This study was supported by the Adelson Medical Research Foundation (AMRF), the Melanoma Research Alliance (MRA), and U54CA224068. Figure 1, Figure 4, and Figure 5 were created with BioRender.com.

This study complied with all institutional guidelines regarding human tissue sampling. Informed consent was received from patients, and identifiable sample data was anonymized. Samples are collected in the operation room, placed in a solution of RPMI, saline, or PBS, and confirmed cancerous via the pathology department before use in research. All steps, except when indicated, should be carried out at 4 &#176;C or on ice. Work inside a biosafety hood when processing human tissue. See the Table of Materials</strong...

Tumor Dissociation Protocol for Single-Cell RNA Sequencing Analysis

<ol>
	<li>Liu, C., Yang, M., Zhang, D., Chen, M., Zhu, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+cancer+immunotherapy:+Current+progress+and+prospects.">Clinical cancer immunotherapy: Current progress and prospects.</a> Front Immunol. 13, 961805 (2022).</li><li>Baghban, 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=Tumor+microenvironment+complexity+and+therapeutic+implications+at+a+glance.">Tumor microenvironment complexity and therapeutic implications at a glance.</a> Cell Commun Signal. 18 (1), 59 (2020).</li><li>Sun, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+RNA+sequencing+in+cancer:+Applications,+advances,+and+emerging+challenges.">Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges.</a> Mol Ther Oncolytics. 21, 183-206 (2021).</li><li>Huang, 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=Advances+in+single-cell+RNA+sequencing+and+its+applications+in+cancer+research.">Advances in single-cell RNA sequencing and its applications in cancer research.</a> J Hematol Oncol. 16 (1), 98 (2023).</li><li>Ottaiano, 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=From+chaos+to+opportunity:+decoding+cancer+heterogeneity+for+enhanced+treatment+strategies.">From chaos to opportunity: decoding cancer heterogeneity for enhanced treatment strategies.</a> Biology. 12 (9), 1183 (2023).</li><li>Hwang, B., Lee, J. H., Bang, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+RNA+sequencing+technologies+and+bioinformatics+pipelines.">Single-cell RNA sequencing technologies and bioinformatics pipelines.</a> Exp Mol Med. 50 (8), 1-14 (2018).</li><li>Erfanian, 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=Deep+learning+applications+in+single-cell+genomics+and+transcriptomics+data+analysis.">Deep learning applications in single-cell genomics and transcriptomics data analysis.</a> Biomed Pharmacother. 165, 115077 (2023).</li><li>Jovic, 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=Single-cell+RNA+sequencing+technologies+and+applications:+A+brief+overview.">Single-cell RNA sequencing technologies and applications: A brief overview.</a> Clin Transl Med. 12 (3), e694 (2022).</li><li>Burja, 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=An+optimized+tissue+dissociation+protocol+for+single-cell+RNA+sequencing+analysis+of+fresh+and+cultured+human+skin+biopsies.">An optimized tissue dissociation protocol for single-cell RNA sequencing analysis of fresh and cultured human skin biopsies.</a> Front Cell Dev Biol. 10, 872688 (2022).</li><li>Denisenko, 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=Systematic+assessment+of+tissue+dissociation+and+storage+biases+in+single-cell+and+single-nucleus+RNA-seq+workflows.">Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows.</a> Genome Biol. 21 (1), 130 (2020).</li><li>Sade-Feldman, 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=Defining+T+cell+states+associated+with+response+to+checkpoint+immunotherapy+in+melanoma.">Defining T cell states associated with response to checkpoint immunotherapy in melanoma.</a> Cell. 176 (1-2), 404 (2019).</li><li>Pelka, K., 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=Spatially+organized+multicellular+immune+hubs+in+human+colorectal+cancer.">Spatially organized multicellular immune hubs in human colorectal cancer.</a> Cell. 184 (18), 4734-4752.e20 (2021).</li><li>Bill, 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=CXCL9:SPP1+macrophage+polarity+identifies+a+network+of+cellular+programs+that+control+human+cancers.">CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers.</a> Science. 381 (6657), 515-524 (2023).</li><li>Al'Khafaji, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+RNA+isoform+sequencing+using+programmed+cDNA+concatenation.">High-throughput RNA isoform sequencing using programmed cDNA concatenation.</a> Nat Biotechnol. 42 (4), 582-586 (2024).</li><li>Xing, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+cell+isolation+methods+on+the+human+transcriptome+profiling+and+microbial+transcripts+of+peripheral+blood.">The effect of cell isolation methods on the human transcriptome profiling and microbial transcripts of peripheral blood.</a> Mol Biol Rep. 48 (4), 3059-3068 (2021).</li><li>Ma, F., Hernandez, G. E., Romay, M., Iruela-Arispe, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+RNA+sequencing+to+study+vascular+diversity+and+function.">Single-cell RNA sequencing to study vascular diversity and function.</a> Curr Opin Hematol. 28 (3), 221-229 (2021).</li><li>Fan, X. -. 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=Impact+of+cold+ischemic+time+and+freeze-thaw+cycles+on+RNA,+DNA+and+protein+quality+in+colorectal+cancer+tissues+biobanking.">Impact of cold ischemic time and freeze-thaw cycles on RNA, DNA and protein quality in colorectal cancer tissues biobanking.</a> J Cancer. 10 (20), 4978-4988 (2019).</li><li>LoCoco, P. 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=Reliable+approaches+to+extract+high-integrity+RNA+from+skin+and+other+pertinent+tissues+used+in+pain+research.">Reliable approaches to extract high-integrity RNA from skin and other pertinent tissues used in pain research.</a> Pain Rep. 5 (2), e818 (2020).</li><li>Montanari, 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=Automated-mechanical+procedure+compared+to+gentle+enzymatic+tissue+dissociation+in+cell+function+studies.">Automated-mechanical procedure compared to gentle enzymatic tissue dissociation in cell function studies.</a> Biomolecules. 12 (5), 701 (2022).</li><li>Yosefov-Levi, O., Tornovsky, S., Parnas, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pancreatic+tissue+dissection+to+isolate+viable+single+cells.">Pancreatic tissue dissection to isolate viable single cells.</a> J Vis Exp. (195), (2023).</li><li>Janssen, 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=The+effect+of+background+noise+and+its+removal+on+the+analysis+of+single-cell+expression+data.">The effect of background noise and its removal on the analysis of single-cell expression data.</a> Genome Biol. 24 (1), 140 (2023).</li><li>Adam, M., Potter, A. S., Potter, S. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Psychrophilic+proteases+dramatically+reduce+single+cell+RNA-seq+artifacts:+A+molecular+atlas+of+kidney+development.">Psychrophilic proteases dramatically reduce single cell RNA-seq artifacts: A molecular atlas of kidney development.</a> Development. 144 (19), 3625-3632 (2017).</li><li>Sutermaster, B. A., Darling, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Considerations+for+high-yield,+high-throughput+cell+enrichment:+fluorescence+versus+magnetic+sorting.">Considerations for high-yield, high-throughput cell enrichment: fluorescence versus magnetic sorting.</a> Sci Rep. 9 (1), 227 (2019).</li></ol>

