tumors, and histopathology markers reflect human GBM subgroups. Tumor growth is monitored by serial MRI scans. Due to the invasive nature of the intracranial tumors in immunocompetent models, carefully following the injection procedure outlined here is essential to prevent extracranial tumor growth.

Here, we describe a preclinical orthotopic mouse model for GBM, established by intracranial injection of cells derived from genetically engineered mouse model tumors. This model displays the disease hallmarks of human GBM. For translational studies, the mouse brain tumor is tracked by in vivo MRI and histopathology.

Genetically engineered mouse (GEM) models for human glioblastoma multiforme (GBM) are critical to understanding the development and progression of brain ...

Quantifying Telomere Length Using Non-Radioactive Chemiluminescence Detection

Optimization of Performance Parameters of the TAGGG Telomere Length Assay

Telomeres are repetitive sequences which are present at chromosomal ends; their shortening is a characteristic feature of human somatic cells. Shortening occurs due to a problem with end replication and the absence of the telomerase enzyme, which is responsible for maintaining telomere length. Interestingly, telomeres also shorten in response to various internal physiological processes, like oxidative stress and inflammation, which may be impacted due to extracellular agents like pollutants, infectious agents, nutrients, or radiation. Thus, telomere length serves as an excellent biomarker of aging and various physiological health parameters. The TAGGG telomere length assay kit is used to quantify average telomere lengths using the telomere restriction fragment (TRF) assay and is highly reproducible. However, it is an expensive method, and because of this, it is not employed routinely for large sample numbers. Here, we describe a detailed protocol for an optimized and cost-effective measurement of telomere length using Southern blots or TRF analysis and non-radioactive chemiluminescence-based detection.

Author Spotlight: Optimization of Performance Parameters of the TAGGG Telomere Length Assay  

Here, we describe in detail the protocol for quantifying telomere length using non-radioactive chemiluminescent detection, with a focus on the optimization of various performance parameters of the TAGGG telomere length assay kit, such as buffer quantities and probe concentrations.

Telomeres are repetitive sequences which are present at chromosomal ends; their shortening is a characteristic feature of human somatic cells. Shortening ...