M.S-F. received funding from Bristol Myers-Squibb, Istari Oncology, and was a consultant for Galvazine Therapeutics.

This protocol describes human or murine tumor samples dissociation into a single-cell suspension for scRNA sequencing using the 10x Genomics microfluidic system. In processing tissues that often come from rare cancers or are part of ongoing clinical trials or long experiments for murine tumors, the sample must be optimally and carefully preserved between all steps. All steps should be carried out rapidly on ice or at 4 &#730;C to keep the native cellular RNA profiles and prevent degradation, as working at room temperatur...

Although many advancements in cancer research have led to the development and FDA approval of agents targeting inhibitory receptors expressed on immune and tumor cells, known as checkpoint blockade inhibitors, therapy resistance and identifying mechanisms that drive patient response remain challenging1. The complex challenge of characterizing tumor heterogeneity on its molecular diversity and the intricate interplay between tumor cells and the immune microenvironment necessitates new approaches to dissect this complex ecosystem at the single-cell resolution. Understanding the molecular intricacies within tumors and their microenvironments is pivotal for advancing therapeutic strategies and deciphering the complex biology underlying cancer progression2. Single-cell RNA sequencing (scRNA-seq) has become increasingly popular because it provides high-resolution analysis of individual cells within complex tumor samples3,4.
Tumor heterogeneity, encompassing genetic, epigenetic, and phenotypic diversities, poses a challenge in uncovering the intricacies of cancer biology5. The conventional methods of bulk RNA sequencing tend to obscure the unique expression profiles and phenotypes of heterogeneous cell populations present within tumors, as these methods average signals across entire cell populations4. In contrast, scRNA-seq allows the dissection of individual cell types, revealing diverse gene expression, repression patterns, and cellular states otherwise overlooked4,6. The premise of scRNA-seq lies in its capacity to decode individual cells&#39; genetic and molecular signatures, holding immense promise in discovering new cancer therapeutics7.
By deciphering the gene expression profiles of tumor cells and the surrounding stromal and immune cells, researchers can identify novel therapeutic targets and develop precision genetic medicine strategies tailored to individual patients6. Furthermore, dissecting the immune repertoire within the tumor microenvironment provides crucial insights into the interplay between tumor cells and immune effectors, paving the way for immunotherapeutic interventions3. Despite advances in using scRNAseq on clinical samples, several challenges during the processing steps can harm the cell&#39;s RNA integrity, viability, and quality of the data generated. Moreover, processing tissue with low cell viability can increase ambient RNA levels in the droplets generated during the encapsulation of individual cells, resulting in cross-contamination and incorrect annotation of cell types, while long dissociation protocols performed at 37 &#176;C can lead to the upregulation of a stress response gene signature in multiple cell types8,9,10.
The stepwise procedure (Figure 1A) outlined in this protocol commences with rapid mechanical and enzymatic dissociation of tumors, followed by filtration and the removal of dead cells, depending on the viability of each tumor sample. At present, this procedure has been verified in melanoma11, colorectal12, head and neck squamous cell carcinoma13, pancreatic and lung (unpublished data) tumor samples. These techniques ensure the generation of high-quality viable cell suspensions crucial for downstream analyses14. Notably, removing red blood cells, devoid of synthesized RNA, becomes imperative to purify the sample15. Subsequent evaluation of cell counts and the elimination of dead cells serve as a prerequisite for successful 10x Genomics Gel bead-in Emulsion (GEM) generation, barcoding, and increase the recovery of transcripts and sequenced cells without jeopardizing the exclusion of sensitive populations (e.g., neutrophils and epithelial cells)16. These steps are fundamental in unlocking the potential of single-cell resolution analysis within tumor samples9,10, uncovering novel gene expression profiles and immune signatures necessary for driving innovative therapeutic interventions, and identifying new tumor vulnerabilities.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1x PBS</td>
			<td>Corning</td>
			<td>21-040-CV</td>
			<td></td>
		</tr>
		<tr>
			<td>10 mL serological pipette</td>
			<td>Corning</td>
			<td>357551</td>
			<td></td>
		</tr>
		<tr>
			<td>1000 &#956;L low-retention pipette tips</td>
			<td>Rainin</td>
			<td>30389213</td>
			<td></td>
		</tr>
		<tr>
			<td>1000 &#956;L low-retention wide pipette tips</td>
			<td>Rainin</td>
			<td>30389218</td>
			<td></td>
		</tr>
		<tr>
			<td>1000 &#956;L pipette tips</td>
			<td>Rainin</td>
			<td>30389212</td>
			<td></td>
		</tr>
		<tr>
			<td>10x Magnetic Separator</td>
			<td>10x Genomics</td>
			<td>120250</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL conical tubes</td>
			<td>Corning</td>
			<td>430052</td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL aspirating pipette</td>
			<td>Corning</td>
			<td>357558</td>
			<td></td>
		</tr>
		<tr>
			<td>20 &#956;L low-retention pipette tips</td>
			<td>Rainin</td>
			<td>30389226</td>
			<td></td>
		</tr>
		<tr>
			<td>20 &#956;L pipette tips</td>
			<td>Rainin</td>
			<td>30389225</td>
			<td></td>
		</tr>
		<tr>
			<td>200 &#956;L low-retention pipette tips</td>
			<td>Rainin</td>
			<td>30389240</td>
			<td></td>
		</tr>
		<tr>
			<td>200 &#956;L pipette tips</td>
			<td>Rainin</td>
			<td>30389239</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL Polypropylene Conical Tube</td>
			<td>Falcon</td>
			<td>352098</td>
			<td></td>
		</tr>
		<tr>
			<td>60 x 15 mm Tissue Culture Dish</td>
			<td>Falcon</td>
			<td>353004</td>
			<td></td>
		</tr>
		<tr>
			<td>ACK Lysing Buffer</td>
			<td>Gibco</td>
			<td>A10492-1</td>
			<td></td>
		</tr>
		<tr>
			<td>BD 1 mL syringe</td>
			<td>Becton, Dickinson and Company</td>
			<td>3090659</td>
			<td></td>
		</tr>
		<tr>
			<td>Bright-Line Hemocytometer</td>
			<td>Hausser Scientific</td>
			<td>551660</td>
			<td></td>
		</tr>
		<tr>
			<td>Calcium Chloride Solution</td>
			<td>Sigma Aldrich</td>
			<td>2115-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Cell Ranger&#160;</td>
			<td>10x Genomics</td>
			<td>N/A</td>
			<td>https://www.10xgenomics.com/support/software/cell-ranger/latest</td>
		</tr>
		<tr>
			<td>Cell counting slides for TC20 cell counter</td>
			<td>Bio-Rad</td>
			<td>1450015</td>
			<td></td>
		</tr>
		<tr>
			<td>CellTrics 30&#956;m sterile disposable filters</td>
			<td>Sysmex</td>
			<td>04-004-2326</td>
			<td></td>
		</tr>
		<tr>
			<td>CellTrics 50&#956;m sterile disposable filters</td>
			<td>Sysmex</td>
			<td>04-004-2327</td>
			<td></td>
		</tr>
		<tr>
			<td>Dead Cell removal Kit&#160;</td>
			<td>Miltenyi Biotec</td>
			<td>130-090-101</td>
			<td>Store at -20 &#176;C; kit 2</td>
		</tr>
		<tr>
			<td>Dissecting Forceps, Fine Tip</td>
			<td>VWR</td>
			<td>82027-386</td>
			<td></td>
		</tr>
		<tr>
			<td>DNA LoBind Microcentrifuge tubes, 1.5 mL</td>
			<td>Eppendorf</td>
			<td>22431021</td>
			<td></td>
		</tr>
		<tr>
			<td>EasySepTM Dead Cell Removal 
			(Annexin V) Kit</td>
			<td>STEMCELL Technologies</td>
			<td>17899</td>
			<td>Store at 4 &#176;C; Kit 1</td>
		</tr>
		<tr>
			<td>Eppendorf centrifuge 5425R</td>
			<td>Eppendorf</td>
			<td>5406000640</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf centrifuge 5910R</td>
			<td>Eppendorf</td>
			<td>2231000657</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf Easypet 3 Electronic Pipette controller</td>
			<td>Eppendorf</td>
			<td>EP4430000018</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf Thermomixer F1.5 Model 5384</td>
			<td>Eppendorf</td>
			<td>EP5384000012</td>
			<td></td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>Gibco</td>
			<td>26140-079</td>
			<td>Store at 4 &#176;C, use in a Biological hood</td>
		</tr>
		<tr>
			<td>German Stainless Scissors</td>
			<td>Fine Science Tools</td>
			<td>14568-12</td>
			<td></td>
		</tr>
		<tr>
			<td>Leica Dmi1 Microscope</td>
			<td>Leica Microsystems</td>
			<td>454793</td>
			<td></td>
		</tr>
		<tr>
			<td>LS Column</td>
			<td>Miltenyi Biotec</td>
			<td>130-042-401</td>
			<td></td>
		</tr>
		<tr>
			<td>MACS Multistand</td>
			<td>Miltenyi Biotec</td>
			<td>130-042-303</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet-Lite LTS Pipette L-1000XLS+</td>
			<td>Rainin</td>
			<td>17014382</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet-Lite LTS Pipette L-200XLS+</td>
			<td>Rainin</td>
			<td>17014391</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet-Lite LTS Pipette L-20XLS+</td>
			<td>Rainin</td>
			<td>17014392</td>
			<td></td>
		</tr>
		<tr>
			<td>Quadro MACS Magnet</td>
			<td>Miltenyi Biotec</td>
			<td>130-091-051</td>
			<td></td>
		</tr>
		<tr>
			<td>RPMI Medium 1640 (1x)</td>
			<td>Gibco</td>
			<td>21870-076</td>
			<td>Store at 4 &#176;C</td>
		</tr>
		<tr>
			<td>TempAssure 0.2 mL PCR 8-Tube strips</td>
			<td>USA Scientific</td>
			<td>1402-4700</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypan blue stain 0.4%</td>
			<td>Thermo Fisher Scientific</td>
			<td>T10282</td>
			<td></td>
		</tr>
		<tr>
			<td>Tumor Dissociation Kit, Human</td>
			<td>Miltenyi Biotec</td>
			<td>130-095-929</td>
			<td>Store at -20 &#176;C, prepare enzymes according to kit instructions: 
			Reconstitute lyophilized Enzyme H vial in 3 mL of RPMI 1640 
			Reconstitute lyophilized Enzyme R vial in 2.7 mL of RPMI 1640 
			Reconstitute lyophilized Enzyme A vial in 1 mL of Buffer A supplied with the kit.</td>
		</tr>
		<tr>
			<td>Tumor Dissociation Kit, Mouse</td>
			<td>Miltenyi Biotec</td>
			<td>130-096-730</td>
			<td>Store at -20 &#176;C, prepare enzymes according to kit instructions: 
			Reconstitute lyophilized Enzyme D vial in 3 mL of RPMI 1640 
			Reconstitute lyophilized Enzyme R vial in 2.7 mL of RPMI 1640 
			Reconstitute lyophilized Enzyme A vial in 1 mL of Buffer A supplied with the kit.</td>
		</tr>
		<tr>
			<td>UltraPure Distilled Water</td>
			<td>Invitrogen</td>
			<td>10977-015</td>
			<td>Store at 4 &#176;C</td>
		</tr>
	</tbody>
</table>

dissociation of human and mouse tumor tissue samples for single-cell rna sequencing

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into viable cell suspensions is a required input for the single-cell RNA sequencing (scRNAseq) pipeline. Unlike bulk RNA sequencing approaches, scRNAseq enables us to infer the transcriptional heterogeneity in tumor specimens at the single-cell level. Incorporating this approach in recent years has led to many discoveries, such as identifying immune and tumor cellular states and programs associated with clinical responses to immunotherapies and other types of treatments. Moreover, single-cell technologies applied to dissociated tissues can be used to identify accessible chromatin regions T and B cell receptor repertoire, and the expression of proteins, using DNA barcoded antibodies (CITEseq).
The viability and quality of the dissociated sample are critical variables when using these technologies, as these can dramatically affect the cross-contamination of single cells with ambient RNA, the quality of the data, and interpretation. Moreover, long dissociation protocols can lead to the elimination of sensitive cell populations and the upregulation of a stress response gene signature. To overcome these limitations, we devised a rapid universal dissociation protocol, which has been validated on multiple types of human and murine tumors. The process begins with mechanical and enzymatic dissociation, followed by filtration, red blood lysis, and live dead enrichment, suitable for samples with a low input of cells (e.g., needle core biopsies). This protocol ensures a clean and viable single-cell suspension paramount to the successful generation of Gel Bead-In Emulsions (GEMs), barcoding, and sequencing.

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing

The scope of our research is to study the mechanisms of response or resistance in standard of care immunotherapies. Our lab is trying to understand what drives a successful immune response against tumors, and if we can identify these predictors of therapy to find targets that can overcome resistance. The biggest advancement in recent years has been the development and integration of single-cell RNA sequencing techniques.They enable us in real time to systematically study molecular features in individual cells in an unbiased manner, which is helpful in the dissection of these complex and evolving tumor ecosystems. While many preclinical models are being used to study the response mechanisms to immunotherapy, we still don't know the immunological determinants that are important in human immunity. Processing and analyzing patient samples in real time is crucial to our ability to investigate all cellular compartments within a given tumor.Using unbiased genomic and transcriptomic techniques, our lab discovered that defects in the antigen presentation machinery are associated with immunotherapy resistance in melanoma. More recently, using single-cell approaches, we discovered unique T cell states and myeloid cell polarities associated with patient outcomes in melanoma and head neck cancer, respectively. The biggest advantage of our protocol lies in its simplicity.It is a universal protocol adjusted for the dissociation of small and large tumor specimens from multiple types of cancers in a short period of time, ending in the generation of highly-viable, single-cell suspensions.

A melanoma biopsy suspended in RPMI was obtained and immediately placed on ice. The sample was transferred into a 1.5 mL microcentrifuge tube containing 420 &#181;L of RPMI and digestion enzymes, minced into small pieces using scissors, and subjected to subsequent enzymatic digestion for 15 min in a 37 &#730;C vertically positioned thermal mixer (Figure 1). Following digestion, the sample was filtered through a 50 &#181;m sterile disposable filter, and the filter was washed with fresh RPMI t...

This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into ...

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Research

JoVE Journal

Cancer Research

Rapid Dissociation of Tumor Tissue to Gain Enhanced Single-Cell Tumor Insights

To begin tumor digestion, pour the sample into a 60-millimeter tissue culture dish placed on ice. Pipette 420 microliters of media from the dish to a 1.5-milliliter microcentrifuge tube. Using tweezers, transfer the sample tissue to the tube containing media.Cut up the sample with clean scissors to pieces that are two to three millimeters in diameter. Add appropriate volumes of digestion enzymes and media to the sample. Vortex the tube for five seconds, and incubate it in a thermal mixer positioned vertically on its side.Place a 50-micrometer cell filter on top of a new 15-milliliter conical tube. And prime the filter with one milliliter of fresh RPMI media. Using a 1, 000-microliter lower tension wide pipette tip, load the sample to the filter and add the media.Then, with the back of a syringe plunger, grind and push the sample on the filter in a twisting motion. Wash the filter with five milliliters of media and any remaining media from the dish that contain the sample.

Red Blood Cell Lysis in Digested Tumor Samples for Single-Cell RNA Sequencing

To begin, obtain the filtered and digested tumor sample. Centrifuge the sample at 450 G for five minutes at four degrees Celsius. Aspirate the media without disturbing the pellet and resuspend the pellet in ACK lysis buffer to remove red blood cells and record the volume used.Repeat the centrifugation and the lysis steps until the sample pellet has no visible red color after centrifugation. Then resuspend the sample pellet in fresh media. Mix 10 microliters each of trypan and blue and the dissociated cells in a 1.5 milliliter tube.Load 10 microliters on each side of a hemocytometer. to count the cells. Record the cell concentration.Total live cell count viability percentage, and final media volume after count.

Dead Cell Removal from Dissociated Tumor for Single-Cell Sequencing

To begin, obtain the digested tumor tissue sample and lice the red blood cells. Centrifuge the sample at 450G for five minutes at four degrees Celsius. After removing the media, resuspend the pellet in one milliliter of the isolation media.After repeating the centrifugation, resuspend the pellet in 100 microliters of isolation media. Transfer 100 microliters of sample into a well of a 0.2 milliliter PCR strip tube. In a biosafety hood, add 10 microliters each of annexin V cocktail and biotin selection cocktail to the sample.Pipette mix the solution and incubate at room temperature for four minutes. Next, vortex the dextran-coated magnetic particles for 30 seconds. Mix 20 microliters of the beads and 60 microliters of isolation media with the sample.After three minutes, place the strip tube onto a 10x Genomics magnetic separator on the high setting for five minutes at room temperature. Then transfer the liquid from the strip tube without disturbing the beads into a new 1.5 milliliter low bind micro centrifuge tube. Centrifuge the tube as demonstrated earlier, and resuspend the pellet in an appropriate volume of our PMI media based on the pellet size.Finally, count the cells in a hemocytometer. Following dead cell removal, the live cell count was 4.9 times 10 to the power of 5 per milliliter, with viability above 90%

1.0K Views.  Massachusetts General Hospital.  This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.

Tumor Dissociation Protocol for Single-Cell RNA Sequencing Analysis

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